AN ABSTRACT OF THE THESIS OF
Anthony D. Bertagnolli for the degree of Doctor of Philosophy in Microbiology
presented on April 12, 2012.
Title: Microbial Diversity, Metabolic Potential, and Transcriptional Activity along the
Inner Continental Shelf of the Northeast Pacific Ocean
Abstract approved: _____________________________________________________
Stephen J. Giovannoni
Continental shelves located along eastern boundary currents occupy relatively
small volumes of the world’s oceans, yet are responsible for a large proportion of global
primary production. The Oregon coast is among these ecosystems. Recent analyses of
dissolved oxygen at shallow depths in the water column has suggested increasing
episodes of hypoxia and anoxia, events that are detrimental to larger macro-faunal
species. Microbial communities, however, are metabolically diverse, capable of utilizing
alternative electron donors and acceptors, and can withstand transient periods of low
dissolved oxygen. Understanding the phylogenetic and metabolic diversity of
microorganisms in these environments is important for assessing the impact hypoxic
events have on local and global biogeochemistry. Several molecular ecology tools were
used to answer questions about the distribution patterns and activities of microorganisms
residing along the coast of Oregon in this dissertation. Ribosomal rRNA fingerprinting
and sequence analyses of samples collected during 2007-2008 suggested that bacterial
community structure was not substantially influenced by changes in dissolved oxygen.
However, substantial depth dependent changes were observed, with samples collected in
the bottom boundary layer (BBL) displaying significant differences from those collected
in the surface layer. Phylogenetic analyses of bacterial rRNA genes revealed novel
phylotypes associated with this area of the water column, including groups with close
evolutionary relationships to putative or characterized sulfur oxidizing bacteria (SOB).
Analysis of metagenomes and metatranscriptomes collected during 2009 suggested
increasing abundances of chemolithoautrophic organisms and their activities in the BBL.
Thaumarchaea displayed significant depth dependent increases during the summer, and
were detected at maximal frequencies during periods of hypoxia, suggesting that
nitrification maybe influenced by local changes in dissolved oxygen. Metagenomic
analysis of samples collected from 2010 revealed substantial variability in the metabolic
potential of the microbial communities from different water masses. Samples collected
during the spring, prior to upwelling clustered independently of those collected during the
summer, during a period of upwelling, and did not display any clear stratification.
Samples collected during the summer did cluster based on depth, consistent with previous
observations, and increases in the relative abundances of chemolithotrophic gene suites
were observed in the BBL during stratified conditions, suggesting that the metabolic
potential for these processes is a repeatable feature along the Oregon coast. Overall, these
observations suggest that depth impacts microbial community diversity, metabolic
potential, and transcriptional activity in shallow areas of the Northeast Pacific Ocean. The
increase in lithotrophic genes and transcripts in the BBL suggests that this microbial
community includes many organisms that are able to use inorganic electron donors for
respiration. We speculate that the dissolved organic material in the BBL is semi-labile
and not available for immediate oxidation, favoring the growth for microorganisms that
are able to use alternative electron donors.
©Copyright by Anthony D. Bertagnolli
April 12, 2012
All Rights Reserved
Microbial Diversity, Metabolic Potential, and Transcriptional Activity along the Inner
Continental Shelf of the Northeast Pacific Ocean
by
Anthony D. Bertagnolli
A THESIS
submitted to
Oregon State University
In partial fulfillment of
the requirements for the
degree of
Doctor of Philosphy
Presented April 12, 2012
Commencement June 2012
Doctor of Philosophy thesis of Anthony D. Bertagnolli presented on April 12, 2012
APPROVED:
_____________________________________________________________________
Major Professor, representing Microbiology
_____________________________________________________________________
Chair of the Department of Microbiology
_____________________________________________________________________
Dean of the Graduate School
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader
upon request.
_____________________________________________________________________
Anthony D. Bertagnolli, Author
ACKNOWLEDGEMENTS
The author wishes to thank…
Advisors: Dr. Stephen J. Giovannoni, Dr. Peter J. Bottomley, Dr. Frederick Cowell, Dr.
Allen Milligan and Dr. Kaichang Li
Past and present Giovannoni lab members: Dr. Uli Stingl, Dr. Olivia Mason, Dr. Alex
Treusch, Dr. Bank Beszteri, Dr. Laura Steindler, Dr. Sarah Sowell, Kevin Vergin, Amy
Carter, Dr. Cameron Thrash, Zach Landry, Paul Carini, Dr. James Tripp, Dr. Ben
Temperton
Research groups: Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) at
Oregon State University, the Microbial initiative in low oxygen waters of the coasts of
Chile and Oregon (MI_LOCO): Dr. Francis Chan, Dr. Ricardo Letelier, Marnie-Jo Zirbel,
Ruth Milston-Clements, Becky Focht, Dr. Osvaldo Ulloa, Salvador Ramirez-Flandes, Dr.
Alex Galan
Family, friends, and other inspirations: Norma and Kim Bertagnolli; Brenda Bennett,
Andrew Schwartz, Hyatt Green, Matt Stintson, Josh and Raina Powell, Steve and Kath
Lawton
CONTRIBUTION OF AUTHORS
Dr. Giovannoni served as major advisor and contributed to the experimental design and
writing of manuscripts. Dr. Ulrich Stingl, Dr. Alexander Treusch, and Dr. Olivia Mason
provided assistance with selection of molecular techniques, analytical interpretation of
fingerprint data, and phylogenetic interpretation of 16S rRNA genes. Kevin Vergin
assisted with field sampling in Chapters 2-4, and isolation of nucleic acids in Chapters 3
and 4. Dr. Francis Chan provided dissolved oxygen and other metadata associated with
our samples. Salvador Ramirez-Flandes provided a nucleic acids database for
metagenomic and metatranscriptomic analysis in Chapters 4 and 5. Dr. Osvaldo Ulloa
contributed to the experimental design and writing of manuscripts 4.
TABLE OF CONTENTS
Page
Chapter 1: Introduction ........................................................................................................2
Chapter 2: Bacterial diversity in the bottom boundary layer of the inner continental shelf
of Oregon, USA .................................................................................................................15
Abstract ..........................................................................................................................16
Introduction ....................................................................................................................17
Materials and methods ...................................................................................................19
Results ............................................................................................................................23
Discussion ......................................................................................................................24
Conclusion......................................................................................................................29
Chapter 3: Archaeal diversity in the bottom boundary layer of the inner continental shelf
of Oregon, USA .................................................................................................................41
Abstract ..........................................................................................................................42
Introduction ....................................................................................................................43
Materials and methods ...................................................................................................44
Results and Discussion...................................................................................................45
Conclusion......................................................................................................................47
Chapter 4: Coupled metagenomic and metatranscriptomic profiling over a depth gradient
in the northeast Pacific ocean ............................................................................................51
Abstract ..........................................................................................................................52
Introduction ....................................................................................................................53
Materials and methods ...................................................................................................55
Results and Discussion...................................................................................................60
Conclusion......................................................................................................................66
Chapter 5: Coupled metagenomic and metatranscriptomic profiling over a depth gradient
in the northeast Pacific ocean ............................................................................................80
Abstract ..........................................................................................................................81
TABLE OF CONTENTS (Continued)
Page
Introduction ....................................................................................................................82
Materials and methods ...................................................................................................83
Results and Discussion...................................................................................................84
Conclusion......................................................................................................................86
Chapter 6: Conclusion........................................................................................................95
Bibliography ......................................................................................................................98
LIST OF FIGURES
Figure
Page
Figure 2.1: NMDS analyses of TRFLP profiles from 2007-2008 .....................................33
Figure 2.2: TRF contributions to NMDS analyses ............................................................34
Figure 2.3: Neighbor joining tree of γ-Proteobacteria 16S rRNAs ..................................35
Figure 2.4: Neighbor joining tree of Planctomycetales 16S rRNAs .................................37
Figure 2.5: Neighbor joining tree of α-Proteobacteria 16S rRNAs..................................39
Figure 3.1: Neighbor joining tree of Archaeal 16S rRNAs ...............................................49
Figure 4.1: NMDS analyses of TRFLP profiles from 2009...............................................73
Figure 4.2: NMDS analyses of metagenomic and metatranscriptomic profiles ................74
Figure 4.3: Genome sequenced representatives with high scoring pairs in metagenomes
and metatranscriptomes .....................................................................................................75
Figure 4.4: Inorganic nitrogen cycling gene and transcript distributions ..........................76
Figure 4.5: Nitrospina rRNAs and observed TRF distribution in NMDS analyses ..........77
Figure 4.6: Inorganic sulfur cycling gene and transcript distributions ..............................78
Figure 5.1: NMDS analyses of TRFLP profiles from 2010...............................................90
Figure 5.2: Hierarchical clustering of metagenomes from 2009 and 2010........................91
Figure 5.3: Temperature and salinity plots associated with metagenomes collected from
2009 and 2010....................................................................................................................92
Figure 5.4: Ammonia monooxygenase and reverse dissimilatory sulfite reductase
distributions in 2010 metagenomes ...................................................................................93
LIST OF TABLES
Figure
Page
Table 2.1: Environmental data associated with samples from 2007-2008 ........................31
Table 2.2: Phylogenetic identities of TRFs ......................................................................32
Table 4.1: Environmental data associated with samples from 2009..................................68
Table 4.2: Sequencing statistics from metagenomes and metatranscriptomes collected
during 2009 ........................................................................................................................70
Table 4.3: Contribution of environmental parameters to NMDS ordination axes of
metagenomes and metatranscriptomes ..............................................................................71
Table 5.1: Environmental data associated with samples from 2009 and 2010..................87
Table 5.2: Sequencing statistics from metagenomes and metatranscriptomes collected
during 2009 ........................................................................................................................89
LIST OF APPENDICES
Appendix
Page
Appendix A: Functional genes observed in metagenomes displaying strong correlations
with depth.........................................................................................................................117
Appendix B: Functional genes observed in metagenomes displaying significant increases
under hypoxic conditions.................................................................................................122
Appendix C: Functional genes observed in transcriptomes displaying significant
increases under hypoxic conditions .................................................................................125
Microbial Diversity, Metabolic Potential, and Transcriptional Activity along the Inner
Continental Shelf of the Northeast Pacific Ocean
2
Chapter 1
Molecular microbial diversity in marine ecosystems under oxygen deprived
conditions
Recent analyses of dissolved oxygen (DO) concentrations in the ocean have suggested an
expansion of oxygen minimum zones (OMZs), environments where DO falls below 20
µM (124). These areas create a substantial barrier to the migration of fish and
invertebrate species and are detrimental to macro-faunal biodiversity. Microorganisms,
however, thrive due to their ability to utilize alternative electron acceptors, creating
unique chemical environments that have tremendous consequences on the earth’s
atmosphere. For example, approximately 30-50% of biologically available nitrogen is lost
within OMZs due to the activity of microorganisms. While the biochemical mechanisms
governing these losses are complex, evidence suggests that both denitrification and
anaerobic ammonia oxidation are the dominant processes facilitating these losses (22).
Because of their impact on biogeochemistry, it is important to thoroughly investigate the
distribution, diversity, function, and activity of microorganisms residing in oxygen
deprived marine environments.
Below is a background regarding the formation of low oxygen conditions in
marine environments as a prelude to describing their associated microbial diversity.
Several different types of oceanic ecosystems experience either permanent or transient
episodes of low dissolved oxygen, yet the physical drivers spawning these events vary.
However, three observations regarding their formation have been made: 1) an increase of
inorganic nutrients spurs primary production in areas of high-light intensity 2) subsequent
degradation of organic matter by heterotrophic microorganisms draws down biologically
available oxygen 3) if the oxygen depleted water does not mix with another oxygen rich
water mass, severe depletion of DO can occur, leading to hypoxia (DO<1.4 ml/L), severe
hypoxia (DO<0.5 ml/L), and sometimes anoxia (non-detectable DO) (31).
The edges of continental margins along eastern boundaries often contain DO
levels that are below 0.5 ml/L (20 µM). These regions are canonical oxygen minimum
3
zones, permanent features of the world’s oceans. High nutrient, low temperature deep
ocean water masses are delivered to the photic zone by wind induced upwelling created
through Ekman transport. Photosynthetic growth is then spurred by the availability of
inorganic nutrients. A lack of mixing in conjunction with high DO demand below the
surface leads to low oxygen conditions. Portions of the eastern Pacific, southeast
Atlantic, and northern Indian Oceans are considered the world’s dominant OMZs (58).
Their vertical extent varies by region, with the deepest OMZ residing in regions of the
central Arabian sea. Below the OMZ, dissolved oxygen values often increase, as
decreased temperature and increased pressure lead to greater oxygen solubility. However,
in some areas, oxygen values remain depleted, creating hypoxic and anoxic conditions in
close proximity to the benthos. The macrofauna associated with these environments are
often unique, having adapted to changes in dissolved oxygen.
Estuaries and gulf systems often experience hypoxia and sometimes anoxia. In
contrast to permanent OMZs, these areas receive excess nutrients from anthropogenic
sources, mainly in the form of reactive nitrogen species. For example, fertilizer use along
the Midwest and Southwestern United States leach into groundwater, running into the
Mississippi river. These nutrients are eventually transported southward into the Gulf of
Mexico, creating hypoxic conditions along the coastal zone. As of 2008, approximately
400 aquatic systems reported anthropogenically induced hypoxia (31). Unlike permanent
OMZs, reversal of hypoxia in estuary and gulf systems has been observed, due largely in
part to changing land management policies.
The coast of Oregon (located in the California Current system) has received
substantial attention in the past 6 years due to increasing reports of seasonal hypoxia in
shallow areas (<200 meter water column depth) of the continental shelf (18, 54). These
events are very similar to those observed in open ocean oxygen minima yet distinct in
their transient nature. Very little information regarding microbial community diversity
and its relationship to hypoxia have been reported along the Oregon coast. However,
other marine environments experiencing anoxia and hypoxia have been surveyed, in
4
some cases quite extensively. These include the OMZs in the Eastern Tropical South
Pacific off the coasts of Chile and Peru, Eastern Tropical South Atlantic off the coast of
Namibia, the coast of India in the Indian Ocean, and the Saanich Inlet located in the
Northeast Pacific Ocean. As such, an overview of these findings is necessary prior to
describing the scientific hypothesis and goals affiliated with this dissertation.
Molecular diversity of denitrifies and anaerobic ammonia oxidizing organisms
Early molecular surveys aimed at characterizing genes involved in dentrification,
as this was assumed as the dominant process governing nitrogen loss in anoxic aquatic
systems prior to 2005. Inorganic nitrogen limits phytoplankton growth (in addition to iron
and phosphorous), creating a barrier to new production in the ocean. Substantial efforts
have been made at describing the activity, abundance, and diversity of denitrifying
organisms in OMZs.
Canonical dentrification produces di-nitrogen gas (N2) through complete
reduction of nitrate (NO3-), while partial dentrification produces nitric oxide (N2O), a
potent green house gas. A key step in this process is the reduction of nitrite (NO2-) to
nitric oxide (NO). In characterized denitrifies, this transformation is mediated by copper
and cytochrome containing nitrite reductases (nirK and nirS, respectively) (154). These
genes are spread amongst many taxonomically dissimilar groups, having undergone
substantial horizontal gene transfer events, making 16S rRNA based investigations
uninformative. However, degenerate primers for PCR amplification have been designed
for interrogating denitrifier diversity at the gene level, and applied to pelagic marine
environments (12).
Phylogenetic surveys of nirS phylotypes in the Arabian sea and Eastern tropical
south Pacific have been performed. In both ecosystems, the highest amount of denitrifier
diversity was consistently observed in anoxic samples with increased nitrite
concentrations (17, 62). These phylotypes are not static, yet display shifts depending on
5
the stage of denitrification, with increased diversity associated with early, nitrate replete
environments, and lower diversity associated with nitrate deplete areas (61).
Despite the consistent detection, and substantial abundances of organisms with
the metabolic capability for denitrification, the process has not been detected in all
oxygen minimum zones. Why such variability exists is still uncertain, and the subject of
much debate (73). Thermodynamically, denitrification provides an energy yield close to
that of aerobic respiration of organic matter. Denitrification has been observed
experimentally (using incubation based rate measurements) in the oxygen minimum zone
located in the central Arabian sea, yet is seldom detected in the eastern Tropical South
Pacific (143). One study has suggested that organic carbon supply, and perhaps quality,
may influence the activity of denitrifiers in OMZs (145).
During denitrification, ammonia is produced during the breakdown of organic
matter. However, the amount of ammonia expected to accumulate in some anoxic marine
environments is often orders of magnitude less than that predicted based on the Redfield
ratio for organic matter re-mineralization (104). An explanation for this absence was
proposed in 1971, the anaerobic oxidation of ammonia (anammox) with nitrite as an
electron acceptor (104). Approximately 30 years later, evidence for a microbial group
with the ability to catalyze such a reaction was discovered in a waste water treatment
facility (125).
Anammox organisms are phylogenetically and physiologically unique, residing in
a deeply branching, monophyletic family in the phylum Planctomycetes (36). During
anammox, nitrite is first converted to nitric oxide, then coupled to ammonia to form
hydrazine. Oxidation of hydrazine generates 378 kJ/mol, as well as di-nitrogen gas, under
standard conditions (66). The energy yield of this reaction is considerably lower in
comparison to that of denitrification (denitrification with HS- as an electron donor
generates 1,200 kJ/mol). Hydrazine is a highly reactive compound formed in a specific
cellular component comprised of ladderdane lipids that, at this time, appear unique to
6
anammox organisms. Because of their unique phylogenetic placement, biochemistry, and
physiology, cells can be detected using a wide array of molecular and biochemical tools.
The first direct evidence for anammox in the oceans came from the permanent
OMZ of the south Atlantic along the coast of Africa (72). Stable isotope pairing
experiments in conjunction with fluorescence in-situ hybridization revealed anammox
activity, and the presence of the associated phylotypes. Ladderdane lipid structures
associated with the annamoxosome were also detected using mass-spectrometry.
Denitrification was detected, yet only after several hours of incubation under anaerobic
conditions, and this result was not reproducible.
Following this initial survey, several other studies using similar techniques
revealed the presence of anammox organisms and the associated process in several
permanent OMZs, including the coast of Peru, Northern Chile, and recently the Omani
shelf in the Arabian Sea (57, 63, 137). A phylogenetic investigation of anammox
Planctomycetales from several aquatic samples under low oxygen conditions revealed
that substantial micro-diversity exists that may not be reflected in 16S rRNA gene
surveys alone (147). Whether these differences can be attributed to differing phenotypic
and physiological capabilities remains to be seen.
Studies in the Peruvian oxygen minimum zone have revealed that the anammox
process is tightly coupled to nitrification and dissimilatory nitrate reduction to ammonia
(74). These results suggest that much of the ammonia lost from these regions is generated
locally, in contrast to previous models indicating an up-welled deep-ocean reservoirs.
The sensitivity of anammox to oxygen appears substantially lower than expected, perhaps
suggesting that oxygen is not the sole determinant dictating the activity of these
organisms in marine environments (64).
Molecular diversity of aerobic nitrifiers
Nitrification is the conversion of ammonia to nitrate and is comprised of two
steps; oxidation of ammonia to nitrite, followed by nitrite oxidation to nitrate. In marine
7
environments, intense competition for inorganic nitrogen exists, especially in the photic
zone. Nitrifiers must compete with larger, photosynthetic organisms, as well as nonchemolithotrophic bacteria for this nutrient. Current knowledge suggests that ammonia
oxidation is mediated by members of the domains Bacteria and Archaea, while nitrite
oxidation is catalyzed exclusively by members of the Bacteria.
Nitrification is performed primarily by chemolithoautotrophic organisms (the
exception being heterotrophic nitrification; a process that is not necessarily used for
energy generation). Prior to molecular diversity surveys of nitrifying organisms in OMZs,
process based studies revealed nitrification and CO2 fixation in the water column of the
Eastern Tropical South Pacific (144). Ammonia oxidation rates and chemolithotrophy
were highest in the oxic-anoxic transition phase (oxycline). Oxidation of ammonia was
detected in the core of the OMZ, and ammonia oxidizing organisms were observed using
immunofluorescent techniques.
Ammonia oxidation has been thoroughly studied in cultivated members of the
domain Bacteria (109). Currently, only members of the β-Proteobacteria and γProteobacteria have been identified as ammonia oxidizing bacteria (AOB). The most
extensively researched of these organisms is Nitrosomonas europaea (β-Proteobacteria).
Although this organism does not dwell in marine ecosystems, its rapid growth rate and
ability to achieve high cell densities have made it an invaluable tool for investigating the
biochemical and molecular mechanisms of ammonia oxidation. In these organisms,
ammonia is oxidized to hydroxalymine, and hydroxyalamine is subsequently oxidized to
nitrite (110). These reactions are catalyzed by a bacterial ammonia monoooxygenase (βAmo) and hydroxylamine oxidoreductase (Hao), respectively.
A majority of the AOB 16S rRNA genes recovered in marine environments are βProteobacteria in the genus Nitrosopira, and fall within groups that do not harbor
cultivated lineages. Nitrosopira like 16S rRNAs and β-Amo genes have been recovered
using cloning and sequencing techniques from the water column of the eastern tropical
south Pacific (88), suggesting the potential for bacterial nitrification in this OMZ system.
8
However, more recent surveys using more analytical approaches, such as quantitative
PCR, have suggested these organisms are often present in lower abundances relative to
other ammonia oxidizing organisms (87).
Previous surveys of microbial diversity in terrestrial and marine environments
revealed the presence (and sometimes high abundances) of mesophilic crenarchaea (65,
82). These rRNA genes were phylogenetically unique from previously identified
Archaea, and initially referred to as Group I. However, their impact on the
biogeochemistry of these systems remained elusive for over a decade. Insight into their
metabolic capabilities initially stemmed from metagenomic surveys of soil ecosystems
(134, 138). The observation of a crenarchaeal Group I 16S rRNA gene in close proximity
to a monooxygenase gene cluster provided evidence in support of the hypothesis of
Archaeal mediated ammonia oxidation in the environment. Direct evidence has since
stemmed from isolation and characterization of the first group I represenative,
Nitrosopumulis maritimus SCM1 (71, 133). Genome sequencing and phylogenetic
analyses have now revealed that these organisms are genetically distinct from other
members of the crenarchaea, perhaps comprising a new phylum (Thaumarchaea) (13,
97).
Archaeal ammonia monoooxygenase genes (AOA) and 16S rRNA genes have
been retrieved from numerous marine environments including oxygen minimum zones
(33, 87). These organisms often occupy their highest absolute abundances in the oxicanoxic transition zones, perhaps suggesting a preference for low oxygen partial pressures
(6, 7). Recent isotopic analyses of AOA enrichment cultures has suggested that ammonia
oxidation proceeds through denitrifier-nitrification, a process that produces, and
consumes, N2O (107). Direct molecular biological evidence has not yet been provided to
support this mechanism. However, genome analyses and isotope fractionation data
strongly support this mode of ammonia oxidation.
Thaumarchaea are now recognized as the dominant ammonia oxidizers in marine
environments, including OMZs, while AOBs tend to occupy different aquatic niches,
9
such as freshwater systems (11, 85). This result is likely due to the low concentrations of
ammonia typically observed in marine ecosystems. Cultivated Thaumarchaea have an
extremely high affinity for ammonia compared to bacteria and eukaryotic phytoplankton
(81). Genome sequence analyses have suggested that this may be due to an enrichment of
copper, rather than iron containing oxidoreductases (141).
Nitrite oxidizing bacteria catalyze the final step in aerobic nitrification, linking the
most reduced and oxidized forms of inorganic nitrogen in the ocean. Despite their
relevance in marine environments, nitrite-oxidizing bacteria (NOB) have not been as
thoroughly studied as ammonia oxidizers within the context of microbial oceanography.
An early survey of denitrification and nitrification in the eastern tropical south Pacific
revealed nitrite oxidation occurring in the oxic-anoxic transition phase, yet the taxonomic
affiliation of the organisms present was not characterized (77).
Phylogenetically, NOBs are distributed amongst α-, γ-, and δ-Proteobacteria and
the phylum Nitrospirae. NOB isolates have been recovered from marine surface waters
(146); Nitrospina gracilus is a member of the δ-Proteobacteria, and Nitrosococcus
mobilus is a member of the γ-Proteobacteria. These organisms were isolated in the early
1970s, however, very little work has been done on either since their initial isolation. In
contrast to marine organisms, much physiological, biochemical, and genomic work has
been performed on α-Proteobacteria in the genus Nitrobacter (116). In these organisms,
nitrite oxidation is likely performed by an enzyme complex homologous to dissimilatory
nitrate reductase that operates in the reverse direction (Nxr). The catalytic subunit of Nxr
(subunit A) likely faces the cytoplasmic side of the periplasmic membrane. This proposed
orientation results in the need to transport nitrite across the periplasm, and may result in
the high observed Ks for nitrite. Nitrite concentrations in marine systems are typically
quite low (below 1 µM, although variance does exist), and this may be why Nitrobacter
phylotypes are rarely observed in these systems using molecular tools.
16S rRNA gene cloning and sequencing have revealed that a majority of the
putative NOB present in marine environments are δ-Proteobacteria in the genus
10
Nitrospina. rRNAs recovered from oligotrophic and coastal areas display unique,
sometimes distant relationships to cultivated members, and tend to reside below the
photic zone (8, 85). AOA and NOB often display overlapping distributions, perhaps
suggesting cooperation between the two groups. However, a differential distribution
patterns have been observed in other marine systems, such as the San-Pedro Ocean time
series in the California Current. Partial sequence analysis of large insert fosmid libraries
containing Nitrospina 16S rRNAs revealed a substantial proportion of open-reading
frames with high sequence similarity to anammox bacteria. A similar trend was observed
when comparing the metagenome of a nitrite oxidizing enrichment culture recovered
from a waste-water treatment facility (Candidatus “Nitrospira defluvii”) (79).
Nitropsina rRNAs have been recovered from the Saanich Inlet OMZ, a marine
fjord in the Northeast Pacific Ocean, occurring in their highest frequencies in the oxicanoxic transition phase (151). Recently, high rates of nitrite oxidation were observed in
the OMZ of the South Atlantic (coast of Namibia) despite low to non-detectable oxygen
concentrations. Both Nitrospina and γ-Proteobacteria in the genus Nitrosococcus were
identified by fluorescence in-site hybridization, comprising 9% of the bacterioplankton
community (38). In this environment, it was suggested that nitrite oxidizing bacteria
compete with anammox bacteria for nitrite, regenerating nitrate. However, it is still
unclear how nitrite oxidizing organisms survive within these ecosystems without
detectable oxygen.
16S rRNA gene based studies
Bacterial diversity surveys relying primarily on cloning and sequencing of the
16S rRNA gene in OMZs has been performed in the Arabian Sea, the eastern Tropical
South Pacific, the south Atlantic off the coast of Namibia, and Saanich Inlet Fjord in
British Columbia (35, 119, 151). A consistent observation made in each of these surveys
is the recovery and high abundances of organisms with close affiliations to putative sulfur
oxidizing symbionts of metazoans. Two clades have been consistently observed; the
SUP05 clade and the ARCTIC96BD-19 clade. The SUP05 clade displays a global
11
distribution in oxygen minimum zones. The group was initially observed in hydrothermal
vent plumes (128). The ARCTIC96BD-19 clade has been recovered in several OMZs, in
addition to oxygenated areas of the water column such as the sub-euphotic zone of the
Arctic Ocean (5). Neither group contains a physiologically characterized member.
However, single cell isolation and partial genome sequencing have been reported for
members of the ARCTIC96BD-19 clade, and the SUP05 clade has been thoroughly
assessed through metagenomic reconstruction (see below) (123).
The Fibrobacter related SAR406 clade and SAR324 clade of δ-Proteobacteria
have also been retrieved from several OMZs. These groups were originally identified in
16S rRNA gene libraries originating in the Sargasso Sea, and display depth dependent
shifts in their distributions, often times residing below the deep-chlorophyll maximum in
the mesopelagic zone (44, 52, 149). The recovery of these groups from marine systems
with oxygen variation may imply an ability to withstand periods of oxygen stress.
Application of next generation sequencing technologies to oxygen minimum zones
Metagenomics is one of many molecular ecology tools used to assess gene
diversity in the environment. Direct cloning and sequencing of large, contiguous nucleic
acids fragments (Escherichia coli F-factor based cosmids or Fosmids) has proven useful
in describing the metabolic potential of microbial communities (27). Fosmid based
surveys in the OMZ of the Saanich Inlet were used to reconstruct the genome of the
SUP05 clade without enrichment or cultivation (142). Gene suites involved in the
oxidation of reduced sulfur compounds and reduction of nitrate to nitrous oxide were
identified, implying that the group may contribute to observed inorganic nitrogen losses.
Presence of ribulose-1,5-bisphosphate also implied the ability to utilize inorganic carbon
lithoautotrophically.
Recent advances in high-throughput sequencing technologies have allowed for
direct analyses of nucleic acids from the environment through pyrosequencing (i.e.
sequencing by synthesis). This method is advantageous to traditional cloning and
12
sequencing techniques for several reasons: 1) direct sequencing of nucleic acids is much
less labor intensive than construction and screening of clone libraries 2) utilization of
cloning is avoided that can potentially bias retrieval of certain nucleic acids. For example,
fosmid libraries are often times enriched in nucleic acids affiliated with low GC
containing organisms (131).
Metagenomic and metatranscriptomic analyses have been performed in the
permanent oxygen minimum zone in the eastern tropical south Pacific off the coast of
northern Chile (121). Differences in the taxonomic affiliations of protein coding
transcripts and genes were observed between samples collected over the oxygen gradient.
In the oxycline, 1 in 5 transcripts displayed high-scoring pairs to Thaumarchaea, and
included protein coding genes involved in ammonia oxidation, providing further evidence
for ammonia oxidation in oxic-anoxic transition phases. Transcripts with high-scoring
pairs to anammox bacteria and SOB were observed in the core of the OMZ, suggesting an
active chemolithoautotrophic community within the OMZ.
A combined geochemical and metagenomic survey revealed active sulfate
reduction occurs within OMZs, supplying the reduced organic sulfur needed by SOB
populations (16). Organic carbon re-mineralization with sulfate as an electron acceptor
could also provide a source of ammonia to fuel anammox. Sulfate reduction is an
energetically limited metabolism compared to the reduction of oxygen or nitrate.
However, sulfate is saturating in marine systems, making its utilization feasible under the
appropriate conditions.
Oregon Coast
Microbial diversity surveys have been reported along the coast of Oregon, and
provide considerable insight into the diversity of microorganisms residing within the
surface of the inner continental shelf (103). 16S rRNA gene studies have revealed that
continental shelves harbor ecotypes that are similar to those encountered in oligotrophic
oceans, as well as those that appear confined to the coastal zone. These communities are
13
not static, either, yet change in concert with local physical, chemical, and biotic
conditions (89). Additionally, abundant phylotypes have been isolated from the surface
waters through dilution to extinction culturing (23, 101). Further genome sequencing of
these isolates has substantially increased our understanding of marine microbial genomics
and their potential impact on oceanic biogeochemistry (45, 135).
Most microbial diversity studies along continental shelves have focused
specifically on bacterioplankton residing in the surface layer. The Oregon coast is no
exception. Because of increased observations of seasonal hypoxia and anoxia in these
regions, we sought to explore the microbial diversity associated with this environment.
Our scientific questions were as follows:
1) Does bacterial community structure and diversity change in response to dissolved
oxygen concentrations along the coast of OR?
2) Does microbial community metabolic potential and transcriptional activity
change in response to dissolved oxygen along the coast of OR?
3) Does microbial community gene potential display variation inter-annually?
In data chapter 2, bacterial communities were assessed during the spring and summer
of 2007-2008 from samples collected in the surface and bottom boundary layer. Briefly,
the results of this study suggested that, despite sampling over a range of dissolved oxygen
conditions, including non-hypoxic and hypoxic conditions, bacterial populations were not
influenced by the DO levels observed during this time period. Rather, samples collected
in the bottom boundary layer were distinct from those collected in the surface, and the
taxonomic composition of this area was unique from that of the surface, harboring some
previously unidentified taxonomic groups.
The unique assemblages of bacteria described in data chapter 1 led us to survey the
Archaeal community associated with the bottom boundary layer in Chapter 2. These data
revealed a high relative abundance of Thaumarchaea (Group I crenarchaea), consistent
with previous surveys of coastal environments, suggesting the presence of organisms
involved in ammonia oxidation. Interestingly, a single clone affiliated with a
14
methylotrophic methanogen was also recovered, perhaps suggesting that the oxidation of
methylated compounds could occur in these environments.
In data chapter 3, the metabolic potential and transcriptional activity of microbial
communities was assessed during the summer (severe hypoxic) and fall (non-hypoxic) of
2009 using next-generation sequencing technologies. These results suggested that
metagenomes and metatranscriptomes also displayed strong vertical changes in their
distribution patterns. Increases in the abundance of genes and transcripts involved in
lithotrophic metabolisms were consistently observed in the bottom boundary layer.
Nitrification genes and transcripts also displayed the strongest correlations with changes
in dissolved oxygen.
In data chapter 4, bacterial community structure and gene diversity were assessed
using TRFLP and metagenomics from samples collected during 2010 from the spring,
prior to the onset of upwelling conditions, and during the summer, after upwelling. These
data were compared to metagenomes collected the previous year to compare and contrast
intra-annual variability in metabolic diversity along the Oregon coast.
15
Chapter 2
Bacterial diversity in the bottom boundary layer of the inner continental shelf of
Oregon, USA
Anthony D. Bertagnolli, Alexander H. Treusch, Oliva U. Mason, Ulrich Stingl, Kevin L.
Vergin, Francis Chan, Stephan J. Giovannoni
Published in:
Aquatic Microbial Ecology
Inter-Research
2011, Vol. 64, No. 1, p. 15-25
16
Abstract: There have been few studies of the bacterial community within the bottom
boundary layer (BBL) - the turbulent region of the water column above the benthos - in
shallow seas. Typically the BBL has high amounts of particulate organic matter
suspended by turbulence, and it is often the first region of the water column to become
hypoxic when oxygen declines. Surface (5 m) and BBL (1-10 m above the sea floor)
communities were compared by T-RFLP and sequencing of the 16S rRNA gene.
Multivariate statistical methods (hierarchical clustering, non-metric multidimensional
scaling and analysis of similarity-ANOSIM) indicated that the bottom boundary layer
microbial community is distinct from the surface community. ANOSIM analysis
supported the distinction between surface and bottom boundary layers (R values 0.427
and 0.463, based on analysis with enzymes BsuR1 and Hin6I, respectively p<0.001). Six
terminal restriction fragments showed an increase in abundance with depth. Cloning,
screening and sequencing identified these as a novel environmental clade (ENPC Eastern North Pacific Chromatiales clade), the ARTIC96BD-19 clade of
Gammaproteobacteria, the 6N14 and Agg8 clades of the phylum Planctomycetes, the
OM60/NOR5 clade of γ-Proteobacteria, and uncultivated members of the Roseobacter
clade in the MB11C09 and ULA23 sub-groups. This analysis is the first to focus on the
unique composition of bottom boundary layer microbial communities in shallow, inner
shelf regions off the coast of Oregon, and the first to report that an uncharacterized clade
of Chromatiales is indigenous in this habitat.
17
Introduction
The northeast Pacific Ocean along the Oregon continental shelf is a productive marine
ecosystem that experiences seasonal upwelling of nutrient rich mesopelagic waters into
the photic zone. The delivery of nutrient rich waters to the surface spurs high primary
production by marine phytoplankton, which in turn supports productivity at higher
trophic levels (95). Thus, while coastal environments occupy relatively small volumes of
the global oceans, they support a substantial proportion (90%) of global fisheries yield,
making these areas an invaluable natural resource for economic and recreational purposes
(94). Coastal Oregon is a particularly interesting ecosystem in light of recent reports of
summer anoxic events in shallow, inner-shelf areas, having detrimental impacts on
pelagic biodiversity (18, 54).
Bacterial communities are important drivers of biogeochemical cycles in marine
ecosystems (3). Heterotrophic bacteria have a massive impact on the global carbon cycle
by transforming organic carbon and re-mineralizing a large fraction of it to CO2 (37).
Studies of plankton communities in deep waters near the edges of continental shelves and
in ocean gyres have revealed that bacterial plankton populations frequently are stratified.
Members of the SAR202 clade, in the green non-sulfur bacteria (GNS) phylum (46), as
well as the SAR406 clade related to Fibrobacter (52), the SAR324 clade of δProteobacteria (149), and marine group I Archaea (47, 65, 82) display vertical
distribution patterns often times coupled to other physical and biological parameters.
Microbial diversity surveys in coastal surface waters have revealed that these
environments harbor some organisms that are also found in open-ocean surface waters,
such as α-Proteobacteria in the SAR11 and SAR116 clades. Other taxa are more
frequently detected in coastal environments. These include the OM43 clade of βProteobacteria related to type I methylotrophs (102, 103), γ-Proteobacteria in the
OM60/NOR5 and SAR92 clades (20, 122), and α-Proteobacteria affiliated with the
18
Roseobacter clade (15). Analyses of bacterial community structure in response to
upwelling induced primary production have been reported off the coast of Oregon. 16S
rRNA gene clone sequencing in conjunction with fluorescence in-situ hybridization
showed that bacterioplankton communities during diatom bloom events differ from nonbloom communities, with members of the genus Pirellula and the OM43 clade increasing
during these periods (89). These studies have painted a detailed picture of the organisms
residing in the surface layer of coastal ecosystems. However, knowledge pertaining to
microbial diversity below the surface layer, yet above the benthos, is lacking for shallow
coastal environments.
In shallow seas, the BBL is coupled to physical processes at the surface, such as
wind and waves (53). In deep ocean BBLs, bacteria experience low concentrations of
labile organic matter and low temperatures whereas in shallow seas, particulate organic
matter, including cells sinking from the surface, can transit the water column quickly and
enter this region (136). From the perspective of ocean stratification, BBLs in shallow
oceans are interesting because decomposition processes (DOM re-mineralization) are
compressed vertically, making them susceptible to hypoxia and anoxia. Because
microbial communities are important drivers of global nutrient cycles, investigating the
phylogeny of the organisms residing in shallow coastal BBLs is a necessary first step in
elucidating their putative biogeochemical functions.
The goal of this study was to examine bacterial diversity in the bottom boundary
layer in near shore regions (< 100 M) of the Oregon shelf, as a part of a long-term study
of seasonal hypoxia in this region. Analyses of two years of samples, collected during
the spring and summer, showed that the bottom boundary layer microbial community is
distinctly different from the surface microbial community, and harbors previously undescribed microbial taxa specific to this environment.
19
Materials and Methods
Site Description
Samples for this study were collected along the Strawberry Hill (SH) line (North Lat.
44°15 ’N) at stations SH50 (West Long. 124°10’ W) and SH100 (West Long. 124°27’
W) on the RV Elakha. The water depth at station SH50 is 50 meters, and at station
SH100 is 100 meters. Samples were collected in the surface (5 m) and bottom boundary
layers (1-10 m above sediment). Ship movement due to wave action can influence the
exact placement of water collection equipment and other types of data analysis tools. We
maintained a distance of at least 1 meter above the benthic water interface for all samples
collected, however, during rougher periods, we were more conservative in our collection
approach, allowing up to 10 meters in order to insure that the benthos not be disturbed.
For a comprehensive list of samples used in this study see Table 1.1.
Environmental Parameters
Conductivity, temperature, salinity, and oxygen were measured using a vertical profiling
system with a mounted oxygen sensor (Sea-Bird Electronics Inc., Bellevue, WA).
Dissolved oxygen sensor values were standardized using Winkler titrations.
Sampling and DNA extractions
Seawater was collected using a 30 L Niskin bottle (General Oceanics Inc., Miami Fl), and
distributed into 20 L sterile polyethylene carboys. Water samples were filtered onto 0.2
µM polysulfone filters (Pall-Gellman, Ann-Arbor MI). Immediately after collection,
filters were frozen in sucrose lysis buffer (50 mM Tris-HCl, 40 mM EDTA, 0.75 M
sucrose) and stored at -80 ºC until processing. Community DNA was isolated as
described previously (52). In brief, DNA was isolated using a phenol
chloroform/isoamyl-alcohol extraction, followed by density centrifugation using cesium
trifluoracetic acid to separate high-molecular weight community ribosomal RNA from
DNA.
20
Terminal Restriction Fragment Length Polymorphism Analysis
For analysis of bacterial SSU 16S rRNA genes by T-RFLP using the enzyme BsuR1, 20
ng of environmental DNA was amplified with the bacteria-specific primer 8F and the
universal primer 519R (90). The 8F primer was 5’ end labeled with the phosphoramidite
fluorchrome 5-carboxy-fluorescein. PCR reactions contained final concentrations
consisting of 0.25 units Taq Polymerase (Fermentas, Glen-Burnie MD), 2.5 mM MgCl2,
0.2 mM deoxyribonucleotides, and 0.2 µM of each primer. PCR amplifications were
performed in a PTC-0200 Thermocycler (MJM Technologies, Cambridge MA) using the
following conditions; 28 cycles of 94 °C for 30 s, 55 °C for 1 min, 72 °C for 2 min.
FAM-labeled products were visualized on a 1% agarose gel, and cleaned using the
QIAquick PCR clean-up kit (Qiagen, Valencia CA). The reaction product was then
digested at 37 °C for 6 hours with the restriction enzyme BsuRI. Digests contained 10
units of restriction enzyme per reaction in 1X Buffer R (Fermentas). Digested FAMlabeled products were cleaned using Sephadex G-50 (Applied Biosystems, Foster City,
CA). Applied Biosystems Genotyper software was used to assess fragment lengths based
on the size of the internal standard Map-Marker (Applied Biosystems), which contained
23 discrete size fragments ranging from 50-1000 bp. PCR products for analysis with the
enzyme Hin6I were treated similarly as with the enzyme BsuR1 with the following
exceptions, DNA was amplified for 26 cycles rather than 28, PCR reactions contained 1
unit of the enzyme Bovine Serum Albumin. Enzyme digests were ethanol precipitated
using 2 volumes ethanol and 0.1 volume sodium acetate. Digests were vacuum dried and
re-suspended in sterile water, and then analyzed.
Statistical Analyses of Community Structure
Prior to the analyses, terminal restriction fragment length polymorphisms were noisefiltered by eliminating fragments that did not contribute to at least 1% of the relative
flourescence in each sample. Noise-filtered relative fluorescence values were then used
for further statistical analysis. Fragments that did not contribute to at least 2 samples were
removed. Hierarchical clustering analysis and multidimensional scaling were performed
21
in version 6 of the software package Primer (Plymouth Marine Laboratories, Plymouth
UK). In brief, a distance matrix was calculated using the Bray-Curtis distance measure.
Hierarchical cluster analysis was performed on the resulting matrix. Multidimensional
scaling analysis was performed on the Bray-Curtis matrix using 25 re-starts and a
minimum stress of 0.01. Analysis of similarity (ANOSIM) was used to test the nullhypothesis of no difference between surface and bottom boundary layer samples. The
software package R was used for regression analysis of relative terminal restriction
fragments against environmental parameters. The significance of each fragment was
examined by testing the correlation between each fragment's logit transformed relative
abundance and depth with the cor.test function of the program R, using the BenjaminiHochberg procedure to correct p values for multiple testing.
16S rRNA Gene Cloning
A 16S SSU rRNA gene clone library was constructed from July 30th, 2008 at station
SH100, station depth of 100 m (Table 1). 16S rRNA genes were amplified using primers
8F and 926R (75). PCR products were amplified with 35 cycles of 94 °C for 30 s, 55 °C
for 1 min, 72 °C for 2 min. Cleaned PCR products were ligated into the pGEM T-easy
vector (Promega, Madison WI) overnight at 4 °C, and the resulting ligation was cloned
into E. coli-DHα chemically competent cells (Invitrogen; Madison WI) as described
previously (46). Clones containing the correct size insert were end-sequenced using the
primer M13F (5'-ATT AAC CCT CAC TAA AGG GA-3’) to produce nearly full length
single strand sequence. Clones from this study were labeled with the library pre-fix ‘ORSH100-100m’. A total of 106 clones from the library corresponding to July 30th SH100100m were end sequenced, of which 90 were identified as non-chimeric and further
analyzed. These clones were digested in-silico with BsuR1 and Hin6I to determine the insilico fragment lengths. Based on these predicted restriction sites, candidate clones were
then selected for analysis by tRFLP to compare predicted and observed restriction site
lengths (which often differ slightly), and to match the phylogenetic identification with the
22
environmental TRFLP peaks (Table 2). Sequence information has been deposited into
Genbank, accession numbers HQ149693, HQ173717-HQ173805.
Phylogenetic Analysis & taxonomic assignment
Cloned sequences were edited to remove vector contamination with Vec-Screen, an
online tool for sequence analysis based on the BLAST algorithm (2). Edited sequences
were aligned with the NAST- alignment tool in Green-Genes and then analyzed with
Bellerophon to identify putative chimeras (28, 29). Sequences were imported into the
software package ARB and aligned to the SILVA alignment version 92 (80). Sequence
alignments were then manually edited and phylogenetic trees were constructed. Treetopologies were analyzed using neighbor-joining, maximum-likelihood, and parsimony
phylogenetic analyses; boot-strap values were based on 1000 re-samplings.
Results
Bacterioplankton Community Structure
Bacterial community structure was assessed by T-RFLP targeting the 16S rRNA gene of
bacteria with two independent restriction enzymes (BsuR1 & Hin6I). Hierarchical
clustering and multidimensional scaling analyses of relative fragment abundances
supported a clear distinction between samples collected in the surface area of the water
column and those collected in the BBL, with BBL samples forming a distinct cluster at
the 40% similarity level under both analyses (Figure 1.1). Analysis of similarity
(ANOSIM) also supported a significant difference in community structure between
surface and BBL communities (R = 0.427, 0.426 with BsuR1 and Hin6I, respectively, p
value < 0.001).
To identify bacterial taxa associated with the BBL, we examined the contribution
of individual terminal restriction fragments to the BBL cluster in each ordination, and
evaluated the depth dependency of each fragment by regression analyses. Overall, six
terminal restriction fragments were identified that significantly contributed to the bottom
boundary layer, four were identified with enzyme BsuR1 (287, 254, 253, and 323 bp) and
23
two were identified with Hin6I (340, 354) (Figure 1.2 A-F, respectively, Table 1.2). To
determine the taxonomic identities of these fragments, a 16S rRNA gene clone library
was phylogenetically characterized and analyzed for the aforementioned fragments.
Lineage identification-BsuR1
Clone library analyses identified several clones with a 323 bp signature. These clones
corresponded to a group of γ-Proteobacteria in the ARTIC96BD-19 clade (Figure 2.2C,
Figure 2.3). This clade is comprised of clones from several marine 16S rRNA gene
surveys, in addition to an uncharacterized bacterial strain (HTCC8012), which was
isolated from coastal Oregon seawater by dilution to extinction culturing (123). These
clones were 99% similar to strain HTCC8012 and 93% similar to the putative sulfuroxidizing symbiont of the hydrothermal vent clam Calyptogena magnifica.
Clones attributed to a 254 bp restriction fragment formed a novel clade in the
order Chromatiales of the γ-Proteobacteria (Figure 2.2A, Figure 2.3). This clade has no
cultured representatives. The nearest relatives in the NCBI-nr database were retrieved
from the Saniich Inlet, British Columbia (clone SHBC668). The physiologically
described organisms closest to this clade are purple sulfur bacteria in the family
Ectothiorodospiraceae (87-89%). Boot-strap support for this clade based on neighborjoining analysis was greater than 70%, and tree-topologies based on parsimony and
maximum likelihood were congruent, suggesting this is a novel marine group, referred to
as the Eastern North Pacific Chromatiales clade (ENPC clade).
Clones with fragment sizes of 287 bp were identified as the 6N14 clade of
uncultured microorganisms related to the genus Pirellula (Figure 2.2B, Figure 2.4). This
clade was named after fosmid clone 6N14 (98-99% to sequences retrieved here) (139),
constructed from nucleic acids collected near the edge of the continental shelf off the
coast of Oregon (117). The nearest cultured representative to these clones is
Rhodopirellula baltica SH1, at 93-94% sequence similarity.
24
A clone corresponding to a fragment size of 253 bp was affiliated with the
uncharacterized agg8 clade of the phylum Planctomycetes (Figure 2.2D, Figure 2.4). This
clade also contained representatives from 16S rRNA gene surveys of marine bacterial
diversity studies, including those of phytoplankton aggregates (26). The clone retrieved
in this study was 99% similar to the 16S rRNA gene located on the fosmid clone 6FN
(148). The closest cultured representative to the clone retrieved in this study is
Planctomyces maris (84% similar).
Lineage Identification-Hin6I
The additional information provided by the digestion with Hin6I enabled us to
identify two organisms that were statistically associated with the bottom boundary layer
community (Figure 2.2E & F, respectively). Clones producing terminal restriction
fragments of 354 bp were identified as members of the OM60/NOR5 clade of marine γProteobacteria. Several microorganisms from this clade have been retrieved in culture,
Congribacter litoralis strain KT71 represents the physiologically best described organism
(92-93% similar to clones reported here), and HTCC2148 is a cultured organism most
closely related to clones reported here (99-100% similar Figure 2.3).
Sequences producing terminal restriction fragments of 340 bp were attributed to
two sub-clades of the marine Roseobacter group, referred to here as the MB11C09 and
ULA23 clades (Figure 2.5). These environmental clades contain no cultured
representatives. The closest physiologically described organisms to the MB11C09 clade
are is Marinosulfinomonas methylotropha (94-95%), while the nearest cultured
representative to the ULA23 clade is Ruegeria pomeroyi (90%).
Discussion
This study provided evidence in support of the hypothesis that surface and bottom
boundary layer communities located in shallow regions of coastal Oregon are different,
and identified several taxa that are associated with the BBL. Multivariate statistical
analysis (hierarchical clustering, multidimensional scaling, and ANOSIM analysis) using
25
two separate TRFLP analyses of environmental samples revealed evidence in support of
the hypothesis that the surface and bottom boundary layer are distinctly different. The
partitioning of community structure by depth has emerged as a common theme in marine
environments (46), but this is the first report to focus on the distinctive composition of
the bottom boundary layer microbial community in the shallow inner-shelf region off the
coast of Oregon. Due to its close proximity with the benthos and lower ventilation in
comparison to the surface waters, especially during summer months, this community is
often first to experience hypoxic and anoxic conditions (54).
We observed three distinct γ-Proteobacteria clades specifically associated with
the bottom boundary layer: ARTIC96BD-19, the novel ENPC, and OM60/NOR5. The
ARTIC96BD-19 clade has been recovered in 16S rRNA gene surveys from various
marine environments, including open-ocean and coastal samples from various depths (5,
129, 153). This clade accounted for a substantial proportion of the 16S rRNA genes
recovered from the permanent oxygen minimum zone of northern Chile (119), and is
closely related to putative thiotrophic symbionts of metazoans in the SUP05
environmental clade (142).
A second BBL clade was in the order Chromatiales. These clones were not
significantly related to any physiologically described organisms (16S rRNA gene
similarity <97%), and are referred to as the Eastern North Pacific Chromatiales Clade
(ENPC; Figure 2). The nearest 16S rRNA gene sequences to clones reported here were
recovered from the Saanich Inlet of British Columbia, an area that experiences seasonal
anoxia (142). Several members of the order Chromatiales are capable of anaerobic
anoxygenic photosynthesis. Commonly referred to as purple sulfur bacteria, these
organisms are often found in low oxygen aquatic environments, where they utilize
reduced sulfur compounds as electron donors to fuel photosynthesis (96).
The closest physiologically described organisms to ENPC are members of the
family Ectothiorhodospiraceae. Isolates from this family are known to inhabit lake
systems, colonizing phytoplankton biomass under anoxic conditions while oxidizing
26
reduced sulfur compounds (14). 16S rRNA gene similarities of clones described here
were not high enough to cultured representatives to make any assumptions regarding the
physiologies of these organisms. However, the ecological distribution of both the order
Chromatiales and the ARTIC96BD-19 clade in other low oxygen aquatic environments,
in conjunction with their evolutionary relationships to other characterized or putative
sulfur oxidizing bacteria, may be taken as evidence in support of the hypothesis that
microbial metabolisms involving reduced sulfur compounds could be occurring in bottom
boundary layers off the coast of Oregon.
Previous investigations of volatile sulfur compound production during the
respiration of algal biomass under anaerobic conditions have shown that hydrogen sulfide
and other reduced sulfur compounds can be produced in large quantities (32, 152).
Hydrogen sulfide fluxes from the benthos have been observed in other productive coastal
environments, such as the south Atlantic off the coast of Namibia (32). A recent
molecular diversity survey has provided evidence to suggest that these fluxes are
consumed by γ-Proteobacteria closely related to putative sulfur oxidizing symbionts
(76). Whether similar biogeochemical processes are occurring off the coast of Oregon
remains to be determined. Dissolved oxygen was present in all of the samples described
in this study (2.55-0.65 ml/L) and nitrate, although not measured here, is typically found
in the BBL in micro-molar concentrations (10-30 µM). Both are potential electron
acceptors for the oxidation of hydrogen sulfide. While transient hypoxia (DO<1.4 ml/L),
severe hypoxia (DO<0.5 ml/L), and anoxia (undetectable oxygen) have been reported off
the coast of Oregon in recent years (18), only hypoxic and non-hypoxic samples were
detected in the BBL environment during this study (2007-2008). Surprisingly perhaps,
dissolved oxygen concentrations were not significantly correlated with microbial
community composition in the BBL.
The third γ-proteobacteria clade associated with the bottom boundary layer was
OM60/NOR5. These organisms are commonly retrieved during ribosomal gene surveys
of coastal surface waters, where they reach as much as 11% of the total bacterial numbers
27
(150). In a previous study, direct quantification of the OM60/NOR5 clade along a
longitudinal gradient off the coast of Oregon revealed a clear increase in cell density in
the coastal zone, with a vertical distribution coupled to the deep-chlorophyll maximum
(20). Congribacter litoralis KT71, the first characterized member of the OM60/NOR5
clade, is an aerobic anoxygenic photosynthetic (AAnP) organism that grows optimally at
oxygen partial pressures of 12%, and the photosynthetic antennae complex in KT71 is
regulated in response to oxygen and light (115). Clones described in this study were very
similar to HTCC2148 (99-100%), yet too diverged from KT71 for physiological
inferences (132). The presence of members of the OM60/NOR5 clade in a coastal bottom
boundary layer sheds new light on the distribution of OM60/NOR5 representatives.
Two environmental clades of Planctomycetes (6N14 and agg8) were associated
with the BBL. Clones affiliated with 6N14 were similar to the 16S rRNA gene located on
the large insert clone 6N14 (97-99%) (117, 139), which was recovered previously from
samples collected from particulates off the coast of Oregon at a depth of 200 m (117).
Recent sequence analysis of this 42 Kbp fosmid sequence revealed gene suites involved
in the degradation of phytoplankton detritus, such as glycosyl hydrolase, in addition to
genes involved in phosphate acquisition, such as 3-dehydroquinate synthase (148).
Interestingly, the closest cultured representative to the 6N14 cluster is Rhodopirellula
baltica (93-94% sequence similarity), which possesses micro-aeroboic and anaerobic
gene suites, such as cytochrome d oxidase and a putative fermentative pathway,
respectively (49). Additionally, the genome of R. baltica contains 110 putative
sulfatases. Glöckner and colleagues hypothesized that these genes would be
advantageous for accessing sulfated carbon compounds in a nutrient depleted
environment. 16S rRNA gene similarities were not significant enough to make a direct
link between clones recovered in this study and R. baltica.
The second Planctomycetes clade associated with the BBL was the agg8 clade
(26). The clone recovered here was 97% similar to a sequence from clone 6FN, recovered
previously from the continental shelf off the coast of Namibia, a region that experiences
28
pronounced deficits in dissolved oxygen. Sequence analysis of this 40 kbp fosmid library
revealed gene suites involved in methylotrophy, such as a formylmethanofuran
dehydrogenase, and a methonal dehyrogenase regulator (148). The closest cultured
representative to this clade is Planctomyces maris at 84% similarity to clones described
here, far too diverged for any meaningful 16S rRNA gene comparisons.
The Planctomycetes are a physiologically, ecologically, and genetically
distinctive phylum. These organisms utilize protein rather than peptidoglycan in their cell
wall, are capable of intracellular compartmentalization, divide by budding, and some
isolates are capable of gliding motility. Planctomycetes are frequently recovered in
freshwater and marine ecosystems and are often attached to particulate matter, including
algal cells, by means of specific holdfast structures. They typically produce flagellated
swarmer cells, apparently enabling them to colonize new surfaces. We postulate that the
propensity of Planctomycetes for particle colonization makes them well-adapted to
occupy the BBL, where organic matter accumulates and is re-circulated by turbulence
during decomposition.
Two uncharacterized lineages in the marine Roseobacter group were affiliated
with the bottom boundary layer. The Roseobacter group is commonly recovered during
16S rRNA gene surveys of marine environments (50, 51, 102), with higher frequency in
coastal environments (15). Cultivated members of the Roseobacter clade are
metabolically diverse, capable of utilizing a wide range of carbon and sulfur compounds
(15). Specifically, certain Roseobacter clade members utilize the reduced sulfur
compound dimethylsulfoniopropionate, having a tremendous impact on the global sulfur
cycle (50, 51, 59), and in addition, several cultivated representatives contain gene suites
involved in the oxidation of reduced sulfur compounds, specifically the sox gene cluster.
Like the Planctomycetes, members of this clade are often found in physical association
with algal biomass, suggesting a link between this group and primary productivity (89,
112).
29
Conclusions
The goal of this study was to examine the bacterial community associated with the
bottom boundary layer off the coast of Oregon. The analysis provided strong statistical
support for taxa specifically associated with the bottom boundary layer. Two of these
clades, the γ-Proteobacteria OM60/NOR5 clade and α-Proteobacteria in the
Roseobacter clade, harbor both taxonomically described and genome sequenced
organisms. However, the 16S rRNA gene similarities of clones recovered in this study
were too diverged from characterized isolates to draw meaningful comparisons between
these organisms. Two of the environmental (un-described) clades - ARTIC96BD-19 and
ENPC - are distantly related to either organisms that can oxidize hydrogen sulfide or
harbor the necessary genetic components to do so. Two BBL clades were affiliated with
uncultured Planctomycetes clades 6N14 and agg8. Both Planctomycetes and Roseobacter
organisms are often found particle associated.
Re-suspended matter from benthic surface environment is a likely source of
bacterial diversity in the bottom boundary layer, especially during turbulent mixing
events. The benthic subsurface often contains layers where there is very little or no
oxygen, and hydrogen sulfide from sulfate reducing bacteria can accumulate. Given the
presence of transient hypoxic and anoxic conditions in the bottom boundary layer, the
benthic surface and subsurface environments may provide a source of microorganisms
that colonize the BBL environment during transient hypoxic events. A study of the
diversity of organisms in free-living, aggregate associated, and sediment surface
associated communities in the shallow intertidal zone of the Wadden Sea suggested
considerable overlap between the three community types, suggesting that exchange
processes between these communities may be occurring (118). Whether similar exchange
processes occur between the benthos and BBL community off the coast of Oregon
remains to be determined.
We contrasted the BBL community with the surface community to identify taxa
that might be specifically associated with this region of the water column where DOM
30
decomposition is elevated, photosynthesis is minimal, and oxygen demand is high.
Future studies aimed at understanding the geochemistry of marine DOM oxidation and
coastal hypoxic zones may find the unusual micro-flora of this habitat fruitful topics for
investigation.
31
Table 2.1. Sample collection dates, location, and associated environmental parameters.
Date
Lat. (˚N)
April 2nd 2007
44.15
April 2nd 2007
44.15
May 7th 2007
44.15
June 7th 2007
44.15
June 7th 2007
44.15
July 11th 2007
44.15
July 11th 2007
44.15
April 8nd 2008
44.15
May 14th 2008
44.15
June 18th 2008
44.15
June 18th 2008
44.15
June 26th 2008
44.15
July 21st 2008
44.15
July 21st 2008*
44.15
July 21st 2008
44.15
July 21st 2008
44.15
July 30th 2008
44.15
July 30th 2008
44.15
July 30th 2008
44.15
July 30th 2008*
44.15
Station
Long. (˚W) Designation Depth Designator
124.1
SH50
surface
SH50
124.1
BBL
SH50
124.1
surface
SH50
124.1
surface
SH50
124.1
BBL
SH50
124.1
surface
SH50
124.1
BBL
SH50
124.1
surface
SH50
124.1
surface
SH50
124.1
surface
SH50
124.1
BBL
SH50
124.1
BBL
SH50
124.1
surface
SH50
124.1
BBL
SH100
124.7
surface
SH100
124.7
BBL
SH50
124.1
Surface
SH50
124.1
BBL
SH100
124.7
surface
124.7
SH100
BBL
*16S rRNA gene clone library constructed from sample
Temp. (°C)
9.87
8.91
11.08
11.27
7.58
10.1
7.28
9.03
9.64
9.35
7.2
7.13
9.19
7.12
9.46
6.88
10.21
7.51
11.64
7.1
Sal. (ppt)
31.7
33.65
31.66
33.1
33.92
33.35
33.94
31.77
32.63
33.48
33.94
33.94
33.4
33.92
33.2
33.98
33.76
33.93
33.32
33.96
Density (σ)
24.4
26.07
24.16
25.25
26.48
25.65
26.54
24.59
25.16
25.87
26.56
26.56
25.83
26.55
25.64
26.63
25.94
26.5
25.35
26.58
Oxygen (ml/L)
8.71
2.55
7.73
10.68
2.04
5.24
0.7
7.68
8.42
4.61
1.21
1.21
5.24
1.19
6.29
0.61
8.33
1.88
8.69
0.65
32
Table 2.2. R values for depth computed with the enzymes BsuR1 (A) and Hin6I (B). Only
fragments that showed correlation values of 0.70 or greater with Benjamini-Hochberg corrected
p-values of less than 0.05 are reported. Phylogenetic associations for observed fragments are
listed as well as an index describing the initial phylogenetic characterization of each organism
from the marine library.
33
Figure 2.1.NMDS analysis of relative terminal restriction fragments produced from
samples collected in this study with the enzymes BsuR1 (A) and Hin6I (B). Hierarchical
clustering analysis was performed as well, and similarity levels based on these analyses
are represented at the 40% similarity level. Samples are labeled with the month, day, and
year followed by the site designation. Example; 040207_SH50 is interpreted as April 2nd
2007 site SH50.
34
Figure 2.2. Individual terminal restriction fragment contributions to the NMDS
ordinations based on analysis with BsuR1 (A-F) and Hin6I (E-F). The inset of each plot
indicates the relative abundance of a given fragment.
35
Figure 2.3.Neighbor-joining tree describing the phylogeny of 16S rRNA genes affiliated
with the γ-Proteobacteria from this study (red) that could be assigned to environmental
fragments showing a positive correlation with depth. The observed fragment size for
selected 16S rRNA gene clones (indicated by a *) is in red parentheses below each clone.
Sequences affiliated with the SILVA92 reference database included with the ARB
software package are listed as well. NCBI accession numbers followed by clone
indicators or organism names are listed, respectively. Boot-strap support values of 70%
or greater based on 1000 re-samplings. Polaribacter dokodonesis MED154 was used as
the out-group (not shown).
36
37
Figure 2.4. Neighbor-joining tree describing the phylogeny of 16S rRNA genes affiliated
the Planctomycetes from this study (red) that could be unambiguously assigned to
environmental fragments showing a positive correlation with depth. The observed
fragment size for selected 16S rRNA gene clones (indicated by a *) is in red parentheses
below each clone. NCBI accession numbers followed by clone indicators or organism
names are listed, respectively. Boot-strap support values of 70% or greater based on
1000. Polaribacter dokodonesis MED154 was used as the out-group.
38
39
Figure 2.5.Neighbor-joining tree describing the phylogeny of 16S rRNA genes affiliated
the Roseobacter group from this study (red) that could be assigned to environmental
fragments showing a positive correlation with depth. The observed fragment size for
selected 16S rRNA gene clones (indicated by a *) is in red parentheses below each clone.
NCBI accession numbers followed by clone indicators or organism names are listed,
respectively. Boot-strap support values of 70% or greater based on 1000 re-samplings.
Alcanivorax borkumenesis was used as the out-group.
40
41
Phylogenetic diversity of Archaea in the bottom boundary layer of the continental
shelf off the coast of Oregon
Anthony D. Bertagnolli and Stephen J. Giovannoni
Unpublished results
42
Abstract: A previous investigation regarding the phylogeny of bacteria in the bottom
boundary layer (BBL) off the coast of Oregon revealed novel lineages associated with
this environment (Chapter 2). To expand upon knowledge regarding microbial diversity
in these areas, we phylogenetically characterized Archaea associated with the BBL by
16S rRNA gene cloning and sequencing. Marine Group-I (MGI) Crenarcheoata closely
related to Nitrosopumulis maritimus SCM1 were the dominant group, followed by a
second MGI Crenarcheota group referred to here as the SB95-57 clade. A single clone
affiliated with Euryarcheota was recovered, displaying sequence similarity to cells
present in a methylotrophic methanogen enrichments (99%) and Methanococcoides
burtonii (98%). To our knowledge this is the first report regarding the Archaeal
assemblage affiliated with the BBL in the Northeast Pacific Ocean off the coast Oregon,
and the first to report on the presence of a putative methanogen residing in these areas.
43
Introduction
The initial discovery of previously un-described Archaeal lineages in coastal surface
waters represented a major milestone in microbial oceanography (25). Since 1992,
significant progress has been made in describing the ecology of pelagic marine Archaea.
A consensus has been reached that describes two evolutionarily distinct groups which
compromise a majority of the dominant lineages retrieved from open-ocean and coastal
ecosystems (i.e. greater than 1%). These two groups, the Marine Group I Crenarchaea
(MGI), and the Marine Group II Euryarchaea (MGII), show distinct distribution patterns,
with MGI dominating below the euphotic zone in oligotrophic and coastal oceans, and
MGII dominating primarily in the euphotic zones of coastal zones (65, 82).
The earliest clues into the biogeochemical relevance of MG1 Crenarcheaota
came from environmental genomics. Studies linking non-thermophilic Crenarcheaota
with nitrification initially stemmed from sequencing of fosmid libraries in soil (13). The
presence of an ammonia monooxygenase gene in close proximity to a Crenarchaeal 16S
rRNA gene led to the hypothesis that non-thermophilic Crenarcheota maybe involved in
ammonia oxidation. The application of similar metagenomics enabled approaches with
samples from marine environments quickly followed, and provided further evidence in
support of this hypothesis (33, 134, 138). Cultivation efforts, genome sequencing, and
physiology experiments on the first isolated MGI member, Nitrosopumulis maritimus
SCM1, have revealed that it is an autotrophic ammonia oxidizing Archeon, with an
unusually high affinity for ammonium compared to other organisms (71, 81, 141). SCM1
and its MGC1 relatives can occupy up to 30% of the bacterioplankton population below
the euphotic zone of some oligotrophic and coastal areas, and are likely the major
microbial groups mediating the balance between ammonium and nitrite throughout the
ocean.
Continental shelves are dynamic, highly productive ecosystems that are of crucial
ecological significance, providing a substantial proportion of global primary production.
The Oregon continental shelf is particularly interesting in light of recent observations of
44
severe hypoxia and anoxia in shallow coastal areas (2). These phenomena have obvious
consequences to fish and other wildlife (30). However, the impact that these events have
on microbial communities is still being investigated. Chapter 2 revealed that the bottom
boundary layer harbors a distinct bacterial community, including some putatively novel
groups such as the Eastern North Pacific Chromatiales Clade (ENPC) in the γProteobacteria. While the biogeochemical role that ENPC play in coastal ecosystems is
still unclear, their evolutionary relationships to characterized thiotrophic bacteria suggest
these organisms may utilize reduced sulfur compounds to proliferate in the BBL.
Given the ubiquity and biogeochemical significance of Archaeal communities in
marine systems, our objective was to investigate the 16S rRNA gene diversity of these
organisms in the BBL off the coast of Oregon. This area of the water column is relatively
un-explored in terms of microbial diversity, with few studies regarding the phylogenetic
affiliations of organisms being reported. Bottom boundary layers are important from a
biogeochemical perspective, as re-mineralization processes are elevated at the expense of
dissolved oxygen, leading to seasonal hypoxia and in certain cases anoxia. Additionally,
the close proximity of these environments to sediments yields a complex coupling of
benthic and pelagic processes, which may significantly impact oceanic nutrient cycles.
Materials and Methods
Sampling and DNA extractions:
Seawater was collected using a 30 L Niskin bottle (General Oceanics Inc., Miami Fl), and
distributed into 20 L sterile polyethylene carboys. Water samples were filtered onto 0.2
µM polysulfone filters (Pall-Gellman, Ann-Arbor MI). Immediately after collection,
filters were frozen in sucrose lysis buffer (50 mM Tris-HCl, 40 mM EDTA, 0.75 M
sucrose) and stored at -80 ºC until processing. Community DNA was isolated as
described previously (44). In brief, DNA was isolated using a phenol
chloroform/isoamyl-alcohol extraction, followed by density centrifugation using cesium
45
trifluoracetic acid to separate high-molecular weight community ribosomal RNA from
DNA.
16S rRNA gene cloning:
An Archaeal 16S SSU rRNA gene clone library was initially constructed from samples
acquired on July 30th, 2008 at station SH100, the depth of sampling was between (1-10m
above the benthos). 16S rRNA genes were amplified using the Archaeal specific forward
primer 20F and the universal primer 1492R. PCR products were amplified with 35 cycles
as described previously. Cleaned PCR products were ligated into the pGEM T-easy
vector (Promega, Madison WI) overnight at 4 °C, and the resulting ligation was cloned
into E. coli-DHα chemically competent cells (Invitrogen; Madison WI). Blue-white
screening was then used to screen colonies. White colonies (positive transformants) were
analyzed by tooth-pick PCR with M13F and M13R. Seventy-four positive inserts with
sizes of approximately 1.6 Kbp were identified and analyzed by RFLP with the restriction
enzyme BsuR1. Based on these analyses, 22 unique RFLP patterns were identified and
partially end sequenced, of which 21 produced quality sequence for further analyses.
Putative Archaeal clones were identified based on preliminary BLASTN analyses and
used for downstream phylogenetic analyses (Figure 1). Several of the 16S rRNAs
displayed best BLASTN pairs to eukaryotic plastid 16S rRNA genes, likely due to the
non-pre-filtered nature of the samples in conjunction with the non-archaeal reverse
primer combination. These sequences were not analyzed any further.
Phylogenetic analysis & taxonomic assignment:
Cloned sequences were edited to remove vector contamination with Vec-Screen, an
online tool for sequence analysis based on the BLAST algorithm (2). Edited sequences
were aligned with the NAST- alignment tool in Green-Genes and then analyzed with
Bellerophon to identify putative chimeras (28, 29). Sequences were imported into the
software package ARB and aligned to the SILVA alignment version 92 (80). Aligned
sequences were initially added to the backbone 16S rRNA tree in the ARB software
46
package using the parsimony tool. Sequence alignments were then manually edited and
phylogenetic trees were constructed. Tree-topologies were analyzed using neighborjoining, maximum-likelihood, and parsimony phylogenetic analyses, and were supported
by boot-strap values of at least 70% for neighbor-joining based on 1000 re-samplings.
Results and Discussion:
Archaeal 16S rRNA genes recovered in the BBL library fell amongst several
previously described lineages collected primarily from the water column of marine
environments. Nitrosopumilis maritimus SCM1 relatives were the dominant group
(36/74). Clones described here were between 99-96% similar to SCM1 (Figure 3.1). The
recovery of SCM1 like lineages in coastal ecosystems is not surprising, and confirms
previous observations regarding the ubiquity of MG1 Crenarcheaota in coastal
environments. The presence of SCM1 relatives in this ecosystem does suggest that
Archaea may potentially be mediating ammonia oxidation in these systems.
A second MG1 clade was recovered. This clade, referred to here as the SB95-57
clade, is distantly related to SCM1, and was recovered in substantially lower proportions
(1/74 clones, 93% to SCM1) (Figure 3.1). The nearest relatives to this clone were
recovered from the mesopelagic zone of the Pacific Ocean, an oligotrophic gyre.
Unfortunately, a cultured representative of this group has yet to be obtained, and the
physiological capabilities of these organisms remain unresolved.
Although detected in lower frequency, a single 16S rRNA gene affiliated with a
methanogenic enrichment culture from the sediments of Skan Bay Alaska was present
(99% to near-neighbor) (67). The closest cultivated representative to this 16S rRNA gene
is Methanococcoides burtonii, a physiologically characterized and genome sequenced
organism (98% similar) (1).
M. burtonii and near relatives (based on 16S rRNA gene similarity) utilize
methylated substrates, rather than CO2, in methanogenesis (67). The presence of
methylotrophic methanogenesis is of particular significance in anoxic, yet sulfate replete
47
environments, where hydrogenotrophic bacteria are typically out-competed by sulfur
reducing bacteria (68, 70). Genome sequencing of M. burtonii revealed the genetic
potential for adapting to a dynamic environment, with signal transduction genes
significantly over-represented. Of interest were 19 putative two-component histidine
kinases containing PAS domains (1). PAS containing histidine kinases were speculated as
having a putative role in sensing dissolved gas. Allen et. al. hypothesized that M. burtonii
may have to cope with fluxes of oxygen in cold environments (ie. sediments) due an
increase in oxygen solubility with decreased temperatures, such as those seen observed in
sediment environments (1). As well, M. burtonni contains a putative coenzyme F420dependent sulfite reductase. This enzyme could be useful in detoxifying hydrogen
sulfide, a compound that often accumulates in anaerobic sediment environments during
sulfate reducing periods in subsurface environments.
Methane production has been observed in anoxic sulfate saturated hyper-saline
algal mats, where the speculated substrate for methylotrophy was tri-methlyamine (TMA)
derived from glycine betaine (69). BBL environments often experience enhanced periods
of primary productivity, which could provide a rich source of TMA, as this compound is
often used as an osmolite in certain eukaryotic species. Dissolved oxygen was present
during the time of sample collection, making methanogenesis unlikely. The presence of a
given 16S rRNA gene does not allow for direct inference of a given metabolism.
However, the recovery of a putative methylotrophic methanogen in a coastal BBL does
suggest that, under the appropriate conditions, these environments harbor organisms that
make hypotheses regarding methane formation in coastal BBLs feasible.
Conclusion
The 16S rRNA genes recovered in our library suggest that coastal BBLs harbor
organisms maybe able to oxidize ammonia and transform methylated compounds. Both
of these pathways impact carbon and nitrogen cycling, and our data support a more
comprehensive study of both processes in coastal ecosystems. Recently, much attention
has been focused on methane saturation in ocean surface waters, an interesting
48
observation given the high amount of oxygen that would inhibit classical
methanogenesis. This phenomena has been termed the “ocean methane paradox”. Karl et.
al. suggested that the production of methane in ocean surface waters could be a product
of aerobic decomposition of methylphosphonate to methane. While this path is certainly
feasible, our data suggest that BBL environments may harbor the microbial components
for methane production. It is generally assumed that most methane produced in coastal
sediments is consumed before reaching the water column. The 16S rRNA genes retrieved
in this study were related to sediment derived enrichments and described organisms.
Thus, it could well be that the close proximity of the BBL to the benthos can, at certain
times and conditions, provide these areas with organisms capable of producing methane.
Observations described here should be used in further evaluating the sources and sinks of
biological methane production in the marine environment.
49
Figure 3.1.Neighbor-joining tree describing the phylogenetic affiliation of Archaea
recovered in this study as well as those in the ARB data base (SILVA 92 release). Red
clones were recovered from the BBL environment. Boot-strap support values of 70% or
greater are based on 1000- re-samplings.
50
70%
78% 8
MG1 Crenarcheoata
Nitrospumulis relatives
MG1 Crenarcheoata
SB95-57 clade
Methanococoiddes
Euryarchaea
Marine Group II
OR-SH10-100m clone_96
71%
OR-SH100-100m clone_3
AF121094, env. clone ODPB A6
AF393307, env. clone 83A10
71% EF645854, env. clone N67a_43
M88076, env. clone SBAR12
OR-SH100-100m clone_36
91%
OR-SH100-100m clone_87
DQ085097, Nitrosopumilus maritimus SCM1
DQ299266,env. clone app654
EF645845, env. clone N67a_41
U71118, env. clone C48, C48
EF367590, env. clone ZES 153
AJ567651, env. clone MBMPA22
EF367646, env. clone ZES 209
73%
AF083072, Cenarchaeum symbiosum
OR-SH10-100m clone_20
94%
DQ300523, env. clone HF500_61D01
82% AY856356,env. clone CTD005 37A
DQ300517, env. clone HF500_25H11
99%
EF645850, env. clone N67a_76
OR-SH10-100m clone 18
DQ280485, 'SBAK CO2 reducing Enrichment
85% AY177810, env. clone sp. SB01
CP000300, Methanococcoides burtonii DSM 6242
DQ058817,env. clone HR CF Enrichment 017
92%
AY454743, env. clone EJ_E04
98%
AF142978, env. clone ACE3_A
M59140, Methanosarcina thermophila
AJ276397, env. clone AMPB Zg
AF220166, Ferroglobus placidus
D43628, Natronococcus amylolyticus
BX957219, Methanococcus maripaludis S2
Crenarchaea
91%
0.10
0.1 nucleotide substitutions
51
Chapter 4
Coupled metagenomic and metatranscriptomic profiling over a depth gradient in
the coastal Northeast Pacific Ocean
Anthony D. Bertagnolli, Salvador Ramirez-Flandes, Kevin Vergin, Osvaldo Ulloa and
Stephan Giovannoni
In preparation for submission to:
The International Society for Microbial Ecology Jounral
Nature Publishing Group
The Macmillan Building
4 Crinan St. London N1 9XW, UK
52
Abstract
As part of a long-term study of the effects of seasonal hypoxia and anoxia on marine
microbial communities (MI_LOCO), pyrosequencing was applied to metagenomes and
metatranscriptomes collected from several depths at a coastal Oregon site during summer
upwelling and fall downwelling. Multivariate statistics revealed protein coding genes in
the bottom boundary layer (BBL) that were different from those collected in the surface
layer, and were mainly implicated in chemolithotrophic metabolisms. Thaumarchaea
homologs were dominant in the BBL, reaching 12% of metagenomic reads during the
summer and decreasing during the fall to 1%. Analysis of metatranscriptomes revealed
that putative thaumarchaeal nitrifiers were most active during the summer during severe
hypoxia. Highly detected transcripts included hypothetical proteins, ammonia
monoxygenases, ammonia transporters, and copper containing nitrite reductases that are
predicted to produce nitric-oxide. In the BBL, transcripts increased for reversible
variants of nitrate reductase that are predicted to function in nitrite oxidation. Sulfuroxidizing bacterial (SOB) homologs were higher in BBL metagenomic data than in the
surface (3-4% of classified reads). Reverse dissimilatory sulfite reductase was also
detected in metatranscriptomes and was highest in the BBL. Adenosine-5’phosphosulfate reductase genes and transcripts increased in relative abundance in the
BBL and displayed high-scoring pairs to several microbial groups, including the SAR11
clade. Overall, the results strongly support the conclusion that Thaumarchaea activity is
seasonally influenced by hypoxia in shallow environments along the coastal Northeast
Pacific Ocean.
53
Introduction
Continental shelves along eastern boundary currents are some of the most productive
regions of the global oceans. The coast of Oregon, in the California current system, is
among these areas. Upwelling of high nutrient, low temperature water masses in the
coastal zone throughout the spring and summer stimulates photosynthetic growth,
creating a net sink for carbon dioxide (55, 56). The fate of organic matter produced by
phytoplankton is dictated by physical processes, such as transport, as well as biological
processes, such as respiration. The latter is mediated primarily by microorganisms, and
has tremendous consequences on oceanic and atmospheric chemistry. For example,
increased respiration rates in conjunction with poor water column ventilation can lead to
transient episodes of seasonal hypoxia. Interestingly, such events have been increasing in
frequency and intensity on the coast of Oregon (18).
Microbial plankton communities on continental shelves are remarkably diverse,
harboring some taxa that are distributed ubiquitously throughout the global oceans (e.g.,
the SAR11 clade), as well as some primarily found in coastal waters (e.g., the OM43
clade) (102). The metabolic activities of surface water plankton communities have been
investigated with metaproteomics, revealing that transport functions dominate, similar to
observations made in open ocean environments (113, 114). In contrast to oligotrophic
environments, proteins involved in methanol oxidation were detected in coastal
environments, suggesting methylotrophy is a distinguishing feature of coastal metabolic
diversity.
Vertical patterns in the distributions of bacterioplankton have been observed in
shallow coastal water columns. A recent analysis of the bottom boundary layer (BBL),
the water column region above the benthos that it is often the first to experience hypoxia
and anoxia, revealed microbial lineages residing in this environment that differed from
those commonly retrieved in the surface layer (9). Some of these taxa displayed close
phylogenetic relationships to sulfur-oxidizing microorganisms, implying that lithotrophic
strategies maybe important in the BBL. However, little information has been reported
describing the functional gene diversity of microbial plankton communities in this area.
54
Recent advances in molecular ecology have made the acquisition and
interpretation of transcript data derived from microorganisms in their indigenous habitats
readily accessible (98). The application of coupled metagenomic and metatranscriptomic
approaches can bridge the gap between community abundance and activity at the level of
transcription. The method has been applied to several marine environments, including the
eastern tropical South Pacific oxygen minimum zone, a 4000 meter depth gradient in the
North Pacific subtropical gyre (NPSG, station ALOHA), the surface waters of the
western English Channel (L4 observatory), and autonomously collected surface waters
from the Northeast Pacific Ocean (43, 93, 111, 121).
Two observations common to each of these studies are 1) the representation of
organisms in metagenomic samples rarely reflects their activity in the metatranscriptome
and 2) many of the most frequently detected transcripts are those that display no
homology with characterized protein coding genes. For example, Shi et. al. observed
three taxa in high proportions throughout the water column in metagenomic analyses in
the NPSG: SAR11, Prochlorococcus and Nitrosopumulis (111). However, the
representation of these organisms in metatranscriptomes was different. Members of the
SAR11 clade represented 36% of protein coding genes in metagenomes retrieved from
125 meters, while their representation in the metatranscriptome was only 11%. Several
organisms found at relatively low metagenomic abundances displayed high levels of
activity, such as an increase in the proportion of transcripts from the Roseobacter clade in
the deep-chlorophyll maximum. These observations suggest that bacterial abundance and
activity are not necessarily congruent. As such, it is important to evaluate microbial
communities within the context of environmental parameters over space and time to
understand the underlying physical and chemical cues influencing their activity.
Interpretation of environmental sequence data is dependent on reference taxa with
genome sequences available for comparative analyses. The coast of Oregon is arguably
one of the best locations for metagenomic and transcriptomic surveys as numerous
environmentally relevant organisms have been isolated from this area by dilution to
extinction culturing in a high-throughput manner (23). (23). Members of the SAR11
55
clade (HTCC1062 & HTCC1002), Roseobacter clade (HTCC2255), OM60/NOR5 clade
(HTCC2080, HTCC2148), and SAR92 clade (HTCC2207) have been isolated, genome
sequenced, annotated, and are available for analysis through multiple public repositories.
Genome sequences can provide a bioinformatic scaffold for the organization and
interpretation of sequence data collected directly from the environment (19, 48, 101).
The goal of this study was to assess the metabolic potential and transcriptional
activity of microbial communities in a shallow coastal region bordering an eastern
boundary current system in the northeastern Pacific ocean. This is part of a broader, longterm comparative survey regarding the impacts of seasonal hypoxia and anoxia on marine
microbial communities in coastal environments (Microbial Initiative in Low Oxygen
areas off the coasts of Concepcion, Chile and Oregon-MI_LOCO). We hypothesized that
organisms residing in the BBL may display changes in their metabolic potential and
activity that maybe influenced by dissolved oxygen concentrations. Here we present the
analysis of data spanning seasonal variation across the spring, summer, and fall of 2009
from 4 depths that include severe hypoxic and non-hypoxic samples off the coast of
Oregon which support the conclusion that significant differences in microbial community
structure, metabolic potential, and transcriptional activity exist within shallow coastal
ecosystems. Samples collected along the inner continental shelf were analyzed using
TRFLP to assess changes in bacterial community structure over the course of the time
series. Based on our assessment of terminal restriction fragment length polymorphism
(TRFLP) data, metagenomic and metatranscriptomic samples were then selected and
analyzed by pyrosequencing from two time points over several depths (8 metagenomic
samples, 7 metatranscriptomic samples) from the summer upwelling and fall downwelling periods (Table 4.1). Sequence data were analyzed using BLASTX/NR searches,
and sample comparisons were made using multiple statistical analyses (2). Gene centric
tests were performed to delineate trends in gene and transcript distributions.
Materials and Methods
56
Site Description
This study was conducted along the Strawberry Hill Line, stations SH70 (44.15 N,
124.14 W) and SH90 (44.15, 124.22). The water column depths at these sites are
approximately 70 and 90 m, respectively. Previous surveys of biogeochemistry and
microbial diversity have been reported at stations in close proximity to the area sampled
(9, 18).
Biogeochemical Data
Phosphate, nitrate + nitrite, nitrite, ammonia, chlorophyll-A, particulate organic carbon,
particulate organic nitrogen, were measured for all samples collected in this study, and a
time-series analysis of these data are reported elsewhere (Galan et. al., in prep). Nutrient
data corresponding to the metagenomic and metatranscriptomic samples from the data
presented here are listed in Table 4.1.
Sample Collection
Prior to collection of samples for nucleic acids analyses, biophysical characteristics of the
water column were assessed on each cruise with a free falling optical profiling system
with an attached CTD (Satlantic, Nova Scotia, Canada). Four depths were chosen for
collection of DNA and RNA based on these analyses (site SH70), corresponding to the
surface (5 m), deep chlorophyll maximum (when present, 15-25 m, DCM), bottom
boundary layer transition (50-55 m, BBLTran) and bottom boundary layer (60-70 m,
BBL). At site SH90, only samples from the BBL were collected (80-90 m).
Nucleic Acids Sample Collection
Samples for DNA and RNA were collected by positive filtration using a peristaltic pump
through nitex (20 µM) and GFA filters (GE Life Sciences), and collected on to 147 mm
(for DNA samples) or 25 mm 0.2 µM Supor filters (for RNA samples) (GE Life
Sciences), respectively. The time between collection and filtration was minimized to less
than 20 minutes for RNA samples. The total sample volume per depth was approximately
2 L. Samples were preserved in 300 µL RNA later (Invitrogen), and placed in liquid
57
nitrogen until storage at -80 °C. For genomic DNA analysis, approximately 35-40 L of
water was collected and stored in sucrose lysis buffer (50 mM Tris-HCl, 40 mM EDTA,
0.75 M sucrose) and then stored in liquid nitrogen.
DNA for PCR and metagenomic analysis was separated from high-molecular weight
RNA as described previously (44). 3 µg of genomic DNA per sample was used for
preparation of single stranded DNA libraries for pyrosequencing (GS-FLX-Titanium 454
Life Sciences, Roche).
Terminal Restriction Fragment Length Polymorphism Analysis
For analysis of bacterial SSU 16S rRNA genes by TRFLP, 20 ng of environmental DNA
was amplified with the Bacteria-specific primer 8F and the universal primer 519R. The
forward primer was labeled with phosphoramidite fluorchrome 5-carboxy fluoresin (6FAM). PCR reactions contained final concentrations consisting of 0.25 U Taq
Polymerase (Fermentas, Glen-Burnie MD), 2.5 mM MgCl2, 0.2 mM
deoxyribonucleotides, and 0.2 µM of each primer in a 50 µL reaction volume. PCR
amplifications were performed in a PTC-0200 Thermocycler (MJM Technologies,
Cambridge MA) using the following conditions; 26 cycles of 94 °C for 30 s, 56 °C for 1
min, 72 °C for 2 min, with a final extension of 72 °C for 10 min. FAM-labeled products
were digested with 1 U BsuR1 in 1 × enzyme digest buffer for 6 hours. Digests were
ethanol precipitated (2 × vol. ethanol, 0.1 × vol. sodium acetate) at -80 °C for 1 hour,
centrifuged at 13,000 rpm for 30 minutes at 16 °C, vacuum dried, and re-suspended in 20
µL sterile water. Samples were cleaned using Sephadex, and analyzed on an ABI 3100
bio-analyzer (Applied Biosystems, Foster City CA). A 16S rRNA gene clone library was
constructed with universal primers 8F and 1492R using 20 ng of DNA from the BBL
collected July 30th 2009. PCR reactions contained the same reagents as those used for
TRFLP analyses, with slightly different amplification step; 30 cycles of 94 °C for 30 s,
56 °C for 1 min, 72 °C for 2 min, with a final extension of 72 °C for 10 min. Clone
library construction and screening was performed as previously described (89). Clones
were compared to a pre-aligned database (SILVA_102) using the ARB software
58
environment (80, 99). Sequences were added to the backbone tree using the parsimony
function, phylogenetic trees were then calculated using neighbor-joining.
TRFLPs were noise-filtered by eliminating fragments that did not contribute to at least
1% of the relative fluorescence in each sample. These values were used for further
analysis. Multivariate comparisons of TRFLP data were performed in PRIMER V6 (21).
Hierarchical cluster analysis was performed based on the Bray-Curtis distance measure.
Non-metric multidimensional scaling (NMDS) analysis was then performed using 25 restarts and a minimum stress of 0.01. Analysis of similarity (ANOSIM) was performed to
test for significant differences between samples at different depth horizons.
RNA Sample preparation:
RNA for metatranscriptomic analysis was isolated as described previously (34). To
increase detection of transcripts affiliated with putative protein coding genes, a
subtractive rRNA hybridization reaction was applied to mRNA pools. The efficacy of the
method has recently been reported (120). Briefly, subtractive hybridization probes
targeting the small and large rRNA for Bacteria, Archaea, and the 18S of Eukaryotes
were PCR amplified using genomic DNA from each of the corresponding samples as a
template. Reverse primer pairs contained the T7 RNA polymerase promoter sequence.
Positive PCR reactions for each RNA type were purified with a Qiagen PCR Purification
kit, quantified using a nano-drop spectrometer, and pooled before generating in vitro
transcripts. In vitro transcripts produced from genomic DNA template were biotinylated
using labeled nucleotides and T7 RNA polymerase. The resulting labeled products were
purified using a MEGAclear kit (Life Technologies, Grand Island, NY), quantified, and
pooled in a ratio of 8:8:1:1:1:1, Bacterial 16S:Bacterial 23S:Archaeal 16S:Archaeal
23S:Eukaryotic 18S:Eukaryotic 28S rRNA. The labeled RNA transcripts were hybridized
to environmental RNA samples, which were extracted using the mirVANA kit (Life
Technologies, Grand Island, NY), and subtracted using magnetic streptavidin beads.
Subtracted RNA was then amplified using the MessageAmp II-Bacteria kit (Life
Technologies, Grand Island, NY). Amplified RNA was then converted to double stranded
59
cDNA, and the resulting product was quantified and used for pyrosequencing on the GSFLX-Titanium platform (454 Life Sciences, Branford, CT).
Bioinformatic Analyses of nucleic acids
Metagenomic reads were de-replicated using CD-HIT 454 with a similarity threshold of
97% (60). Only reads identified as exact duplicates were removed from
metatranscriptomic data sets (39). Sequence data were then compared to an rRNA
database consisting of small and large subunit rRNAs from SILVA, GreenGenes, and
RFAM by BLASTN analyses. Reads with a bit-score of 50 or greater were considered
RNAs, and removed from subsequent analyses. The remaining reads were compared by
BLASTX to a pre-clustered NCBI-nr protein database. Reads displaying a bit-score of 50
or greater were considered putative protein coding genes or transcripts, and used for
downstream analyses.
Effective Sequence Count Estimation
Average genome size estimates were calculated for metagenomic samples. Effective
sequence counts were then determined and used to standardize metagenomic data as
performed in Besteri et. al.. For transcriptomic data, the number of classified protein
coding reads were used to standardize samples prior to statistical analyses.
Multivariate and univariate analyses
Multivariate analyses of metagenomic and metatranscriptomic profiles were performed
with the statistical software package R and PrimerV6 (21). Data matrices consisting of 8
metagenomic samples and 7 metatranscriptomic samples were assembled independently
(ie. one metagenomic matrix and one metatranscriptomic matrix). Each metagenomic
matrix was normalized by dividing raw gene counts by effective sequence counts. These
data were then transformed using a log (X+1) transformation to approach a normal
distribution. The resulting matrices were compared using the Bray-Curtis distance.
Hierarchical clustering dendograms were calculated by group average. NMDS was
performed using 25 restarts and a minimum stress of 0.01. For metatranscriptomic data,
matrices were divided by the number of classified reads, then transformed using a
log(X+1) transformation to approach a normal distribution prior to multivariate analyses.
60
Hierarchical clustering and NMDS were then performed similarly to metagenomic data.
The contribution of environmental variables to NMDS axes was assessed. A contribution
was considered significant if a p value of 0.05 or less was observed based on 999
permutations.
Gene-Centric approaches
Regression analyses were performed in the software packages ShotgunFunctionalizeR
and testGeneFamilies2.regression (10). For regression analyses, effective sequence
counts were used as the exposure term in gene-centric analyses. For transcripts, the
numbers of classified expressed genes were used as the exposure term.
Results and Discussion
Evaluation of Community Structure at station SH70 using TRFLP
TRFLP of 16S rRNA genes was used to survey bacterial communities at station SH70
and station SH90 (BBL only) to evaluate community structure variation for subsequent
high-throughput sequencing. NMDS analyses revealed clear spatial and temporal patterns
(Figure 4.1A). Samples collected in the BBL transition and BBL ordinated together,
distinct from samples collected in the surface and deep-chlorophyll maximum. The
strongest pair-wise difference in community types was between the surface and BBL
(ANOSIM R=0.720, p<0.01), consistent with a previous report regarding the
stratification of bacterial communities in the inner-shelf of the Oregon coast (9).
A primary experimental goal was to compare differences in microbial community
metabolisms due to changes in dissolved oxygen (DO). Thus, we combined TRFLP
profiles with environmental DO data to select samples for high-throughput sequence
analyses. The lowest DO concentrations were observed during the summer, in the BBL
on July 30th (DO 0.44 mL/L or 19.67 µmol/L) (Table 4.1). During September, downwelling introduced re-oxygenated water into this region, elevating water column DO
levels to above hypoxia (DO 2.76 mL/L or 123.38 µmol/L). Therefore, samples from
September 21st were chosen to represent non-hypoxic conditions, whereas samples from
July 30th were chosen to represent severe hypoxic conditions. Samples were also
analyzed from the surface, deep-chlorophyll maximum, bottom boundary layer transition,
61
and BBL from the July 30th and September 21st at station SH70. In analyzing samples
from these depths, each of the community types observed based on NMDS analyses of
TRFLPs were captured (Figure 4.1B, orange symbols).
Sequence Characteristics of Metagenomes and Metatranscriptomes
Sequencing statistics for metagenomes and metatranscriptomes are listed in Table
4.2. Pyrosequencing generated approximately 2,900 and 1,100 Mbp of metagenomic and
metatranscriptomic data, respectively. The number of non-rRNA reads in
metatranscriptomes was approximately one-third of that in metagenomes- likely due to
the high proportion of rRNAs in metatranscriptomic samples. A subtractive rRNA
method was applied prior to the synthesis of cDNA from bulk mRNA pools. However,
cDNA reads were still detected by BLASTN analyses as rRNA transcripts, depressing the
contribution of putative protein coding reads in metatranscriptomes. These sequences
were removed prior to analyzing sequences using BLASTX. Estimated average genome
sizes were between 1.6-3.0Mbp (average 2.2 Mbp), within the range reported for marine
bacterioplankton in the Sargasso Sea (1.6-3.2 Mbp).
Multivariate assessment of metagenomes and metatranscriptomes
Multivariate statistics were applied to metagenomic profiles to assess differences
in samples based the contribution of protein-coding genes to metagenomes and
metatranscritpomes. Hierarchical clustering and NMDS analyses revealed clear
differences in metagenomes, with samples collected in the BBL and BBL transition
clustering together and separately from those collected in the surface and deepchlorophyll maximum (Fig. 4.2A). Pearson correlation coefficients were calculated based
on the contribution of environmental variables to NMDS axes (Table 4.3). Temperature,
salinity, depth, and silicate all displayed significant contributions to the ordination axes
(p<0.05). ANOSIM analysis provided further evidence in support of the hypothesis that
the surface and BBL communities are distinct based on functional gene representation
(R=0.6042, p<0.05). Despite sampling severe hypoxic and non-hypoxic water masses, an
62
oxygen-driven change in metagenomic profiles was not observed (ANOSIM hypoxic vs.
non-hypoxic, R= 0.09375, p= 0.307).
Multivariate statistical analyses were applied to metatranscriptomes and
demonstrated that samples collected in the BBL ordinated together, similar to
metagenomic samples (Fig. 4.2B). ANOSIM analyses did not provide convincing
evidence for differences between the bottom boundary layer and surface layer (R=0.343,
p=0.056), or differences between hypoxic and non-hypoxic conditions (R=0.5521,
p=0.0721). These data may suggest, perhaps, that these samples did not capture the full
spectrum of functional gene activity. As such, further sampling of microbial
transcriptomes may substantially aide in assessing the full diversity of transcriptional
diversity associated with these environments. Depth, oxygen, dissolved organic nitrogen,
nitrate, and silicate had significant correlations with metatranscriptomic NMDS axes
(Table 4.3, Figure 4.2B), similar to the results observed in metagenomic analyses.
Taxonomic and functional changes in metagenomes and metatranscriptomes
The putative taxonomic affiliation of protein coding genes in metagenomic and
metatranscriptomic samples was investigated using the information associated with each
read’s best BLASTX hit. Highly represented taxa from both metagenomes and
metatranscriptomes were assessed (top 20 organisms, Figure 4.3 A and B, respectively).
Organisms, genes, and activities putatively involved in inorganic nitrogen and sulfur
cycling consistently increased in the BBL. While previous multivariate analyses
suggested that oxygen did not select for a unique microbial community, deeper analyses
of individual genes and transcripts suggested significant variation in inorganic nitrogen
cycling genes and transcripts between hypoxic and non-hypoxic conditions.
Inorganic Nitrogen Cycling
Putative protein coding genes with high-scoring pairs to four genome sequenced
Thaumarchaea (Nitrosopumilus maritimus SCM1, Cenarchaeam symbiosum, Candidatus
Nitrosarchaeaum koreensis MY1, Candidatus Nitrosarchaeaum limnia SFB1) were
observed in high frequencies in metagenomes, increasing in the BBL during the summer,
and accounted for 11% of classified reads in the BBL (Fig. 4.3A). A single ammonia
63
oxidizing bacterium (AOB), Nitrosospora multiformis, recruited a minor component
(~1%) of classified reads. Nitrosopumulis maritmus SCM1 recruited the majority of best
hits (8% of classified reads in the BBL). During the fall, ammonia oxidizing organisms
decreased in relative abundance in the BBL and were not detected in the surface waters
(Thaumarchaea ~1%, AOB <0.5%, respectively). Genes involved in inorganic nitrogen
transformations, as well as hypothetical proteins affiliated with Nitrosopumulis maritimus
SCM1 (Nmar) displayed significant depth dependent changes (R value >1, Benjamanihochberg corrected p-value<0.001) (Figure 4.4A, Appendix A). Direct comparison of
metagenomes collected in the BBL and BBL-transition revealed that inorganic nitrogen
cycling genes were significantly over-represented under hypoxic conditions during the
summer (R value >1, p<0.001)(Appendix B).
Similar to metagenomes, transcripts with best hits to Thaumarchaea were
detected throughout the water column during the summer, displaying maximal
frequencies in the BBL (4% of classified reads) (Fig. 4.4B). Highly detected transcripts
were conserved hypothetical proteins (Nmar_1547 and associated homologs), an
ammonia transporter (Amt), ammonia monooxygenase (Amo), nitric-oxide forming
nitrite reductase (NirK), and small blue copper containing domain proteins (Fig. 4B).
Amt, Amo, and NirK are involved in ammonia oxidation, while the physiological role of
Nmar_1547 is unknown. Thaumarchaeal transcripts were also over represented under
severe hypoxia, suggesting a preference for low dissolved oxygen conditions (oxygen
correlation R value less than -1, Benjamani-Hochberg corrected p-value <0.001)
(Appendix C). Physiological and genomic evidence has suggested that Thaumarchaea are
successful in marine environments due to a low Ks for ammonia, likely the result of a
copper rather than iron-based biochemistry (81). The detection of Thaumarhcaeal genes
and transcripts in the photic zone amidst elevated chlorophyll-A is similar to a time series
assessment performed in the surface waters Monterey Bay, California (105).
Dissimilatory nitrate reductase (Nar) was detected in metagenomes and
metatranscriptomes (Fig. 4.4), and displayed the same distribution patterns as genes and
transcripts involved in ammonia oxidation. Nar is part of a large superfamily of
64
molybdopterin binding proteins that work in both oxidative and reductive directions
(154). Half of the metagenomic and >99% of transcriptomic Nar best hits were to
Candidatus ‘Kuenenia stuttgartiensis’, an anaerobic ammonia oxidizing bacterium in the
phylum Planctomycetales. Nar has been speculated to operate in an oxidative direction in
Can. ‘K. stuttgartiensis’, in contrast to the canonical reductive mechanism used by
denitrifiers (127). High potential electrons from nitrite are then used for carbon fixation
through the acetyl-CoA pathway. Anammox organisms gain energy from the oxidation of
ammonium with nitrite as an electron acceptor, a process that produces nitrogen gas and
contributes to inorganic nitrogen losses in some oxygen minimum zones (126). Proposed
intermediates in the process included nitric oxide and hydrazine. Several other enzymes
participate in the reaction, including nitrite reductase, hydrazine synthase, and hydrazine
dehydrogenase (66). However, none of these protein-encoding genes with high-scoring
pairs to anammox organisms were detected in either metagenomes or metatranscriptomes
during this survey.
A 16S rRNA gene clone library was constructed from the same nucleic acids pool
submitted for high-throughput sequence analyses associated with the BBL during the
summer and analyzed with TRFLP. δ-Proteobacteria with evolutionary relationships to
characterized nitrite-oxidizing organisms were identified (Fig. 4.5A) with an observed
TRF of 194 bp. Interestingly, this same fragment size contributed exclusively to samples
collected in the BBL transition and BBL, suggesting that nitrite-oxidizing organisms
reside in the planktonic bacterial community in the BBL (Fig. 4.5B). Metagenomic
analysis of a nitrite-oxidizing enrichment culture, Candidatus ‘Nitrospira defluvii’,
revealed substantial horizontal gene transfer events between Can. ‘K. stuttgartiensis’, and
included the enzymes involved in nitrite oxidation (79). Evidence for similar horizontal
gene transfer events has been reported in the north Pacific subtropical gyre at station
ALOHA. Mincer et. al. reported several fosmid clones containing 16S rRNA genes
affiliated with Nitrospina. Sequence analyses of open reading frames associated with a
representative fosmid revealed several putative gene suites with high-scoring pairs to
Can. ‘K. stuttgartiensis’ (85). Overall, our metagenomic, metatranscriptomic, and TRFLP
65
data suggest that nitrite oxidation maybe occurring in the BBL, and is most active during
periods of hypoxia.
Inorganic sulfur cycling
Reads with high-scoring pairs to putative SOB consistently increased in relative
abundance in the BBL during the summer and fall (3-4% in both seasons) (Fig. 3.3A),
and were affiliated primarily with SUP05 and Candidatus ‘Ruthia magnifica’, with minor
recruitment to Candidatus ‘Vesicomyosocius okutanni’ HA. The presence of putative
SOB in the BBL is consistent with a previous bacterial diversity study of Oregon coastal
waters (9). SUP05 and relatives have been recovered in high proportions during 16S
rRNA gene diversity surveys of low oxygen marine environments (119, 151). Can.
‘Ruthia magnifica’ is an endosymbiont of the hydrothermal vent dwelling clam
Calyptogena magnifica. Vent areas, like oxygen minimum zones, are typically void of
oxygen, and under reducing conditions. Metagenomic and genomic analyses of SUPO5
and Can. ‘R. magnifica’, respectively, have revealed the genetic components necessary
for the oxidation of a wide range of reduced sulfur compounds (92, 106, 142). Increased
frequencies of metagenomic reads with high-scoring pairs to these organisms in Oregon
coastal waters is evidence in support of the hypothesis that thiotrophy maybe an
important component of the BBL.
Reverse dissimilatory sulfite reductase (rDSR) increased in relative abundance in
the BBL in metagenomes (Fig. 4.6A, Appendix A). rDSR is a multi-subunit complex
involved in oxidation of hydrogen sulfide to sulfite in characterized sulfur oxidizing
organisms such as Allochromatium vinosum (24). The gene is also distributed amongst
sulfate reducing bacteria (SRB), catalyzing the reverse reaction (91, 140). SOB and SRB
are phylogenetically distinguishable based on rDSR phylogenies, and congruent with 16S
rRNA gene topology, making these genes useful for molecular surveys of sulfur utilizing
organisms (78). Metagenomic best hits to rDSR were affiliated with three SOB: SUP05,
Can. ‘V. oktunanii’, Can. ‘R. magnifica’. In metatranscriptomes, rDSR also displayed
substantial increases with depth, although detected at low count levels (less than 50 reads
detected, high 40). Regardless, rDSR subunits with best hits to SOB were only observed
66
during the summer in metatranscriptomes. In the fall, rDSR best hits were to organisms
that have yet to be characterized as obligate SOB, such as Lentisphaera araenosa
(HTCC2155) and Flavobacterium johnsinaea. rDSR genes and transcripts did not display
substantial differences under hypoxic conditions.
Like rDSR, Apr is a reversible enzyme, catalyzing the oxidation of sulfite to
adenosine-5’-phosphosulfate in SOB, and the reverse reaction in SRBs (83, 84). In both
metagenomic and metatranscriptomic data sets, Apr was detected most frequently in the
BBL during the summer. High-scoring pairs were affiliated with the SAR11 clade
(HTCC1062, HTCC1002, HTCC7211) and an uncharacterized marine organism (HF4000
NPSG fosmid) (Fig. 4.5C), with minor contributions from characterized SOBs. The
physiological role of Apr in cultivated members of the SAR11 clade remains unknown.
HTCC1062 requires reduced organic sulfur compounds for optimal growth in batch
culture conditions (135). Since the addition of inorganic sulfur compounds to HTCC1062
cultures did not promote growth in significant quantities, Apr may serve an alternative
physiological role for members of the SAR11 clade. Apr genes and transcripts were not
strongly over-represented under hypoxic conditions.
Conclusions
This is the first survey to analyze both the metabolic potential and transcriptional
activity of microbial communities during time periods corresponding to severe hypoxic
and non-hypoxic conditions in the northeast Pacific Ocean. Our data indicate that
Thaumarchaea exhibit pronounced changes in their abundance and activity that maybe
controlled by local variability in water column conditions. Isotopic analysis of marine
enrichments has revealed that ammonia oxidation proceeds by “denitrifier nitrification”, a
process that produces N2O (107). In the same study, Santoro and colleagues reported an
elevated site preference for N2O, and suggested that in-situ nitrification was likely
associated with low oxygen microenvironments. Our data support this result, as
thaumarchaeal genes and transcripts were most highly detected during severe hypoxia.
Recent surveys have revealed the highest abundances and transcriptional activities in
67
other Eastern Boundary Current systems, such as the oxycline of the Eastern Tropical
South Pacific (6, 121).
Reverse dissimilatory nitrate reductase transcripts increased in the BBL during
severe hypoxia, and were affiliated with an anaerobic ammonia oxidizing Planctomycete.
It is tempting to speculate that anammox could be occurring in the BBL. However, the
substantial horizontal gene transfer events observed between Can. ‘K. stuttgartiensis’ and
nitrite-oxidizers is indirect evidence for an alternative metabolic use (79). Thaumarchaea
and nitrite oxidizing bacteria are often detected together in open ocean and coastal
regions, perhaps suggesting that nitrification is dependent mainly on these two groups in
marine environments (85, 108). Data presented here suggest that Amo and Nar were
tightly coupled, suggesting similar distributions in shallow coastal areas.
To our knowledge, the increase in relative abundance of Apr transcripts affiliated
with members of the SAR11 clade in the BBL has not been reported in the coastal
northeast Pacific ocean. This result adds another layer of knowledge to the in-situ
metabolic activity of this ubiquitous microorganism. Apr is one enzyme involved in the
oxidation of sulfite to sulfate. Genome sequenced representatives isolated along the coast
of Oregon lack the metabolic machinery required to take full advantage of the energy
derived from this substrate, including sulfate adenyl transferase (Sat) and quinone
interacting membrane bound oxidoreductase (Qmo). In characterized organisms capable
of utilizing sulfite, SAT conjugates AMP with sulfite to produce APS, while Qmo passes
the electrons from this oxidation to the quinone pool. As such, an alternative metabolic
role for Apr in coastal members of the SAR11 clade is highly probable.
Prior to this survey, we expected that hypoxia and anoxia would be important in
dictating microbial community structure, but previous data had revealed that the BBL
community was relatively stable despite variable oxygen concentrations. This survey
confirms this finding, while providing evidence that some organisms residing in this
environment may alter gene expression patterns in accordance with other, unknown
changing environmental conditions. The increase in abundance of genes and transcripts
affiliated with lithotrophic processes in the BBL can be interpreted in several ways.
68
Enzymes involve oxidation of inorganic electron donors such as nitrite and ammonia may
suggest that labile organic carbon compounds (ie. glucose) maybe lacking in shallow
coastal environments. While data presented here do not definitely prove this result, they
do provide a scaffold for the generation of new hypotheses and experiments.
69
Table 4.1 Environmental data collected in association with metagenomic and
metatranscriptomic profiles.
July 30th, 2009
Temp (°C)
Salinity
Depth (m)
Sigma-t (kg m-3)
O2 Winkler (ml/L)
Expected O2 (µm/L)
Sat O2 (%)
N total
AOU (µm/L)
Chl-a (ng/L)
DON
PO4 (µM)
NO3 (µM)
SiO3 (µM)
NO2 (µM)
NH4(µM)
POC (µM)
PON (µM)
POP (µM)
C:N
C:P
N:P
Bacterioplankton (cell mL-1)
Synechococcus (cell mL-1)
Phyto Euk (cell mL-1)
Diatoms (cell mL-1)
5 meters
9.54
33.51
5.00
25.77
10.79
481.73
175.25
0.11
-206.85
2126.97
7.25
0.15
0.00
0.74
0.09
0.03
68.49
68.49
0.49
11.13
141.26
12.69
5333858.96
3275.24
4374.06
2405.82
25 meters
8.67
33.66
25.00
26.20
3.44
153.68
52.25
23.95
140.43
6523.79
24.95
2.49
21.40
15.68
0.37
2.18
139.33
139.33
0.70
6.74
198.30
29.43
2785422.03
441.22
3938.22
2945.41
55 meters
7.38
33.89
55.00
26.49
0.52
23.27
7.72
32.52
278.22
420.75
34.67
3.20
32.26
78.17
0.17
0.10
7.22
7.22
0.09
7.67
81.13
10.58
888932.56
121.38
1413.78
180.22
70 meters
7.33
33.89
70.00
26.50
0.44
19.68
6.52
32.88
282.24
660.60
35.46
3.24
32.56
81.75
0.22
0.10
9.88
9.88
0.10
9.93
100.46
10.12
867370.71
236.54
1680.59
311.06
5 meters
15.01
32.48
5.00
24.09
6.77
302.49
117.48
0.64
-45.01
4033.71
9.17
0.42
0.51
0.89
0.06
0.07
27.94
27.94
0.23
20 meters
10.98
32.84
25.00
25.49
5.69
251.29
89.25
12.84
30.26
1796.75
21.41
1.33
8.86
8.36
0.24
3.74
9.17
9.17
0.09
50 meters
8.62
33.41
50.00
25.93
3.92
175.27
59.91
24.80
117.31
207.33
29.72
2.16
22.46
26.43
0.29
2.05
5.12
5.12
0.06
70 meters
8.39
33.61
70.00
26.13
2.76
123.39
41.78
29.59
171.94
279.71
41.58
2.62
25.81
48.14
0.61
3.17
6.66
6.66
0.09
September 21st, 2009
Temp (°C)
Salinity
Depth (m)
Sigma-t (kg m-3)
O2 Winkler (ml/L)
Expected O2 (µm/L)
Sat O2 (%)
N total
AOU (µm/L)
Chl-a (ng/L)
DON
PO4 (µM)
NO3 (µM)
SiO3 (µM)
NO2 (µM)
NH4(µM)
POC (µM)
PON (µM)
POP (µM)
70
Table 4.1 (Continued)
C:N
C:P
N:P
Bacterioplankton (cell mL-1)
Synechococcus (cell mL-1)
Phyto Euk (cell mL-1)
Diatoms (cell mL-1)
7.45
122.04
16.38
1031840.33
9386.72
7519.79
2625.74
5.59
104.28
18.65
495933.75
1690.72
664.50
574.68
5.43
83.17
15.32
296801.11
578.29
163.45
149.46
6.81
78.65
11.55
572050.07
1471.07
675.86
326.05
71
Table 4.2 Sequence characteristics of metagenomic and metatranscriptomic samples
produced by pyrosequencing on the 454 FLX-Titanium platform.
72
Table 4.3 Pearson-Kendall correlation coefficients associated with non-metric
multidimensional scaling axes for metagenomic (top) and metatranscriptomic (bottom)
analyses.
Metagenomes
Parameter
Temperature
Salinity
Depth
Density
Oxygen (ml.L)
Oxygen (umol/kg)
Oxygen Saturation
Total Nitrogen
AOU
Chlorophyll-A
Dissolved organic nitrogen
Phosphate
Nitrate
Silicate
Nitrite
Ammonia
particulate organic carbon
particulate organic nitrogen
particulate organic phosphate
Bacterioplankton
Synechococcus
Phytosynthetic Eukaryotes
Diatoms
Axis 1
0.91
-1.00
-0.49
-0.90
0.44
0.44
0.45
-0.59
-0.47
-0.11
-0.48
-0.61
-0.64
-0.60
-0.62
0.39
-0.06
-0.06
-0.04
-0.11
0.74
0.31
0.20
Axis 2
-0.42
0.05
0.87
0.43
-0.90
-0.90
-0.89
0.80
0.88
-0.99
0.88
0.79
0.77
0.80
0.78
0.92
-1.00
-1.00
-1.00
-0.99
-0.68
-0.95
-0.98
r2
0.91
0.98
0.80
0.89
0.63
0.64
0.66
0.78
0.67
0.41
0.72
0.75
0.81
0.84
0.11
0.20
0.64
0.64
0.76
0.71
0.70
0.71
0.90
Pr(>r)
0.001 ***
0.001 ***
0.014 *
0.001 ***
0.072 .
0.071 .
0.063 .
0.030 *
0.057 .
0.273
0.045 *
0.037 *
0.018 *
0.018 *
0.757
0.538
0.052 .
0.052 .
0.029 *
0.030 *
0.026 *
0.043 *
0.014 *
Axis 1
-0.06
0.06
0.53
0.07
-0.65
-0.65
-0.64
0.55
0.63
0.10
0.62
0.56
0.50
0.32
0.99
0.48
-0.24
-0.24
-0.37
-0.92
-0.08
-0.21
Axis 2
-1.00
1.00
0.85
1.00
0.76
-0.76
-0.77
0.83
0.78
-1.00
0.78
0.83
0.87
0.95
-0.17
-0.88
-0.97
-0.97
-0.93
-0.40
-1.00
-0.98
r2
0.4128
0.4092
0.7176
0.3793
0.8402
0.8385
0.8193
0.7239
0.8218
0.2227
0.7493
0.7225
0.7516
0.8489
0.3848
0.2212
0.2982
0.2982
0.3678
0.6475
0.269
0.3193
Pr(>r)
0.357
0.341
0.068 .
0.389
0.030 *
0.031 *
0.039 *
0.060 .
0.035 *
0.526
0.058 .
0.060 .
0.048 *
0.019 *
0.403
0.597
0.513
0.513
0.432
0.165
0.484
0.491
Metatranscriptomes
Parameter
Temperature
Salinity
Depth
Density
Oxygen (ml.L)
Oxygen (umol/kg)
Oxygen Saturation
Total Nitrogen
AOU
Chlorophyll-A
Dissolved organic nitrogen
Phosphate
Nitrate
Silicate
Nitrite
Ammonia
particulate organic carbon
particulate organic nitrogen
particulate organic phosphate
Bacterioplankton
Synechococcus
Phytosynthetic Eukaryotes
73
Table 4.3 (Continued)
Diatoms
-0.26
-0.97
--Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
P values based on 999 permutations.
0.5905
0.165
74
Figure 4.1 Non metric multidimensional scaling ordination of TRFLP data collected
during 2009 at stations SH70 and SH90 (A). Samples selected for high-throughput
sequence analyses highlighted in orange (B).
75
Figure 4.2 Hierarchical clustering dendograms (top) and NMDS plots (bottom) of
metagenomic (A) and metatranscriptomic profiles (B).
A. Metagenomes
B. Metatranscriptomes
60
Similarity
80
85
70
90
80
Depth
2D Stress: 0
Summer
Fall
Axis II
Fall
Fall
Fall
BBL
metagenomes
Fall
BBL metatranscriptomes
2D Stress: 0
Summer
Summer
Summer
86
Fall
S imilarity
BBL metagenomes
Fall
100
Summer
Fall
Fall
Summer
Fall
Summer
Fall
Summer
Summer
90
Summer
surface
DCM
BBLTran
BBL
100
Summer
95
Axis II
Similarity
75
BBL
metatranscriptomes
Fall
Summer
Summer
Summer
Fall
Axis I
Summer
Axis I
Summer
Fall
76
Figure 4.3 Top 20 genome sequenced reference organisms detected based on the relative
proportion of protein encoding genes in metagenomes (A) and metatranscriptomes (B).
77
Figure 4.4 Inorganic nitrogen and Thaumarchaeal gene (A) and transcript (B)
distributions during the summer (red) and fall (yellow) and fall at station SH70. The yaxis represents the water column depth. Circle sizes are proportional to the effective
count of a given gene or transcript. The absolute gene frequency is listed either directly
below or in the center of a sample’s circle. NS: no sample.
20
2
6
11
2
8
10
16
510
219
482
126
331
164
424
334
40
2
68
7
108
11
90
10
104
6
113
11
261
24
153
27
157
23
60
water column depth (meters)
0
A
Nmar_1547/Nmar_1201
Cu-containing
Ammonia/methane
monoyxgenase (Amo) NO-forming nitrite
reductase (Nir)
Dissimilatory nitrate Recombinase A
reductase (Nar)
(recA)
1
2
127
28
22
7
40
20
4
2109
NS
642
NS
257
NS
262
1170
951
338
703
224
262
NS
60
water column depth (meters)
0
B
3988
38
Nmar_1547/Nmar_1201
Ammonia/methane
monoyxgenase (Amo)
Cu-containing
NO-forming nitrite
reductase (Nir)
Dissimilatory nitrate
reductase (Nar)
78
Figure 4.5 Phylogenetic diversity of 16S rRNA genes affiliated with Nitrospina
recovered in clone libraries (A) and the contribution of the observed TRFs to NMDS
analyses (B). Fragment size 194 (right inset, B) is represented in fluorescence units
relative to all peaks detected in TRFLP profiles.
79
Figure 4.6 Inorganic sulfur oxidation genes (A), Apr transcript distributions (B), and
high-scoring pairs to Apr transcripts from the BBL-transistion (C). y-axis represents
water column depth (A, B). Circle sizes are proportional to the relative amount of a given
protein encoding gene or transcript. The absolute count is listed either directly below or
in the center of a given sample’s circle. NS: no sample.
64
188
41
510
219
482
126
75
12
208
44
204
93
368
149
331
164
223
161
518
317
424
334
40
20
5
60
water column depth (meters)
0
A
Reverse dissimilatory
sulfite reductase (rDSR)
Adenosine-5’-phosphosulfate reductase
adenylsulfate reductase (Apr)
B
Recombinase A (recA)
0
C
11
3
30
30
40
20
putative 4Fe-4S binding domain protein [HF4000_141I21]
58
NS
putative fumarate reductase/succinate
dehydrogenase flavoprotein C-terminal domain protein
[uncultured marine microorganism HF4000_141I21]
predicted adenylylsulfate
reductase alpha subunit [EBAC2C11]
hypothetical protein
ALOHA_HF4000141I21ctg1g14
[ HF4000_141I21]
AprA [Thiocapsa roseopersicina]
AprA [Desulfonauticus submarinus]
AprA [Chlorobaculum limnaeum]
AprA [Bathymodiolus thermophilus]
adenylylsulfate reductase [Chlorobium tepidum TLS]
adenylylsulfate reductase [Psy. torquis ATCC 700755]
60
Apr alpha subunit [uncultured marine bacterium]
50
40
adenylyl-sulfate reductase chain B [HTCC1002]
adenylyl-sulfate reductase chain B [HTCC1062]
adenylylsulfate reductase membrane anchor [HTCC1062]
adenylylsulfate reductase membrane anchor [ HTCC7211]
adenylylsulfate reductase,
alpha subunit [HTCC7211]
adenylylsulfate reductase [HTCC1062]
Adenosine-5’-phosphosulfate reductase
adenylsulfate reductase (Apr)
adenylylsulfate reductase membrane anchor [ HTCC1002]
adenylylsulfate reductase, beta subunit [ HTCC7211]
SAR11 clade
23/58 in BBL Tran
80
Chapter 5
Inter-annual comparison of the variability in microbial metabolic diversity along
the inner-continental shelf of Oregon assessed using metagenomics
Anthony D. Bertagnolli, Salvador Ramirez-Flandes, Kevin Vergin, Osvaldo Ulloa and
Stephan Giovannoni
Unpublished
81
Abstract: Bacterial community structure and metabolic potential were assessed along the
coast of Oregon during 2010 using a combination of molecular ecology tools and
compared to previously published data from 2009. Terminal restriction fragment length
polymorphism analyses targeting the 16S rRNA gene from samples collected during the
spring, summer, and fall revealed spatial and temporal changes in microbial communities.
Consistent with previous surveys, samples collected in the bottom boundary layer
differed significantly from those collected in the surface layer. Subtle differences in
community structure were observed between samples collected during the early spring
and mid-summer in the BBL transition. These periods corresponded to well-mixed preupwelling conditions and mid-upwelling hypoxic summer conditions, respectively. These
two dates were selected for metagenomic sequencing. Hierarchical clustering analyses of
metagenomes based on the contribution of functional genes to each sample revealed
relationships driven largely by season. Spring metagenomes were not significantly
different based on spatial basis. In contrast, summer metagenomes did display depth
specific clustering, with samples collected in the BBL distinct from those collected in the
surface layer. Gene centric analyses suggested Thaumarchaeal nitrification potential
increased significantly with depth during the summer, consistent with previous
observations. Data presented here support the conclusion that upwelling contributes to
changes in microbial community diversity along the coast of Oregon.
82
Introduction
The microbial initiative in low oxygen waters located off the coasts of
Concepcion and Oregon (MI_LOCO) is a two-year pilot project aimed at identifying the
impact of transient episodes of hypoxia and anoxia on micoroorganisms along eastern
boundary current systems in the northern and southern hemispheres. Several molecular
ecology tools were applied to both the Oregon and Chilean field sites to assess the
temporal evolution of microbial communities in response to oxygen deprivation. These
included terminal restriction fragment length polymorphism analyses (TRFLP),
environmental genomics (metagenomics), and environmental transcriptomics
(metatranscriptomics). These techniques are exploratory in nature, yet useful for
generating hypotheses regarding the biogeochemical function of microorganisms in-situ
(40, 42).
During year one at the Oregon field site (2009), TRFLPs targeting the 16S rRNA
gene, metagenomes, and metatranscriptomes were analyzed within the context of
physical and chemical parameters. Data generated from 2009 are currently in review.
Briefly, TRFLP data suggested that bacterial communities displayed strong temporal
trends in the surface layer, while samples collected in the bottom boundary layer
transition and bottom boundary layer (BBL) appeared un-influenced by seasonality.
Analyses of metagenomes and metatranscriptomes revealed similar depth dependent
shifts in microbial community genomic and transcriptional potential. However, several
functional genes and transcripts were identified that displayed strong, oxygen dependent
shifts. A large proportion of these genes were affiliated with Thaumarchaea, indicating
that ammonia oxidation in shallow areas of the coastal marine environment maybe
influenced by variables such as dissolved oxygen.
Samples from this initial survey were collected from July 30th, under severe
hypoxic conditions, and September 21st, when water column conditions recovered to
non-hypoxic conditions. The water column characteristics associated with each period
suggested that similar masses had been sampled throughout the BBL and BBL transition
83
during both time periods (Figure 5.3B). Because the physical characteristics associated
with the water masses remained constant, changes observed in microbial communities
could be correlated with observed differences in measured nutrient and chemical data.
This initial survey was strong in establishing preliminary observations regarding the
impact of hypoxia on microbial communities along the Oregon coast. However, questions
regarding the variability of microbial diversity within the system remained, as only one
year of data had been presented. As well, little information regarding the microbial
communities associated with differing physical properties were identified.
To address questions about the inter-annual variability of our previous
observations and answer new questions concerning the metabolic potential associated
with differing water masses along the coast, 16S rRNA gene TRFLPs and metagenomes
from 2010 were analyzed and compared to those collected in 2009. Samples were
selected that represented non-hypoxic and hypoxic conditions. These samples also
represented substantially different water column conditions; well-mixed, pre-upwelling
water during the spring, and post-upwelling, stratified conditions corresponding to
hypoxia in the summer. In making these sample selections, the metabolic potential
associated with differing water masses could be analyzed. As well, we could assess the
reproducibility of previous observations regarding the distribution of different gene
suites, specifically those involved in inorganic sulfur and nitrogen transformations.
Materials and Methods
Environmental variables
Biogeochemical and physical measurements for samples associated with
metagenomic/metatranscriptomic sequence analyses are listed in Table 5.1.
Sample collection
Collection, isolation, and analyses of nucleic acids, have all been reported previously
(Chapter 4, Materials Methods). Only one difference was made in our analysis of the
2010 samples, and this was during the TRFLP analysis. Briefly, PCR conditions were
84
kept constant. However, environmental fragments were analyzed on an ABI3730
bioanalyzer, rather than an ABI3100. This difference is not trivial. While the peak sizes
made using the ABI3730 are similar to those observed on the ABI3100, the capillary
length of the ABI3730 is longer, and the limit of detection lower. These two differences
make comparison of environmental samples using the two different instruments difficult,
as fragment lengths observed using one instrument appear that would go unrecognized
using the other. The termination of the ABI3100 at the CGRB during fall of 2010 was
made by members of the core lab facility, as well as ABI Biosciences.
Statistical Methods
All statistical methodology used was previously reported. Briefly, Non-metric
multidimensional scaling was applied to TRFLP profiles using PRIMER-V6 software
package. Multivariate analyses of metagenomic profiles and gene-centric analyses were
performed in the R software environment. Metagenomic samples were analyzed against
the COG database to assess the frequency of putative single copy marker genes in MGRAST (4, 86). These values, in conjunction with other sequencing statistics were used to
make estimated average genome size comparisons.
Results & Discussion
Bacterial community structure as assessed by TRFLP
TRFLP data was applied to 31 samples collected during the 2010 field season. NMDS
analyses revealed clear spatial patterns (Figure 5.1A). Samples collected in the BBL
(SH70, SH90) and BBL transition were distinct from those collected in the surface and
deep-chlorophyll maximum. The strongest pair-wise difference in depth horizons was
between samples collected in the surface and BBL (ANOSIM R=0.569, p<0.002),
consistent with a previous molecular ecology survey off the coast of Oregon (9).
TRFLP profiles from the BBL transition during April clustered slightly away
from samples collected in the BBL (Figure 5.1B). Dissolved oxygen concentrations were
85
relatively homogenous throughout the water column, around 300 µmol/L (Table 5.1).
These samples were selected for high-throughput sequencing. During August, severe
hypoxic conditions were experienced in the BBL at station SH70 (59 µmol/L).
Temperature and salinity profiles suggested substantially different physical
characteristics between the April and August dates (Figure 5.3A). In making these sample
selections, differing water mass characteristics would be sampled in addition to hypoxic
conditions.
General sequence characteristics of metagenomes:
Pyrosequencing of planktonic nucleic acids generated a total of 3 Gbp of sequence
information between 8 samples (Table 5.2). Estimated average genome sizes based on the
distribution of 35 putative single copy marker genes were between 1.6-2.2 Mbp,
consistent with previous size estimates for planktonic microbial communities (100).
Multivariate assessment of 2010 metagenomes:
Hierarchical clustering analyses were used to assess differences in metagenomes
collected during 2010. Samples collected during the spring clustered in a separate group,
differing from those collected during the summer (Figure 5.2A). A clear depth dependent
trend was not observed in samples collected during April. For example, surface and BBL
samples were more closely associated with one another. August samples displayed a
depth dependent organization, with samples collected in the BBL and BBL transition
differing from those collected in the surface and deep-chlorophyll maximum.
The hierarchical clustering trends observed in 2009 were considerably different than
those observed in 2010 (Figure 5.2B). Previous observations in open ocean environments
have suggested that depth is the most crucial factor in governing microbial metabolic
potential (3). While depth is no doubt a major factor along the Oregon coast, data from
2010 suggest that seasonal differences may also influence microbial communities
throughout differing depth horizons.
86
Gene centric analyses:
Functional gene cluster frequencies were assessed to determine whether
previously observed trends in microbial metabolic function were repeatable. During
2009, several gene suites and transcripts affiliated with chemolithotrophic processes were
identified that increased significantly in the BBL environment. Reverse dissimilatory
sulfite reductase (rDSR), involved in inorganic sulfur transformations, increased
significantly in the BBL during 2009. This gene did not display a depth dependent trend
in its distribution during the spring of 2010 (Figure 5.4). During the summer, however, a
significant increase in the relative abundance of this gene was observed. rDSR was
detected maximally in the BBL, consistent with data from 2009. High scoring BLASTX
pairs (HSPs) affiliated with rDSR were assessed. During the spring, a substantial
proportion of the HSPs throughout the water column were affiliated with organisms that
have as of yet un-identified roles in sulfur oxidation. During the summer, however, a
significant shift in the HSPs was observed, with putative sulfur oxidizing symbionts
dominating the HSPs, and included SUP05 and Candidatus Ruthia magnifica (142).
Ammonia monooxygenase (Amo) was identified in metagenomes and
metatranscriptomes and displayed significant depth dependent shift in its distribution
during 2009. Like rDSR, Amo did not display any significant depth dependency during
the spring, and HSPs were to organisms that have not been identified as canonical
ammonia oxidizers (Figure 4). However, during the summer, amo distributions displayed
significant linear increases, with maximal frequencies in the BBL. HSPs shifted to
ammonia oxidizing organisms, and were dominated by HSPs to characterized or
environmental Thaumarchaeal genes. These data suggest that temporal variability exists
in the distribution patterns of inorganic nitrogen and sulfur cycling gene suites.
Conclusion
Data collected during 2010 suggest metagenomes of pre-upwelling spring water
residing along the coast of Oregon are different from those collected during the summer
87
amidst upwelling conditions, and that stratification does not occur until after upwelling
has occurred. A previous survey of the western English channel revealed substantial
seasonality in metagenomes, metatranscriptomes, and 16S rRNA gene amplicons
attributed with differing water masses in the surface layer (41). Our data support this
observation as well, and suggest that water masses along eastern boundaries also harbor
differing functional potential.
The increase in abundance of chemolithotrophic gene suites with depth during the
summer months is a repeatable feature. Increased frequencies of sulfur oxidizing genes
suggests that the potential for microaerophilic thiotrophy is harbored within this
environment. Whether inorganic sulfur oxidation actually occurs remains to be tested.
The increase in abundance of ammonia oxidizing organisms during the summer is
suggests that nitrification maybe strongest during the summer, amidst seasonal hypoxia.
Previous studies have suggested that Thaumarchaeal nitrifiers are most transcriptionally
active in the oxyclines of oxygen minimum zones. These environments contain similar
dissolved oxygen concentrations as those in severe hypoxic areas. As such, it is not
surprising that these groups display substantial increases in low oxygen areas.
This preliminary analysis of metagenomes from 2010 provides yet another layer
of knowledge regarding microbial community diversity along the Oregon coast. This data
will be incorporated into larger, multi-hemisphaere comparison between eastern
boundary current systems susceptible to severe hypoxia in the near future. The
observations made here regarding the underlying metabolic potential of water masses
should guide these analyses.
88
Table 5.1 Environmental metadata associated with metagenomes from both 2009 and
2010.
Date
July30th 2009
July30th 2009
July30th 2009
July30th 2009
September 21st 2009
September 21st 2009
September 21st 2009
September 21st 2009
April 14th 2010
April 14th 2010
April 14th 2010
April 14th 2010
August 10th 2010
August 10th 2010
August 10th 2010
August 10th 2010
July30th 2009
July30th 2009
July30th 2009
July30th 2009
September 21st 2009
September 21st 2009
September 21st 2009
September 21st 2009
April 14th 2010
April 14th 2010
April 14th 2010
April 14th 2010
August 10th 2010
August 10th 2010
August 10th 2010
August 10th 2010
July30th 2009
July30th 2009
July30th 2009
July30th 2009
September 21st 2009
September 21st 2009
September 21st 2009
September 21st 2009
April 14th 2010
April 14th 2010
April 14th 2010
April 14th 2010
August 10th 2010
August 10th 2010
Depth (m)
Temp (°C)
70
7.328
55
7.362
25
8.450
5
11.486
70
8.382
50
8.815
25
10.575
5
15.046
70
10.234
55
10.436
10.517
25
5
11.069
70
7.078
40
7.267
11
9.253
5
11.455
Fluo-CTD (mg/m3) PAR (µmol/m2/s)
3.104
0.008
1.133
0.012
45.766
0.033
1.104
273.600
0.969
0.458
1.372
1.701
14.109
12.627
386.435
2.799
0.109
1.897
0.268
4.366
15.935
7.535
536.824
2.627
0.003
2.987
0.028
17.290
74.746
2.412
382.141
NO2 (µM)
NH4(µM)
0.219
0.100
0.167
0.097
0.365
2.183
0.085
0.030
0.608
3.173
0.289
2.045
0.238
3.736
0.059
0.069
0.265
1.093
0.183
1.237
0.018
0.090
0.016
0.004
0.123
0.040
0.080
0.023
Salinity
33.893
33.889
33.720
33.821
33.619
33.441
33.249
32.573
32.719
32.532
32.471
31.785
33.906
33.702
33.586
33.475
PO4 (µM)
3.241
3.198
2.490
0.149
2.618
2.157
1.333
0.416
0.977
0.765
0.564
0.311
2.808
2.386
0.496
0.113
SiO3 (µM)
81.748
78.173
15.680
0.738
48.139
26.428
8.356
0.895
11.565
6.570
2.752
4.076
62.604
42.990
Sigma-t (kg m-3)
26.501
26.494
26.202
25.765
26.133
25.926
25.488
24.092
25.133
24.952
24.891
24.261
26.546
26.359
25.971
25.506
NO3 (µM)
32.560
32.255
21.398
-0.005
25.810
22.463
8.864
0.508
5.793
2.444
0.170
0.189
34.643
31.117
0.245
0.029
O2 winkler (µm/L)
20
23
154
482
123
175
251
302
270
287
256
327
59
108
89
Table 5.1 (Continued)
August 10th 2010
August 10th 2010
July30th 2009
July30th 2009
July30th 2009
July30th 2009
September 21st 2009
September 21st 2009
September 21st 2009
September 21st 2009
April 14th 2010
April 14th 2010
April 14th 2010
April 14th 2010
August 10th 2010
August 10th 2010
August 10th 2010
August 10th 2010
0.089
0.059
POC (µM)
9.877
7.218
139.331
68.491
6.663
5.124
9.171
27.938
11.636
8.287
40.430
23.867
10.686
8.857
87.820
28.297
0.592
0.025
PON (µM)
0.995
0.941
20.675
6.155
0.979
0.944
1.641
3.750
1.847
1.181
4.514
2.076
1.443
1.058
13.116
3.133
3.341
0.991
POP (µM)
0.098
0.089
0.703
0.485
0.085
0.062
0.088
0.229
0.084
0.087
0.044
0.176
0.118
0.095
0.489
0.273
382
423
90
Table 5.2 General sequencing statistics from metagenomes aquired in 2010.
Sample
April 14th 2010 5m
April 14th 2010 25m
April 14th 2010 55m
April 14th 2010 70m
August 10th 2010 5m
August 10th 2010 11m
August 10th 2010 40m
August 10th 2010 70m
reads
1119236
807130
1285216
876686
1194267
1324098
1056559
1489042
Bps
415789165
311905824
557492020
307804568
467503314
531683652
414323580
590937865
average read length
391.46
386.44
433.77
386.44
385.79
397.3
387.24
393.6
read length SD Average Genome Size Effective Sequence Counts
130.61
1793895
1169191
150.37
2115413
715005
120.14
1942192
1240065
150.37
1623346
1012031
132.06
1967056
1137746
126.49
2029716
1222491
131.81
1734445
1141547
116.28
1785629
1562703
91
Figure 5.1 NMDS analyses of TRFLP profiles. Samples labeled according to depth (A)
and those samples submitted for high-throughput sequencing (B).
A
Resemblance: S17 Bray Curtis similarity
2D Stress: 0.14
Depth
Surface
DCM
BBL­TRAN
BBL­90
BBL
B
Resemblance: S17 Bray Curtis similarity
2D Stress: 0.14
selection
YES
NO
August 10th
BBL
August 10th
BBL Transition
April 6th
DCM
April 6th
BBL Transition
April 6th
BBL
August 10th
Surface
April 6th
Surface
August 10th
Surface
Fall Surface Samples
Height
0.10
Sep21.5m.2009
0.05
Sep21.20m.2009
Summer Surface Samples
Bottom Boundary Layer Samples
BBLSep21.2009
BBLTranSep21.2009
BBLJuly30.2009
0.15
0.20
0.05
0.10
Apr9.70m.2010
Apr9.5m.2010
Apr9.50m.2010
Apr9.20m.2010
0.00
BBLAug10.2010
BBLTranAug10.2010
DCMAug10.2010
SurfaceAug10.2010
Spring Samples
BBLTranJuly30.2009
DCMJuly30.2009
July30.5m.2009
0.00
0.20
Height
0.15
0.25
92
Figure 5.2 Hierarchical clustering analysis of metagenomes based on the relative
abundance of functional genes to metagenomes (ie. nrcDB clusters) for 2010 (A) and
2009 (B) samples.
A
Summer Samples
B
93
Figure 5.3 Temperature and salinity plots from 2009 (A) and 2010 (B). Temperature (Xaxis) and Salinity (Y-axis).
A
70m.Aug10.2010
55m.Aug10.2010
5m.Aug10.2010
SurfaceAug10.2010
33.0
Summer samples
70m.Apr9.2010
32.5
50m.Apr9.2010
20m.Apr9.2010
32.0
Spring Samples
5m.Apr9.2010
7
8
9
10
11
temperature
70m.July30.2009
55.July30.2009
70m.Sep21.2009
33.4
50m.Sep21.2009
20m.Sep21.2009
summer surface,
summer and fall BBL
33.0
33.2
5m.July30.2009
25m.July30.2009
33.6
33.8
B
32.8
fall surface
32.6
salinity
salinity
33.5
25m.Aug10.2010
5m.Sep21.2009
8
10
12
temperature
14
SurfaceSep21.2009
94
Figure 5.4 Relative abundance of ammonia/methane monooxygenase (dark) and reverse
dissimilatory sulfite reductase (light) in 2010 metagenomes.
0.04
Ammonia/methane monooxygenase and reverse dissimilatory sulfite reductase gene frequencies
Ammonia/methane monooxygenase
0.03
0.02
0.01
0.00
gene frequency (effective sequence counts)
reverse dissimilatory sulfite reductase
april5m
april20m
spring samples
april50m
april70m
august5m
august25m
august55m
summer samples
august70m
95
Chapter 6
Conclusion
Prior to this dissertation there was little information about microbial diversity in
shallow coastal environments, other than for surface samples. Depth was previously
identified as the major factor correlated with microbial community diversity in deeper
ocean regions, but it was not known how this variable shaped the phylogenetic and
metabolic diversity of microorganisms in shallow waters of continental shelves.
Analyses of bacterial 16S rRNA genes using TRFLP in chapters two, four, and
five consistently revealed strong pair-wise differences between the surface and bottom
boundary layer environments. The data support the conclusion that depth strongly
influences bacterial community structure in shallow coastal regions, as it does in deep,
less productive offshore ocean regions, but revealed the presence of many taxa unique to
the lower depths of the coastal environment. Phylogenetic analysis of 16S rRNA gene
clones recovered from these areas in chapter two, three, and four demonstrated multiple
novel evolutionary lineages in this region of the water column. Organisms with
evolutionary relationships to either both putative and well-characterized lithotrophic taxa
were consistently observed in bacterial and archaeal 16S rRNA gene clone libraries from
the BBL. These included organisms ostensibly involved in transformations of inorganic
sulfur and nitrogen compounds.
Analyses of metagenomes and metatranscriptomes in chapter 4 provided new
insights into the metabolic potential and physiological state of microorganisms in shallow
coastal waters. Oxygen dependent changes in organisms and their transcriptional
activities were also identified. Thaumarhcaea activity varied significantly between
hypoxic and non-hypoxic conditions. Functional genes identified as being actively
transcribed were those involved in ammonia oxidation, as well as hypothetical genes that,
as of yet, have no known function. This is evidence in support of the hypothesis that
dissolved oxygen may substantially influence nitrification. This thesis followed an
96
experimental design utilizing metatranscriptomics coupled with metagenomics.
Accessing nucleic acids information from genes and transcripts has become increasingly
cost effective due to the development high-throughput, massively paralleled sequencing
platforms. Transcript data was appropriate for answering questions regarding seasonal
variability in microbial activity, as the average half-life of bacterial mRNAs are between
30 seconds to 50 minutes (130). It is likely that results observed here represented
relatively recent microbial activities, and did not represent previous environmental
conditions.
Genes and transcripts encoding for proteins putatively involved in inorganic
sulfur transformations increased in relative abundance in the BBL after upwelling0.
These data suggest that microbes in this environment are poised to utilize reduced
inorganic sulfur compounds. Members of the SAR11 clade were identified as actively
transcribing adenosine-5’-phosphosulfate reductase, an enzyme that is predicted to
oxidize sulfite to sulfate. It is unclear at this time whether this gene suite is truly used for
utilization of inorganic sulfur oxidation. Future experimentation will yield more
definitive evidence regarding the importance of these observations.
In Chapter 5, metagenomics was used to assess the underlying metabolic potential
of samples collected during the spring prior to upwelling, and the summer, during an
upwelling period. The data suggested that the microbial communities associated with the
well-mixed conditions typical of the spring and the up-welled waters of the summer are
unique from one another, and that depth impacts metabolic diversity most substantially
during the summer, after water masses have become stratified.
One of the most interesting observations made within this dissertation is the
increased frequency of genes and transcripts affiliated with utilization of inorganic
electron donors in the BBL despite the presence of organic matter. This would imply,
perhaps, that these compounds are semi-labile, and not of sufficient quality for utilization
as substrates for growth.
97
Currently, few oceanographic models exist that take into account specific details
regarding microbial community diversity. Subtle changes in the distribution and activity
of these organisms will no doubt impact oceanic and atmospheric chemistry. This
dissertation has displayed that substantial differences in microbial communities exist
along physical and chemical gradients within the coastal realm. This information could
be useful in creating more holistic predictions regarding the impact of changes in
dissolved chemical species, such as oxygen, on global climate change.
98
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Appendices
118
Appendix A
Metagenome annotations displaying depth dependent increases (R>1, p<0.001)
Radical.SAM.domain.containing.proteins
CENSYa_0159,.0161,.2059,.Nmar_1547,.1201
Hypothetical.archael.protein.related.to.Nmar_0067
Copper.domain.containing.protein..blue,.type1,.plastocyanin.azurin.
MCM.family.protein
CoA.binding.domain.protein
Ammonia.Methane.Monooxygenase
Glycosyl.transferases
UbiD.family.decarboxylase
Adenosine.5..phosphosulfate.reductase.Adenylylsulfate.reductase.APS.reductase
Dissimilatory.nitrate.reductase
SMC.domain.containing.protein
Geranylgeranyl.reductase
urea.ABC.transporter.permease
Thiamine.biosynthesis.protein..ThiC,ThiF,ThiL.
Transcription.initiation.factors
Exosome.complex.exonuclease
Dissimilatory.Sulfite.reductase.Sulfur.oxidation
IMP..inosine.5.monophosphate..dehydrogenase.family.protein
isopropylmalate.homocitrate.citramalate.synthase
Ig.family.protein
metal.cation.transporter
ArsR.family.transcriptional.regulator
Dissimilatory.nitrite.reductase..CuNIR,.NO.forming.
Aspartate.ammonia.lyase
4.hydroxybutyryl.CoA.dehydratase
Phosphoribosylamine.glycine.ligase
Glu.Leu.Phe.Val.dehydrogenase
N.acetyl.gamma.glutamyl.phosphate.reductase
glutamyl.tRNA.reductase
Proteasome..endopeptidase,.nucleotidase.and.core.complexes.
Lysine.2,3.aminomutase
Dehydrogenase..flavoprotein..like.protein
Snf7,.COG5491:.protein.secretion
homocysteine.S.methyltransferase
Peptidylprolyl.isomerase
Cysteinyl.tRNA.synthetase.Cysteine..tRNA.ligase
Mechanosensitive.ion.channel
Ornithine.carbamoyltransferase
Cell.division.protein..archaeal.cdvABC.
2,.4.dienoyl.CoA.reductase..NADPH..Short.chain.dehydrogenase.reductase.SDR
glucosamine.6.phosphate.synthetase
methylamine
Collagen.triple.helix.repeat
solute.binding.protein.like.protein
hypothetical.protein.Nmar_0343
pyruvate.carboxyltransferase
Nitrilase.cyanide.hydratase.and.apolipoprotein.N.acyltransferase
119
Appendix A (Continued)
hydroxymethylglutaryl.CoA.3.hydroxy.3.methylglutaryl.CoA.synthase
phosphoesterase.DHHA1
Ribosome.Pseudouridylate.synthase
SPFH.domain.containing.protein.band.7.family.protein
Trans.Sialidase
Pyridoxal.5..phosphate.dependent.proteins
isocitrate.isopropylmalate.dehydrogenase
Molybdopterin.biosynthesis.MoeA.protein
Citrate.transporter.Na+:H+.antiporter.NhaD
hypothetical.protein.Nmar_0467.
ATP.phosphoribosyltransferase
peptidyl.prolyl.cis.trans.isomerase
ROK.family.protein
Secreted.periplasmic.Zn.dependent.protease
hypothetical.protein.Nmar_1648
Poly.R..hydroxyalkanoic.acid.synthase
histone.acetyltransferases
Homoserine.O.succinyltransferase
thioredoxin.reductase
saccharopine.dehydrogenase
Diaminopropionate.ammonia.lyase
2.dehydro.3.deoxyphosphooctonate.aldolase
hypothetical.protein.Nmar_0627
polyprenyl.synthetase
Asparagine.synthase,.glutamine.hydrolyzing
ribulose.1,5.biphosphate.synthetase..thiazole.biosynthetic.protein.
cytochrome.P.450
N,N.dimethylformamidase
Homoserine.kinase
diphthine.synthase
ATPase.involved.in.DNA.replication
UDP.N.acetylmuramoylalanyl.D.glutamate..2,6.diaminopimelate.ligase
Morn.motif.containing.protein
Multicopper.oxidases
UbiA.prenyltransferase
peptidoglycan.glycosyltransferase
aspartate.dehydrogenase
3.dehydroquinate.synthase
hypothetical.protein.Nmar_1501
hypothetical.protein.Nmar_0344
replication.factor.C
2.alkenal.reductase
aspartate.glutamate.uridylate.kinase
COG1085:.Galactose.1.phosphate.uridylyltransferase
Acyl.phosphate:Glycerol.3.phosphate.acyltransferase
Hydantoinase.oxoprolinase
response.regulator.receiver.protein
cobalt.zinc.cadmium.resistance.protein..CzcA..like
hydroxymethylglutaryl.CoA.reductase
120
Appendix A (Continued)
Co.Zn.Cd.cation.transporter
FG.GAP.repeat.protein
diphthamide.biosynthesis.protein
Serine.protein.kinase
Serine.Threonine.protein.kinases
precorrin.4.C11.methyltransferase
lipid.A.disaccharide.synthetase
Transcriptional.regulator,.LysR.family
GXGXG.motif.containing.protein
Thiol:disulfide.interchange.protein..DsbD..protein.disulfide.reductase
Signal.peptidase.I
5..nucleotidase
pfam03781:.FGE.sulfatase..Formylglycine.generating.sulfatase.
H.+..transporting.two.sector.ATPase.V.type.ATPase
3.methyl.2.oxobutanoate.hydroxymethyltransferase
cobalamin.5..phosphate.synthase
Lipoate.synthase
Hypothetical.protein.CENSYa_1985.[Cenarchaeum.symbiosum.A]
Alba,.DNA.RNA.binding.protein
phosphate.uptake.regulator
major.facilitator.transporter
Diaminopimelate.epimerase
dolichyl.diphosphooligosaccharide..protein.glycotransferase
Pyridoxal.phosphate.biosynthetic.protein.PdxJ
tRNA.Ile..lysidine.synthetase
oxidoreductase,.aldo.keto.reductase.family
[Acyl.carrier.protein].S.malonyltransferase
hypothetical.protein.Nmar_1599
Transaldolase
Cytochrome.bd.type.quinol.oxidase
Hydroxylamine.Hydrazine.oxidoreductase..HAO.
precorrin.3B.C17.methyltransferase
metal.dependent.phosphohydrolase
Thymidine.phosphorylase
Dihydrodipicolinate.synthetase
Glycerol.3.phosphate.dehydrogenase...glucose.1.phosphate.uridylyltransferase
UDP.N.acetylglucosamine.acyltransferase
Phosphopentomutase
isopropylmalate.synthase.homocitrate.synthase
molybdenum.ABC.transporter
5.carboxymethyl.2.hydroxymuconate.Delta.isomerase
Universal.stress.protein.UspA
NHL.repeat.containing.protein
Thymidine.kinase
eRF1.domain.containing.1.protein
Hypothetical.protein.Nmar_1506.[Nitrosopumilus.maritimus.SCM1]
Thiazole.synthase
Leucine.rich.repeat.protein
SpoVR.family.protein
121
Appendix A (Continued)
Propanoyl.CoA.C.acyltransferase
COG0790:.FOG:.TPR.repeat,.SEL1.subfamily
pyridoxine.biosynthesis.protein
3.deoxy.D.manno.octulosonic.acid.transferase
hypothetical.protein.Nmar_1538
phosphoglycolate.phosphatase
Myo.inositol.1.phosphate.synthase
Inositol.3.phosphate.synthase
S.adenosyl.methyltransferase
phosphoribosylanthranilate.isomerase
tRNA.delta.2..isopentenylpyrophosphate.transferase
Zn.dependent.protease
ATP.grasp.domain.containing.protein
Transcriptional.regulator..thaumarchaea.
Small.nuclear.ribonucleoprotein
KOW.domain.containing.protein
Organic.solvent.tolerance.protein
peptidyl.tRNA.hydrolase
Sec.independent.protein.translocase,.TatC.subunit
CTP.synthase
Cytidylate.kinase
Shikimate.dehydrogenase
hypothetical.protein.Nmar_0836
glutamine..scyllo.inositol.transaminase
hypothetical.protein.Nmar_1507.[Nitrosopumilus.maritimus.SCM1]
Glyoxalase.bleomycin.resistance.protein.dioxygenase
antioxidant.protein..peroxidase.
Iron.sulfur.cluster.insertion.protein.erpA
Glucose.sorbosone.dehydrogenase
thrombospondin.type.3.repeat.containing.protein
UDP.N.acetylmuramoylalanine..D.glutamate.ligase
Adenylate.Cyclase.Adenylyl.cyclase
Pyruvate:ferredoxin.oxidoreductase
Phosphoribulokinase
D.amino.acid.dehydrogenase
Multihaem.cytochrome.c.[Candidatus.Nitrospira.defluvii]
Kinetoplast.DNA.associated.protein
histidinol.phosphate.aminotransferase
Antibiotic.biosynthesis.monooxygenase
undecaprenyl.diphosphate.synthase
7,8.dihydro.6.hydroxymethylpterin..pyrophosphokinase.[uncultured.SUP05.cluster.bacterium]
Ribosome.maturation.factor.rimP
Exonucleases
Negative.regulator.of.genetic.competence.ClpC.MecB
Pyridoxal.biosynthesis.lyase.pdxS
Uracil.phosphoribosyltransferase
DNA.adenine.methylase
beta.alanine..pyruvate.transaminase
dual.specificity.protein.phosphatase
122
Appendix A (Continued)
dephospho.CoA.kinase
Subtilase.family.protein
Sodium.solute.transporter.symporter
Tryptophanase
Assimilatory.nitrate.reductase
beta.lactam.antibiotic.acylase.family.protein
Translation.elongation.factor.G
hypothetical.protein.Nmar_0968
Isocitrate.dehydrogenase.kinase.phosphatase
Prepilin.peptidase
Metal.efflux.pump
Hemimethylated.DNA.binding.region
acetoacetyl.CoA.synthase
Malate:quinone.oxidoreductase..Mqo.
Adenylyl.sulfate.kinase.APS.kinase
dehydratase,.YjhG.YagF.family
Dihydroneopterin.aldolase
carbohydrate.kinases
cobyrinic.acid.a,c.diamide.synthase
SsrA.binding.protein
Formyl.CoA.transferase
TldD.PmbA.family.protein
Aldehyde.ferredoxin.oxidoreductase
Dihydropteroate.synthase
Toluene.tolerance.ABC.efflux.transporter,.permease
hypothetical.protein.Rmag_0224.
COG0716:.Flavodoxins
CO.dehydrogenase.acetyl.CoA.synthase
Anaerobic.dehydrogenase.molybdopterin.oxidoreductase
Hypothetical.protein.Nmar_0298.[Nitrosopumilus.maritimus.SCM1]
Hypothetical.protein.Nmar_0992.[Nitrosopumilus.maritimus.SCM1]
Methyltransferase.type.11.arsenite.S.adenosylmethyltransferase
UDP.N.acetylglucosamine.pyrophosphorylase
RNA.3..terminal.phosphate.cyclase
4.hydroxybutanoyl.CoA.dehydratase.Vinylacetyl.CoA.Delta.isomerase
Octaheam.cytochrome.c.[NC10.bacterium..Dutch.sediment.]
Secretion.protein.HlyD
pyruvate.oxaloacetate.carboxylase
COG0107:.Imidazoleglycerol.phosphate.synthase
Nitrous.oxide.reductase
3.ketoacyl.CoA.thiolase
Pyridoxine.5..phosphate.synthase..PNP.synthase.
Malate.IMP.dehydrogenase
.p.ppGpp.synthetase
Sulfite.oxidases..molybdopterin,.cytochrome.subunits.
Phosphoribosylglycinamide.formyltransferase
Formiminoglutamate.deiminase
SirA.family.protein
123
Appendix B
Annotation
Radical.SAM.domain.containing.proteins
CENSYa_0159,.0161,.2059,.Nmar_1547,.1201
Copper.domain.containing.protein..blue,.type1,.plastocyanin.azurin.
urea.ABC.transporter.permease
Transcription.initiation.factors
SMC.domain.containing.protein
Hypothetical.archael.protein.related.to.Nmar_0067
Geranylgeranyl.reductase
ArsR.family.transcriptional.regulator
Ammonia.Methane.Monooxygenase
MCM.family.protein
Proteasome..endopeptidase,.nucleotidase.and.core.complexes.
UbiD.family.decarboxylase
CoA.binding.domain.protein
metal.cation.transporter
isopropylmalate.homocitrate.citramalate.synthase
IMP..inosine.5.monophosphate..dehydrogenase.family.protein
Glu.Leu.Phe.Val.dehydrogenase
4.hydroxybutyryl.CoA.dehydratase
Serine.protein.kinase
solute.binding.protein.like.protein
Dissimilatory.nitrate.reductase
Lysine.2,3.aminomutase
glucosamine.6.phosphate.synthetase
oxidoreductase,.aldo.keto.reductase.family
H.+..transporting.two.sector.ATPase.V.type.ATPase
Exosome.complex.exonuclease
pyruvate.carboxyltransferase
histone.acetyltransferases
Ig.family.protein
homocysteine.S.methyltransferase
Peptidylprolyl.isomerase
Dissimilatory.nitrite.reductase..CuNIR,.NO.forming.
polyprenyl.synthetase
Dehydrogenase..flavoprotein..like.protein
Cell.division.protein..archaeal.cdvABC.
ribulose.1,5.biphosphate.synthetase..thiazole.biosynthetic.protein.
SPFH.domain.containing.protein.band.7.family.protein
Phosphoribosylamine.glycine.ligase
ROK.family.protein
hydroxymethylglutaryl.CoA.3.hydroxy.3.methylglutaryl.CoA.synthase
Homoserine.kinase
phosphoesterase.DHHA1
thioredoxin.reductase
UbiA.prenyltransferase
hypothetical.protein.Nmar_0467.
ATPase.involved.in.DNA.replication
aspartate.glutamate.uridylate.kinase
124
Appendix B (Continued)
Aspartate.ammonia.lyase
hypothetical.protein.Nmar_1501
Myo.inositol.1.phosphate.synthase
hydroxymethylglutaryl.CoA.reductase
Poly.R..hydroxyalkanoic.acid.synthase
aspartate.dehydrogenase
Universal.stress.protein.UspA
Phosphopantothenoylcysteine.decarboxylase.phosphopantothenate..cysteine.ligase
dolichyl.diphosphooligosaccharide..protein.glycotransferase
cobalamin.5..phosphate.synthase
diphthine.synthase
hypothetical.protein.Nmar_0344
Secreted.periplasmic.Zn.dependent.protease
Multicopper.oxidases
hypothetical.protein.Nmar_0343
Snf7,.COG5491:.protein.secretion
diphthamide.biosynthesis.protein
SpoVR.family.protein
hypothetical.protein.Nmar_0627
isocitrate.isopropylmalate.dehydrogenase
Trans.Sialidase
2.alkenal.reductase
Pyridoxal.5..phosphate.dependent.proteins
hypothetical.protein.Nmar_1599
precorrin.3B.C17.methyltransferase
Collagen.triple.helix.repeat
replication.factor.C
Hypothetical.protein.CENSYa_1985.[Cenarchaeum.symbiosum.A]
Nitrilase.cyanide.hydratase.and.apolipoprotein.N.acyltransferase
hypothetical.protein.Nmar_1648
eRF1.domain.containing.1.protein
5.carboxymethyl.2.hydroxymuconate.Delta.isomerase
Glucose.sorbosone.dehydrogenase
response.regulator.receiver.protein
Propanoyl.CoA.C.acyltransferase
pfam03781:.FGE.sulfatase..Formylglycine.generating.sulfatase.
Glyoxalase.bleomycin.resistance.protein.dioxygenase
COG1085:.Galactose.1.phosphate.uridylyltransferase
metal.dependent.phosphohydrolase
DNA.adenine.methylase
Small.nuclear.ribonucleoprotein
ATP.grasp.domain.containing.protein
Dihydropteroate.synthase
undecaprenyl.diphosphate.synthase
NHL.repeat.containing.protein
hypothetical.protein.Nmar_1507.[Nitrosopumilus.maritimus.SCM1]
thrombospondin.type.3.repeat.containing.protein
Transcriptional.regulator..thaumarchaea.
hypothetical.protein.Nmar_0836
125
Appendix B (Continued)
hypothetical.protein.Nmar_1538
Tail.tubular.protein.B
precorrin.4.C11.methyltransferase
glutamine..scyllo.inositol.transaminase
Alba,.DNA.RNA.binding.protein
Cytochrome.bd.type.quinol.oxidase
hypothetical.protein.Nmar_0968
126
Appendix C
Transcriptome Annotations Overrepresented in hypoxic conditions (R>1, p<0.001)
CENSYa_0159..0161..2059..Nmar_1547..1201
Hypothetical.protein.RAZWK3B_00595..Roseobacter.Magnetospirillum.Brucella.etc.
Ammonium.transporter..Amt.
Photosystems.I.and.II
Ammonia.Methane.Monooxygenase
Translation.initiation.elongation.factors
Dissimilatory.nitrite.reductase..CuNIR..NO.forming.
Dissimilatory.nitrate.reductase
Major.facilitator.superfamily
Copper.domain.containing.protein..blue..type1..plastocyanin.azurin.
Ferredoxin..iron.sulfur.protein.
SNF2.related.protein
Hypothetical.protein.Nmar_0992..Nitrosopumilus.maritimus.SCM1
Ribulose.1.5.bisphosphate.carboxylase.oxygenase..RuBisCO.&.regulators.
PKD.domain.protein
hypothetical.protein.Nmar_0343
Trans.Sialidase
YD.repeat.containing.protein
Viral.capsid.assembly.protein..virus
Beta.Ig.H3.Fasciclin
Rubrerythrin.rubredoxin
hypothetical.protein.SAR11_0864
Hypothetical.protein.GCWU000323_01826..Leptotrichia.hofstadii.F0254
porin
hypothetical.protein.Nmar_0344
Cytochrome.bd.type.quinol.oxidase
Unnamed.protein.product..Ostreococcus.tauri
Transcription.initiation.factors
Cold.shock.DNA.binding..transcriptional.regulator.
Cell.division.protein..archaeal.cdvABC.
hypothetical.protein.Nmar_0333
Snf7..COG5491:.protein.secretion
Cell.wall.associated.hydrolase
pfam03781:.FGE.sulfatase..Formylglycine.generating.sulfatase.
Pyruvate.2.oxoglutarate.ferredoxin.flavodoxin.synthase.oxidoreductase
hypothetical.protein.Nmar_1501
Extracellular.solute.binding.protein..families.1..7.
D5.protein
Senescence.associated.protein
Phasin..PhaP.
DNA.ligase
Superoxide.dismutase
Exocyst.complex
Histone.H2A.x
hypothetical.protein.Nmar_1507..Nitrosopumilus.maritimus.SCM1
ssDNA.binding.protein..phage.
Glyoxalase.bleomycin.resistance.protein.dioxygenase
MotA.TolQ.ExbB.proton.channel.family.protein
127
Appendix C (Continued)
Prohead.core.scaffolding.protein.and.protease..phage.
Hypothetical.protein.CENSYa_1985..Cenarchaeum.symbiosum.A
Altronate.dehydratase
Phage.g32.protein
glycerophosphodiester.phosphodiesterase
Hypothetical.protein.Nmar_0298..Nitrosopumilus.maritimus.SCM1
Molybdopterin.oxidoreductase.polysulphide.reductase..NrfD
carboxyl.terminal.protease
Enolase.2.phospho.D.glycerate.hydro.lyase.2.phosphoglycerate.dehydratase
Universal.stress.protein.UspA
mannitol.transporter
Multicopper.oxidases
Tricarboxylic.transport.TctA..TctC
Collagen.triple.helix.repeat
Exosome.complex.exonuclease
MnxG
Thiamine.biosynthesis.protein..ThiC.ThiF.ThiL.
Chromosomal.replication.initiator.proteins
Fructose.6.phosphate.aldolase.Fructose.1.6.bisphosphatase
Transcription.elongation.termination.factors
6.phosphogluconate.dehydrogenase.2.hydroxy.3.oxopropionate.reductase
Actin.related.proteins
Pyruvate:ferredoxin.oxidoreductase
DNA.polymerase..viruses.
Acyl.carrier.protein