Response of Prochlorococcus ecotypes to co-culture with
diverse marine bacteria
The MIT Faculty has made this article openly available. Please share
how this access benefits you. Your story matters.
Citation
Sher, Daniel et al. “Response of Prochlorococcus ecotypes to
co-culture with diverse marine bacteria.” ISME J (2011).
As Published
http://dx.doi.org/10.1038/ismej.2011.1
Publisher
Nature Publishing Group
Version
Author's final manuscript
Accessed
Thu May 26 18:27:49 EDT 2016
Citable Link
http://hdl.handle.net/1721.1/61703
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Detailed Terms
http://creativecommons.org/licenses/by-nc-sa/3.0/
RESPONSE OF PROCHLOROCOCCUS ECOTYPES TO CO-CULTURE WITH
DIVERSE MARINE BACTERIA
5
Daniel Sher*, Jessie W. Thompson, Nadav Kashtan, Laura Croal, and Sallie W.
Chisholm
Department of Civil and Environmental Engineering, Massachusetts Institute of
Technology, Cambridge, Massachusetts 02139, USA
10
* Current address: Department of Marine Biology, Leon H. Charney School of Marine
Sciences, University of Haifa, Mt. Carmel, 31905, Israel
Running title: Prochlorococcus-heterotroph interactions
15
Subject category: Microbe-microbe and microbe-host interactions
Abstract
Interactions between microorganisms shape microbial ecosystems. Systematic studies of
mixed microbes in co-culture have revealed widespread potential for growth inhibition
20
among marine heterotrophic bacteria, but similar synoptic studies have not been done
with autotroph/heterotroph pairs, nor have precise descriptions of the temporal evolution
of interactions been attempted in a high throughput system. Here, we describe patterns
in the outcome of pair-wise co-cultures between two ecologically distinct, yet closely
related, strains of the marine cyanobacterium Prochlorococcus and hundreds of
25
heterotrophic marine bacteria. Co-culture with the collection of heterotrophic strains
influenced the growth of Prochlorococcus strain MIT9313 much more than that of strain
MED4, reflected both in the number of different types of interactions and in the
magnitude of the effect of co-culture on various culture parameters. Enhancing
interactions, where the presence of heterotrophic bacteria caused Prochlorococcus to
30
grow faster and reach a higher final culture chlorophyll fluorescence , were much more
common than antagonistic ones, and for a selected number of cases were shown to be
mediated by diffusible compounds. In contrast, for one case at least, temporary inhibition
of Prochlorococcus MIT9313 appeared to require close cellular proximity. Bacterial
strains whose 16S gene sequences differed by 1-2% tended to have similar effects on
35
MIT9313, suggesting that the patterns of inhibition and enhancement in co-culture
observed here are due to phylogenetically-cohesive traits of these heterotrophs.
Keywords: heterotrophic bacteria/interactions/phylogeny/Prochlorococcus
2
40
Introduction
Interactions such as symbiosis, competition and allelopathy are a central feature of
microbial communities (Azam and Malfatti, 2007; Bassler and Losick, 2006; Hibbing et
al.). Even in dilute oceanic environments, microbial interactions abound: Antagonistic
45
interactions can promote biodiversity (Bidle and Falkowski, 2004; Czaran et al., 2002;
Pernthaler, 2005), and synergistic interactions can provide sources of sustenance in
complex communities (Amin et al., 2009; Azam et al., 1983; Azam and Malfatti, 2007;
Boetius et al., 2000; Croft et al., 2005; Tripp et al., 2010). While marine microbial
interactions often occur on scales of nanometers or microns (Blackburn et al., 1998;
50
Malfatti and Azam, 2009; Seymour et al., 2010; Stocker et al., 2008), they ultimately
affect entire ecosystems and global biogeochemical cycles (Azam and Malfatti, 2007).
Heterotrophic bacteria have been shown to both enhance and inhibit the growth of marine
and freshwater algae (Grossart et al., 2006; Grossart and Simon, 2007; Mayali et al.,
55
2008) and cyanobacteria (Bratbak and Thingstad, 1985; Manage et al., 2000; Morris et
al., 2008) in liquid culture and on solid media. Through these and similar studies we have
come to recognize specific mechanisms of interaction which can occur in the marine
environment, such as facilitation of iron uptake (Amin et al., 2009; D'Onofrio et al.,
2010), transfer of essential vitamins (Croft et al., 2005), inter- and intra-specific
60
communication (Bassler and Losick, 2006; Vardi et al., 2006) and allelopathy (Hibbing et
al., 2009; Mayali et al., 2008). Hypothesizing that bacterium-bacterium antagonistic
interactions shape microbial community structure at the microscale, Long and Azam
3
(Long and Azam, 2001) analyzed interactions among 86 pairs of co-isolated marine
bacteria on solid media, revealing the widespread distribution of the potential for growth
65
inhibition among these bacterial strains (Grossart et al., 2004; Long and Azam, 2001;
Rypien et al.). More recently, several strains of heterotrophic bacteria have been shown
to enhance the growth of a number of ecotypes of Prochlorococcus – the dominant
phototroph in temperate and tropical oceans (Coleman and Chisholm, 2007; Partensky
and Garczarek, 2010) - at low cell concentrations on solid and liquid media (Morris et al.,
70
2008). It was shown that the mechanism of enhancement in this case was the reduction
of oxidative stress, explaining in part long-standing anecdotal observations that culturing
Prochlorococcus is usually more robust when indigenous bacterial contaminants are
present.
75
While Prochlorococcus have been extensively studied vis-à-vis the role of environmental
factors such as light, temperature and nutrient availability in shaping their ecology
(Bouman et al., 2006; Coleman and Chisholm, 2007; Johnson et al., 2006; Moore et al.,
2002; Moore et al., 1998), and ‘top down’ processes such as predation and viral lysis
have also been studied to some degree (Frias-Lopez et al., 2009; Lindell et al., 2007;
80
Lindell et al., 2005; Sullivan et al., 2005), systematic studies of their interaction with
heterotrophic bacteria are limited to that of Morris and Zinser (Morris et al., 2008)
described above, who focused on the growth-enhancing role of bacteria in low density
cultures of Prochlorococcus. Inspired by this work, and by systemic analyses of Long
and Azam (27), we undertook a broad- based and quantitative analysis of co-cultures of
85
two axenic Prochlorococcus ecotypes (Moore et al., 2005; Saito et al., 2002) with
4
hundreds of diverse heterotrophic bacteria, examining the response of the
Prochlorococcus cells to the presence of bacteria over the entire growth curve of the
cultures.
90
We chose two strains of Prochlorococcus, one adapted to low light (MIT9313) and one
adapted to high light (MED4), for these studies because they are ecologically and
phylogenetically distinct. Additionally, MIT9313 is known to produce a diverse array of
secondary metabolites of unknown function, whereas the genes encoding this system are
absent in MED4 (Li et al., 2010). We paired each strain with each of 344 strains of
95
heterotrophic bacteria isolated from an oligotrophic marine environment. We asked: 1)
How does the presence of added heterotrophic bacteria influence the growth of each
Prochlorococcus strain over the course of its growth curve? 2) Do the two ecotypes
respond differently to the presence of the same heterotroph? 3) Do different strains of
heterotrophs have different effects, and are they related to the phylogeny of the
100
heterotrophs? 4) Are the observed interactions mediated by soluble compounds or do they
require close cellular proximity or contact?
While the experimental system does not mimic the natural environment in many ways
(Sup Info), it reveals some fundamental differences between the responses of two
105
Prochlorococcus ecotypes to co-culture with hundreds of bacteria - differences that may
hold clues to factors governing their realized niches in the ocean. It further highlights a
strong correlation of the outcome of co-culture with the phylogeny of the heterotrophic
5
bacteria, yielding hypotheses for further study on the mechanisms of these interactions
and their potential role in marine microbial communities.
110
Results and Discussion
Differences between Prochlorococcus MIT9313 and MED4 in outcome of co-culture
To determine what kinds of interactions occur when Prochlorococcus is grown in co115
culture with many different strains of bacteria, we constructed a “library” of 344
heterotrophic bacterial isolates from seawater collected in the open ocean, at the Hawaii
Ocean Time Series (HOT) station ALOHA (22º45’ N, 158º W) (Sup Fig. 1). The
heterotrophic strains were isolated on solid media (see Sup. Info) and consist of at least
65 unique ribotypes (based on partial 16S rDNA sequences) clustering into 23, 13, 8 and
120
6 distinct OTUs at 1%, 3%, 5% and 7% rDNA sequence divergence, respectively (Sup
Fig 1). The strains belong to the gamma-proteobacteria (primarily Alteromonas,
Marinobacter and Alcanivorax) and alpha-proteobacteria (Rhodobacter) classes. Each of
the 344 heterotrophic strains was inoculated into co-culture with axenic Prochlorococcus
strains MED4 and MIT9313 in 96 well plates (under our conditions the outcome of co-
125
culture does not depend on the initial number of heterotrophs inoculated – see Sup Info,
Sup Fig 2). We measured the bulk in-vivo chlorophyll fluorescence (FL) of the cultures,
which is widely used (Grossart, 1999; Malmstrom et al., 2010; Mayali et al., 2008) to
follow the dynamics of phytoplankton cultures in a non-invasive manner. While FL is
only proportional to cell number when the cultures are in balanced growth (Log phase,
6
130
see Sup. Info) the shape of the FL curve can reveal differences between the bulk behavior
of the cultures throughout the culture period.
From the hundreds of co-cultures analyzed, only a few general types of co-culture
outcomes emerged, as defined by the shape of the FL curves (Fig 1). Fifty seven percent
135
of the MIT9313 co-cultures fell into the group described as “early” (green, Fig. 1B) as
these cultures entered exponential growth earlier, and reached higher maximal
fluorescence than the heterotroph-free MIT9313 cultures (Fig. 1C). A small fraction of
the co-cultures (3%) displayed the same initial timing as the “early” group, but
fluorescence stopped increasing at an early stage and then declined rapidly (“early
140
arrested”, purple Fig. 1B). Thirty four percent of the cultures stopped increasing in
fluorescence after 2-3 days, declined to undetectable levels, and then increased again
much later (the “late” group, red Fig. 1B). Finally, only 6 % of the co-cultures with
MIT9313 behaved similarly to the heterotroph-free cultures (“intermediate” black Fig.
1B).
145
The synoptic response of MED4 to co-culture with the same library of bacterial strains
was dramatically different from that of MIT9313. Ninety-eight percent of the
heterotroph culture collection revealed no clear effect on the growth of MED4 – as
evidenced by their “intermediate” growth patterns which are very similar to the
150
heterotroph-free cultures. The growth of Prochlorococcus MED4 in the remaining 2% of
the co-cultures was arrested early, displaying strong inhibition by the presence of these
7
heterotrophs (Fig 1B). The heterotrophic bacterial strains that inhibited MED4 were the
same strains that defined the “early arrested” group in the MIT9313 cultures.
155
Quantifying the parameter space of the MED4 and MIT9313 co-culture outcomes
To provide a quantitative estimate of the effect microbial interactions can have on
Prochlorococcus culture dynamics, we extracted from the FL curves shown in Fig. 1
biologically-relevant descriptive parameters (similar to those used by Warringer et al
(Warringer et al., 2008)): the maximum growth rate (, the time it took the cultures to
160
reach half of the maximal fluorescence (T50), and the maximum FL (Fmax). As was clear
in the qualitative analysis, the parameter space is not homogenously covered (Fig 2;
Suppl. Figs 3,4). Rather, parts of the parameter space are densely populated, whereas
others regions are empty or sparse, representing parameter combinations which are not
observed in our co-culture curves (e.g. co-cultures in which the log phase growth rate was
165
significantly reduced compared to heterotroph-free cultures).
While the growth rate in log phase was influenced by the presence of bacteria in most of
the MIT9313 co-cultures, the median of this parameter actually increased in most of the
types of co-culture outcomes compared to the heterotroph-free cultures (Sup Fig. 3) even
170
when the overall effect was clearly one of much later onset of growth. Therefore, in
agreement with other studies (Warringer et al., 2008), our results suggest that a
combination of different growth parameters is necessary in order to fully describe the
complex effect of microbial interactions.
8
175
As described above, the most striking is the difference between the large parameter space
inhabited by MIT9313 co-cultures and the much more limited space inhabited by MED4
co-cultures (Fig. 2). The suite of heterotrophic bacteria that strongly influences the
growth of MIT9313, decreasing some parameters up to ten-fold or increasing them up to
four-fold has minimal, if any, impact on MED4.
180
Heterotroph phylogeny and co-culture outcome.
We next asked whether closely related bacteria, as defined by their partial 16S rDNA
sequence (ribotype), affect the growth of Prochlorococcus cultures similarly. As shown
in Fig. 3, the heterotroph ribotypes which induced “early”, “early arrested” and “late
185
growth” phenotypes were significantly different for MIT9313 (UniFrac test with
Bonferroni correction, P≤0.06 [Lozupone and Knight, 2005]), as were the groups that
induced “intermediate” and “early inhibited” for MED4 (P≤0.01). For example, all but
two of the heterotrophic strains which induced a “late” outcome of MIT9313 belong to
two well-defined clades of Alteromonads (Fig. 3, Sup Fig. 1). Similarly, the same strains
190
induced the “early arrested” outcome in both MED4 and MIT9313, and all of these
strains belong to a well-defined clade of Rhodobacters, similar to Marinovum algicola
and Ruegeria sp. In most of these cases, the differentiation between strains which inhibit
Prochlorococcus in co-culture and strains which do not is relatively deep-rooted, within
the resolution afforded by our cultured collection of heterotrophs. For example, two
195
Alteromonad clades differing by 1-2% in their partial 16S sequence both inhibit
MIT9313, whereas a third clade which differs by 4-5% from these two clades enhances
MIT9313. Similarly, the clade of Rhodobacters inducing “early arrested” phenotype
9
differs from the most closely related strains in our collection that do not induce this
phenotype by about 4% in their 16S. This level of divergence corresponds to one
200
commonly used to delineate species or genus level differentiation (Schloss and
Handelsman, 2005).
Co-culture outcome and proximity of cells
While many interactions between microorganisms are mediated by diffusible soluble
205
compounds, some have also been observed to occur when cells live in close proximity or
even necessitate direct cell-cell contact (Croft et al., 2005; Mayali and Azam, 2004). To
test whether close cell-cell proximity is necessary for the different co-culture outcomes
observed with MIT9313, we selected five heterotroph strains representing different
phylogenetic clades and co-culture outcomes, and co-cultured them with MIT9313 either
210
separated by a membrane permeable to small molecules or mixed together as in the
experiment presented above. As shown in Fig. 4, when the FL of the co-cultures
increased earlier than that of the axenic cultures this happened regardless of whether or
not the heterotrophic bacteria were separated from MIT9313 by a membrane. Thus, the
“early” outcome of Prochlorococcus cultures is likely mediated in these cases by soluble,
215
diffusible compounds, although we cannot preclude the possibility that the small number
of heterotrophic bacteria than can cross the membrane during these 19-day long
experiments (see Sup Info) may also directly impact the growth of MIT9313. In contrast,
the late co-culture outcome occurred only when MIT9313 and Alteromonas strain
HOTo1A3 were grown in close proximity and not when they were separated by a
220
membrane.
10
Potential mechanisms underlying different co-culture outcomes
MIT9313 and MED4 represent two taxonomic extremes within the Prochlorococcus
225
lineage, differing by ~3% in their 16SrRNA sequence. MED4 is a small cell with a
highly streamlined genome, and is a member of the high-light adapted clade of
Prochlorococcus. MIT9313, in contrast, is a slightly larger cell with a larger genome,
and is better adapted for growth at the low light levels found deeper in the water column
(Bouman et al., 2006; Coleman and Chisholm, 2007; Johnson et al., 2006; Moore et al.,
230
2002; Moore et al., 1998; Rocap et al., 2003). Both strains are growing in these
experiments below their respective temperature and light optima (although closer to those
of MIT9313, (Rocap et al., 2003; Zinser et al., 2007)), but have been pre-acclimated to
the experimental conditions for >7 months (~120 generations) and thus the difference in
co-culture outcome is likely not caused by a general stress response in one strain due to
235
culture conditions.
The “early” culture outcome is the one most commonly observed with MIT9313, is
widely distributed among the different phylogenetic groups, and in all cases tested is
caused by soluble, diffusible molecules. This is consistent with a “helper” effect where
240
the growth of Prochlorococcus increases as a result of basic attributes common to many
lineages of heterotrophic cells, as suggested by Morris et al (Morris et al., 2008). Such
attributes may include scavenging of reactive oxygen species, (Morris et al., 2008),
increasing carbon dioxide concentration (Moore et al., 2007) or cycling waste products.
11
MED4 as a high-light adapted strain, may be better adapted to deal with oxidative stress
245
(often generated during photosynthesis) than MIT9313, thus the latter strain may benefit
more from interacting with heterotrophs. Notably, however, MED4 can readily form
colonies on solid media only with the help of heterotrophs, and thus this strain is not
immune to the effect of co-occurring bacteria (Morris et al., 2008).
250
In contrast, inhibition of MIT9313 (early arrested or late outcomes) was observed mainly
in co-cultures with two-well defined groups of bacteria belonging to the Alteromonads
and Rhodobacters, with the latter group being the only one to clearly affect the growth of
MED4 under our conditions. Related bacteria have previously been shown to inhibit other
microbes through the production of secreted allelochemicals (e.g. (Gram et al.; Mayali
255
and Azam, 2004)). An intriguing observation is that inhibition of MIT9313 by an
Alteromonas strain required proximity between the heterotrophic bacteria and MIT9313 –
i.e. the effect could not be mimicked when the cells were kept apart by a semi-permeable
membrane. Recently, close physical association (cell-cell contact) has been observed in
natural seawater samples between Synechococcus cells, which are closely related to
260
Prochlorococcus, and heterotrophic bacteria of unknown taxonomy (Malfatti and Azam,
2009; Malfatti et al.). These observations suggest the potential for close or contactmediated interactions even in tiny picoplankton cells.
265
Conclusions
12
While some features of our experimental system limit extrapolation of our results to the
experience of wild Prochlorococcus – e.g. the co-cultured strains were not co-isolated
and the cell densities were higher than found in the wild (see also Sup Info) – our study
has revealed some properties of these microbial interaction that likely have ecological
270
relevance. First, the two Prochlorococcus ecotypes display fundamentally different
responses to the presence of bacteria, both in terms of general patterns, and in terms of
specific responses to specific bacterial strains. These differences could influence the
connectivity of these two strains within the microbial network in the wild. If so, MIT9313
may be more susceptible to changes in the microbial community than MED4. Similar
275
trends have been suggested for other marine bacterioplankton based on network analysis
of patterns of co-occurrence in the oceans (Fuhrman and Steele, 2008).
Second, both the antagonistic and enhancing interactions in our system revealed a clear
phylogenetic signature, with closely related bacteria causing similar responses in the co280
cultured Prochlorococcus. Furthermore, only a handful of different interaction types, as
measured through their effect on Prochlorococcus growth curves, were observed. The
heterotroph culture collection we used represents only a fraction of diversity found in the
oceans, and does not include many of the most common lineages. Future work with a
wider diversity of bacteria may either reveal additional types of interactions or highlight
285
unknown constrains on the types of interactions which can affect cells in the aquatic
environment.
13
Considering the high levels of microheterogeneity in both marine microbial populations
(Hunt et al., 2008; Thompson et al., 2005) and their environment (Azam and Malfatti,
290
2007; Blackburn et al., 1998; Seymour et al., 2010; Stocker et al., 2008), the task of
understanding how complex microbial populations interact in the oceans is a daunting
one. Although it is encouraging, as we seek general patterns, that the co-culture
outcomes we observe are not random with respect to the phylogeny of the heterortophs,
the opposite has been observed in cultures of interacting heterotrophc bacteria (Long and
295
Azam, 2001). Clearly expanded and in depth study of the network of possible interactions
between microbial groups is essential, if we ever wish to incorporate microbial
interactions into our understanding of marine microbial communities.
Materials and Methods
300
We isolated heterotrophic bacteria from the Hawaii Ocean Time Series (HOT) station
ALOHA (22º45’ N, 158º W), one of the most comprehensively studied sites in the ocean,
with a microbial community dominated by Prochlorococcus and characterized in some
detail (DeLong et al., 2006). The heterotrophs were re-streaked for purity three times, and
305
the final library was preserved at -80°C in 25% glycerol. Prochlorococcus strains
MIT9313 and MED4 were isolated from the Gulf Stream and the Mediterranean Sea,
respectively (Rocap et al., 2003), and were maintained in the lab at 20°C and 27E
constant cold white illumination. Co-culture was initiated by adding 2L of an overnight
culture of each heterotroph from the library to 200L of Prochlorococcus culture (106
310
cells/mL) in 96 well plates. The culture media was Pro99 (Moore et al., 2007) with the
14
addition of 0.01% w/v Pyruvate, Acetate, Lactate and Glycerol as well as a vitamin mix
(Morris et al., 2008). The co-culture plates were maintained for 42 days at 20°C and
27E constant cold white illumination, and the bulk chlorophyll fluorescence (ex440
em680) measured almost daily using a Bio-Tek Synergy HT plate reader. The resulting
315
curves were filtered to retain consistent curves, defined as those in which the Euclidian
Distance between normalized curves fell within the range defined by 95% of the
between-plate replicates of axenic curves. The growth parameters were extracted from
the growth curves using macros written in Excel VBA, which are available from the
authors upon request. Hierarchical Clustering was performed in Matlab. For detailed
320
materials and methods see Supplementary Information.
Acknowledgements:
We thank Daniele Veneziano for help with statistical analyses and two anonymous
325
referees for many constructive remarks. This study was supported by grants from the
Gordon and Betty Moore Foundation, the NSF, and the US DOE-GTL (to S.W.C). D.S.
was supported by postdoctoral fellowships from the Fullbright Foundation and the United
States - Israel Binational Agricultural Research and Development Fund (Vaadia-BARD
Postdoctoral Fellowship Award No. FI-399-2007). N.K. was supported by a postdoctoral
330
fellowship from the Rothschild Yad Hanadiv Foundation and L.C. was supported by a
postdoctoral research fellowship in biology from the National Science Foundation.
15
References
Amin SA, Green DH, Hart MC, Kupper FC, Sunda WG, Carrano CJ (2009). Photolysis
335
of iron-siderophore chelates promotes bacterial-algal mutualism. Proceedings of the
National Academy of Sciences of the United States of America 106: 17071-17076.
Anisimova M, Gascuel O (2006). Approximate likelihood-ratio test for branches: A fast,
accurate, and powerful alternative. Syst Biol 55: 539-52.
340
Azam F, Fenchel T, Field JG, Gray JS, Meyerreil LA, Thingstad F (1983). The
Ecological Role of Water-Column Microbes in the Sea. Marine Ecology-Progress Series
10: 257-263.
345
Azam F, Malfatti F (2007). Microbial structuring of marine ecosystems (vol 5, pg 782791, 2007). Nature Reviews Microbiology 5: 966-U23.
Bassler BL, Losick R (2006). Bacterially speaking. Cell 125: 237-46.
350
Bidle KD, Falkowski PG (2004). Cell death in planktonic, photosynthetic
microorganisms. Nat Rev Microbiol 2: 643-55.
Blackburn N, Fenchel T, Mitchell J (1998). Microscale nutrient patches in planktonic
habitats shown by chemotactic bacteria. Science 282: 2254-6.
355
16
Boetius A, Ravenschlag K, Schubert CJ, Rickert D, Widdel F, Gieseke A et al (2000). A
marine microbial consortium apparently mediating anaerobic oxidation of methane.
Nature 407: 623-6.
360
Bouman HA, Ulloa O, Scanlan DJ, Zwirglmaier K, Li WK, Platt T et al (2006).
Oceanographic basis of the global surface distribution of Prochlorococcus ecotypes.
Science 312: 918-21.
Bratbak G, Thingstad TF (1985). Phytoplankton-Bacteria Interactions - an Apparent
365
Paradox - Analysis of a Model System with Both Competition and Commensalism.
Marine Ecology-Progress Series 25: 23-30.
Coleman ML, Chisholm SW (2007). Code and context: Prochlorococcus as a model for
cross-scale biology. Trends Microbiol 15: 398-407.
370
Croft MT, Lawrence AD, Raux-Deery E, Warren MJ, Smith AG (2005). Algae acquire
vitamin B-12 through a symbiotic relationship with bacteria. Nature 438: 90-93.
Czaran TL, Hoekstra RF, Pagie L (2002). Chemical warfare between microbes promotes
375
biodiversity. Proc Natl Acad Sci U S A 99: 786-90.
17
D'Onofrio A, Crawford JM, Stewart EJ, Witt K, Gavrish E, Epstein S et al (2010).
Siderophores from Neighboring Organisms Promote the Growth of Uncultured Bacteria.
Chemistry & biology 17: 254-264.
380
DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, Frigaard NU et al (2006).
Community genomics among stratified microbial assemblages in the ocean's interior.
Science 311: 496-503.
385
Frias-Lopez J, Thompson A, Waldbauer J, Chisholm SW (2009). Use of stable isotopelabelled cells to identify active grazers of picocyanobacteria in ocean surface waters.
Environ Microbiol 11: 512-25.
Fuhrman JA, Steele JA (2008). Community structure of marine bacterioplankton:
390
patterns, networks, and relationships to function. Aquatic Microbial Ecology 53: 69-81.
Gram L, Melchiorsen J, Bruhn J (2009). Antibacterial Activity of Marine Culturable
Bacteria Collected from a Global Sampling of Ocean Surface Waters and Surface Swabs
of Marine Organisms. Marine Biotechnology 10.1007/s10126-009-9233-y.
395
Grossart H-P (1999). Interactions between marine bacteria and axenic diatoms
(Cylindrotheca fusiformis, Nitzschia laevis, and Thalassiosira weissflogii) incubated
under various conditions in the lab. Aquatic Microbial Ecology 19: 1-11.
18
400
Grossart HP, Czub G, Simon M (2006). Algae-bacteria interactions and their effects on
aggregation and organic matter flux in the sea. Environ Microbiol 8: 1074-84.
Grossart HP, Schlingloff A, Bernhard M, Simon M, Brinkhoff T (2004). Antagonistic
activity of bacteria isolated from organic aggregates of the German Wadden Sea. Fems
405
Microbiology Ecology 47: 387-96.
Grossart HP, Simon M (2007). Interactions of planktonic algae and bacteria: effects on
algal growth and organic matter dynamics. Aquatic Microbial Ecology 47: 163-176.
410
Hibbing ME, Fuqua C, Parsek MR, Peterson SB (2009). Bacterial competition: surviving
and thriving in the microbial jungle. Nat Rev Microbiol 8: 15-25.
Hunt DE, David LA, Gevers D, Preheim SP, Alm EJ, Polz MF (2008). Resource
partitioning and sympatric differentiation among closely related bacterioplankton.
415
Science 320: 1081-5.
Johnson ZI, Zinser ER, Coe A, McNulty NP, Woodward EM, Chisholm SW (2006).
Niche partitioning among Prochlorococcus ecotypes along ocean-scale environmental
gradients. Science 311: 1737-40.
420
19
Li B, Sher D, Kelly L, Shi Y, Huang K, Knerr PJ et al (2010). Catalytic promiscuity in
the biosynthesis of cyclic peptide secondary metabolites in planktonic marine
cyanobacteria. Proc Natl Acad Sci U S A 107: 10430-5.
425
Lindell D, Jaffe JD, Coleman ML, Futschik ME, Axmann IM, Rector T et al (2007).
Genome-wide expression dynamics of a marine virus and host reveal features of coevolution. Nature 449: 83-6.
Lindell D, Jaffe JD, Johnson ZI, Church GM, Chisholm SW (2005). Photosynthesis
430
genes in marine viruses yield proteins during host infection. Nature 438: 86-9.
Long RA, Azam F (2001). Antagonistic interactions among marine pelagic bacteria. Appl
Environ Microbiol 67: 4975-83.
435
Lozupone C, Knight R (2005). UniFrac: a new phylogenetic method for comparing
microbial communities. Applied and Environmental Microbiology 71: 8228-8235.
Malfatti F, Azam F (2009). Atomic force microscopy reveals microscale networks and
possible symbioses among pelagic marine bacteria. Aquatic Microbial Ecology 58: 1-14.
440
Malfatti F, Samo TJ, Azam F High-resolution imaging of pelagic bacteria by Atomic
Force Microscopy and implications for carbon cycling. Isme J 4: 427-39.
20
Malmstrom RR, Coe A, Kettler GC, Martiny AC, Frias-Lopez J, Zinser ER et al (2010).
445
Temporal dynamics of Prochlorococcus ecotypes in the Atlantic and Pacific oceans. Isme
J.
Manage PM, Kawabata Z, Nakano S (2000). Algicidal effect of the bacterium
Alcaligenes denitrificans on Microcystis spp. Aquatic Microbial Ecology 22: 111-117.
450
Mayali X, Azam F (2004). Algicidal bacteria in the sea and their impact on algal blooms.
Journal of Eukaryotic Microbiology 51: 139-144.
Mayali X, Franks PJ, Azam F (2008). Cultivation and ecosystem role of a marine
455
roseobacter clade-affiliated cluster bacterium. Appl Environ Microbiol 74: 2595-603.
Moore LR, Coe A, Zinser ER, Saito MA, Sullivan MB, Lindell D et al (2007). Culturing
the marine cyanobacterium Prochlorococcus. Limnology and Oceanography-Methods 5:
353-362.
460
Moore LR, Ostrowski M, Scanlan DJ, Feren K, Sweetsir T (2005). Ecotypic variation in
phosphorus acquisition mechanisms within marine picocyanobacteria. Aquatic Microbial
Ecology 39: 257-269.
21
465
Moore LR, Post AF, Rocap G, Chisholm SW (2002). Utilization of different nitrogen
sources by the marine cyanobacteria Prochlorococcus and Synechococcus. Limnology
and Oceanography 47: 989-996.
Moore LR, Rocap G, Chisholm SW (1998). Physiology and molecular phylogeny of
470
coexisting Prochlorococcus ecotypes. Nature 393: 464-7.
Morris JJ, Kirkegaard R, Szul MJ, Johnson ZI, Zinser ER (2008). Facilitation of robust
growth of Prochlorococcus colonies and dilute liquid cultures by "helper" heterotrophic
bacteria. Appl Environ Microbiol 74: 4530-4.
475
Partensky F, Garczarek L (2010). Prochlorococcus: Advantages and Limits of
Minimalism. Annual Review of Marine Science 2: 305-331.
Pernthaler J (2005). Predation on prokaryotes in the water column and its ecological
480
implications. Nat Rev Microbiol 3: 537-46.
Rocap G, Larimer FW, Lamerdin J, Malfatti S, Chain P, Ahlgren NA et al (2003).
Genome divergence in two Prochlorococcus ecotypes reflects oceanic niche
differentiation. Nature 424: 1042-7.
485
Rypien KL, Ward JR, Azam F (2009). Antagonistic interactions among coral-associated
bacteria. Environmental Microbiology 12: 28-39.
22
Saito MA, Moffett JW, Chisholm SW, Waterbury JB (2002). Cobalt limitation and
490
uptake in Prochlorococcus. Limnology and Oceanography 47: 1629-1636.
Schloss PD, Handelsman J (2005). Introducing DOTUR, a computer program for
defining operational taxonomic units and estimating species richness. Appl Environ
Microbiol 71: 1501-6.
495
Seymour JR, Simo R, Ahmed T, Stocker R (2010). Chemoattraction to
Dimethylsulfoniopropionate Throughout the Marine Microbial Food Web. Science 329:
342-345.
500
Stocker R, Seymour JR, Samadani A, Hunt DE, Polz MF (2008). Rapid chemotactic
response enables marine bacteria to exploit ephemeral microscale nutrient patches. Proc
Natl Acad Sci U S A 105: 4209-14.
Sullivan MB, Coleman ML, Weigele P, Rohwer F, Chisholm SW (2005). Three
505
Prochlorococcus cyanophage genomes: signature features and ecological interpretations.
PLoS Biol 3: e144.
Thompson JR, Pacocha S, Pharino C, Klepac-Ceraj V, Hunt DE, Benoit J et al (2005).
Genotypic diversity within a natural coastal bacterioplankton population. Science 307:
510
1311-3.
23
Tripp HJ, Bench SR, Turk KA, Foster RA, Desany BA, Niazi F et al (2010). Metabolic
streamlining in an open-ocean nitrogen-fixing cyanobacterium. Nature 464: 90-4.
515
Vardi A, Formiggini F, Casotti R, De Martino A, Ribalet F, Miralto A et al (2006). A
stress surveillance system based on calcium and nitric oxide in marine diatoms. PLoS
Biol 4: e60.
Warringer J, Anevski D, Liu B, Blomberg A (2008). Chemogenetic fingerprinting by
520
analysis of cellular growth dynamics. BMC Chem Biol 8: 3.
Zinser ER, Johnson ZI, Coe A, Karaca E, Veneziano D, Chisholm SW (2007). Influence
of light and temperature on Prochlorococcus ecotype distributions in the Atlantic Ocean.
Limnology and Oceanography 52: 2205-2220.
525
530
24
Titles and legends to figures:
Figure 1: Features of Prochlorococcus MED4 and 9313 growth patterns in response
535
to co-culture with 250 different strains of heterotrophic bacteria. A) Heat maps of
the normalized FL of all 338 growth curves (250 co-cultures and 88 controls) as
clustered using Hierarchical Clustering (HC). A clearly different pattern can be seen
between four major clusters in MIT9313 but only two in MED4. B and C) FL curves of
the 250 co-cultures (B) and 88 axenic Prochlorococcus cultures (C). The curves are
540
colored as shown in the legend based on the clustering results in panel A. Four different
types of curves which differ in their growth timing and maximal FL, can be observed for
MIT9313, whereas only two clusters are observed for MED4. Note the similarity in the
shape of the “early arrested” outcome between MIT9313 and MED4.
545
Figure 2: The quantitative three-dimensional parameter spaces defining the effect
co-culture on Prochlorococcus MIT9313 and MED4. A three-dimensional parameter
space is shown, with the axes being the maximum growth rate (, the time it took the
cultures to reach half of the maximal fluorescence (T50), and the maximum FL (Fmax).
The parameter spaces shown includes both the co-cultures and the control axenic
550
cultures, and are normalized to axenic wells on the same plates (i.e. values larger than
one represent an increase in the relevant parameter compared to axenic culture, smaller
than one represent a decrease). The data points are colored based on the clustering shown
in Fig 1. Large circles represent the median coordinates of each co-culture outcome.
25
555
Figure 3: The relationship between patterns observed in co-cultures and the
ribotype of the heterotroph. A maximum likelihood (ML) tree (partial 16S rDNA
sequences) is shown, with the co-culture outcome (as defined in Fig. 1) shown for
MIT9313 (middle ring) and MED4 (outer ring). Spheres on the tree branches denote
>80% aLRT confidence (Anisimova and Gascuel, 2006). Different shading of the
560
branches of the tree denotes Operational Taxonomic Units (OTUs) at 0.01 resolution (see
also Sup Fig. 1 and Sup Table 1). Asterisks denote the phylogenetic position of strains
used for the experiments shown in Fig. 4.
Figure 4: Comparison of outcomes of co-culture experiments between
565
Prochlorococcus MIT9313 and 5 strains of bacteria grown together in mixed culture
or separated by a 0.4 µm permeable membrane. Results shown are averages and
standard deviations (n=4 for axenic MIT9313, n=2 for co-cultures). The phylogenetic
positions of the strains used in this experiment are shown in Fig. 3 as asterisks.
570
26
575
Amin SA, Green DH, Hart MC, Kupper FC, Sunda WG, Carrano CJ (2009). Photolysis
of iron-siderophore chelates promotes bacterial-algal mutualism. Proceedings of the
National Academy of Sciences of the United States of America 106: 17071-17076.
Anisimova M, Gascuel O (2006). Approximate likelihood-ratio test for branches: A fast,
accurate, and powerful alternative. Syst Biol 55: 539-52.
580
585
Azam F, Fenchel T, Field JG, Gray JS, Meyerreil LA, Thingstad F (1983). The
Ecological Role of Water-Column Microbes in the Sea. Marine Ecology-Progress Series
10: 257-263.
Azam F, Malfatti F (2007). Microbial structuring of marine ecosystems (vol 5, pg 782791, 2007). Nature Reviews Microbiology 5: 966-U23.
Bassler BL, Losick R (2006). Bacterially speaking. Cell 125: 237-46.
590
Bidle KD, Falkowski PG (2004). Cell death in planktonic, photosynthetic
microorganisms. Nat Rev Microbiol 2: 643-55.
Blackburn N, Fenchel T, Mitchell J (1998). Microscale nutrient patches in planktonic
habitats shown by chemotactic bacteria. Science 282: 2254-6.
595
600
605
Boetius A, Ravenschlag K, Schubert CJ, Rickert D, Widdel F, Gieseke A et al (2000). A
marine microbial consortium apparently mediating anaerobic oxidation of methane.
Nature 407: 623-6.
Bouman HA, Ulloa O, Scanlan DJ, Zwirglmaier K, Li WK, Platt T et al (2006).
Oceanographic basis of the global surface distribution of Prochlorococcus ecotypes.
Science 312: 918-21.
Bratbak G, Thingstad TF (1985). Phytoplankton-Bacteria Interactions - an Apparent
Paradox - Analysis of a Model System with Both Competition and Commensalism.
Marine Ecology-Progress Series 25: 23-30.
Coleman ML, Chisholm SW (2007). Code and context: Prochlorococcus as a model for
cross-scale biology. Trends Microbiol 15: 398-407.
610
Croft MT, Lawrence AD, Raux-Deery E, Warren MJ, Smith AG (2005). Algae acquire
vitamin B-12 through a symbiotic relationship with bacteria. Nature 438: 90-93.
Czaran TL, Hoekstra RF, Pagie L (2002). Chemical warfare between microbes promotes
biodiversity. Proc Natl Acad Sci U S A 99: 786-90.
615
27
D'Onofrio A, Crawford JM, Stewart EJ, Witt K, Gavrish E, Epstein S et al (2010).
Siderophores from Neighboring Organisms Promote the Growth of Uncultured Bacteria.
Chemistry & biology 17: 254-264.
620
625
DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, Frigaard NU et al (2006).
Community genomics among stratified microbial assemblages in the ocean's interior.
Science 311: 496-503.
Frias-Lopez J, Thompson A, Waldbauer J, Chisholm SW (2009). Use of stable isotopelabelled cells to identify active grazers of picocyanobacteria in ocean surface waters.
Environ Microbiol 11: 512-25.
Fuhrman JA, Steele JA (2008). Community structure of marine bacterioplankton:
patterns, networks, and relationships to function. Aquatic Microbial Ecology 53: 69-81.
630
Gram L, Melchiorsen J, Bruhn J (2009). Antibacterial Activity of Marine Culturable
Bacteria Collected from a Global Sampling of Ocean Surface Waters and Surface Swabs
of Marine Organisms. Marine Biotechnology 10.1007/s10126-009-9233-y.
635
640
Grossart H-P (1999). Interactions between marine bacteria and axenic diatoms
(Cylindrotheca fusiformis, Nitzschia laevis, and Thalassiosira weissflogii) incubated
under various conditions in the lab. Aquatic Microbial Ecology 19: 1-11.
Grossart HP, Czub G, Simon M (2006). Algae-bacteria interactions and their effects on
aggregation and organic matter flux in the sea. Environ Microbiol 8: 1074-84.
Grossart HP, Schlingloff A, Bernhard M, Simon M, Brinkhoff T (2004). Antagonistic
activity of bacteria isolated from organic aggregates of the German Wadden Sea. Fems
Microbiology Ecology 47: 387-96.
645
Grossart HP, Simon M (2007). Interactions of planktonic algae and bacteria: effects on
algal growth and organic matter dynamics. Aquatic Microbial Ecology 47: 163-176.
650
Hibbing ME, Fuqua C, Parsek MR, Peterson SB (2009). Bacterial competition: surviving
and thriving in the microbial jungle. Nat Rev Microbiol 8: 15-25.
Hunt DE, David LA, Gevers D, Preheim SP, Alm EJ, Polz MF (2008). Resource
partitioning and sympatric differentiation among closely related bacterioplankton.
Science 320: 1081-5.
655
Johnson ZI, Zinser ER, Coe A, McNulty NP, Woodward EM, Chisholm SW (2006).
Niche partitioning among Prochlorococcus ecotypes along ocean-scale environmental
gradients. Science 311: 1737-40.
28
660
665
Li B, Sher D, Kelly L, Shi Y, Huang K, Knerr PJ et al (2010). Catalytic promiscuity in
the biosynthesis of cyclic peptide secondary metabolites in planktonic marine
cyanobacteria. Proc Natl Acad Sci U S A 107: 10430-5.
Lindell D, Jaffe JD, Coleman ML, Futschik ME, Axmann IM, Rector T et al (2007).
Genome-wide expression dynamics of a marine virus and host reveal features of coevolution. Nature 449: 83-6.
Lindell D, Jaffe JD, Johnson ZI, Church GM, Chisholm SW (2005). Photosynthesis
genes in marine viruses yield proteins during host infection. Nature 438: 86-9.
670
Long RA, Azam F (2001). Antagonistic interactions among marine pelagic bacteria. Appl
Environ Microbiol 67: 4975-83.
675
Lozupone C, Knight R (2005). UniFrac: a new phylogenetic method for comparing
microbial communities. Applied and Environmental Microbiology 71: 8228-8235.
Malfatti F, Azam F (2009). Atomic force microscopy reveals microscale networks and
possible symbioses among pelagic marine bacteria. Aquatic Microbial Ecology 58: 1-14.
680
685
Malfatti F, Samo TJ, Azam F High-resolution imaging of pelagic bacteria by Atomic
Force Microscopy and implications for carbon cycling. Isme J 4: 427-39.
Malmstrom RR, Coe A, Kettler GC, Martiny AC, Frias-Lopez J, Zinser ER et al (2010).
Temporal dynamics of Prochlorococcus ecotypes in the Atlantic and Pacific oceans. Isme
J.
Manage PM, Kawabata Z, Nakano S (2000). Algicidal effect of the bacterium
Alcaligenes denitrificans on Microcystis spp. Aquatic Microbial Ecology 22: 111-117.
690
Mayali X, Azam F (2004). Algicidal bacteria in the sea and their impact on algal blooms.
Journal of Eukaryotic Microbiology 51: 139-144.
Mayali X, Franks PJ, Azam F (2008). Cultivation and ecosystem role of a marine
roseobacter clade-affiliated cluster bacterium. Appl Environ Microbiol 74: 2595-603.
695
Moore LR, Coe A, Zinser ER, Saito MA, Sullivan MB, Lindell D et al (2007). Culturing
the marine cyanobacterium Prochlorococcus. Limnology and Oceanography-Methods 5:
353-362.
700
Moore LR, Ostrowski M, Scanlan DJ, Feren K, Sweetsir T (2005). Ecotypic variation in
phosphorus acquisition mechanisms within marine picocyanobacteria. Aquatic Microbial
Ecology 39: 257-269.
29
705
Moore LR, Post AF, Rocap G, Chisholm SW (2002). Utilization of different nitrogen
sources by the marine cyanobacteria Prochlorococcus and Synechococcus. Limnology
and Oceanography 47: 989-996.
Moore LR, Rocap G, Chisholm SW (1998). Physiology and molecular phylogeny of
coexisting Prochlorococcus ecotypes. Nature 393: 464-7.
710
Morris JJ, Kirkegaard R, Szul MJ, Johnson ZI, Zinser ER (2008). Facilitation of robust
growth of Prochlorococcus colonies and dilute liquid cultures by "helper" heterotrophic
bacteria. Appl Environ Microbiol 74: 4530-4.
715
Partensky F, Garczarek L (2010). Prochlorococcus: Advantages and Limits of
Minimalism. Annual Review of Marine Science 2: 305-331.
Pernthaler J (2005). Predation on prokaryotes in the water column and its ecological
implications. Nat Rev Microbiol 3: 537-46.
720
Rocap G, Larimer FW, Lamerdin J, Malfatti S, Chain P, Ahlgren NA et al (2003).
Genome divergence in two Prochlorococcus ecotypes reflects oceanic niche
differentiation. Nature 424: 1042-7.
725
Rypien KL, Ward JR, Azam F (2009). Antagonistic interactions among coral-associated
bacteria. Environmental Microbiology 12: 28-39.
Saito MA, Moffett JW, Chisholm SW, Waterbury JB (2002). Cobalt limitation and
uptake in Prochlorococcus. Limnology and Oceanography 47: 1629-1636.
730
Schloss PD, Handelsman J (2005). Introducing DOTUR, a computer program for
defining operational taxonomic units and estimating species richness. Appl Environ
Microbiol 71: 1501-6.
735
740
745
Seymour JR, Simo R, Ahmed T, Stocker R (2010). Chemoattraction to
Dimethylsulfoniopropionate Throughout the Marine Microbial Food Web. Science 329:
342-345.
Stocker R, Seymour JR, Samadani A, Hunt DE, Polz MF (2008). Rapid chemotactic
response enables marine bacteria to exploit ephemeral microscale nutrient patches. Proc
Natl Acad Sci U S A 105: 4209-14.
Sullivan MB, Coleman ML, Weigele P, Rohwer F, Chisholm SW (2005). Three
Prochlorococcus cyanophage genomes: signature features and ecological interpretations.
PLoS Biol 3: e144.
Thompson JR, Pacocha S, Pharino C, Klepac-Ceraj V, Hunt DE, Benoit J et al (2005).
Genotypic diversity within a natural coastal bacterioplankton population. Science 307:
1311-3.
30
750
Tripp HJ, Bench SR, Turk KA, Foster RA, Desany BA, Niazi F et al (2010). Metabolic
streamlining in an open-ocean nitrogen-fixing cyanobacterium. Nature 464: 90-4.
755
Vardi A, Formiggini F, Casotti R, De Martino A, Ribalet F, Miralto A et al (2006). A
stress surveillance system based on calcium and nitric oxide in marine diatoms. PLoS
Biol 4: e60.
Warringer J, Anevski D, Liu B, Blomberg A (2008). Chemogenetic fingerprinting by
analysis of cellular growth dynamics. BMC Chem Biol 8: 3.
760
Zinser ER, Johnson ZI, Coe A, Karaca E, Veneziano D, Chisholm SW (2007). Influence
of light and temperature on Prochlorococcus ecotype distributions in the Atlantic Ocean.
Limnology and Oceanography 52: 2205-2220.
765
31
Supplementary Information
770
775
780
785
790
795
Detailed Materials and Methods
General considerations and caveats: The experimental system described here was
designed in order to enable the quantitative analysis of hundreds of cultures in parallel. It
does not mimic the natural oceanic environment in many ways: the concentrations of
nutrients and cell densities were significantly higher than in the oligotrophic ocean (see
below for media composition); the heterotrophs were supplemented with organic
compounds in the media, and not dependent on the phototrophs for sustenance; the light
intensity was constant, and the diffusion of gasses was likely limited in the 96 well plates.
The heterotrophic strains used are those which are relatively easily isolated on solid
medium, and do not represent the majority of bacteria in the oceans (although
Alteromonads and Rhodobacters are an important part – up to 10% - of the total marine
microbial population, as measured using metagenomic methods (DeLong et al., 2006;
Ivars-Martinez et al., 2008)). Finally, batch cultures were used by necessity, whereas the
ocean environment is more like a chemostat. It is important to recognize these caveats
(and others, described below) when interpreting the results of the described experiments.
We isolated heterotrophic bacteria from the Hawaii Ocean Time Series (HOT) station
ALOHA (22º45’ N, 158º W), one of the most comprehensively studied sites in the ocean,
with a microbial community dominated by Prochlorococcus and characterized in some
detail (DeLong et al., 2006). The bacteria were isolated on a relatively nutrient-poor
seawater-based media, ProMM, which is similar to PLAG (Morris et al., 2008) but using
100% rather than 75% seawater. This media is based on the Pro99 media used to culture
Prochlorococcus (Moore et al., 2007), with the addition of a set of defined organic
compounds (0.05% w/v each of Lactate, Pyruvate, Acetate and Glycerol) and vitamins
(Waterbury and Willey, 1988)). We chose to use this media because growth of
Prochlorococcus from low cell numbers in 96 well plates is much more robust with the
addition of low concentrations (1:20 v/v) of ProMM in Pro99 (manuscript in preparation).
Thus, we could perform the co-culture in diluted ProMM, providing for robust growth of
both Prochlorococcus and the co-cultured heterotroph.
800
805
810
Several methods are used traditionally to measure growth rates of phytoplankton cultures,
including bulk fluorescence (Grossart, 1999; Malmstrom et al., 2010; Mayali et al., 2008;
Osburne et al., 2010), optical density at 600nm (OD600, (Bruckner et al., 2008)),
chlorophyll concentration (Bruckner et al., 2008) and cell number (Grossart and Simon,
2007). We chose to measure bulk chlorophyll fluorescence (ex440 em680) (FL) since it
is widely used and the easiest to measure in a non-invasive, high throughput manner.
During steady-state, balanced growth, bulk fluorescence is linearly correlated with
Prochlorococcus cell numbers (R2 = 0.82 for MIT9313 and 0.97 for MED4, see also
(Malmstrom et al., 2010; Osburne et al., 2010)). During lag, stationary and decline
phases, however, FL is no longer correlated with cell number and thus can only be used
to compare the state of one culture with respect to another. We extracted three
biologically-intuitive parameters of the fluorescence curve: growth rate, growth time and
32
815
820
825
maximal fluorescence. Briefly, the growth rate, , was defined as the maximal slope of a
linear regression, performed on Log10-transformed fluorescence data, in a sliding window
of four consecutive data points within the exponential growth phase. The growth time,
T50, was defined as the time it took the bulk culture fluorescence to reach 50% of the
maximal fluorescence, Fmax, value for that curve.
In order to simplify the experimental setup, the same volume of heterotrophic bacteria
was added into each co-culture well. Thus, the number of heterotrophs initially inoculated
into co-culture differs between different heterotroph strains. However, the outcome of coculture in our experimental system does not depend on the initial density of heterotrophic
bacteria added, even when this density varied over six orders of magnitude (sup Fig. 2).
This was observed for 8 out of 9 strains tested in co-culture with MIT9313 and for all 8
strains tested in co-culture with MED4. The lack of dependence on initial heterotroph
density is likely due to the significantly higher growth rates of the heterotrophs in this
media, which reach stationary growth (“quasi steady state”) typically after 1-2 days
compared to 7-10 days for Prochlorococcus (Sup Fig. 2B, D, F).
830
835
840
845
While heterotrophs were inoculated into each well of the co-culture plates, occasionally
wells were observed in which the inoculated heterotrophs did not visibly grow. If indeed
no heterotrophs grew in these wells this could lead to the Prochlorococcus revealing a
similar pattern as axenic cultures (e.g. “intermediate” response, Fig. 1). To bound how
important this issue was, we monitored in parallel to the bulk culture fluorescence the
turbidity (OD600) for all co-cultures. While these turbidity measurements cannot allow
quantitative estimation of the heterotroph numbers, they do enable us to roughly
determine whether heterotroph growth occurred in a specific well, based on a sharp
increase in turbidity after on a different timescale from that caused by Prochlorococcus.
In 94% of the co-cultures with MIT9313 and 91% of the co-cultures with MED4, clear
heterotroph growth was observed after 1.5 days, defined as an OD600 value of >0.086,
and these included co-cultures revealing all of the different effects on Prochlorococcus
(Early, Early arrested, Intermediate and Late growth). Of the remaining cultures, in the
case of MIT9313 more than 2/3 revealed an “Early” phenotype. Thus, while we cannot
rule out that some of “indifferent” co-cultures were due to a failed heterotroph
inoculation, this possibility affects at most 2% of the MIT9313 and 9% of the MED4 cocultures, and does not affect the overall conclusions of this study.
850
855
Isolation of heterotrophic bacteria from ALOHA: Seawater was collected during the
C-MORE BLOOMER cruise on August 18, 2007, transported back to the lab and
maintained for one month in clear polycarbonate bottles at 21ºC under 18 E constant
cold white illumination. 1-100L of seawater were spread on ProMM agar plates, and
colonies picked as they appeared over a period of 16 days into liquid ProMM. Colonies
were further re-streaked three times for purity on ProMM plates, and the final library was
maintained at -80°C in 25% glycerol.
33
860
865
870
875
880
885
PCR amplification and sequence analysis of the 16S gene: PCR amplification was
performed from 2l of the bacteria in ProMM using the universal bacterial primers 8F
and 1492R and sequenced using Sanger sequencing. Several samples which did not
amplify in several attempts using these primers were amplified using the ReaX kit (Q
Chip, Cardiff, UK, utilizing 27F and 905R primers). Sequence traces were analyzed in
CodonCode Aligner (CodonCode Corporation, Dedham, MA,
http://www.codoncode.com/aligner/download.htm), with the poor quality segments of the
sequences removed using clip parameters set to “maximize region with error rate below
0.01”. Reads with fewer than 200 consecutive high quality base pairs were also removed
from the dataset. 257 sequences (Sup Fig. 1) which passed the quality threshold were
analyzed using GreenGenes ((DeSantis et al., 2006a; DeSantis et al., 2006b),
http://greengenes.lbl.gov). The sequences were aligned to the Core Set of aligned
sequences using NAST (minimum length set to 250) to produce a set of aligned 7682character sequences (DeSantis et al., 2006b), and were checked for chimeric sequences
using Bellerophon 3.0 (600bp Core set threshold and 200bp window size) (DeSantis et
al., 2006a). The nearest neighbors and nearest isolates were determined using Simrank,
and sequence divergence from near-neighbors calculated using the DNAML option of
DNADIST (PHYLIP package, all performed within GreenGenes) with Lane Mask
restricting calculation to 1,287 conserved columns, the A, C, G, T 16S rRNA base
frequency being 0.2537, 0.2317, 0.3167, 0.1979, respectively, and the
Transition:Transversion Ratio assumed to be 2.0. The phylogenetic classification is
shown using the Hugenholz Genus classifier. Operational Taxonomic Unites (OTUs)
were estimated using DOTUR (Schloss and Handelsman, 2005) using the furthest
neighbor algorithm and a precision value of 1000. The phylogenetic trees in Fig 3 and
Sup Fig. 1 were created using PhyML (model=HKY, estimated t, v and a, (Guindon and
Gascuel, 2003)) with aLRT test for branches (Anisimova and Gascuel, 2006) and
visualized using iTOL ((Letunic and Bork, 2007), http://itol.embl.de/). Percent
divergence in the 16S gene sequences reported throughout this manuscript were based on
BLAST2seq comparisons performed at the NCBI website
(http://blast.ncbi.nlm.nih.gov/Blast.cgi) using the default parameters. The sequences have
been submitted to the GenBank under accession numbers HQ537134-HQ537390.
890
895
900
Co-culture setup and parameter extraction: Prochlorococcus strains MIT9313 and
MED4 were maintained at 20°C and 27E constant cold white illumination. Under these
conditions the two strains grow at comparable rates (=0.32±0.04 for MIT9313,
0.43±0.01 for MED4, growth rate  is described using base e). Duplicate mid-exponential
cultures were counted by using an Influx flow cytometer (BD biosciences), diluted to a
final cell density of 106 cells/ml in 5% ProMM in Pro99 and distributed into the wells of
96 microtitre plates. Duplicates of the heterotroph library were inoculated into 5%
ProMM in Pro99 24 hours prior to the initiation of the experiment, and 2L of the
heterotroph plates were used to inoculate the co-culture plates. The outer wells of the 96
well plates were not used for the experiments as growth in these wells is less robust,
possibly due to a higher evaporation rate. Each of the 96 well plates used in this
experiment had at least 12 control wells (columns 2 and 11), in which Prochlorococcus
was grown axenically, and 48 co-culture wells. The co-culture plates were maintained
for 42 days at 20°C and 27E constant cold white illumination, and the fluorescence
34
905
(ex440 em680) read almost daily using a Bio-Tek Synergy HT plate reader. The culture
parameters described above were extracted from the FL curves using several macros
written in Excel VBA, which are available from the authors upon request.
910
Selecting consistent curves and hierarchical clustering: The 96 well plates used for the
experiment contained 344 heterotroph strains, of which 257 had their 16S sequences
determined (Sup Fig 1B). We next removed from the study co-cultures in which the two
biological duplicates were not consistent. We defined a consistent pair of fluorescencebased growth curves as one in which the Euclidian distance between the normalized
curves is within the range defined by 95% of the between-plate pairs of axenic curves
(Sup Fig 5). Using this definition, 94.4% of the MED4 and 77.9% of the MIT 9313
duplicate curves were consistent, and we from the 344 original strains retained for further
analysis 250 strains which were consistent in co-culture with both Prochlorococcus
strains. These include 180 strains for which partial 16S sequences was determines, and
from which the phylogenetic tree in Fig. 3 was constructed. Duplicate curves deemed to
be consistent and the parameters extracted from these curves were averaged. For
Hierarchical Clustering, each averaged fluorescence curve was first normalized to a
vector of length one. We then applied standard Hierarchical Clustering using Matlab
(UPGMA linkage (Sokal and Michener, 1958)) using the default Euclidian distances and
a threshold for determining the clusters of 1 for the large experiment and 0.7 for the
smaller one described below. Similar results were observed in both the clustering of
fluorescence curves and in the phylogenetic analysis of the outcomes both with and
without the filtered “inconsistent” curves.
915
920
925
930
935
940
945
950
Testing the robustness of the observed patterns across different experiments: To test
the consistency of the general pattern of interactions observed, we randomly selected a
subset of 96 strains from the heterotroph library and performed a second co-culture
experiment under similar conditions several months later. Similar patterns emerged in the
second experiment, including the main different co-culture outcomes for MIT9313, the
striking lack of effect of co-culture on MED4, and the dependence of the effect on the
phylogeny of the heterotrophs (sup Fig. 6). These results show that the pattern of
interactions observed across the collection of bacteria sampled, as well as the specific
effect of each heterotroph strain, is highly robust.
Co-cultures separated by membranes: To test whether diffusible compounds mediated
the interactions we observed, or whether close cellular proximity was needed, we
performed co-culture experiments in 6-well plates containing “ThinCert” tissue culture
inserts containing a transparent 0.4m PET membrane (Greiner Bio-one). These inserts
allow each well to be partitioned into two compartments separated by a porous
membrane, which enables the rapid exchange of small molecules between the
compartments (~95% exchange of the dye phenol red within 27 hours) but blocks almost
completely the exchange of bacteria (<0.1% exchange of either Prochlorococcus or
Alteromonas HOTo1A3 (Fig 4) in 1:20 ProMM after 24 hours, as counted by flow
cytometry). The 6-well plates and tissue-culture inserts were acid washed for 15 minutes,
washed extensively with sterile mili-Q water and sterilized by UV irradiation (5 minutes
35
955
960
using a Stratagene UV cross-linker). Each compartment contained 3.5mL of 5% ProMM
in Pro99. Prochlorococcus MIT9313 was inoculated at 2×106 cells/mL into the interior
compartment, and 35L of the appropriate heterotroph strain (from an overnight culture)
were inoculated either together with MIT9313 in the interior compartment or in the
exterior compartment, separated by the membrane from MIT9313. The 6-well plates were
maintained for 19 days at 20°C and 27E constant cold white illumination. The
fluorescence (ex440 em680) was read almost every two days a Bio-Tek Synergy HT plate
reader using a 9×9 matrix per well, the middle 32 cells were averaged, and the reading
from a cell not containing any Prochlorococcus (blank cell) subtracted to produce the
final fluorescence value.
36
Titles and legends to supplementary figures:
965
970
975
980
985
Sup Fig 1: Composition and diversity of the heterotroph library used for co-culture
experiments with Prochlorococcus. A) Phylogeny of the heterotroph library and the
outcome of co-culture with Prochlorococcus. A maximum likelihood (ML) tree is
shown built from the partial 16S rDNA sequences of 257 library strains and 13 of
cultured reference strains. Spheres on the tree branches denote >80% aLRT confidence
(Anisimova and Gascuel, 2006). The leaves are colored according to the genus level
identity, and with black boxes showing Operational Taxonomic Units at 0.01 resolution
calculated using DOTUR (Schloss and Handelsman, 2005). The results of the co-culture
experiments are shown as in Figure 3. Strains which did not produce consistent curves in
replicate experiments are shown in white. For the Alteromonad reference strains, the
location where they were isolated is shown in parentheses to stress the global distribution
of these strains. The insert shows the bacterial classes represented in the library
(highlighted in red) in the context of a global phylogenetic tree (“Tree of life”
downloaded from iTOL (Letunic and Bork, 2007), http://itol.embl.de/)). Cyanobacteria
(the phylum including Prochlorococcus) are highlighted in green. B) Order level
composition of the heterotroph library, determined using the Hugenholz Genus
classifier in GreenGenes (DeSantis et al., 2006a; DeSantis et al., 2006b). Unknown
means that either no PCR amplicon, or good quality sequence, was obtained in several
reactions using the16S primers described in the materials and methods. C) Number of
Operational Taxonomic Units (OTUs) as a function of 16S rDNA gene sequence
divergence. There are 257 sequenced heterotroph strains in the library, corresponding to
65 distinct partial 16S sequences. These cluster into 23, 13, 8 and 6 distinct OTUs at 1%,
3%, 5% and 7% rDNA sequence divergence, respectively.
990
995
1000
1005
Sup Fig 2: The outcome of a co-culture as a function of initial density of
heterotrophs. Ten-fold serial dilutions of three selected heterotroph strains (each
representing one of the co-culture outcomes shown in Fig. 1), spanning 5-6 orders of
magnitude, were co-inoculated with duplicate Prochlorococcus MIT9313 cultures. The
left panels (A, C, E) show fluorescence curves, the right panels (B, D, F) show OD600
curves. The purpose of the OD600 curves is to assess the growth of the heterotrophs:
during the first few days of co-culture the increase in OD600 is caused only by heterotroph
growth, as Prochlorococcus cells numbers remain low and no such increase in OD600 is
seen in axenic Prochlorococcus cultures. A second increase in OD600 mirrors the increase
in culture fluorescence and is likely due to the increase in Prochlorococcus cell numbers.
Green curves are axenic controls, colored curves show co-cultures at different serial
dilutions (dark-more heterotrophic cells). Results show mean and range of duplicates. No
clear difference could be seen between the outcomes of the co-cultures at different initial
heterotroph densities. The growth rates of the heterotrophic strains, as calculated from the
OD600 curves during the initial four days of co-culture, were 1.44±0.1 for Alteromonas
HOTo3B7, 1.19±0.1 for Alteromonas HOTo1A3 and 1.01±0.1 for Roseobacter
HOTo5H2, significantly higher than the growth rate of MIT9313 as determined using
culture fluorescence (0.28-0.40 calculated during the MIT9313 exponential stage and
depending on the heterotroph strain). These data support our interpretation that upon
37
1010
initiation of co-culture the heterotrophic bacteria grow much faster than Prochlorococcus
and reach a quasi-steady-state which does not depend on the initial number of cells. A, B)
Early Growth (Alteromonas HOTo3B7,dilution range 2-2x105 cells/mL), C, D) Late
Growth (Alteromonas HOTo1A3, dilution range 5-5x105 cells/mL), E, F) Intermediate
Growth (Roseobacter HOTo5H2, dilution range 0.24-2.4x104 cells/mL).
1015
1020
1025
1030
1035
1040
1045
1050
Sup Fig. 3: Details of the co-culture parameter space for MIT9313. For each culture
(shown by a single curve in Fig. 1) three parameters were measured: max growth rate ,
growth time T50 and maximal fluorescence Fmax. Histograms are shown of these three
parameters in all of the cultures belonging to a specific co-culture outcome (Early
growth, intermediate growth, late growth, as defined in Fig. 1) as well as in the MIT9313only cultures. X-axis = relative parameter value, Y-axis = number of cultures. Within
each histogram the median +/- one standard deviation are written.
Sup Fig. 4: Details of the co-culture parameter space for MED4. For each culture
(shown by a single curve in Fig. 1) three parameters were measured: max growth rate ,
growth time T50 and maximal fluorescence Fmax. Histograms are shown of these three
parameters in all of the cultures belonging to a specific co-culture outcome (Early
growth, intermediate growth, late growth, as defined in Fig. 1) as well as in the MED4only cultures. X-axis = relative parameter value, Y-axis = number of cultures. Within
each histogram the median +/- one standard deviation are written.
Sup Fig. 5: Estimating the consistency of duplicate co-cultures. Histograms are shown
of the Euclidian distance between pairs of axenic cultures (upper panels) and co-cultures
(lower panels). Pairs of control cultures were defined as those controls found in
corresponding wells from duplicate plates. The dashed line represents the 95% cutoff
used to determine which co-cultures were consistent. 94.4% of the MED4 cultures and
77.9% of the MIT9313 co-cultures from the large experiment were deemed to be
consistent using these criteria.
Sup Fig. 6: Reproducibility of general patterns observed using a smaller, randomly
selected group of heterotrophs in co-cultures. A second set of co-culture experiments
was performed with 96 randomly-selected strains from the heterotroph library, several
months after the experiments shown in Figs 1-3. A) Heat maps of the normalized bulk
chlorophyll fluorescence of 85 co-cultures and 20 controls clustered using
Hierarchical Clustering (HC). B and C) Fluorescence curves of the co-cultures (B)
and axenic cultures (C). Six main co-culture outcomes can be differentiated using HC,
three of which are similar to the “Late Growth” observed in Fig. 1 but differing in the
timing of the final growth. Only two co-culture outcomes can be seen for MED4. Note
the similarity in the shape of the “early arrested growth” outcome between MIT9313 and
MED4. D) Similarity in the phylogenetic pattern of co-culture outcomes between the
two experiments. The maximum likelihood tree from Fig. 3 is shown, with the coculture outcomes (see legend) of the second experiment added. Middle rings are
MIT9313, outer rings are MED4. Spheres on the tree branches denote >80% aLRT
confidence (Anisimova and Gascuel, 2006).
1055
38
OTU
Order
number
Rhodobacterales
1
Rhodobacterales
2
Rhodobacterales
3
4
Oceanospirillales
OM60
5
6
Alcanivoracaceae
7
Alcanivoracaceae
8
Alcanivoracaceae
9
Alcanivoracaceae
Marinobacter
10
Marinobacter
11
Marinobacter
12
Marinobacter
13
Marinobacter
14
Marinobacter
15
Alteromonadales
17
Alteromonadales
18
Alteromonadales
19
Alteromonadales
20
Alteromonadales
21
1060
Effect on MIT9313
Early Early
Intermearrested diate
0
4
1
1
0
0
7
0
0
0
0
1
0
0
0
0
Effect on MED4
Early
Intermearrested diate
4
1
0
1
0
7
0
1
3
3
0
0
0
0
0
0
0
0
3
3
1
0
0
0
0
1
1
0
0
0
0
1
2
0
0
0
0
2
0
3
19
10
1
37
4
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
0
1
1
0
0
0
0
1
0
0
32
1
41
0
0
0
0
0
0
0
0
0
0
0
1
3
21
11
1
38
4
1
32
1
42
Late
Supplementary Table 1: Operational Taxonomic Units (OTUs) at 0.01 resolution
and their effect on MIT9313 and MED4 in co-culture. The OTUs are shown in the
same order as in Figure 3 and Supplemental Figure 6D, ordered clockwise. The number
of strains revealing each effect is shown.
References for Supplementary Information
1065
1070
Anisimova M, Gascuel O (2006). Approximate likelihood-ratio test for branches: A fast,
accurate, and powerful alternative. Syst Biol 55: 539-52.
Bruckner CG, Bahulikar R, Rahalkar M, Schink B, Kroth PG (2008). Bacteria associated
with benthic diatoms from Lake Constance: phylogeny and influences on diatom growth
and secretion of extracellular polymeric substances. Appl Environ Microbiol 74: 7740-9.
39
DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, Frigaard NU et al (2006).
Community genomics among stratified microbial assemblages in the ocean's interior.
Science 311: 496-503.
1075
DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K et al (2006a).
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible
with ARB. Appl. Environ. Microbiol. 72: 5069-5072.
1080
1085
DeSantis TZ, Jr, Hugenholtz P, Keller K, Brodie EL, Larsen N, Piceno YM et al (2006b).
NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA
genes. Nucl. Acids Res. 34: W394-399.
Grossart H-P (1999). Interactions between marine bacteria and axenic diatoms
(Cylindrotheca fusiformis, Nitzschia laevis, and Thalassiosira weissflogii) incubated
under various conditions in the lab. Aquatic Microbial Ecology 19: 1-11.
Grossart HP, Simon M (2007). Interactions of planktonic algae and bacteria: effects on
algal growth and organic matter dynamics. Aquatic Microbial Ecology 47: 163-176.
1090
Guindon S, Gascuel O (2003). A simple, fast, and accurate algorithm to estimate large
phylogenies by maximum likelihood. Syst Biol 52: 696-704.
1095
1100
Ivars-Martinez E, Martin-Cuadrado A-B, D'Auria G, Mira A, Ferriera S, Johnson J et al
(2008). Comparative genomics of two ecotypes of the marine planktonic copiotroph
Alteromonas macleodii suggests alternative lifestyles associated with different kinds of
particulate organic matter. Isme J 2: 1194-1212.
Letunic I, Bork P (2007). Interactive Tree Of Life (iTOL): an online tool for phylogenetic
tree display and annotation. Bioinformatics 23: 127-8.
Malmstrom RR, Coe A, Kettler GC, Martiny AC, Frias-Lopez J, Zinser ER et al (2010).
Temporal dynamics of Prochlorococcus ecotypes in the Atlantic and Pacific oceans. Isme
J.
1105
Mayali X, Franks PJ, Azam F (2008). Cultivation and ecosystem role of a marine
roseobacter clade-affiliated cluster bacterium. Appl Environ Microbiol 74: 2595-603.
1110
1115
Moore LR, Coe A, Zinser ER, Saito MA, Sullivan MB, Lindell D et al (2007). Culturing
the marine cyanobacterium Prochlorococcus. Limnology and Oceanography-Methods 5:
353-362.
Morris JJ, Kirkegaard R, Szul MJ, Johnson ZI, Zinser ER (2008). Facilitation of robust
growth of Prochlorococcus colonies and dilute liquid cultures by "helper" heterotrophic
bacteria. Appl Environ Microbiol 74: 4530-4.
40
1120
Osburne MS, Holmbeck BM, Frias-Lopez J, Steen R, Huang K, Kelly L et al (2010). UV
hyper-resistance in Prochlorococcus MED4 results from a single base pair deletion just
upstream of an operon encoding nudix hydrolase and photolyase. Environmental
Microbiology.
Schloss PD, Handelsman J (2005). Introducing DOTUR, a computer program for
defining operational taxonomic units and estimating species richness. Appl Environ
Microbiol 71: 1501-6.
1125
Sokal RR, Michener CD (1958). A statistical method for evaluating systematic
relationships. University of Kansas Scientific Bulletin 38: 1409-1438.
1130
Waterbury JB, Willey JM (1988). Isolation and Growth of Marine Planktonic
Cyanobacteria. Methods in Enzymology 167: 100-105.
41
9313
A
0.8
0.6
0.4
0.2
0
Fluorescence
0.1
-0.1
sample
Color legend
for co-culture
outcomes:
Prochlorococcus + heterotrophs
15000
15000
10000
10000
5000
5000
0
0
10
20
30
C
Fluorescence
0.3
-0.2
sample
B
MED4
0.5
40
0
Early
0
10
20
30
40
Prochlorococcus alone
15000
15000
10000
10000
5000
5000
0
0
10
20
30
40
0
In te rm e d ia te
E a rly
arrested
0
time (days)
10
20
30
40
Late
3
2
1
0
0
0
ax
1
1
T50
2
2
Fm
Growth Rate µ
MIT9313
Early
3 3
MED4
Interm ediate
3
E arly arrested
2
Late
1
0
0
0
ax
1
1
T50
2
2
3 3
Fm
Growth Rate µ
Color legend for
co-culture
outcomes:
Outer ring: Middle ring:
MED4
931 3
Inner ring:
phylogeny:
Scale: 0.05
*
5C4
HOT4G8
HOT4C7
HOT
HOT5G
7
HOT5D
8
HO
T5F4
HO
T5D1
0
HO
T4G9
HO
T9
C6
HO
T4
G5
HO
T4
E4
HO
T4
D4
HO
T4
F1
HO
0
T4
E10
HO
T4C
HO
3
T7G
HO
7
T5E
HO
8
T4
H
E9
O
T4
E6
HOT5G5
HOT4D10
HOT4E8
HOT2G5
HOT4F6
HOT1D9
HOT4F8
HOT4F4
HOT4C5
HOT5C7
HO
HO
F6
T5
HO
B3
T4
HO
E7
T4
HO
B9
T9
10
0F
T1
10
HO
T5G
3
HO
T8D
8
HO
T8G 3
C
HO
T5
F4
HO
T8
O
H
4B5
HOT
8
HOT9B
10
HOT9B
G9
HOT7
T9C7
HO
7
T10F
HO
T3F6
HOT4F7
*
*
HO
HO
HO
T5
HO
HO
T5
HO
HO
HO
T8
T5B
8
T9B
B10
T7
B8
F3
T5
G
T5
HO
6
E8
E5
9
HO
5
T4E
10
T4C
HO
F8
T5
3
HO
0G
T1
HO
G6
T5
HO
C4
T4
T5
HO
E6
G8
T2
HO
HO
*
HOT2E
HOT2D
8
HOT
1C10
T5
C9
T9C5
HO
T4B7
HO
T2G6
HO
0D7
HOT1
C5
HOT10
7
HOT5E
HOT
HOT1E6
HOT8F3
HOT3F9
HOT5D3
HOT3E7
HOT1G8
HOT3D9
HOT1G9
HOT3C8
HOT2G7
HOT1E5
HOT3D6
HOT3G6
HOT1G3
HOT4C8
HOT1E9
HOT1D10
HOT10B5
HOT1E4
HOT8D9
HOT1E7
HOT3E1
HOT5C10
0
HOT4D5
4B6
HOT
3
HOT4F
10
HOT3F
HOT
9C3
HOT3C
HOT9B
E6
T3
E5
T3
0
F1
T2
F9
10
9
T4B
C5
HO
T3
HO
6
0D
T1
10
O
G
H
T4
6
HO
T4G
9
HO
T4F
5
HO
T4F
HO
B8
T2
HO
G8
T3
HO
F3
T3
HO
D8
T3
HO
D6
T1
HO
T3E8
HO
T3E9
HO
T4G4
HO
6
7
HOT3D5
1B10
HOT
T2E9
HOT2B
HOT2C
HO
HOT2B9
HOT1B5
HOT10C8
Rhodobacterales
Oceanospirillales
OM60
Alcanivoracaceae
Marinobacter
Alteromonadales
HOT2E8
α proteobacteria
HOT2D9
Inner ring:
P hylog eny (Clockwise)
HOT2D7
HOT2C8
T4B
H
O
T3
HO
D
3
T2
HO
C
T2B 7
HO
6
T1D
HO
7
T3C
HO
9
T1
D8
HO
T3
G7
HO
T2
E5
HO
T3
B4
HO
T3
B1
0
HO
T10F
8
HO
T2D6
HO
T3D7
HO
T4D7
HOT3B
9
HOT4C
6
HOT
3C4
HO
HOT2B4
T2
HO
HOT1E3
HO
HOT3B5
HO
HOT1B3
HO
HOT3F5
T3E3
HO
T3B6
HO
0
T3D1
HO
G5
T3
HO
C6
T3
HO
7
3
HO
T8G1
0
HO
T5E4
HO
T4D6
HO
T8D7
HO
T3
B8
HO
T5
F9
HO
T5
G4
HO
T5
D4
HO
T4
D9
HO
T3
F4
HO
T1G
HO
10
T1G
HO
5
T1
0F
6
T3E4
HO
γ proteobacteria
10
1G6
HOT1G7
HOT3G10
*
O uter rings: co
culture outcom e
Early
Interm ediate
E aarly arrested
Late
Fluorescence
250
200
Marinobacter HOT4G9
Alcanivorax HOT7G9
Rhodobacter HOT5F3
Alteromonas HOTs2G3
150
100
50
0
250
200
150
100
50
0
250
200
0
Alteromonas HOTo1A3
15
co-culture
together
100
50
0
10
9313 alone
150
0
5
5
10
Days
15
20
Co-culture
separated by
membrane
20
Co-culture outcome
MIT9313
MED4
α-Proteobacteria
A
Prochlorococcus MIT9313
Pelagibacter ubique
Dinoroseobacter shibae
Roseobacter denitrificans
Marinovum algicola
Pro MIT931
Pelagibac
Dinoroseo
HOT10F8
HOT10C7
Roseobact
HOT9B6
HOT10B9
HOT5E6
HOT7E8
HOT5E5
HOT5F3
Marinovum
HOT5B10
HOT8G6
HOT8G8
HOT8C6
HOT8F5
HOT8C5
HOT8D3
HOT8G5
HOT8B6
HOT8F10
HOT5C3
HOT8F4
HOT8F6
Rhodobacter
HOT5G10
HOT8B4
HOT9C10
HOT8F9
HOT8B9
HOT9B5
HOT8C10
HOT8C8
HOT8B5
HOT8C9
HOT5B8
HOT8B8
HOT8D8
HOT8B3
HOT8G9
HOT7G10
HOT8F7
HOT8C7
HOT8D5
HOT8D6
HOT7C10
HOT9C7
HOT7G9
HOT10F9
HOT10B10
HOT10G9
Alcanivorax borkumensis
HOT9B8
HOT9B10
Alcanivor
HOT10G3
HOT10C4
HOT10F7
Alcanivorax
HOT5F6
HOT10G4
HOT10D3
HOT10F10
HOT10F3
HOT10G8
Marinobacter AP10
HOT3F6
HOT10C3
Marinobact
HOT4E5
HOT4C10
HOT10B3
HOT5F8
HOT5G9
HOT4E6
HOT4B5
Scale
0.01
HOT4F8
HOT4F4
HOT4C5
HOT5C7
HOT1D9
HOT5G5
HOT4F6
HOT4D10
HOT5F4
HOT5D10
HOT4G9
HOT9C6
HOT4G5
HOT4E4
HOT4D4
HOT4F10
HOT4E10
HOT4C3
HOT7G7
HOT4E9
HOT5E8
HOT4E8
HOT2G5
HOT4F7
HOT4G8
HOT4C7
HOT5C4
HOT5G7
HOT5D8
HOT5G6
HOT10C9
HOT5C9
Marinobacter
HOT2G8
HOT4C4
HOT10C5
HOT10F5
HOT9C5
HOT4B7
HOT2G6
HOT10F4
HOT10G5
HOT10D8
HOT5E10
HOT1G7
HOT1G6
HOT8F3
HOT5D3
HOT1G8
HOT1G9
HOT2G7
HOT1G3
HOT10C8
HOT1E9
HOT10D5
HOT8D9
HOT9C3
HOT3C7
HOT5C10
HOT4D5
HOT9B3
HOT8G10
HOT5E4
HOT4D6
HOT8D7
ia
cter
ba
yano
C
HOT3B8
HOT5F9
HOT5G4
HOT4D9
HOT3F4
HOT1G10
HOT1G5
HOT10G10
Spongiibacter tropicus
HOT9C4
HOT2G9
Spongiibac
HOT9B9
HOT9C8
HOT4E7
Vibrio splendidus
HOT4B3
Vibrio spl
HOT10B6
OM60
Alt MED
HOT10B6
Alteromonas MED102 (Mediterranean)
HOT4G10
HOT4G6
HOT10G6
HOT10D6
HOT10F6
HOT10D7
HOT11C6
Alteromonas macleodii
Deep Ecotype (Adriatic Sea)
HOT4F9
Alt DE
γ-proteobacteria
HOT3D8
HOT3E8
HOT2F5
HOT3C3
HOT1E8
HOT2B8
HOT1D6
HOT4G7
HOT3G8
HOT4F5
HOT3E9
HOT2E9
β-p
rot
bac eoteri
a
Firmicutes
Oceanospirillales
HOT5D4
pylo s
m
a
C
e
eral
bact
γ-Proteobacteria
HOT3D6
HOT2C6
HOT3B9
HOT1D5
HOT2G10
HOT1C6
HOT4D3
HOT3B5
HOT1F3
Alteromonas CF12-6 (South China Sea)
HOT2F6
HOT2D7
Alt SCS
HOT3D7
HOT4B4
pr
α-
HOT4D7
HOT2D6
HOT4C6
HOT2E8
HOT1B9
HOT2D9
HOT1B5
HOT3D5
HOT2B9
HOT2F8
HOT3F5
HOT1B10
Alteromonadales
b
eo
HOT1B7
HOT2B4
HOT1E3
HOT3F3
HOT2C8
HOT1B3
HOT4G4
Alteromonas L188s.610
(Mid-Atlantic Ridge sediment)
HOT2B7
ac
HOT2F7
Alt MAR
HOT4C8
HOT3G6
te
HOT3C8
HOT1E5
HOT1C10
HOT2G4
ria
HOT1C4
HOT3D9
HOT3B6
HOT3E7
HOT1D7
HOT3G10
HOT1E6
HOT1B6
HOT2D8
HOT2D10
eae
ttsiac
Ricke
ot
HOT3C4
HOT2E7
HOT1D4
HOT2B6
HOT3F10
HOT2F10
HOT3E4
HOT3C10
HOT3D10
HOT2F9
HOT3E3
HOT2C4
HOT3E5
HOT3G3
HOT3E6
HOT3C6
HOT3G5
HOT4F3
HOT4B6
HOT1E4
Color legend for
co-culture
outcomes:
HOT2D5
HOT3E10
HOT2C7
HOT2E4
HOT2C10
HOT4B10
HOT4B9
Archaea
HOT3B10
HOT3B4
HOT2E6
HOT1B8
HOT1D3
HOT3C5
Eukarya
HOT1B4
HOT2E5
HOT3G7
HOT1F4
HOT2B3
HOT1D10
HOT1E7
HOT3F9
HOT1D8
HOT3C9
HOT2C9
HOT3D3
C
1%
unkno wn 26%
1%
26%
33%
Rho d o b a cte ra le s 12%
A lca nivo ra ca ce a e 3%
M a rino b a cte r 24%
12%
3%
24%
A lte ro m o na d a le s 33%
O M 6 0 1%
O ce a no sp irilla le s 1%
Number of OTUs
B
Early
Interm ediate
E arly arrested
Late
70
60
50
40
30
20
10
0
0
0 .1
0 .2
Sequence divergence
0 .3
A
B
C ulture fluorescence
100000
C ulture turbidity
1
10000
0.1
1000
100
Alteromonas sp H O To3B 7
10
C
0
20
30
0.01
D
40
O D600nm
F lu o re s c e n c e
10000
1000
100
0
10
20
30
0
10
20
30
40
0
10
20
30
40
0
10
20
30
40
1
0.1
Alteromonas sp H O To1A 3
10
E
10
0.01
40
F
10000
1
1000
0.1
100
Roseobacter sp H O To5H 2
10
0
10
20
30
40
0.01
D ays
Heterotroph
density
(cells/mL)
Alteromonas
HOTo3B7
2x10^ 5
2x10^ 4
2x10^ 3
200
20
2
Alteromonas
HOTo1A3
5x10^ 5
5x10^ 4
5x10^ 3
500
50
5
M ean all con trols
Roseobacter
HOTo5H2
2.4x10^ 4
2.4x10^ 3
240
24
2.4
0.24
Relative Growth Time T50
Relative Growth Rate µ
40
20
0
Early
0
0.5
1
Interm ediate
1.5
2
2.5
1.49 (+0.28 −0.31)
20
0
0
0.5
1
1.5
2
2.5
1.16 (+0.42 −0.27)
2
0
0
0.5
1
100
0
0
0.5
1
1.5
2
2.5
1.5
2
2.5
0
0.5
1
1.5
2
2.5
1.01 (+0.16 −0.24)
0
0
0.5
1
40
2
2.5
1.25
(+0.11 −0.05)
20
0
1.5
0
0.5
1
1.5
2
Relative growth rate
2.5
0
0
0.5
1
1.5
2
2.5
0.42 (+0.03 −0.05)
1
2
3
4
1.71 (+0.49 −0.83)
0
0
1
2
4
3
4
1.11 (+0.71 −0.40)
0
0
1
4
2
3
4
0.41 (+0.05 −0.14)
2
0
0.5
1
40
1.5
2
2.5
1.94 (+0.21 −0.26)
20
0
0
2
5
E arly arrested
0
20
10
1.58 (+0.03 −0.09)
1.01 (+0.16 −0.16)
40
0.74 (+0.10 −0.07)
4
0
40
20
2
5
Late
0.99 (+0.11 −0.09)
50
4
0
40
20
40
Number of cultures
Co-cultures
9313 alone
1.00 (+0.10 −0.10)
Relative Maximal
Fluorescence Fmax
0
0
1
2
40
3
4
0.32 (+0.17 −0.42)
20
0
0.5
1
1.5
Relative growth time
2
2.5
0
0
1
2
3
Relative maximal
fluorescence
4
Relative Maximal
Fluorescence Fmax
Relative Growth Rate µ Relative Growth Time T50
60
60
60
1.00 (+0.03 −0.03)
1.00 (+0.03 −0.03)
MED4 alone
40
40
40
20
20
20
Co-cultures
Number of cultures
0
Interm ediate
0
0.5
1
200
1.5
2
2.5
0
0
0.5
1
150
1.03 (+0.06 −0.05)
150
1.5
2
2.5
1
2
3
4
1.10 (+0.23 −0.23)
40
50
50
0
0.5
1
1.5
2
2.5
0
20
0
0.5
1
3
1.5
2
2.5
0
0
1
2
3
4
4
0.62 (+0.05 −0.05)
0.98 (+0.17 −0.17)
1.5
0.13 (+0.05 −0.12)
3
2
1
2
1
0.5
0
0
60
100
0
0
80
1.01 (+0.05 −0.03)
100
2
E arly arrested
1.00 (+0.08 −0.10)
0
0.5
1
1.5
2
Relative growth rate
2.5
0
1
0
0.5
1
1.5
2
Relative growth time
2.5
0
0
1
2
3
Relative maximal
fluorescence
4
MIT9313 alone
15
MED4 alone
15
mean=0.18 std=0.07
Number of curves
mean=0.38 std=0.18
10
10
5
5
0
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0
0.1
0.2
0.3
MIT9313 Co-cultures
30
40
10
20
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0
0.4
0.5
0.6
0.7
0.8
0.6
0.7
0.8
MED4 Co-cultures
60
20
0
0
0
0.1
0.2
0.3
0.4
Euclidian distance between duplicate curves
0.5
MIT9313
A
MED4
0.
7
0.
5
0.
6
0.
5
0.
4
0.
4
0.
3
0.
3
0.
2
0.
2
0.
1
0.
1
0
0
−0.
1
B
D
sample
Prochlorococcus + heterotrophs
Fluorescence
C
15000
15000
10000
10000
5000
5000
0
0
10
20
30
0
10
20
30
40
20
30
40
Prochlorococcus alone
15000
15000
10000
10000
5000
5000
0
0
10
20
30
40
0
time (days)
0
10
HOT5G5
HOT4D10
HOT4E8
HO
HO T8
T5 B8
H
HO OT9 B8
B
T
HO 5B10 6
HO T7E
8
HO T5F3
HO T5E5
T5
E6
HOT1G9
HOT2G7
HOT3D6
HOT1G3
HOT1E9
HOT10B5
HOT8D9
HOT5C10
HOT4D5
HOT9C
HOT3C 3
HOT9 7
B3
HO
T8G1
HO
T5E4 0
HO
T4D6
HO
T8D7
HO
HO T3B8
HO T5F9
HO T5G
HO T5D 4
HO T4D 4
HO T3F 9
H T1 4
HO OT1 G1
T1 G5 0
0F
6
HOT10C8
HOT2B9
HOT1B5
H
O
HO T3
HO T2 D3
HO T2 C7
B
HO T1D 6
HO T3C 7
HO T1D 9
T3 8
HO
G7
HO T2E5
HO T3B4
T3
B1
HO
0
T1
HO 0F8
T2D6
HO
T3D7
HO
T4
HOT3 D7
B9
HOT4C
6
HOT3C
4
HOT2B4
HOT1E3
HOT3B5
HOT1B3
HOT3F5
HOT2C8
9
G
T5 E5
HO T4 C10
HO T4 8
HO T5F G3
HO T10 6
HO T5G 4
HO T4C
8
HO T2G
HO T5C9
HO
T9C5
HO
T4B7
HO
T2G6
HO
0D7
HOT1 0C5
HOT1 10
HOT5E 6
HOT1G
HOT1G7
HOT8F3
HOT5D3
HOT1G8
6
0D 0
T1 G1
O
H OT4 G6
H T4 F9
HO T4 5
HO T4F 8
HO T2B 8
HO T3G
HO T3F3
HO T3D8
D6
HO
T1
HO
T3E8
HO
T3E9
HO G4
T4
HO
T2E9
HO
C6
HOT2 7
HOT2B
10
HOT1B
HOT3D5
HOT2D7
HOT2D9
HOT2E8
HOT2
E7
HOT2D
HOT1C 8
10
HOT1E6
HOT3G10
HOT3F9
HOT3E7
HOT3D9
HOT3C8
HOT1E5
HOT3G6
HOT4C8
HOT1D10
HOT1E4
HOT1E7
0
HOT3E1
6
HOT4B
3
HOT4F 0
F1
HOT3 E4
T3
HO
T3E3
HO
T3B6
HO D10
T3
5
HO T3G
C6
HO
T3
HO T3E6
5
HO T3E
HO 2F10 9
T
HO OT2F 10
H 4B 9
T 4B
HO OT 3C5
H
T
HO
HOT2G5
HOT4F7
HOT4G8
HOT4C7
HOT5C
HOT5G 4
HOT5 7
D8
HO
T5F4
HO
T5D1
HO
T4G9 0
HO
HO T9C6
HO T4G5
HO T4E4
HO T4D
HO T4F1 4
HO T4E 0
HO T4C 10
HO T7 3
H T5 G7
H OT E8
O 4E
T4
9
E6
Scale: 0.05
HOT4F6
HOT1D9
HOT5C7
HOT4C5
HOT4F4
HOT4F8
5
HOT4B 8
HOT9B 0
B1
HOT9 G9
HOT7 C7
T9
HO 0F7
T1
HO T3F6
HO
F6
T5
HO
B3
T4
HO T4E7
9
HO T9B
HO F10
T10 10
HO T5G 8D3
HO OT G8
H T8 C3
HO T5 F4
8
HO OT
H
MED4
experiment 2
0
40
MIT9313 experiment 1
MIT9313
experiment 2
MED4
experiment 1
−0.
1
sample
Color legend for co-culture outcomes:
Early
Interm ediate
E arly arrested
Late (1)
Late (2)
Late (3)