Towards ‘Environomics’
Uptake and Molecular Studies of Nitrate Assimilation
by Marine Heterotrophic Bacteria
Marc E. Frischer
Skidaway Institute of Oceanography
Preparation
1985
A.B.
Washington University in St. Louis
(Microbial Genetics)
1985 - 1988
Protein Chemist - Sigma Chemical Co.
1988 - 1993 Ph.D.
University of South Florida
(Marine Science/Microbial Ecology)
1994 - 1996 Postdoc
Rensselaer Polytechnic Institute
(Molecular Microbial Ecology)
1996 - Present
Skidaway Inst. Of Oceanography
Research Interests
Exploration of microbial diversity and the
elucidation of linkages between the diversity
of microorganisms, the activity of microbial
populations, and the role that microbial diversity
plays in maintaining the stability and functioning
of marine/aquatic ecosystems.
Aquatic Molecular Microbial Ecology
Development and Use of Novel Molecular Techniques to
Measure Microbial Diversity and Link These Parameters
to the Functional Role of Microbes in Aquatic Systems.
Applied Aquatic Molecular Planktonic Studies
Application of Molecular Techniques for the
Study of Eukaryotic Pathogens and Planktonic
Bivalve Larvae
Linking N & C Cycles
Role of Molecular Approaches in Biogeochemical
Studies
Case Study: Nitrate Assimilation
by Heterotrophic Bacteria
Because most marine environments are
nitrogen limited, the nitrogen and carbon cycles
are intimately linked
In particular, the pathway of nitrate assimilation
into autotrophic or heterotrophic organisms
can have a profound influence on carbon cycling
Denitrification
N2
Nitrogen Fixation
Nitrate
Assimilation
NO3-
Nitrification
NH4+
Decomposition
Organic N
Assimilation
CO2
Primary Questions
Do Heterotrophic Marine Bacteria Assimilate Nitrate?
If so, How Much? What are the Controls? Are they
Competitive with Phytoplankton
Can Molecular Tools (Gene Based) Be Used to Determine
Who are the Nitrate Assimilators and What Controls Them?
Are Gene Presence and Expression of nasA Quantitatively
Linked to Nitrate Uptake Rates? CO2 Flux?
Are bacteria or the bacterial size
class (<0.2µ) taking up a significant
amount of NO3- in marine
environments?
Estimation of Total and Bacterial N Uptake Rates
Debbie Bronk - VIMS
Whole Sea Water
> 0.8 µm filtered Sea Water
< 0.8 µm filtered Sea Water
15N
NO3
15N NH
4
Incubate
1–3 hours
Mass
Spectrometry
Filter onto
0.2 µm Silver
Filters
Calculate
NO3 & NH4
Uptake Rates
By Size Class
Barents Sea
ICE
Open Water
% Uptake of NH4 and NO3 by < 0.8
Bacterial Uptake of DIN, Barents Sea June/July 1999
50
NO3
NH4
40
30
20
10
0
I
II
III
IV
V
Station
NCC
North
Atlantic
Polar
Front
Drift
Ice
Pack
Ice
Barents Sea Study
60
%NO3- Uptake <0.8
50
40
30
1:1 line
20
10
0
0
10
20
30
%NH4+ Uptake <0.8
40
50
60
SkIO
South Carolina
Georgia
Florida
% Uptake of NH4 and NO3 by < 0.8
South Atlantic Bight , April, 2000
50
NO3
40
NH4
30
20
10
0
Estuary
Inner-Shelf
Mid-Shelf
Bacteria Appear to Account for Significant
NO3 Uptake and Utilization
Up to 40% of Total NO3 Utilization May Be Due To
Bacteria Under Some Circumstances, but 10-15% is
Probably a More Reasonable Estimate
However, Experimental Methods are Flawed, Manipulative
and Laborious … Can Molecular Approaches be Useful?
Molecular Level Studies Cannot Provide
Rate and Flux Estimates, but Can Provide
Information Regarding
 Genetic capability
 Identification
 Study Regulation: Transcription into mRNA
 Study Regulation: Translation into protein, and
post-translational modification
 Protein characterization
 Signal Transduction
narB
narB
nasA
Presence of nasA = Ability to Assimilate NO3
Growth on NO3As Sole N Source
Growth
+
Growth
-
PCR
+
16
16
16
0
(32 Isolates from the Barents Sea)
0.1 substitutions/site
Marinobacter (45 clones, 2 isolates)
Marinomonas (10 clones, 1 isolate)
159 Clones
Unknown (12 clones)
10 Clone Libraries
Alpha (13 clones, 3 strains)
Vibrio (14 clones, 3 isolates)
Alteromonas (11 clones, 4 isolates)
100
Barents Sea Clones (43 clones)
100
Unknown SAB Clones (3 clones)
Psychrobacter (1 clones, 1 isolate)
100
Unknown SAB Clones (6 clones)
100 Unknown Barents Sea Clones (2 clones)
100
Beta (2 strains)
96
100
72
100
Methanobacterium sp. (Formate Dehydrogenase
Cyanobacteria (6 strains)
Are Genetic Differences Functionally Meaningful?
Growth Characteristics
Strain
Doubling Time
(hours)
Yield
(log Increase)
BS-4
3.78
3.60
BS-25
5.16
3.13
BS-10
5.48
3.31
BS-23
No Growth
0.59*
BS-26
No Growth
0.47*
All growth determination in NFG media (Tibbles and Rawlings, 1994)
supplemented with 10 mM nitrate (KNO3)
nasA expression regulation in Klebsiella oxytoca
6
K. oxytoca NO3- to NH4+
K. oxytoca NH4+ to NO3-
4.903
4
Gene Regulation
3
1.878
2
1.2304
1.1806
1
0.119
0
Tp
T0
T30
T60
Time
15NO 3
uptake into Klebsiella oxytoca
35000
30000
K. oxytoca nasA strictly
regulated
by NO3- and NH4+
25000
[NO3- ](µgatN/L/hr)
O.D./ngTotalRNA used in 1st Rnd
5
Are Genetic Differences
Functionally Meaningful?
20000
15000
10000
5000
0
Tp
T0
Time
T60
nasA expression regulation in Vibrio diazotrophicus
60
51.36
40
Gene Regulation
30
20
10
1.015
0
1.043
0
1.134
0
1.082
0
Tp
T0
T30
15NO 3
T60
Time
uptake in Vibrio diazotrophicus
2000.00
V. diazotrophicus:
nasA expression inhibited
By NH4+, but not stimulated
By NO3-
However, NO3- uptake occurs
In presence of NO3(long lived transcripts?)
1500.00
[NO3- ](µgatN/L/hr)
OD/ngTotal RNA in 1st Rnd
50
Are Genetic Differences
Functionally Meaningful?
V. diazotrophicus NO3- to NH4+
V. diazotrophicus NH4+ to
NO3-
1000.00
500.00
0.00
Tp
T0
Time
T60
nasA expression regulation in Pseudoalteromonas citrea
12
P.3- citrea
NO
to NH4+ NO3- to NH4+
+
P. citrea NH
to NO3- NH4+ to NO3P.4 citrea
Are Genetic Differences
Functionally Meaningful?
P. citrea
9.7
OD/ngTotal RNA in 1st
Round
10
8.509
8.697
8
7.312
6.612
6
Gene Regulation
4
2
1.9226
1.793
1.312
1.6198
1.2856
0
Tp
T0
T15
T30
T60
Time
15NO - uptake in Pseudoalteromonas citrea
3
3000
NO3- to NH4+
P. citrea NH4+ to NO3-
P. citrea
Pseudoaltermonas citrea:
Inhibited by NH4, but not
Stimulated by NO3
[NO3-](µgatN/L/hr)
2500
2000
1500
1000
500
0
Tp
T0
Time
T60
Does Genetic Identity Matter?
• The nasA Gene is Regulated Differently in Different Bacteria
• Growth Rates of Bacteria with Genetically Distinct nasA
Gene Sequences Differ
Presumably These are Important Contributing Factors to
The Ecology & Biogeochemistry of Nitrate Assimilation
By Heterotrophic Bacteria in Nature
Molecular Field Ecology
 Community Finger Printing –
(TRFLP & RT-TRFLP)
 Quantification – Q-PCR & QRT-PCR
Is community composition of nasA containing bacteria
correlated with nitrate parameters
(NO3 concentration & NO3 uptake rates) and other
biological/chemical parameters?
Is nasA expression correlated with nitrate and other parameters?
Back to the Barents Sea
Open Water (Station IV)
Ice (Station I)
Barents Sea T-RFLP Patterns
Cluster Analysis
57
Ice
62
79
80
Open
Water
65
Principal Components
Analysis
Ice
Open Water
PLS Model – Barents Sea July 1999
DNA TRFLP Fingerprints
LV1, x & y: 14% & 10%
1.0
NO30.5
NO3-
Bac Abundance
0.0
Bac Prod
% Active Cells
Chl a
-0.5
NH4+
-1.0
-0.6
-0.4
-0.2
0.0
0.2
LV1, x & y: 56% & 11%
0.4
0.6
Are nasA-encoding communities and
nasA expressing communities the same?
related? What factors are the diversity
of each related to?
Sequences derived
from transcripts
cluster together and
distinctly from sequences
derived from total community
DNA
Expressed Sequences from Clone Library
Expressed Sequences Detected by
RT-TRFLP
DK14 (14 sequences)
GSD10 (12 sequences)
DK18
TWS29
GSD10 (3 sequences)
GSS39
TWS2100015
GSD16 (7 sequences)
DK100013
DK3.5
DK2
GSS26 (2 sequences)
TWS210007 (2 sequences)
DK10003
TWS210008
TWS225
TWS210005
GSS4 (10 sequences)
TWS1 (19 sequences)
DK4 (4 sequences)
GSD11 (sequences) TWS31
GSD19
GSD9
GSS33
TWS2100010
DK10006
TWS210003 (10 sequences)
DK31 (5 sequences)
DK100014
DK100012
TWS21006
GSD7
TWS216
TWS230
DK10007
DK3h22
DK4h19
DK29
DK3.11
GSD23DK3.1
GSD26
GSS1
GSD27
GSS32
TWS2100014
TWS220
GSS12
GSS13
GSS24
GSS27 DK9 (5 sequences)
GSD34
DK3.3
GSS34
DK100011
DK10009 (2 sequences)
DK3.10
DK23
DK10005
DK35
Sargasso DNA- and RNA-derived nasA
(RT) TRFLP Studies
8
6
35d(DCM)
PC2
4
6-100r
2
5d
800r
18r
82.9r(DCM)
85.9d(DCM)
450r
40r(DCM)
800d
82.9d(DCM)
40d(DCM)
450d
800d
0
-2
82.9d(DCM)
100d
-4
-6
-4
-2
0
PC1
2
4
Can we relate nasA expression
measured with our PCR-based
methods to 15N uptake or nutrient
concentrations?
Quantification of nasA Transcripts
(Skidaway River Estuary – 2001)
Cycle Threshold (Ct)
30
28
26
Y = -3.416 (log10X) + 36.25
r2 = 0.989
24
22
Standard
20
Unknown
18
16
14
12
2
3
4
5
6
7
Log10 Copy Number
Real Time Q-PCR
0.005
15N Bacterial NO - Uptake (<0.8 um size-fraction)
3
SYBR Green Real-Time PCR
0.004
15
0.003
10
0.002
5
0.001
0
0.000
July '01
June '01
May '01
April '01
March '01
Janurary '01
Ocotber '00
August '00
Skidaway River Estuary
Marinobacter sp. nasA/16S rRNA Gene Copies
NO3 Uptake (nmole-N l-1 d-1) (< 0.8 µm)
20
NO3- Uptake (nmol-N l- d-1) (<0.8 um size fraction)
20
18
r2 = 0.77
16
14
12
10
8
6
4
2
0
0.000
0.001
0.002
0.003
0.004
Marinobacter sp. nasA / 16S rRNA Genes
Skidaway River Estuary
0.005
nasA Gene Expression Sometimes Correlates with
NO3 Concentration
Barents Sea – Ice Stations
South Atlantic Bight
Other times with NO3 uptake Rates
Skidaway River Estuary
Barents Sea – Open Water Stations
Sargasso Sea (sometimes)
Sometimes Not With Either ???
Probably Dependent on Many Factors, Available Carbon,
Community Composition, etc.
Detection of mRNA transcripts may be transient
Primary Questions & Conclusions
Do Heterotrophic Marine Bacteria Assimilate Nitrate?
YES – Varies in Space and Time But Can Account for a
Significant Fraction of DIN Uptake
Can Molecular Tools (Gene Based) Be Used to Determine
Who are the Nitrate Assimilators and What Controls Them?
Yes – Molecular Tools Provide Unique Insights
and indicate that Genetic Identity Matters and
Contributes to System Complexity
Are Gene Presence and Expression of nasA Quantitatively
Linked to Nitrate Uptake Rates? CO2 Flux?
Sometimes, Incorporation into GCM Models Will
Be Interesting!
But, Unsurprisingly, More Questions
Than Answers … Complex Systems
100’s - 1,000’s of genes per organism involved
Multiple Regulation Pathways per Organism
1,000’s of organisms involved
Lots of Signals
So Where Do We Start???
Identification of and Focus on Simple But Relevant Systems
and Primary Processes (e.g. Nitrogen Cycle)
Focus on Key Functional Genes and Pathways
(not just single genes)
Simultaneous Analysis of Suites of Genes
Combine Chemical, Nucleic Acid, and Protein Analyses
HIGH THROUGPUT!!!!
Microarray Development In Progress
Jizhong Zhou (Joe) – Oakridge National Laboratory
Gene
rbcl
PEPcase
GDC
nir, nos, nor
amoA
nifH
nar, nasA
dsrA
pmo
mcr
Function
Primary Production
Primary Production
Photooxidation
Denitrification
Nitrification
Nitrogen Fixation
Nitrate Assimilation
Sulfate reduction
Methane Oxidation
Methanogenesis
Environomics ???
Chemical
Stimuli
Chemical
Stimuli
Black
Box
Chemical
Stimuli
Biogeochemical
Rates
Combined Molecular & Chemical Approaches Are
Complementary and Appear to be Leading to a
More Complete Mechanistic Understanding of Bacterial
Behavior … ENVIRONOMICS
Chemical
Stimuli
Chemical
Stimuli
Gene Response
Gene Expression
Chemical
Stimuli
Proteins
Biogeochemical
Rates
Acknowledgements
Peter Verity (SkIO)
Andy Allen (Princeton Univ)
Debbie Bronk (VIMS)
Marta Sanderson
Hendi Hendrickson
Jon Zehr (UC Santa Cruz)
Christina Archer
Melissa Booth (SkIO/Roanoke)
Corina Knapp
Sandra Walters
Department of Energy
National Science Foundation
Office of Naval Research