Microbial Diversity of Co-Occurring Heterotrophs in Cultures of Marine Picocyanobacteria

bioRxiv preprint doi: https://doi.org/10.1101/2020.07.15.205195; this version posted July 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

1 TITLE:

2 Microbial Diversity of Co-occurring Heterotrophs in Cultures of Marine Picocyanobacteria

4 AUTHORS:

5 Sean M. Kearney1,*,+, Elaina Thomas1,+, Allison Coe1, Sallie W. Chisholm1,*

7 1Department of Civil and Environmental Engineering, Massachusetts Institute of Technology

8 *co-corresponding authors: Sean M. Kearney ([email protected]), Sallie W. Chisholm

9 ([email protected])

10 + these authors contributed equally

12 ABSTRACT

13 Prochlorococcus and Synechococcus are responsible for around 10% of global net primary

14 productivity, serving as part of the foundation of marine food webs. Heterotrophic bacteria

15 are often co-isolated with these picocyanobacteria in seawater enrichment cultures that

16 contain no added organic carbon; heterotrophs grow on organic carbon supplied by the

17 photolithoautotrophs. We have maintained these cultures of Prochlorococcus and

18 Synechococcus for 100s to 1000s of generations; they represent ideal microcosms for

19 examining the selective pressures shaping autotroph/heterotroph interactions. Here we

20 examine the diversity of heterotrophs in 74 enrichment cultures of these picocyanobacteria

21 obtained from diverse areas of the global oceans. Heterotroph community composition

22 differed between clades and ecotypes of the autotrophic ‘hosts’ but there was significant

23 overlap in heterotroph community composition. Differences were associated with timing,

24 location, depth, and methods of isolation, suggesting the particular conditions surrounding

25 isolation have a persistent effect on long-term culture composition. The majority of

26 heterotrophs in the cultures are rare in the global ocean; enrichment conditions favor the

27 opportunistic outgrowth of these rare bacteria. We did find a few examples, such as

28 heterotrophs in the family Rhodobacteraceae, that are ubiquitous and abundant in cultures

29 and in the global oceans; their abundance in the wild is also positively correlated with that of

30 picocyanobacteria. Collectively, the cultures converged on similar compositions, likely from

31 bottlenecking and selection that happens during the early stages of enrichment for the

32 picocyanobacteria. We highlight the potential for examining ecologically relevant

33 relationships by identifying patterns of distribution of culture-enriched organisms in the

34 global oceans.

36 IMPORTANCE

37 One of the biggest challenges in marine microbial ecology is to begin to understand the rules

38 that govern the self-assembly of these complex communities. The picocyanobacteria

39 Prochlorococcus and Synechococcus comprise the most numerous photosynthetic organisms

40 in the sea and supply a significant fraction of the organic carbon that feeds diverse

41 heterotrophic microbes. When initially isolated into cultures, Prochlorococcus and

42 Synechococcus carry with them select heterotrophic microorganisms that depend on them for

43 organic carbon. The cultures self-assemble into stable communities of diverse

44 microorganisms and are microcosms for understanding microbial interdependencies.

45 Primarily faster-growing, relatively rare, copiotrophic heterotrophic bacteria – as opposed to

46 oligotrophic bacteria that are abundant in picocyanobacterial habitats – are selected for in

47 these cultures, suggesting that these copiotrophs experience these cultures as they would high

48 carbon fluxes associated with particles, phycospheres of larger cells, or actual attachment to

49 picocyanobacteria in the wild.

51 INTRODUCTION

52 Microorganisms perform a variety of matter and energy transformations in the oceans that

53 underlie global biogeochemical cycles. At the base of these transformations are

54 photosynthesis and other forms of autotrophic fixation of carbon dioxide. The

55 picocyanobacteria, Prochlorococcus and Synechococcus, contribute approximately 25% of

56 this global ocean net primary productivity (Flombaum et al., 2013).

58 Abundant, free-living oligotrophic bacteria like Prochlorococcus, many strains of

59 Synechococcus, and members of the SAR11 clade of heterotrophs exhibit genome

60 streamlining, likely driven by reductive evolutionary pressures acting on bacteria that have

61 large population sizes and live in relatively stable environments (Biller, Berube, et al., 2014;

62 Giovannoni et al., 2005; Rocap et al., 2003). Together these three groups can represent more

63 than 50% of free-living bacteria in the oligotrophic surface oceans (Becker et al., 2019;

64 Giovannoni, 2017). By contrast, opportunistic marine copiotrophic organisms typically have

65 larger genomes and cell sizes, and are subject to periodic fluctuations in abundance, typically

66 depending on an influx of organic matter for growth (López-Pérez et al., 2012; Romera-

67 Castillo et al., 2011; Tada et al., 2011; Zemb et al., 2010).

69 Unlike the low nutrient regimes of the oligotrophic oceans, cultures of Prochlorococcus and

70 Synechococcus have high concentrations of inorganic nutrients (N, P, Fe) and accumulate

71 dissolved organic matter and detritus as cells grow and die (Becker et al., 2014; Moore et al.,

72 2007). These conditions might favor sympatric heterotrophic microorganisms adapted to

73 higher organic carbon concentrations such as those associated with detrital particles or

74 phytoplankton blooms (Buchan et al., 2014; Seymour et al., 2017; Stocker, 2012; Tada et al.,

75 2011; Teeling et al., 2012). Even in oligotrophic oceans, the concentration of dissolved

76 organic matter derived from phytoplankton can be hundreds of times higher in the diffusive

77 boundary layer surrounding cells – the “phycosphere” (Bell & Mitchell, 1972; Seymour et

78 al., 2017) than in the surrounding water. The size of the sphere is a function of the size of the

79 cell producing it, thus large eukaryotic phytoplankton can create phycospheres extending

80 100s to 1000s of microns from their surface, while those of Prochlorococcus and

81 Synechococcus span only a few cell lengths in diameter – i.e. 1-2 microns (Seymour et al.,

82 2017). The assembly of heterotrophic bacterioplankton strongly depends on the nature of

83 organic matter exudate (Amin et al., 2012; Durham et al., 2015, 2017; Fu et al., 2020; Gärdes

84 et al., 2011; Goecke et al., 2013; Landa et al., 2017), which includes a diverse collection of

85 compounds (Becker et al., 2014; Durham et al., 2015; Hellebust, 1967), and the bacteria in

86 these communities can alter the physiology of their hosts (Amin et al., 2012; Durham et al.,

87 2017).

89 While studies of the interactions between bacterioplankton in the phycosphere of eukaryotic

90 hosts has received extensive attention, heterotrophs also exhibit chemotaxis towards

91 metabolites derived from Prochlorococcus and Synechococcus (Seymour et al., 2010),

92 hinting that some of the principles of interactions for large-size class phytoplankton may also

93 hold for the picocyanobacteria. Instead of being derived from the relatively limited diffusive

94 boundary layer around picocyanobacteria, free diffusion of dissolved organic carbon (DOC)

95 in bulk seawater may be the most common way for heterotrophs in the oligotrophic oceans to

96 obtain carbon for growth (Zehr et al., 2017). Hence, diffusion-limited uptake of DOC may

97 limit growth for free-living heterotrophs in the oceans. Yet, there’s also evidence of direct

98 interactions between picocyanobacteria and heterotrophs. Given the small size of

99 picocyanobacteria, cells that attach directly to the picocyanobacterial host (apparent for some

100 Synechococcus (Malfatti & Azam, 2009)) or associate with them in particulate matter (e.g.

101 through heterotroph-mediated aggregation of cyanobacteria (Cruz & Neuer, 2019)) would be

102 spatially co-localized enough to experience a so-called “phycosphere”.

103

104 Cyanobacterial cultures accumulate cells and organic carbon, which may lead to more

105 frequent physical interactions as well as metabolic exchanges between the host

106 cyanobacterium and associated heterotrophs, analogous to a phycosphere. Indeed,

107 Prochlorococcus in culture exhibits both growth improvement and inhibition when grown in

108 the presence of various co-occurring microbes (Aharonovich & Sher, 2016; Biller et al.,

109 2016; Sher et al., 2011). The co-culture benefits include improved recovery from, and

110 longevity in, stationary phase (Roth-Rosenberg et al., 2020), revival from low cell numbers

111 during inoculation (Morris et al., 2008), expanded tolerance to temperature changes (Ma et

112 al., 2017), and survival under extended darkness (Biller, Coe, et al., 2018; Coe et al., 2016).

113 These various benefits have been attributed to the presence of these heterotrophic partners.

114 However, culturing with heterotrophic bacteria can inhibit or delay the onset of growth in

115 some strains of Prochlorococcus (Sher et al., 2011). Furthermore, at high concentrations

116 Alteromonas strains that normally improve Prochlorococcus growth characteristics can

117 inhibit it (Aharonovich & Sher, 2016).

118

119 When interactions are beneficial, heterotrophic bacteria often provide complementary

120 functions for their “host” cyanobacteria. For example, Prochlorococcus strains lack the

121 ability to produce catalase, which can detoxify radical oxygen species (ROS) formed during

122 growth, but co-isolated heterotrophs that can produce catalase have been shown to

123 complement this deficiency (Morris et al., 2008, 2011, 2012). The benefits provided to

124 phototrophs by these heterotrophic microorganisms extend beyond removal of ROS, and

125 include recycling and release of reduced N (López-Lozano et al., 2002; Zubkov et al., 2003)

126 and P (Christie-Oleza et al., 2017) for resumption of autotrophic growth. In some cases, this

127 nutrient recycling can allow cultures to have apparent indefinite longevity without transfer to

128 fresh medium. Synechococcus can exhibit long-lasting growth when co-cultured with

129 heterotrophic bacteria (Christie-Oleza et al., 2017), and we too have found that in co-cultures

130 of Prochlorococcus str. MIT9313 with a Rhizobium species, and Prochlorococcus str.

131 NATL2A with Alteromonas macleodii MIT1002, the cells can survive without transfer for

132 over three years, in contrast to a few weeks for axenic cultures (unpublished data).

133

134 Because of their beneficial interdependencies, separating cyanobacteria from their

135 heterotrophic “helpers” (sensu Morris et al., 2008) in enrichment cultures is a challenge when

136 trying to obtain pure cultures (Christie-Oleza et al., 2017; Morris et al., 2008). At the same

137 time, however, xenic cultures of these phototrophs present a unique opportunity to investigate

138 the effects of selection on self-assembled mixed microbial communities, and ultimately,

139 probe their interdependencies. While the boom-bust and high nutrient concentration

140 conditions of batch culture do not mimic the conditions present in the open ocean (except for

141 on particles or in phytoplankton blooms), these cultures represent a theater for extending the

142 phycosphere of these cells throughout the culture volume. In these phycosphere analogues,

143 we can observe what selective forces act on indigenous communities, and ultimately explore

144 their mechanistic underpinnings. These data can inform future work on the dynamics of

145 particle-attachment or aggregation among picocyanobacteria and associated heterotrophs.

146 The robustness of these cultures may also provide insights into designing more efficient

147 methods for obtaining and sustaining axenic strains of picocyanobacteria.

148

149 We have maintained cultures of Prochlorococcus [56] and Synechococcus [18], and

150 accompanying heterotrophic “bycatch” for 100s to 1000s of generations in the laboratory by

151 serial liquid transfer. We used this collection to address several questions about the nature of

152 these phototroph-associated microbial communities. What is the composition and diversity of

153 these heterotroph communities after many passages? How does the composition of our long-

154 term cultures compare to that in cultures of picocyanobacteria or diatoms maintained for less

155 time? Which factors best determine composition of the heterotrophic community: the method

156 of isolation, the age of the culture, the inoculum from which the culture was derived (i.e. the

157 specific time and place of isolation)? And finally, how does the composition of heterotrophs

158 in culture compare to the communities in the waters from which the host cyanobacterium was

159 isolated?

160

161 RESULTS AND DISCUSSION

162 The cyanobacterial culture collection. The cyanobacterial isolates used in the analysis span

163 multiple clades of Prochlorococcus and Synechococcus obtained from many locations and

164 times (between 1965 and 2013) in the global oceans (Figure 1A, Table S1). The isolates –

165 most of which are from the oligotrophic oceans – have been maintained by serial transfer for

166 many years, with cultures ranging in age from 6 to 55 years, and thus represent what we

167 believe to be stable consortia of single algal isolates associated with diverse heterotrophic

168 bacterial communities (see Materials and Methods, and Figure S1) (Figure 1B).

169

170 Heterotroph communities in the cultures. We anticipated that heterotrophic culture

171 richness – as defined by amplicon sequence variants (ASVs) of the V4 region of 16S rRNA

172 gene – might decrease with age of the culture due to extinctions over time. However, the

173 number of ASVs, which ranged from 1 to 23 (Figure 1B), was only weakly, and not

174 significantly anti-correlated with the age of the culture (Spearman’s rho = -0.19, p-value =

175 0.11). NATL2A, for example, at nearly 30 years old, is one of the oldest cultures, but has 22

176 ASVs, while P1344 is 6 years old and contains 23 ASVs – a difference of just one ASV for

177 an age difference of 24 years. Further, we sampled three sets of cultures (Prochlorococcus

178 str. MED4, NATL2A, and MIT9313) in 2018 and one year later, and found a general

179 correspondence in the community composition over time (Figure S1). Cultures of the same

180 Prochlorococcus maintained by different individuals (MIT0604a & MIT0604b) also showed

181 similar community composition, as well as cultures derived from the same starting

182 enrichment culture (e.g. SS2, SS35, SS51, SS52, and SS120, were all derived from the LG

183 culture (Table S1)) (Figure 2). These results suggest that the heterotroph communities in

184 these cultures remain similar over time and independent maintenance, but exhibit slight drift

185 over time (i.e. the cultures are similar but not identical in composition) (Figure S1).

186

187 We next explored whether the heterotrophic community composition was related to the

188 cyanobacterial “host” – i.e. Prochlorococcus or Synechococcus – in the cultures. Which

189 taxonomic groups were common to both, and which were more common in one or the other?

190 Grouping ASVs at the phylum level, heterotroph communities in all cultures were largely

191 comprised of bacteria from the phyla Proteobacteria (primarily in the classes Alpha- and

192 Gammaproteobacteria, with some Delta- and Betaproteobacteria), Bacteroidetes (classes

193 Cytophagia, Flavobacteria, and Rhodothermi), and Planctomycetes (class Phycisphaerae),

194 with a minor contribution from Spirochaetes (class Leptospirae) and candidate phylum

195 SBR1093 (class A712011) (Figure 2, Figure S2). SBR1093 was only in the LLIV clade

196 (Figure 2). With respect to heterotrophic phyla, Prochlorococcus and Synechococcus cultures

197 contain Proteobacteria and Planctomycetes at similar frequencies, but Bacteroidetes are more

198 common, though not significantly, in Synechococcus cultures (94% versus 80%) (Figure 3A).

199 At the class level, Alpha- and Gammaproteobacteria as well as Phycisphaerae have equal

200 representation across the two cyanobacterial hosts (Figure 3B). Flavobacteria (90% of

201 Synechococcus cultures versus 56% of Prochlorococcus, Fisher Exact Test p-value = 0.01)

202 and Rhodothermi (56% of Synechococcus cultures versus 14% of Prochlorococcus, Fisher

203 Exact Test p-value = 0.06), however, are more well-represented in Synechococcus cultures,

204 suggesting that compounds in the exudate derived from Synechococcus may be better

205 matched to their growth requirements. Indeed, Prochlorococcus and Synechococcus secrete

206 distinct compounds during growth (Becker et al., 2014), few of which are characterized, but

207 likely promote differential growth of associated heterotrophs as shown previously (Zheng et

208 al., 2018, 2020).

209

210 Minor differences in heterotroph communities between Prochlorococcus and Synechococcus

211 hosts at the phylum and class level suggested that there might be more pronounced

212 differences at the genus level. This was not the case, however; instead they were quite similar

213 (Figure 3C). For instance, the most ubiquitous genus (present in over 60% of both culture

214 types) is Marinobacter (Figure 3C), which is well-known to be associated with

215 picocyanobacteria in culture (Morris et al., 2008). In addition to Marinobacter, other genera

216 present in at least 15% of cultures including Thalassospira, Methylophaga, Alteromonas,

217 Alcanivorax, Maricaulis, Muricauda, and Hyphomonas (but not Shimia) have been associated

218 with metabolism of hydrocarbons or C1 compounds derived from lipid catabolism (Coulon et

219 al., 2007; Dong et al., 2018; Hara et al., 2003; Kappell et al., 2014; Koch et al., 2020; Kostka

220 et al., 2011; Lea-Smith et al., 2015; Liu et al., 2007; López-Pérez et al., 2012; Neufeld et al.,

221 2007; Vila et al., 2010; Yakimov et al., 2007; Zhao et al., 2010), suggesting that hydrocarbon

222 metabolism might play an important role in their growth in these cultures. Indeed, previous

223 work showed an upregulation of genes for fatty acid metabolism including lipid beta-

224 oxidation in co-culture of Alteromonas macleodii with Prochlorococcus (Biller et al., 2016).

225 Prochlorococcus secretes vesicles (potentially a source of lipids) in culture and in the wild

226 (Biller et al., 2017; Biller, Schubotz, et al., 2014), which can outnumber cells by a factor of

227 10 or more, and marine heterotrophs like Alteromonas are capable of growing on these

228 vesicles as a sole source of carbon (Biller, Schubotz, et al., 2014). Recent work also suggests

229 that Alteromonas isolates derived from cultures of Prochlorococcus carry genes for the

230 degradation of aromatic compounds produced by the cyanobacterium (Koch et al., 2020),

231 which may provide a selective advantage. Additionally, metagenomics on a Synechococcus-

232 associated culture revealed high abundance of TonB-dependent transporters in Muricauda,

233 potentially involved in lipid uptake, and proteins involved in the export of lipids in the

234 proteome of the Synechococcus host (Zheng et al., 2020).

235

236 Finally, we investigated whether specific ASVs were differentially represented between

237 culture types (Prochlorococcus vs Synechococcus). Using indicator species analysis

238 (see Materials and Methods), a method to identify taxa associated with a specific habitat

239 (here either a Synechococcus or Prochlorococcus culture), we found that 20 ASVs were more

240 prevalent among Synechococcus cultures than Prochlorococcus cultures, but only one ASV

241 (a Marinobacter sequence) more prevalent in Prochlorococcus cultures (Table S2). These

242 associations strengthen the possibility that the structure of heterotrophic communities may

243 arise in response to cyanobacterial host-specific secretion of compounds.

244

245 Consistent with there being more indicator species in Synechococcus cultures, community

246 composition was more similar across Synechococcus cultures than Prochlorococcus cultures

247 (as measured by unweighted UniFrac distance at the ASV level (PERMANOVA, p-value <

248 0.01)) (Figure 4A, Figures S3 & S4). Further, heterotroph community composition using the

249 same metric was significantly associated (PERMANOVA, p-value < 0.01) with

250 cyanobacterial ecotype (Figure S4A) and clade (Figure S4C), but there were no discernible

251 patterns in these associations.

252

253 Integrating the dataset with similar studies. To assess the similarity of other

254 phytoplankton-associated microbiomes to those obtained in this study we re-processed - in

255 the context of our dataset – 16S rDNA amplicon sequence data as 97% OTUs (see Materials

256 and Methods) – from published diatom (Behringer et al., 2018) and recently isolated

257 Synechococcus-associated microbial communities (Zheng et al., 2018). Surprisingly, the

258 heterotrophic communities in diatom and Synechococcus cultures each shared almost half the

259 OTUs found in our cultures: 45% (13/29) for the diatoms and 41% (29/70) for the

260 Synechococcus cultures (Table S3, Figure S5). Among these OTUs, 11 were present in

261 cultures of all three groups of phytoplankton, potentially comprising a ‘core’ set of sequence

262 clusters associated with phytoplankton isolates. These include three of the ubiquitous genera

263 (Roseivirga, Maricaulis, and Alteromonas) from this study, which derive from three separate

264 classes (Figure 3C). At a high level, the taxonomic diversity in cultures from A. tamarense

265 and T. pseudonona in a separate study (Fu et al., 2020) exhibited many of the same marine

266 heterotrophs seen here (Figure S6), which suggests a generic selective effect of diverse

267 phytoplankton on their associated microbial communities.

268

269 In contrast to this core of shared bacteria, several additional classes (Acidimicrobiia,

270 Actinobacteria, Planctomycetes class OM190, and Saprospirae) were represented in the

271 Zheng et al. 2018 Synechococcus dataset, but absent from our study; only the class

272 Saprospirae was present in the diatom dataset and absent in ours (Figure S6). Notably, the

273 Actinobacteria from the Synechococcus dataset were only found in isolates from eutrophic

274 waters; by contrast, all except for two (Prochlorococcus SB & Synechococcus WH8017) of

275 the isolates obtained in this study were from oligotrophic waters, while the diatoms of

276 Behringer et al. 2018 were isolated from coastal waters. Further work should examine the

277 extent to which these differences are driven by differences in starting inoculum versus

278 physiological features of the host phytoplankton.

279

280 Relationships between heterotroph community and features of the sample of origin. We

281 examined the extent to which differences in heterotroph communities – here measured at the

282 level of ASVs – in the cultures were related to factors involved in isolation (Table S1).

283 Specifically, we investigated whether the heterotroph composition between all pairs of

284 communities varied with: cruise on which it was isolated, isolation method, sample location

285 and depth, and date the culture was isolated. Each of the tested metadata variables showed a

286 significant association (PERMANOVA, p-value < 0.01) with differences in community

287 composition as measured by unweighted UniFrac distance (a measure of the phylogenetic

288 similarity between two communities), and there were no obvious cases in which the pattern

289 of associations for one variable completely overlapped those for another (Figure 4, Figure S3,

290 Figure S4). Notably, richness (number of ASVs) in the cultures showed no association with

291 any of the tested variables, as previously mentioned for culture age (Wilcoxon Rank Sum

292 Test, p-value > 0.05). In other words, differences in the heterotroph membership of

293 communities (unweighted UniFrac distance) associated with features of the sample of origin

294 did not arise from differences in the total number of heterotroph ASVs (richness).

295

296 While “cruise” itself is not a particularly informative variable on its own, we did see a

297 reproducible tendency for cultures obtained on the same cruise to have similar heterotroph

298 community composition. For example, cultures with names beginning in MIT13 or P13 (i.e.

299 MIT13XX or P13X), were isolated by the same person on the same cruise (HOE-PhoR) in

300 2013 from a depth of 150 m, and include Prochlorococcus from multiple different low light

301 clades (LLIV, LLII/LLIII, and LLVII) (Table S1). They were isolated with a variety of

302 methods including filtration, flow sorting, and dilution-to-extinction. With two exceptions

303 (the LLIV cultures P1344 and MIT1313, the latter of which was dominated by a single

304 heterotroph ASV after flow sorting the Prochlorococcus) from the suite of eight cultures, the

305 MIT13XX and P13X strains clustered together by unweighted UniFrac, suggesting a sensitive

306 dependence of microbial community diversity on the conditions – not solely the physical

307 isolation methodology – under which the culture was first isolated (Figure 4B). These

308 conditions include the initial composition of heterotrophic bacteria in the collected seawater

309 sample, the specific media formulation or light and temperature conditions used for a given

310 enrichment attempt, and the duration of time an enrichment culture had been maintained

311 before derivation of individual algal strains. Together, these factors may drive the

312 observation that cultures obtained from a given cruise frequently share similar communities

313 (seen also with the CoFeMUG and EqPac/IRONEX cruises) (Figure 4B). We think these

314 similarities result from a bottlenecking of community diversity shortly after cultures are

315 sampled and phytoplankton are enriched.

316

317 To look into the effects of potential bottlenecking during the initial culturing phase, we

318 examined the relationship between culture composition and physical isolation methods

319 (Figure 4C). We see a tendency for cultures obtained using only filtration (not accompanied

320 by dilution-to-extinction or flow sorting) to be more similar in heterotroph composition to

321 each other than cultures also subjected to dilution-to-extinction or flow sorting (Figure 4C).

322 Again, however, communities tended to cluster more by the corresponding cruise than by

323 isolation method. These findings suggest that stochastic loss of heterotrophs that might occur

324 by dilution-to-extinction reduces the structural convergence of heterotroph communities.

325

326 Finally, heterotroph community composition in the cultures differs by collection depth

327 (Figure 4D). For example, cultures isolated from 0-50 m and 50-100 m tend to cluster more

328 tightly with each other than cultures isolated from 100-150 m and 150-200 m, consistent with

329 the idea that community composition of heterotrophs varies with depth (Agogué et al., 2011;

330 DeLong et al., 2006; Giovannoni & Stingl, 2005). This finding is not surprising given that

331 light and nutrient gradients in the water column lead to more complex biogeochemical

332 regimes – and hence a gradient in dissolved organic carbon compounds (Hansell & Carlson,

333 2001b, 2001a) from the surface.

334

335 In conducting the above analyses, we note that some of these variables are not independent

336 (e.g. because ecotype depends on clade; or because strains were only isolated from one depth

337 or one ecotype was isolated on a given cruise), so associations may arise from

338 interdependencies between factors (Figure S7). These interdependencies may lead to

339 associations with multiple variables which could be explained by a single variable. However,

340 the overall trends show a clear linkage between initial conditions of culture isolation and the

341 long-term composition of the culture.

342

343 Comparison of cultured communities to distributions of their members in the wild.

344 Because all of the cultures are sourced from seawater samples, we wanted to determine how

345 heterotrophs present in cultures were represented in the global oceans. We used the

346 bioGEOTRACES metagenomics dataset, which spans 610 samples over time and at multiple

347 depths in locations throughout the Atlantic and Pacific Oceans (Biller, Berube, et al., 2018) to

348 examine the spatial distributions of heterotroph communities present in our cyanobacterial

349 cultures (Figure 5). We obtained reads mapping to the V4 region of the 16S gene, and

350 clustered the ASVs from our culture collection with the global oceans data at 97% similarity

351 (i.e. 97% OTUs) to accommodate differences in the nature of the data and processing (see

352 Materials and Methods for details). The heterotrophs that dominate global ocean datasets

353 (primarily belonging to the Pelagibacteraceae within the Pelagibacterales) are not well

354 represented in our cultures (Figure 5B, Figure S8). This absence is not surprising as simply

355 culturing oligotrophs like SAR11 is extremely challenging (Button, 1991; Carini et al., 2013;

356 Cho & Giovannoni, 2004); thus, we expected that the high nutrient concentrations and

357 periodic dilution of cells from culture transfers would enrich for opportunistic copiotrophic

358 organisms.

359

360 We next asked how well the prevalent OTUs in cultures were represented in the

361 bioGEOTRACES database. While a few OTUs were readily detected at most sites (Figure

362 5C, Figure S8), this was not the general tendency; most that were prevalent in the cultures

363 were rare or sparsely detectable in the wild (Figure 5C). Of the OTUs that dominated in

364 culture, cosmopolitan OTUs included those classified as Maricaulis, Alteromonodaceae, and

365 Rhodobacteraceae, while unclassified Gammaproteobacteria, Alcanivorax, and Marinobacter

366 were intermediately distributed OTUs present in several sites. Finally, OTUs in the genera

367 Muricauda, Thalassospira, and Hyphomonas were generally sparse or absent across the

368 bioGEOTRACES sites (Figure 5C).

369

370 The sparsity of these organisms in the global oceans coupled with their prevalence in cultures

371 of Prochlorococcus and Synechococcus suggests that they are selected for by the rich culture

372 conditions – conditions that must be patchily distributed in the oceans. As an example, the

373 genus Muricauda (family Flavobacteriaceae), which had an OTU well-represented in

374 cultures, but sparsely detectable in bioGEOTRACES (Figure 5C), is known to be particle-

375 associated, potentially specializing in degradation of high molecular weight organic

376 compounds (Enke et al., 2019). Across all cultures in this study, more heterotroph OTUs in

377 culture were shared with bioGEOTRACES samples taken below the epipelagic zone (>200

378 m) than above (0.3% of OTUs above versus 0.64% below, Fisher Exact Test p-value = 1e-4).

379 The increase in OTUs shared with cultures at depth might be because of the reliance of

380 heterotrophs on organic carbon as a source of energy in both systems.

381

382 Given the cosmopolitan distribution of some of the prevalent culture OTUs in

383 bioGEOTRACES, we expected that they might be positively correlated with

384 picocyanobacterial abundance along the transects. Indeed, we find that across the

385 bioGEOTRACES sites, there is a strong relationship (Spearman’s rho = 0.302, p-value = 0)

386 between the abundance of the Rhodobacteraceae OTU, which is ubiquitous in cultures, and

387 the combined abundance of Prochlorococcus and Synechococcus. Notably, none of the other

388 prevalent culture OTUs showed this relationship, suggesting that this OTU in particular may

389 be coupled to the dynamics of these cyanobacteria in oceans (Table S4). Further laboratory

390 investigations of the interactions of these ubiquitous bacteria with marine picocyanobacteria

391 should reveal interesting and relevant exchanges of matter and energy in the global oceans.

392

393 CONCLUSIONS AND FUTURE DIRECTIONS

394

395 Although the culture collection being analyzed here was not designed with this study in mind,

396 there are some generalizations we can extract from the heterotrophic “bycatch” that was

397 selected for in the enrichment cultures, which may help guide experiments designed to

398 unravel the co-dependencies in these micro-communities. First, as expected from their

399 obligate oligotrophy, the heterotrophs that numerically dominate the open ocean habitats are

400 not present in these xenic cultures. For most of them, including the abundant SAR11 group,

401 high organic carbon conditions present an obstacle (Button, 1991; Cho & Giovannoni, 2004)

402 and hence developing a defined medium for their growth was a challenge (Carini et al.,

403 2013). Although we designed a medium that sustains co-cultures of SAR11 and

404 Prochlorococcus in log phase (Becker et al., 2019), SAR11 dies precipitously when

405 Prochlorococcus enters stationary phase, suggesting that strict oligotrophs may not be able to

406 tolerate the accumulation of substrates that occur during Prochlorococcus growth – a feature

407 that would have eliminated them in the initial stages of isolating the cyanobacterial strains in

408 our culture collection. This challenge during stationary phase might derive from deleterious

409 effects of high nutrient concentrations on streamlined cellular physiology, with oligotrophs

410 unable to regulate transport rates in the face of high nutrient concentrations (Braakman et al.,

411 2017).

412

413 The absence of oligotrophs in the enrichment cultures is in striking contrast to the presence of

414 the numerous copiotrophic heterotrophic strains that thrive in these cultures (this study, and

415 (Aharonovich & Sher, 2016, 2016; Biller, Coe, et al., 2018; Biller et al., 2016; Morris et al.,

416 2008; Sher et al., 2011)) and even “bloom” when Prochlorococcus reaches stationary phase

417 (Becker et al., 2019). Studies of heterotrophic community dynamics in cultures over the

418 course of the exponential and sustained stationary-phase growth (Zheng et al., 2020) have

419 revealed shifts in heterotrophic abundances according to their differential capacities to utilize

420 high- and low-molecular weight dissolved organic compounds. Further work as in that study

421 will enable detailed linkage between functional genes in heterotrophic bacteria for

422 metabolism of cyanobacteria-derived photosynthate and the dynamics of these functions in

423 the global oceans.

424

425 Interestingly, most of the heterotrophic strains that are widespread among the cultures are not

426 very abundant in the wild. These copiotrophs appear to thrive on high concentrations of

427 organic compounds experienced in culture – an environment that must be patchily distributed

428 in the open ocean habitat (Stocker, 2012). While it is likely that individual phytoplankton can

429 selectively permit the growth of particular heterotrophic bacteria, the sharing of over 40% of

430 OTUs between our dataset and each of the other phytoplankton datasets explored here

431 suggests that phytoplankton may modify their environments in similar ways that lead to

432 conservation of bacterial groups across cultures. It is possible that ubiquitous heterotrophic

433 bacteria in cultures are similar to “broad-range taxa” that process simple metabolic

434 intermediates (Enke et al., 2019), and thus grow on compounds that are released as generic

435 byproducts of phytoplankton growth. Indeed, such compounds are likely abundant on nutrient

436 rich particles, or ephemeral patches of high organic carbon in the phycosphere of larger

437 phytoplankton (Seymour et al., 2017; Stocker, 2012; Thornton, 2014).

438

439 Clearly, to understand the metabolic exchanges between picocyanobacteria and oligotrophic

440 heterotrophs we will have to isolate sympatric strains from the same location. In contrast to

441 standard enrichment approaches, which appear to favor the growth of fast-growing,

442 phycosphere-enriched bacteria, using dilution-to-extinction techniques and low nutrient

443 media is likely to yield more of the abundant, free-living bacteria characteristic of the

444 oligotrophic oceans. Like all challenges with these microorganisms, it is only a matter of time

445 and effort.

446

447

448

449

450 MATERIALS AND METHODS

451

452 Culture maintenance. Previously isolated Synechococcus and Prochlorococcus from sites

453 spanning the global oceans (Table S1) are maintained by serial passage in natural seawater

454 medium amended with Pro99 nutrients (800 uM N, 50 uM P, trace metals, no added carbon)

455 under low light intensity (~10 µmol photons m-2 s-1) in continuous light or a 13:11 light:dark

456 incubator (Moore et al., 2007). Prior to DNA extractions, cultures were grown until mid-

457 exponential growth phase to increase the comparability of the communities across all

458 cultures.

459

460 Describing the cyanobacteria-associated microbial community composition. We used

461 amplicon sequence variants (hereafter ASVs) of 16S rDNA as our marker. We analyzed the

462 composition of the community of heterotrophs in our isolates when harvested in mid-

463 exponential growth. To this end, we inoculated maintenance cultures (n=74) into fresh

464 medium and allowed them to grow until mid-exponential growth before collecting cells by

465 centrifugation for preparation of 16S rDNA libraries. Sequence libraries had an average depth

466 of 113,602 (min: 72,369) reads after quality filtering, and in most samples, reads derived

467 predominately from the cyanobacterial host (Synechococcus or Prochlorococcus). For the

468 purposes of characterizing the associated community, we excluded reads derived from

469 Prochlorococcus or Synechococcus in downstream analyses. The cultures contained a median

470 of 11 ASVs (range 1-23) that were at or above an abundance of 0.2%, and a median of 16

471 ASVs estimated by rarefaction (range 3-31) (Figure 1B). We do not make quantitative claims

472 about the abundances of ASVs in samples because of the dependence of heterotroph

473 abundance on cyanobacterial growth state (Becker et al., 2019; Zheng et al., 2018) and biases

474 in amplicon sequence data (Polz & Cavanaugh, 1998); we instead focus on the distribution of

475 observed ASVs, and higher order taxonomic classifications across the cultures.

476

477 Sequence generation and processing. DNA samples were prepared by pelleting 5 mL of

478 exponentially growing cultures by centrifugation at 8,000 x g for 15 min. DNA was extracted

479 using the DNeasy Blood & Tissue Kit (QIAGEN Cat No. 69504) following manufacturer

480 instructions. The V4 region of the 16S rRNA gene was amplified using the 515F-Y (5’-

481 GTGYCAGCMGCCGCGGTAA-3’) and 926R (5’-CCGYCAATTYMTTTRAGTT-3’)

482 primers (Parada et al., 2016), and sequencing libraries prepared in duplicate before pooling

483 using a two-step protocol described previously (25), with the exception of the MED4,

484 NATL2A, and MIT9313 cultures from 2018, which used the same two-step protocol, but

485 were generated in a different sequencing run using 515F (5’-

486 GTGCCAGCMGCCGCGGTAA-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’)

487 primers (Preheim et al., 2013). The libraries were sequenced on an Illumina MiSeq (Illumina,

488 San Diego, CA, USA) platform, using 250 bp paired-end reads (except for the 2018 MED4,

489 NATL2A, and MIT9313 cultures, which used 150 bp paired-end reads). The fastq sequence

490 data files were processed to generate a table of amplicon sequence variants (ASVs) using

491 DADA2 in R (Callahan et al., 2016), with the parameters for each dataset specified in the

492 corresponding R script (https://github.com/microbetrainer/Heterotrophs).

493

494 Mock community construction for sequencing validation. We extracted DNA as described

495 previously from eleven bacteria with distinct V4 16S regions: axenic cultures of

496 Prochlorococcus strains MED4, NATL2A, MIT9313, and MIT9312; Synechococcus strains

497 WH7803, and WH8102; Polaribacter MED152, Alteromonas macleodii MIT1002, and three

498 other heterotrophic bacteria. We amplified the full 16S gene using the primers 27F 5’-

499 AGAGTTTGATCMTGGCTCAG-3’ and 1492R 5’-GGTTACCTTGTTACGACTT-3’,

500 verified the 16S sequence by Sanger sequencing (Eton Bioscience, Inc. San Diego, CA,

501 USA), then cloned the 16S gene from each culture using the Zero BluntTM TOPOTM PCR

502 Cloning Kit (ThermoFisher Cat #450245). The resulting plasmids were combined either in

503 equimolar concentrations or in a 2-fold dilution series (with the most concentrated 16S 1024x

504 more concentrated than the least) with three technical replicates, which were included as

505 samples in 16S DNA library preparation.

506

507 16S amplicon sequence data analysis. In order to limit the extent to which we were

508 measuring contaminating PCR products from adjacent wells, we excluded ASVs that had

509 anomalously low abundance in one well given its abundance in an adjacent well. Because this

510 approach is conservative (and likely removing true positive ASVs), it will have the tendency

511 to deflate the estimates of taxonomic richness within a sample. We applied the following

512 filter: if the relative abundance of an ASV in a specified well was less than one-tenth that of

513 the maximum relative abundance in an adjacent well on the 96-well plate, the relative

514 abundance of the ASV in the specified well was set to 0. Based on analysis of the mock

515 community data, we found no contaminating sequences at a relative abundance of more than

516 0.002, thus, sequences were excluded from a sample if they had a relative abundance lower

517 than 0.002. This cutoff tends to be conservative, as rarefaction analysis retained more ASVs

518 per sample overall. For all analyses not involving OTU clustering, the sequences were

519 trimmed to the same length. The sequences were imported to Qiime2 (Bolyen et al., 2019),

520 where they were de-replicated using VSEARCH (Rognes et al., 2016) and assigned

521 taxonomies using the gg-13-8-99-nb-classifier (Caporaso et al., 2010; DeSantis et al., 2006).

522 Using fasttree (Price et al., 2010) and mafft alignment (Katoh & Standley, 2013) within

523 Qiime2, phylogeny of the non-Prochlorococcus, non-Synechococcus ASVs was created.

524

525 Comparative analysis of diatom & Synechococcus culture datasets. We compared sequences

526 identified in this study to sequences found in newly isolated Synechococcus. cultures (Zheng

527 et al., 2018) and sequences isolated from the phycosphere of diatoms in culture (Behringer et

528 al., 2018). The Synechococcus study (Zheng et al., 2018) used 520F (5′-

529 AYTGGGYDTAAAGNG-3′) and 802R (5′-TACNVGGGTATCTAATCC-3′) for 16S data

530 generation and the second study uses 515F (5′-GTGYCAGCMGCCGCGGTAA-3′) and

531 786R (5′-GGACTACNVGGGTWTCTAAT-3′). Both sets of primers produce sequences that

532 are nested inside those generated in this study (515Y-F, 926R). The diatom dataset contained

533 microbial communities measured over time in cultures of four strains of Asterionellopsis

534 glacialis and three strains of Nitzschia longissima. We included the initial measurements of

535 microbial communities from nine new Synechococcus isolates, four from oligotrophic waters

536 and five from eutrophic waters. For this analysis, we clustered at 97% identity (hereafter,

537 OTUs) due to differences in the generation of the amplicon data in the published studies. The

538 sequences from both studies were processed in DADA2 to produce a table of ASVs, with the

539 parameters specified in the corresponding R script

540 (https://github.com/microbetrainer/Heterotrophs). We did not trim ASVs from these three

541 datasets to the same length. We excluded ASVs that were identified as either mitochondria or

542 chloroplast from analysis, and excluded ASVs from a sample if they had a relative abundance

543 less than 0.002. In Qiime2 (Bolyen et al., 2019), the ASVs were clustered at 97% identity

544 using VSEARCH (Rognes et al., 2016), and the taxonomy of each cluster was assigned using

545 the gg-13-8-99-nb-classifier (Caporaso et al., 2010; DeSantis et al., 2006). The samples were

546 clustered using Ward’s method of hierarchical clustering on the unweighted UniFrac distance

547 at the 97% OTU level (Lozupone & Knight, 2005) calculated with the phyloseq package in R

548 (McMurdie & Holmes, 2013).

549

550 BioGEOTRACES comparisons. Reads mapping to the V4 region of the 16S gene between the

551 515F-Y and 926R priming regions were obtained from bioGEOTRACES metagenomes

552 (Biller, Berube, et al., 2018) courtesy of Jesse McNichol (data and code can be found at

553 https://osf.io/n5ftw/). Without trimming the ASVs to the same length, the bioGEOTRACES

554 and culture ASVs were imported to Qiime2. Within Qiime2, the sequences were dereplicated

555 and clustered at 97% identity with VSEARCH. The OTUs were then assigned taxonomies

556 using the gg-13-8-99-nb-classifier and represented on maps using the accompanying

557 bioGEOTRACES metadata.

558

559 Comparison of 2018 and 2019 heterotroph communities. The cultures described in this study

560 were sampled in the summer of 2019. The non-axenic cultures of Prochlorococcus MED4,

561 MIT9313, and NATL2A were sampled in 2018 and again in 2019. To investigate whether the

562 composition of heterotrophs changed over this period, we compared the ASVs in these

563 cultures sampled over time. Using DADA2, we trimmed the primers (the first 20 bases) from

564 the reads from the 2018 samples, as quality decreased at this point in the sequences. We

565 trimmed the ASVs from the two sources to the same length. For both datasets, ASVs were

566 excluded from a sample if they had a relative abundance less than 0.002. In Qiime2, the

567 ASVs were de-replicated across the two datasets using VSEARCH and assigned taxonomies

568 using the gg-13-8-99-nb-classifier. Within Qiime2, fasttree, and mafft were used to create a

569 phylogeny of the non-Prochlorococcus, non-Synechococcus ASVs. The abundance of each

570 ASV in each sample was normalized by the number of Prochlorococcus sequences in the

571 sample. The Spearman correlation between each pair of samples was calculated based on the

572 abundance of each non-Prochlorococcus ASV normalized by the number of Prochlorococcus

573 reads.

574

575 Accession numbers. The 16S rDNA sequence data from this study were deposited in the

576 NCBI Sequence Read Archive under BioProject ID PRJNA607777.

577

578 ACKNOWLEDGMENTS

579 This work was funded by grants from the Simons Foundation (Life Sciences Project Award

580 ID 337262, S.W.C.; SCOPE Award ID 329108, S.W.C.). S.M.K is funded by the Simons

581 Foundation Fellowship in Marine Microbial Ecology. Jesse McNichol graciously shared the

582 data for reads mapping to the V4 region of the 16S gene from bioGEOTRACES and HOT

583 and BATS. We thank Dave VanInsberghe and the Polz lab for the 16S amplicon sequencing

584 of the three Prochlorococcus cultures from 2018. We thank everyone who has contributed to

585 this work through the isolation and maintenance of Prochlorococcus and Synechococcus

586 cultures. Specific contributors are listed as “Isolators” in Table S1. We thank Fatima Hussain,

587 Paul Berube, and Nikolai Radzinski for critical reading of the manuscript.

588

589 CRediT taxonomy for author contributions

590 Conceptualization, S.M.K., A.C., S.W.C.; Methodology, S.M.K., E.T., A.C.; Software,

591 S.M.K., E.T.; Validation, S.M.K., E.T., A.C.; Formal Analysis, S.M.K., E.T.; Investigation,

592 S.M.K., E.T., A.C.; Resources, S.M.K., A.C., S.W.C; Data Curation, S.M.K., E.T.; Writing –

593 Original Draft, S.M.K.; Writing – Review & Editing, S.M.K., E.T., A.C., S.W.C;

594 Visualization, S.M.K., E.T.; Supervision, S.M.K., A.C; Project Administration S.M.K., A.C.;

595 Funding Acquisition, S.M.K., S.W.C.

596

597

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971 FIGURES 972

973 974 Figure 1. Microbial diversity in enrichment cultures from the global oceans. (A) Origin of 975 Prochlorococccus and Synechococcus cultures obtained over several decades and maintained 976 in serial transfer batch cultures for 100s – 1000s of generations. The size of each point on the 977 map represents the number of cultures obtained from a given location. For date and methods 978 of isolation see Table S1. (B) Richness of heterotrophic bacteria measured by the number of 979 amplicon sequence variants (ASVs) exceeding a threshold relative abundance of 0.2% in 980 Prochlorococcus (green) and Synechococcus (magenta) cultures. Richness is organized by 981 the phylogeny of host organisms (built using the 16S-23S intertranscribed spacer (ITS) 982 sequence, and collapsed to indicate monophyletic groups) indicated along the bottom. HL 983 (high light) and LL (low light) designations in the triangles refer to light-adaptation features 984 of Prochlorococcus ecotypes, as reviewed in (Biller et al., 2014), and 5.1a and 5.1b refer to 985 subclusters of Synechococcus group 5.1 (Ahlgren & Rocap, 2012). Colored boxes above each 986 culture name indicate the years between when the culture was isolated and this analysis, as 987 specified by the color bar in the upper left-hand corner.

988

989 990 Figure 2. Composition of heterotroph communities, as defined by class membership of 991 ASVs, in long-term cultures of Prochlorococcus and Synechococcus hosts (tree on the left as 992 defined in Figure 1). The heterotroph communities in each culture are arranged using the 993 phylogenetic tree of the host cyanobacterium based on the ITS sequence and collapsed into 994 monophyletic groups as in Figure 1B. Relative abundance of heterotrophic community 995 members, by class, is shown to the right of each strain name. To view the same data by 996 hierarchical clustering see Figure S2. 997

998 999 Figure 3. Proportion of cultures of either Prochlorococcus (green) or Synechococcus 1000 (magenta) containing ASVs belonging to a given bacterial (A) phylum, (B) class, or (C) 1001 genus (restricted to genera found in at least six cultures). Note that HTCC is listed in the 1002 Greengenes taxonomy, but is not formally recognized as a bacterial genus. 1003

1004 1005 Figure 4. Ordination of heterotroph community composition at the ASV level overlaid with 1006 metadata pertaining to conditions of isolation of enrichment cultures. Non-metric 1007 multidimensional scaling (NMDS) of heterotroph communities using unweighted UniFrac as 1008 the distance metric overlaid with (A) the host cyanobacterium genus in the enrichment 1009 culture, (B) the cruise name from which the culture was isolated, (C) the isolation method 1010 (pre-filtered to exclude larger cells, pre-filtered and sorted via flow cytometry, pre-filtered 1011 and diluted-to-extinction (DTE), not filtered and sorted via flow cytometry, or cloned from a 1012 mother culture), and (D) the depth of the seawater sample. The closeness of two points in 1013 NMDS space reflects the distance between communities, with communities having more 1014 similar phylogenetic structure (as measured by unweighted UniFrac) grouping more closely 1015 together. Heterotroph communities for which metadata was not known are indicated as NAs. 1016 See also Figures S3, and S4 for relationships between community structure and ecotype, 1017 clade, isolation location, and culture age. 1018

1019 1020 Figure 5. Representation of picocyanobacterial enrichment culture heterotrophic bacterial 1021 OTUs in global ocean surveys. (A) Location of the sampling sites of the bioGEOTRACES 1022 expeditions. (B) Example of a heterotrophic OTU (in the family Pelagibacteraceae) abundant 1023 in bioGEOTRACES, but absent from cultures. (C) Distribution of the most ubiquitous OTUs 1024 in cultures across the bioGEOTRACES sites. Such OTUs were present in almost all 1025 bioGEOTRACES sites (Cosmopolitan), some sites (Intermediate), or only a few sites 1026 (Sparse). Scale bar indicates the log10 relative abundance (number of reads normalized by 1027 number of non-Prochlorococcus, non-Synechococcus reads) at a given site. See also Figure 1028 S8 for the distribution of some OTUs abundant in bioGEOTRACES, but not prevalent in 1029 culture. 1030

1031 SUPPLEMENTARY FIGURES

1032 1033 Figure S1. Stability of heterotroph community composition in three cultures sampled one 1034 year apart. (A) The Prochlorococcus-normalized relative abundance (indicated by the color 1035 bar) of each of the heterotroph ASVs is shown in the heatmap for each of three 1036 cyanobacterial enrichment cultures (Prochlorococcus strains MED4, MIT9313, and 1037 NATL2A) sampled once in 2018 and again in 2019 for amplicon sequencing. The 1038 phylogenetic tree on the left is based on the heterotroph ASV sequences. (B) The Spearman 1039 correlation (comparing the correspondence in rank) of relative abundance of heterotroph 1040 ASVs is indicated by the color bar.

1041 1042 Figure S2. Composition of heterotroph communities, as defined by class membership of 1043 ASVs, in long-term cultures of Prochlorococcus (green) and Synechococcus (magenta) hosts. 1044 This is the same data as depicted in Fig. 2, but here the heterotroph communities in each 1045 culture are arranged using Ward’s method of hierarchical clustering with unweighted UniFrac 1046 on ASVs as the distance metric to emphasize the relationships between communities. 1047 Relative abundance of heterotrophic community members, by class, is shown to the right of 1048 each strain name. 1049

1050 1051 1052

1053 1054 Figure S3. Mapping of cultures onto ordination plots labeled to indicate the position of each 1055 cyanobacterial host’s community at the ASV level in the ordination plots from Figure 4 and 1056 Figure S4. Non-metric multidimensional scaling (NMDS) of heterotroph communities using 1057 unweighted UniFrac as the distance metric. Each point in the NMDS plot represents a single 1058 heterotroph community associated with the given cyanobacterial host indicated in the name. 1059 The closeness of two points in NMDS space reflects the distance between communities, with 1060 communities having more similar phylogenetic structure (as measured by unweighted 1061 UniFrac) grouping more closely together. 1062

1063

1064 1065 Figure S4. Ordination of heterotroph community composition at the ASV level overlaid with 1066 enrichment culture metadata. Non-metric multidimensional scaling (NMDS) of heterotroph 1067 communities using unweighted UniFrac as the distance metric overlaid with (A) 1068 cyanobacterial ecotype, (B) isolation location, (C) cyanobacterial clade, and (D) culture age. 1069 The closeness of two points in NMDS space reflects the distance between communities, with 1070 communities having more similar phylogenetic structure (as measured by unweighted 1071 UniFrac) grouping more closely together. Heterotroph communities for which metadata was 1072 not known are indicated as NAs. See also Figure 4, and Figures S3 and S7. 1073

1074 1075

1076 1077 1078 Figure S5. Venn diagram showing the number of OTUs shared in heterotroph communities 1079 from diatoms (Behringer et al., 2018) and Synechococcus (Zheng et al., 2018) compared to 1080 the Prochlorococcus and Synechococcus in this study. The area of the ellipses is not to scale 1081 with the number of OTUs. 1082

1083 1084 Figure S6 Heterotroph communities accompanying diatoms (dark blue) (Behringer et al., 1085 2018) and Synechococcus (orange) in culture for less than a year (Zheng et al., 2018) 1086 compared to this study (green (Prochlorococcus) and magenta (Synechococcus)) with 1087 cultures over 5 years old. Bacterial classes are indicated by the colors in the legend, and 1088 relative abundance of each class in the heterotroph community of the corresponding culture is 1089 shown. Heterotroph communities in each cyanobacterial culture (vertical axis) are organized 1090 by the hierarchical clustering tree on the left using Ward’s method of hierarchical clustering 1091 with unweighted UniFrac as the distance metric on 97% OTUs. See also Figure 2 and Figure 1092 S2. 1093

1094

1095 1096 Figure S7 Associations between metadata pertaining to isolation or host phylogeny of 1097 enrichment cultures. The pairwise association between each variable indicated on the vertical 1098 and horizontal axes were calculated using an asymmetric measure of association, Goodman 1099 and Kruskal’s τ, ranging from 0 to 1. A τ of 1 indicates that there is a perfect correspondence 1100 between the levels in one variable and the record index. For instance, the clade has a τ of 1 1101 with ecotype because clades are perfectly nested within ecotypes (that is, identification of the 1102 clade is sufficient to identify the ecotype). Because of the asymmetry in the metric, ecotype 1103 has a τ less than 1, but greater than 0 with the clade; ecotype only constrains identification of 1104 clades, but does not perfectly determine them. 1105 See also Figures 4, S3, and S4. 1106 1107

1108

1109 1110 Figure S8. (A) Top two most abundant OTUs in bioGEOTRACES; these OTUs are not 1111 present in cyanobacterial cultures. (B) Top two most abundant OTUs (distinct unclassified 1112 OTUs in the family Rhodoobacteraceae) in bioGEOTRACES that are also present in the 1113 cyanobacterial cultures. Scale bar indicates the log10 relative abundance (number of reads 1114 normalized by number of non-Prochlorococcus, non-Synechococcus reads) at a given site. 1115 Related to Figure 5. 1116 1117 1118