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Determinants of synergistic cell-cell interactions in bacteria

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DOI: 10.1515/hsz-2022-0303

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1 Determinants of synergistic cell-cell interactions in bacteria

3 Benedikt Pauli1‡, Shiksha Ajmera1‡, Christian Kost1,2*

1
5 Department of Ecology, School of Biology/Chemistry, Osnabrück University, 49076

6 Osnabrück, Germany

2
7 Center of Cellular Nanoanalytics (CellNanOs), Osnabrück University, Barbarastrasse

8 11, 49076 Osnabrück, Germany

‡
10 These authors contributed equally to this work.

11 * For correspondence: christiankost@gmail.com

12

13 Running title

14 Determinants of synergistic bacterial interactions

15

16

17

18

19

20

21

1
22 Abstract

23 Bacteria are ubiquitous and colonize virtually every conceivable habitat on earth. To

24 achieve this, bacteria require different metabolites and biochemical capabilities. Rather

25 than trying to produce all of the needed materials by themselves, bacteria have evolved

26 a range of synergistic interactions, in which they exchange different commodities with

27 other members of their local community. While it is widely acknowledged that

28 synergistic interactions are key to the ecology of both individual bacteria and entire

29 microbial communities, the factors determining their establishment remain poorly

30 understood. Here we provide a comprehensive overview over our current knowledge

31 on the determinants of positive cell-cell interactions among bacteria. Taking a holistic

32 approach, we review the literature on the molecular mechanisms bacteria use to

33 transfer commodities between bacterial cells and discuss to which extent these

34 mechanisms favour or constrain the successful establishment of synergistic cell-cell

35 interactions. In addition, we analyse how these different processes affect the specificity

36 among interaction partners. By drawing together evidence from different disciplines

37 that study the focal question on different levels of organisation, this work not only

38 summarizes the state of the art in this exciting field of research, but also identifies new

39 avenues for future research.

40

41

42 Keywords

43 Co-aggregation; cooperation; cross-feeding; partner specificity; synergistic interaction

44

45

2
46 Introduction

47 Microbial communities are ubiquitous on our planet and play significant ecological roles

48 – for examples as drivers of global biogeochemical cycles or as symbionts of animals

49 and plants (Strickland et al. 2009; Delgado-Baquerizo et al. 2016; Valdes et al. 2018;

50 Vijay and Valdes 2022). These vital functions typically emerge from ecological

51 interactions among different species that exist within taxonomically diverse microbiota

52 (Wagg et al. 2021). Thus, understanding the mechanisms that shape the

53 establishment, stability, and functioning of microbial communities requires knowledge

54 of the underlying ecological interactions.

55 The tremendous diversity of different ecological interactions that can be

56 observed within microbial communities is generally classified into antagonistic or

57 synergistic interactions. Antagonistic interactions include all of those cases, in which

58 bacteria harm or kill other bacteria in their vicinity in order to gain a competitive

59 advantage. In contrast, in synergistic interactions, bacteria benefit from the intentional

60 or unwitting behaviour of another individual in their local environment. Antagonistic

61 interactions are generally well understood both in terms of the causal molecular

62 mechanisms (Alteri and Mobley 2016; Peterson et al. 2020) and their eco-evolutionary

63 causes and consequences (Ghoul and Mitri 2016; Granato and Foster 2020; Niehus

64 et al. 2021). However, synergistic interactions have only recently started to move into

65 the focus of attention of a broader research community. The pattern that has started to

66 emerge from applying different methodological approaches is that synergistic

67 interactions are not only highly diverse in form and function, but also that they rely on

68 intimate interactions among bacterial cells. However, what determines the

69 establishment of synergistic interaction among bacterial cells? Do the interactions we

70 see in microbial communities result from rather random encounters between cells or

3
71 are there certain rules that structure the emergence and functioning of synergistic

72 interactions within microbial communities? Here we address these issues by drawing

73 together the recent literature on this topic. Taking a holistic approach, we begin by

74 reviewing the different kinds of benefits bacteria exchange in synergistic interactions.

75 After that we analyse which mechanisms bacteria use to exchange benefits between

76 cells, and how the mechanistic nature of the interaction impacts the ecological and

77 evolutionary dynamics within these interactions. By comprehensively summarizing our

78 current knowledge on the factors that determine synergistic cell-cell interactions, this

79 work shall not only provide an overview over this exciting field of research, but also

80 highlight the gaps in our knowledge that can guide the design of future studies.

81

82 Benefits of synergistic cell-cell interaction

83 Synergistic interactions between bacteria of the same or different species are

84 widespread in nature and include a broad range of goods that are exchanged between

85 interacting partners. To provide an overview over the enormous diversity of materials

86 or services that bacteria exchange as part of a synergistic interaction, we classify them

87 into four main categories that are based on the type of exchanged commodity as well

88 as the way this good benefits the receiving cell. The four different types of exchanged

89 goods include: (I) metabolites, (II) energy, (III) services, and (IV) information (Figure

90 1). In the following, we discuss each of these categories.

91 The first and probably most important kind of good that is exchanged among

92 bacteria are metabolites (Figure 1). In a process generally referred to as cross-feeding,

93 bacteria transfer substances between cells that derive from the primary or secondary

94 metabolism (Lilja and Johnson 2016; Pacheco et al. 2019; Fritts et al. 2021) and which

95 benefit the receiving cell. These metabolites can either be useful to the donor cell itself

4
96 (e.g. vitamins) or be metabolic byproducts that are released by the donor cell and which

97 can be metabolized by the recipient (e.g. sequential degradation of complex substrates

98 (Odom and Wall 1983)). The exchanged compounds can serve as metabolic building

99 blocks (e.g. amino acids, nucleotides) or be used as a source of energy by the recipient

100 (Supplementary Table 1). This is in contrast to metabolites that are produced to induce

101 a certain response in the receiver (i.e. signalling molecules; see ‘information exchange’

102 below).

103

Building block Dispersal

104
metabolites
Protection
Metabolites Services
Energy
105 sources Metabolic
Benefits capabilities
of synergistic
interactions i Genetic
106 Redox species material
Energy Information Chemical
107 Electrons signals/ cues

108 Figure 1: Types of benefits bacteria exchange in synergistic interactions.

109

110 Besides metabolites, bacteria can also exchange electrons as a form of non-

111 material energy between cells (Figure 1, Table 1, Supplementary Table 1). This can

112 be achieved by shuttling redox compounds such as H2 or formate via diffusion through

113 the extracellular environment from electron-donating to electron-accepting cells

114 (Stams et al. 2006; Stams and Plugge 2009; Shi et al. 2016). Alternatively, a transfer

115 of electrons can be mediated by a direct physical contact of cell surfaces between

116 interacting cells (Jiang et al. 2018; Meysman et al. 2019) or via long (µm-cm range)

117 electrical connections between cells (Summers et al. 2010; Shi et al. 2016; Walker et

118 al. 2020). The latter includes (i) electrically conductive nanowires that are formed by

119

5
120 Table 1: Mechanisms bacteria use to transfer synergistic benefits between bacterial cells. Both
121 the commodity (i.e. M = metabolites, E = electrons, S = services, and I = information) that has been
122 shown to be exchanged using the different mechanisms and whether the exchange has been observed
123 within members of the same or different species is indicated (- = no example found, + = few cases found
124 (< 50% of examples), ++ = many cases found (>50%)).

Transfer Commodity Within Between References

mechanism species species
Passive diffusion M, E, S, I Abisado et al. 2018; Bernier et al.
+ ++ 2011; Pacheco et al. 2019; van
Tatenhove-Pel et al. 2021; Sher et al.
2011; Grandclement et al. 2016;
Harcombe et al. 2014; Bridges and
Bassler 2019
Active transport M, E, S, I Abisado et al. 2018; Sokolovskaya et
+ ++ al. 2020; Butaite et al. 2021;
Grandclement et al. 2016
Vesicle exchange M, I Woith et al. 2019; Toyofuku et al.
+ + 2017; Berleman et al. 2014;
Schwechheimer and Kuehn 2015;
Brown et al. 2015; Biller et al. 2014;
Kim et al. 2015
Vesicle chains M, I Remis et al. 2014; Pirbadian et al.
++ - 2014; Berleman et al. 2014

Nanowires E Shi et al. 2016; Summers et al. 2010;

+ + Wang et al. 2019; Wegener et al.
2015; Pirbadian et al. 2014
Nanotubes M, I Shi et al. 2016; Dubey and Ben-
+ ++ Yehuda 2011; Dubey et al. 2016;
Pande et al. 2015; John et al. 2017
Pili M, E, I Shi et al. 2016; Walker et al. 2020;
+ ++ Virolle et al. 2020; Wang et al. 2005

Flagella S Muok et al. 2021; Marx 2009; Ishii et

- ++ al. 2005; Shimoyama et al. 2009;
Friedlander et al. 2013
Cell-cell M, E, S, I Shi et al. 2016; Drescher et al. 2014;
attachment
++ + van Tatenhove-Pel et al. 2021;
Benomar et al. 2015; Sah and Wall
2020; Pande et al. 2016; Marchal et
al. 2017; Cao et al. 2015; Kim et al.
2008; Nadell et al. 2016; Hobley et
al. 2015
125

126 unicellular bacteria (e.g. Geobacter species) (Summers et al. 2010; Wang et al. 2019),

127 (ii) conductive conduits that consist of multicellular, filamentous bacteria (Pfeffer et al.

128 2012; Shi et al. 2016; Lovley 2017; Meysman 2018), or (iii) extracellular mineral

129 particles that connect redox reactions that are catalysed by different microbial species

130 (Reguera et al. 2005; Kato et al. 2012; Shi et al. 2016). In all of these cases, the

6
131 transferred electrons are used to establish ion-gradients across the cellular membrane,

132 which in turn is used for ATP synthesis. Although in most cases, the exact mechanisms

133 of electron transfer between cells are not completely understood, the available

134 evidence suggests that this is a very widespread and ecologically important way of

135 how two different species interact synergistically (Morris et al. 2013).

136 The third type of benefit bacteria exchange with each other are services (Figure

137 1, Table 1, Supplementary Table 1). A service results from the behaviour one

138 bacterium performs, typically to enhance its own Darwinian fitness, and which benefits

139 another bacterium in its immediate vicinity. Such services can include a range of

140 different traits such as transport (e.g. hitchhiking of a non-motile bacteria by attaching

141 to the flagellum of another motile bacterium (Muok et al. 2021)), detoxification (e.g.

142 degradation of an antibiotic (Sorg et al. 2016; Cubillos-Ruiz et al. 2022), or niche

143 construction (e.g. changing pH in a favourable direction (Aranda-Díaz et al. 2020)).

144 Other processes falling into this category are the production of biofilms (Madsen et al.

145 2016; Dragoš et al. 2018), the release of digestive enzymes (e.g. proteases, chitinases

146 (Drescher et al. 2014; Smith and Schuster 2019)) to degrade complex molecules or of

147 siderophores to sequester iron (Amin et al. 2009).

148 The final commodity that is exchanged between bacteria is information (Figure 1,

149 Table 1, Supplementary Table 1). Information can be transferred between cells in the

150 form of genetic material, which encodes a certain biochemical capability that is

151 beneficial to the receiver (e.g. a gene conferring antibiotic resistance (Kent et al.

152 2020)). Genetic information such as chromosomal or plasmid DNA can be passed from

153 one bacterium to another one using a variety of mechanisms including conjugation

154 (Lederberg and Tatum 1946), transformation (Griffith 1928), or transduction

155 (Lederberg 1952; Zinder and Lederberg 1952). Besides these canonical pathways of

7
156 horizontal gene transfer, several alternative mechanisms such as nanotubes (Dubey

157 and Ben-Yehuda 2011) and membrane vesicles (Woith et al. 2019; Dell’Annunziata et

158 al. 2021) have been described (Table 1, Supplementary Table 1). The diversity of

159 mechanisms bacteria use to exchange information in the form of genetic material

160 underscores its importance for the ecology and evolution of microbial communities.

161 Besides a transfer of genetic material that potentially leads to a long lasting

162 modification of a cell’s phenotype, bacteria also exchange information as a form of

163 communication. For this, metabolites are released into the surrounding gaseous or

164 aqueous phase, which induces an immediate yet rather momentary response in the

165 receiving cell. The physico-chemical properties (e.g. size, polarity) of the molecules

166 that are used for this purpose determine their diffusion rates and thus the radius around

167 the emitter, within which the molecule takes its full effect (Netzker et al. 2020).

168 Chemical communication of this kind is used to coordinate behaviours within species

169 (e.g. quorum sensing (Cook and Federle 2014; Mould et al. 2020)) or between different

170 species (Abisado et al. 2018; Laganenka and Sourjik 2018; Ranava et al. 2021). In

171 both cases, chemical communication systems regulate the expression of genes that

172 are involved in, for example, the production of biofilms (Laganenka and Sourjik 2018)

173 or virulence factors (Mould et al. 2020). Because members of the same species

174 strongly benefit from a coordinated expression of these genes, these communication

175 systems are frequently highly species-specific (Hawver et al. 2016). Nevertheless, it is

176 well established that chemical signals can also induce responses in unrelated species

177 (Federle and Bassler 2003; Abisado et al. 2018). However, in these cases, the potential

178 benefits resulting for both sender and receiver of the message remain frequently

179 unclear (Bernier et al. 2011).

180

8
181 Mechanisms of metabolite transfer between bacterial cells

182 Bacteria use a wide array of different mechanisms to exchange metabolites or services

183 between cells. These mechanisms are generally subdivided into two main categories,

184 depending on whether the transfer of materials depends on a direct physical contact

185 between bacterial cells (i.e. contact-dependent exchange) or not (i.e. contact-

186 independent exchange) (D'Souza et al. 2018; Pacheco et al. 2019; van Tatenhove-Pel

187 et al. 2021; Figure 2). In addition, these mechanisms differ with regard to the spatial

188 distance that is covered during the transfer process. While interactions that require a

189 close contact of cell surfaces for the interaction to occur result in a direct transfer of

190 metabolites between cells (distance: < 1 µm) (Benomar et al. 2015; Sah and Wall 2020;

191 López-García and Moreira 2021), other mechanisms that depend on the formation of,

192 for example, cell membrane protrusions (e.g. nanowires, pili, nanotubes) can cover

193 intermediate distances between cells (i.e. ~ 1-60 µm) (Remis et al. 2014; Dubey et al.

194 2016; Fischer et al. 2019). In contrast, contact independent interactions that for

195 example rely on an exchange of materials via diffusion through the extracellular

196 environment, can cover gaps between cells that range from direct cell proximity up to

197 very large distances (i.e. > 100 µm) (Be'Er et al. 2009; Cordero and Datta 2016; van

198 Tatenhove-Pel et al. 2021). In the following, we will provide an overview over the

199 different kinds of mechanisms bacteria use to transfer materials between bacterial cells

200 (Figure 2, Table 1, Supplementary Table 1).

201 The first group of mechanisms bacteria use to exchange materials are

202 summarized under the umbrella term contact-independent mechanisms. Processes

203 that fall into this category typically cover longer distances between bacterial cells and

204 rely on a diffusion of exchanged goods either as a free molecule or as compounds that

205 are encapsulated within membrane vesicles.

9
206

207

208 Long-distance
C D
transport
209 E

210 F
B

211 G
A
212 H

213
-TraA/B

214
Intermediate-distance
J I
215 transport
Short-distance
transport
216

217 Figure 2: Mechanisms bacteria use to exchange synergistic benefits between bacterial cells. The
218 different transfer mechanisms are subdivided into three categories based on the distance they can
219 bridge. (A-C) Contact-independent transport mechanism that can cover longer distances (blue
220 background) include (A) passive diffusion, (B) active transport, and (C) vesicle-mediated exchange. (D-
221 H) Contact-dependent transport mechanisms covering short to intermediate distances between bacteria
222 (yellow background) comprise (D) vesicle chains, (E) nanowires, (F) nanotubes, (G) pili, and (H) flagella.
223 (I-J) The last category of contact-dependent processes involves mechanisms that facilitate transport
224 over relatively short-distances (green background) such as the (I) TraA/B-mediated fusion of outer
225 membranes and (J) type-III, -IV or -VI secretion systems. Electron micrographs show the corresponding
226 structures (arrows). Photos reproduced with permission from (C) Prof. Dr. Steven Biller, (D) (Fischer et
227 al. 2019), (E) (Dahl et al. 2022), (G) (Curtiss III, Roy, et al. 1969), (H) (Friedlander et al. 2013), (I,J)
228 (López-García and Moreira 2021).
229

230 Emission of materials from cells can either be passive through an unintended

231 leakage of certain compounds through the cellular membrane (Be'Er et al. 2009;

232 Pacheco et al. 2019; Figure 2A) or be due to an active, transporter-mediated export

233 of compounds out of cells (Sokolovskaya et al. 2020; Butaite et al. 2021; Figure 2B).

234 Functional reasons for an active transport can be the disposal of accumulating waste

235 products to prevent autointoxication (Lilja and Johnson 2016), the externalization of

10
236 specific metabolites to alter the environment (e.g. β-lactamase to degrade ampicillin

237 (Yurtsev et al. 2016)), or the triggering of specific biological responses in other cells

238 (e.g. quorum sensing (Abisado et al. 2018)). Another example of actively released

239 compounds are siderophores that chelate iron. By taking up the iron-siderophore

240 complex, bacteria scavenge this essential nutrient from iron-deplete environments

241 (Sandy and Butler 2009; Butaite et al. 2021). In addition, bacteria can secrete enzymes

242 into the extracellular environment to harvest nutrients by degrading complex polymers

243 (e.g. chitin (Beier and Bertilsson 2013) or lignin (Vicuña 1988)) or to modify

244 environmental conditions (e.g. adjusting the pH (Aranda-Díaz et al. 2020)).

245 Active secretion mechanisms require energy-dependent transporters (e.g. ABC

246 transporters (Rees et al. 2009)) and can be modulated to regulate social behaviours

247 within a group of interacting microorganisms. One example for this is intraspecific

248 (Kalamara et al. 2018) and interspecific (Ayrapetyan et al. 2014) quorum sensing via

249 the secretion of signalling molecules called autoinducers that coordinate physiological

250 processes of a community in a cell density-dependent manner. In Bacillus subtilis for

251 example, it is known that this system regulates the production of metabolites (e.g.

252 surfactin, lipopeptides) that are released into the environment and are available to all

253 community members within a population, thereby controlling cooperative behaviours

254 such as swarming or biofilm formation, which are crucial for the cells’ survival

255 (Kalamara et al. 2018).

256 The third diffusion-based transfer mechanism is an exchange of materials

257 between cells via membrane-encapsulated vesicles (Kim et al. 2015; Figure 2C).

258 These vesicles are bilayered structures that can either be derived from a cell’s outer

259 membrane or be outer-inner membrane vesicles that result from membrane blebbing

260 or the explosive lysis of cells (Toyofuku et al. 2019). Both types of vesicles encapsulate

11
261 the transferred commodity, thereby not only protecting it from environmental

262 influences, but also preventing its dilution into the surrounding medium (Woith et al.

263 2019).

264 The second main group of mechanisms bacteria use to transfer materials between

265 cells depends on a direct physical contact between interacting individuals. The group

266 of processes that are summarized in this category can cover short to intermediate

267 distances between bacterial cells. This can be achieved for example by cell protrusions

268 (Kaplan et al. 2021) that stretch out to the next interaction partner to either connect

269 cells or even bridge the cytoplasm between them.

270 The first mechanism in this category are so-called vesicle chains. By interlinking

271 outer membrane vesicles, bacteria (e.g. Myxococcus) generate a tubular structure with

272 a continuous lumen (Remis et al. 2014; Wei et al. 2014; Figure 2D). In this way, vesicle

273 chains not only connect cells, but also facilitate a targeted exchange of metabolites

274 between cells (Ducret et al. 2013; Remis et al. 2014). More detailed studies have

275 identified two different types of vesicle chains. The first one consists of outer

276 membrane protrusion that then transform into a vesicle chain by a process called

277 pearling (Fischer et al. 2019). The second type of vesicle chains seems to originate

278 from inner membrane vesicles that remain enclosed by the outer membrane and are

279 then transported away from the cell due to the elongation of the outer membrane tube

280 (Fischer et al. 2019). Vesicle chains not only mediate interactions between bacteria,

281 but also extend the cell’s surface. In this way, additional surface space is generated

282 for catalytic/ enzymatic reactions that can also increase the likelihood to detect and

283 import nutrients (Fischer et al. 2019).

284 The second type of structure bacteria use to interact with the environment (Cheng

285 and Call 2016; Shi et al. 2016) or other cells of the same or different species (Summers

12
286 et al. 2010; Wegener et al. 2015; Lovley 2017) are so-called nanowires (Figure 2E).

287 These membrane protrusions facilitate the exchange of electrons by directly shuttling

288 electrons or substitute metabolites like H2 or formate, thus enabling further redox

289 reactions. The formation of nanowires seems to be species-specific and currently two

290 main models exist. In Geobacter sulfurreducens, nanowires have been suggested to

291 be a micrometer-long polymerization of the hexaheme cytochrome OmcS (Wang et al.

292 2019), while in Shewanella oneidensis MR-1, nanowires are considered to be outer

293 membrane extensions containing soluble periplasmic components together with

294 multiheme cytochromes (Pirbadian et al. 2014). Generally, a broad variety of bacterial

295 and archaeal species are known to use different cytochromes to facilitate the

296 extracellular transport of electrons (Cheng and Call 2016; Shi et al. 2016).

297 The third mechanism bacteria employ to establish cell-cell connections are

298 nanotubes. These more recently discovered structures are composed of chains of

299 continuous membranous segments traversed by an uninterrupted lumen (Dubey et al.

300 2016; Figure 2F). As such, their structure shows a striking similarity to the previously

301 discussed vesicle chains. Two types of nanotubes have been described. First,

302 intercellular nanotubes that connect neighbouring cells and, second, extending

303 nanotubes that reach into the surrounding of the cell and seem to function like plant

304 roots by searching for nutrients and interaction partners (Dubey et al. 2016). In general,

305 nanotubes are known to facilitate cell-cell communication and mediate the exchange

306 of cytoplasmic metabolites and plasmid DNA between cells of the same or different

307 bacterial species (Dubey and Ben-Yehuda 2011; Pande et al. 2015; Dubey et al. 2016;

308 Stempler et al. 2017).

309 The fourth structure used by bacteria to interconnect cells are pili (Figure 2G), which

310 are non-flagellar, proteinaceous, multi-subunit surface appendages (Kline et al. 2010).

13
311 Pili facilitate the attachment of the pili-forming individual to other bacteria, host cells,

312 or environmental surfaces. In addition, these structures can be involved in biofilm

313 formation, cell motility, signalling, as well as protein and DNA transport across

314 membranes. Pili can be categorized into five main classes, namely (1) chaperone-

315 usher pili, (2) curli, (3) type III secretion pili, (4) type IV pili, and (5) type IV secretion

316 pili (Fronzes et al. 2008; Kline et al. 2010). Pili cover a wide range of functions and can

317 be involved in both synergistic and antagonistic interactions (Fronzes et al. 2008).

318 The fifth mechanism bacteria use to establish connections over intermediate

319 distances between cells is mediated by flagella (Figure 2H). These filaments, which

320 mainly consist of flagellin, serve the main purpose to propel bacteria forward

321 (Silverman and Simon 1977). However, more recent studies have revealed that flagella

322 can also be used by bacteria to bind interaction partners in order to reduce the spatial

323 distance for an otherwise diffusion-based exchange (Marx 2009; Ishii et al. 2005). One

324 study even suggested that the flagellar cap protein FliD was involved in synchronizing

325 the metabolism of interacting cells of Pelotomaculum thermopropionicum and

326 Methanothermobacter thermautotrophicus, thus pointing to an important role of flagella

327 for triggering the syntrophic interaction between interacting strains (Shimoyama et al.

328 2009).

329 The final way of how bacteria can transfer synergistic benefits between cells is

330 by interacting with each other via immediate cell surface connections (Benomar et al.

331 2015; Charubin et al. 2020; Figures 2I,J). For this, cells frequently produce an

332 extracellular matrix that mainly consists of polysaccharides, proteins, and DNA

333 (Flemming and Wingender 2010), thus leading to the formation of a free-floating

334 (Gilbertie et al. 2019) or surface-attached bacterial aggregate (Madsen et al. 2016).

335 Direct cell surface connections are the closest interaction two cells can form (Benomar

14
336 et al. 2015; López-García and Moreira 2021) and have been shown to be involved in

337 the exchange of membrane material and proteins (Sah and Wall 2020; Figure 2I) as

338 well as cytoplasmic constituents (Benomar et al. 2015; Figure 2J).

339 Although mechanism to exchange synergistic benefits between bacterial cells

340 abound in bacterial communities, the factors determining which mechanism is used

341 under what circumstances still remain unclear. Besides the type of the traded good or

342 physiological constrains operating on cells, it is likely that also eco-evolutionary factors

343 play an important role in determining which mechanism is used given certain

344 environmental condition. In the following, it will be discussed how the interplay between

345 these factors shapes synergistic interactions.

346

347 Transfer mechanisms determine the specificity of synergistic interactions

348 Given the functional and structural diversity of synergistic interactions in bacteria, a

349 key question is which factors determine whether a certain interaction can successfully

350 establish and be maintained in the long-run. The answer to this question is strongly

351 determined by the mechanism that is used to transfer the traded commodity between

352 cells.

353 In the case of contact-independent interactions, goods are mostly unspecifically

354 released into the extracellular environment (e.g. biofilm production, enzymes to

355 degrade toxins, metabolites). These so-called public goods are equally accessible to

356 both the cells producing them and other cells that are present in the local environment.

357 Specificity with regards to the type of cells taking advantage of the traded good can

358 emerge based on the molecular nature of the secreted substance. For example, the

359 majority of quorum sensing signals can only be understood by members of the same

360 species (McCaig et al. 2013). Moreover, a nutrient that has been released into the
15
361 extracellular environment can benefit some cells more than others – for example

362 because of strain-specific preferences for this metabolite (Pacheco et al. 2019). Also

363 vesicle-encapsulated cargos limit the availability of the exchanged materials to certain

364 strains, because the recipient requires a specific machinery to capture and fuse with

365 the membrane vesicle (Toyofuku et al. 2017). Despite these exceptions, contact-

366 independent interactions are, in general, less specific than interactions that rely on a

367 physical contact between cells. A consequence of this is that unintended recipients

368 can take advantage of the public good, potentially resulting in significant costs to the

369 producing cells (van Tatenhove-Pel et al. 2021).

370 In contrast, contact-dependent interactions are intrinsically more specific with

371 regards to the choice of suitable interaction partners. This link stems from the fact that

372 in contact-dependent interactions, the producer of a synergistic benefit can, in

373 principle, actively decide with which other cell it initiates a certain interaction and

374 potentially also the time at which it terminates the relationship. This possibility puts the

375 producer of the beneficial good in control over the establishment and the duration of

376 the interaction. A second factor that contributes to the increased specificity of contact-

377 dependent transfer mechanisms is the fact that the molecular mechanisms that are

378 used to adhere to other cells and establish intercellular interactions are frequently

379 highly species-specific. While a nanotube-mediated exchange of metabolites and

380 protein has been demonstrated to function in a wide range of interspecific interactions

381 (Dubey and Ben-Yehuda 2011; Pande et al. 2015), other transfer mechanisms such

382 as vesicles (Tashiro et al. 2017) or pili (Low et al. 2022) are known to operate within a

383 taxonomically restricted set of species. Also the exchange of genetic information is

384 more likely to be successful within bacterial taxa that are more closely related to each

385 other (Gogarten et al. 2002; Lawrence and Hendrickson 2003; Polz et al. 2013),

386 suggesting that either the mechanisms used to transfer genetic material (e.g.

16
387 conjugation pili, viruses) or the transferred genetic material itself (e.g. ability of a

388 plasmid to replicate in a new host cell (Caspi et al. 2000), fitness costs for expressing

389 foreign genes (San Millan and Maclean 2017)) limits the flow of genes to evolutionarily

390 more distant taxa. Taken together, the presented evidence suggests that the kind of

391 mechanism that is used to transfer synergistic benefits between bacterial cells

392 potentially operates as a filter that biases the taxonomic distribution of synergistic

393 interactions within microbial communities. However, systematic studies that analyse

394 the species-specificity of different transfer mechanisms remain scarce.

395

396 Detection and recognition mechanisms are often highly specific

397 A key issue for the establishment of synergistic interactions between bacterial cells is

398 the detection and recognition of potential interaction partners. The two main steps that

399 are important in this process are (i) the detection of suitable cells from a larger distance

400 and (ii) the recognition of target cells upon closer contact.

401 Bacteria feature highly sensitive olfactory systems that they use to detect and

402 localize suitable food sources (Yawata et al. 2020) or symbiotic partners (Taylor and

403 Stocker 2012). In this context, the successful localisation of the source of a chemical

404 gradient depends on properties of the individual cell (e.g. the sensitivity of a strain’s

405 chemotaxis pathway or its swimming speed) as well as on environmental factors such

406 as the viscosity of the surrounding medium or the amount of chemoattractant that is

407 emitted from the source (Keegstra et al. 2022). To localize a certain target, bacteria

408 require sufficiently strong emission levels of the corresponding chemoattractant. Thus,

409 over longer distances, bacteria are more likely to be attracted to chemicals that are

410 produced by larger assemblages of bacteria (e.g. biofilms (Moore-Ott et al. 2022)) or

411 food particles than to individual cells. Nevertheless, chemotaxis-based mechanisms

17
412 are likely sufficient to attract a specific set of bacterial species from the surrounding

413 environment to a certain location (Lambert et al. 2019).

414 Once bacteria get into closer contact, a suit of mechanisms starts to operate that

415 further enhances the specificity of cell-cell interactions. Three main principles have

416 been described in this context (Rendueles and Ghigo 2012; Troselj et al. 2018).

417 First, bacteria recognize suitable interaction partners by using adhesive structures

418 (e.g. adhesins (Rickard et al. 2003)) that specifically bind to receptors on the surface

419 of other cells (i.e. co-aggregation (Rickard et al. 2003)). This kind of mechanism is

420 typically highly species-specific. The resulting consortia of aggregating cells then

421 benefit from an enhanced ability to colonize a certain environment (e.g. tooth biofilms

422 (Kolenbrander et al. 2006)) or from metabolic interactions between interconnected

423 partners (Bradshaw et al. 1994; Palmer Jr et al. 2001)).

424 Second, bacteria produce structures which allow them to rather unspecifically

425 adhere to other bacteria (e.g. exopolysaccharides) (Burdman et al. 1998). Once other

426 species start to attach, specificity can be introduced by favouring the growth of some

427 strains (Culotti and Packman 2014; Ren et al. 2015), while inhibiting the attachment or

428 growth of others (Rendueles and Ghigo 2012).

429 The third kind of specificity-enhancing mechanisms increases the relatedness within

430 a local assemblage of bacteria (i.e. kin groups) by killing other unrelated individuals.

431 Antagonizing behaviours that aim at obliterating competitors of the same or different

432 species typically rely on the production of toxins. Due to the fact that the survival of

433 cells hinges upon their resistance to the killing mechanism used, cognate pairs of toxin

434 and immunity-conferring proteins contribute to the establishment of genetically well-

435 defined bacterial groups. This kind of mechanism can be beneficial on the consortium-

436 level, because the division of labour among for example toxin-producing cells and the

18
437 faster growing toxin-resistant individuals enhances the competitive ability of the whole

438 group (Zhang et al. 2020). Moreover, the local elimination of susceptible genotypes

439 can efficiently prevent third parties from exploiting other synergistic behaviours among

440 group members such as swarming (Kraigher et al. 2022) or public goods cooperation

441 (McNally et al. 2017).

442 This kind of toxin-based cell-cell recognition mechanisms can be contact-dependent

443 or contact-independent. Contact-dependent recognition of other cells can be mediated

444 by receptors that specifically bind other cells (e.g. interactions between TraA and TraB

445 in myxobacteria (Cao and Wall 2017) or CdiA of the contact-dependent inhibition

446 system in Escherichia coli (Aoki et al. 2005)). In a second step, the toxin is then

447 delivered to target cells where it takes full effect. This can be achieved by a transfer of

448 outer membrane material that contains the toxic protein (Vassallo et al. 2018; Figure

449 2I) or via the delivery of the toxic protein into the cytoplasm of the target cell using type

450 III (Zhu et al. 2006), IV (Souza et al. 2015), VI (Crisan and Hammer 2020), or VII (Cao

451 et al. 2016) secretion systems (Figure 2J). Alternatively, other strains that try to invade

452 a local group of bacteria can also be eradicated by releasing toxins (e.g. bacteriocins)

453 into the extracellular environment (Tait and Sutherland 2002). Again, only bacteria that

454 are resistant to the toxin will be able to survive, thus representing a strong filter that

455 favours closely related kin. In the absence of other, potentially exploitative genotypes,

456 synergistic interactions among the members of the local communities can thrive

457 unrestrictedly.

458 Taken together, all of the abovementioned mechanisms confine the taxonomic

459 diversity within groups of interacting bacteria to only include those that manage to

460 attach to other resident strains and/ or are resistant to the antagonistic behaviours

461 shown by members of the local group. While certain types of cell-cell recognition

19
462 systems only allow the establishment of interactions among conspecific genotypes

463 (Aoki et al. 2005; Cao and Wall 2017), others also include interspecific interactions

464 (e.g. co-aggregation).

465

466 Relatedness among partners determines the establishment of synergistic

467 interactions

468 The above analysis suggests that the mechanism bacteria use to exchange synergistic

469 benefits and recognize suitable partners likely impacts the structure of synergistic

470 interactions within microbial communities. If this is the case, a clear correlation

471 between the probability for a successful establishment of a synergistic interaction and

472 the phylogenetic relationship among interacting partners should be detectable. In

473 theory, three potential patterns can be expected (Figure 3).

474
A B C
475
Synergistic benefit

476

477

478

479
Phylogenetic relatedness Phylogenetic relatedness Phylogenetic relatedness
480
481
482 Figure 3: Potential statistical relationships between the phylogenetic relatedness of two interaction
483 partners and their propensity to establish a synergistic interaction (here shown as synergistic benefit).
484 (A) No statistical relationship. (B) Negative correlation between both parameters (i.e. closely related
485 species are more likely to establish a synergistic interaction). (C) Positive correlation between both
486 parameters (i.e. more distantly related species are more likely to establish a synergistic interaction). In
487 these hypothetical graphs, circles represent the results of independent replicates and differently
488 coloured ribbons the respective 95% confidence interval.
489

490

20
491 First, the phylogenetic relatedness between interacting partners might not

492 predictably influence the formation of synergistic interactions (Figure 3A). Not finding

493 a significant relationship between both parameters could be due to problems of the

494 experimental setup. For example, an imbalanced or biased phylogenetic distribution of

495 strains used to experimentally test this hypothesis could explain the inability to detect

496 a significant statistical relationship (Horner-Devine and Bohannan 2006; Cadotte et al.

497 2017; Mahon et al. 2021). Alternatively, high rates of horizontal gene transfer within

498 communities could erode the taxonomic specificity of synergistic interactions (Butaite

499 et al. 2021). Finally, also other factors such as the simultaneous operation of multiple

500 effects (e.g. different interactions) with opposing consequences or the confounding

501 effect of a previous coevolutionary history could distort the ability to detect a clear

502 relationship between both parameters (Fritschie et al. 2014; Venail et al. 2014).

503 The second possible outcome is a negative relationship between the

504 phylogenetic relatedness between partners and the propensity for the establishment

505 of a synergistic interaction (Figure 3B). In other words, synergistic interactions are

506 more likely to occur between close relatives. A causal explanation for this could be that

507 phylogenetically more closely related bacteria are also more similar in their metabolic

508 capabilities and therefore to occupy a similar ecological niche (Goberna et al. 2019).

509 This could enhance the ecological opportunity to establish synergistic interactions

510 among more closely related individuals (Horner-Devine and Bohannan 2006). In

511 addition, closely related species are also more likely to share the same mechanisms

512 to exchange materials, such as certain contact-dependent interactions, which could

513 introduce a taxonomic bias (Horner-Devine and Bohannan 2006; Sher et al. 2011).

514 Finally, so-called kin selection mechanism that promote interactions among closer

515 relatives (e.g. the production of toxins that kill non-resistant strains) could explain the

516 observed pattern (Sah and Wall 2020).

21
517 The third possible outcome is that synergistic interactions between species are more

518 likely to establish than interactions within species (Figure 3C). This pattern could be

519 due to the fact that bacteria, which occupy different ecological niches, also show a

520 reduced competition for nutrients and other resources. Consequently, growth of

521 interspecific cocultures should, on average, be higher than the one of more closely

522 related taxa that experience enhanced competition (Venail and Vives 2013; Russel et

523 al. 2017). Another important point is that two phylogenetically more dissimilar species

524 are also more likely to differ in the architecture of their metabolic network (Salles et al.

525 2012) A consequence of this can be that the cost to produce certain metabolites and

526 the rates at which they are produced can differ between bacterial species. Hence, two

527 strains can significantly benefit by reciprocally trading cheaper/ easier to produce

528 compounds against more valuable ones. The probability for this kind of synergistic

529 metabolic complementarity is increased in interspecific interactions. Interestingly,

530 entering into an obligate metabolic relationship with another species can also extend

531 the biochemical capabilities of a strain such as the ability to use a new carbon source

532 (Ona et al. 2021).

533 Unfortunately, explicit experimental verifications of the role of phylogenetic

534 relatedness on the establishment and functioning of synergistic interactions are rare

535 so far. One study that addressed this issue in unidirectional cross-feeding interactions

536 between an amino acid donor and an auxotrophic recipient found clear evidence that

537 this kind of synergistic interaction was more likely to establish between

538 phylogenetically more dissimilar species (Giri et al. 2021). However, the experiments

539 performed in this study did not distinguish whether the exchange of amino acids

540 between partners was contact-dependent or contact-independent. The same result

541 was corroborated by a recent study, in which thousands of pairwise interactions were

542 analysed in different carbon sources using a droplet-based cocultivation platform

22
543 (Kehe et al. 2021). The comprehensive data set of this study also suggested that

544 positive interactions among strains were more likely to emerge among taxonomically

545 dissimilar strains. A third study, in which different strains of Pseudomonas bacteria

546 were sampled from natural soil and pond communities found that low or non-producers

547 of the siderophore pyoverdine were more likely to benefit when exposed to the

548 pyoverdine that derived from a more closer related strain (Butaite et al. 2021). This

549 pattern was likely caused by the fact that a strain that is closer related to the

550 siderophore producer is also more likely to share the receptor that is required to take

551 up the iron-siderophore-complex from the environment. Taken together, the above

552 studies suggest that multiple forces - such as a metabolic complementarity between

553 strains or biochemical constrains restricting the access to the exchanged good - are

554 operating simultaneously to determine the establishment and functioning of synergistic

555 interactions among bacteria. However, more studies are needed to unravel how

556 different kinds of transfer mechanisms affect the specificity of the focal synergistic

557 interaction.

558

559 Conclusion and future perspectives

560 Synergistic interactions among bacteria are ubiquitous in natural microbial

561 communities (Strickland et al. 2009; Delgado-Baquerizo et al. 2016; Valdes et al. 2018;

562 Vijay and Valdes 2022). However, the factors that determine their establishment

563 remain poorly understood. By summarizing the knowledge that is currently available

564 on this topic, we aimed at identifying major gaps in our understanding of the

565 mechanisms that govern the establishment of synergistic interactions between

566 bacterial genotypes. In particular, we analysed (i) the types of benefits that are

567 exchanged in synergistic interactions, (ii) the molecular mechanism bacteria use to

23
568 transfer benefits between cells, (iii) the ways of how bacteria choose their interaction

569 partner, and (iv) the consequences these mechanisms have for the phylogenetic

570 relatedness among interaction partners.

571 The overall pattern that emerged from our holistic treatment is that first synergistic

572 interactions are highly diverse in their form and function. This includes both the

573 commodities that are traded between bacteria and the mechanisms that are used to

574 transfer these goods between cells. Second, several lines of evidence suggest that

575 synergistic interactions among bacteria should be rather species-specific (i.e. some

576 combinations of strains perform better than others). Both the majority of mechanisms

577 bacteria use to exchange synergistic benefits as well as the means to recognize and

578 select certain interaction partners revealed a strong element of specificity, albeit the

579 degree of specificity depended on the details of the particular interaction considered.

580 While some mechanisms favoured exclusively interactions among members of the

581 same species, others also included specific combinations of different species.

582 However, studies that systematically analyse the taxonomic specificity of transfer and

583 recognition mechanisms were generally rare. Finally, the few existing studies that

584 experimentally verified the statistical relationship between the phylogenetic

585 relatedness among two bacterial genotypes and their propensity to engage in

586 synergistic interactions did not explicitly analyse which mechanism bacteria used to

587 select a partner and transfer synergistic benefits between cells. However, knowledge

588 on these details is critically important to fully understand the forces that structure

589 microbial communities.

590 Future work should not only aim to further our understanding of the molecular

591 mechanisms bacteria use to choose suitable interaction partners and trade synergistic

592 benefits with them, but also link this information to experimental tests, in which the

24
593 dependence of these mechanisms on the taxonomic identity of the respective

594 interaction partners is explicitly considered. A better understanding of these

595 mechanistic links will help to explain the taxonomic structure of natural microbial

596 communities and thus aid the design of synthetic communities for biotechnological or

597 medical purposes (Giri et al. 2020). Moreover, more detailed knowledge on the causes

598 and consequences of synergistic interactions within microbial communities will shed

599 new light on the biology of the bacterial lifestyle in general. In this context, it will be

600 particularly interesting to unravel the forces that shape the establishment and

601 functioning of intercellular metabolic networks in bacteria (Pande and Kost 2017).

602

603 Acknowledgements

604 The authors would like to thank all members of the Kostlab (past and present) as well

605 as the SFB 944 for valuable discussion. This work was funded by the German

606 Research Foundation (DFG: SFB 944, P19, KO 3909/2-1, KO 3909/4-1, KO 3909/6-1,

607 KO 3909/9-1) and the Volkswagen Foundation (Az: 9B831).

608

609 References

610 Abisado, R. G., Benomar, S., Klaus, J. R., Dandekar, A. A. and Chandler, J. R. (2018). Bacterial quorum

611 sensing and microbial community interactions. mBio 9: e02331-17.

612

613 Alteri, C. J. and Mobley, H. L. (2016). The versatile type VI secretion system. Virulence Mechanisms of

614 Bacterial Pathogens: 337-356.

615

616 Amin, S. A., Green, D. H., Hart, M. C., Küpper, F. C., Sunda, W. G. and Carrano, C. J. (2009). Photolysis

617 of iron-siderophore chelates promotes bacterial-algal mutualism. PNAS 106: 17071-17076.

618

25
619 Aoki, S. K., Pamma, R., Hernday, A. D., Bickham, J. E., Braaten, B. A. and Low, D. A. (2005). Contact-

620 dependent inhibition of growth in Escherichia coli. Science 309: 1245-1248.

621

622 Aranda-Díaz, A., Obadia, B., Dodge, R., Thomsen, T., Hallberg, Z. F., Güvener, Z. T., Ludington, W. B.

623 and Huang, K. C. (2020). Bacterial interspecies interactions modulate pH-mediated antibiotic tolerance.

624 eLife 9: e51493.

625

626 Ayrapetyan, M., Williams, T. C. and Oliver, J. D. (2014). Interspecific quorum sensing mediates the

627 resuscitation of viable but nonculturable vibrios. Appl. Environ. Microbiol. 80: 2478-2483.

628

629 Be'Er, A., Zhang, H., Florin, E.-L., Payne, S. M., Ben-Jacob, E. and Swinney, H. L. (2009). Deadly

630 competition between sibling bacterial colonies. PNAS 106: 428-433.

631

632 Beier, S. and Bertilsson, S. (2013). Bacterial chitin degradation-mechanisms and ecophysiological

633 strategies. Front. Microbiol. 4: 149.

634

635 Benomar, S., Ranava, D., Cardenas, M. L., Trably, E., Rafrafi, Y., Ducret, A., Hamelin, J., Lojou, E.,

636 Steyer, J. P. and Giudici-Orticoni, M. T. (2015). Nutritional stress induces exchange of cell material and

637 energetic coupling between bacterial species. Nat. Commun. 6: 6283.

638

639 Berleman, J. E., Allen, S., Danielewicz, M. A., Remis, J. P., Gorur, A., Cunha, J., Hadi, M. Z., Zusman,

640 D. R., Northen, T. R., Witkowska, H. E., et al. (2014). The lethal cargo of Myxococcus xanthus outer

641 membrane vesicles. Front. Microbiol. 5: 474.

642

643 Bernier, S. P., Létoffé, S., Delepierre, M. and Ghigo, J. M. (2011). Biogenic ammonia modifies antibiotic

644 resistance at a distance in physically separated bacteria. Mol. Microbiol. 81: 705-716.

645

646 Biller, S. J., Schubotz, F., Roggensack, S. E., Thompson, A. W., Summons, R. E. and Chisholm, S. W.

647 (2014). Bacterial vesicles in marine ecosystems. Science 343: 183-186.

648

26
649 Bradshaw, D., Homer, K., Marsh, P. and Beighton, D. (1994). Metabolic cooperation in oral microbial

650 communities during growth on mucin. Microbiology 140: 3407-3412.

651

652 Bridges, A. A. and Bassler, B. L. (2019). The intragenus and interspecies quorum-sensing autoinducers

653 exert distinct control over Vibrio cholerae biofilm formation and dispersal. PLoS Biol. 17: e3000429.

654

655 Brown, L., Wolf, J. M., Prados-Rosales, R. and Casadevall, A. (2015). Through the wall: Extracellular

656 vesicles in Gram-positive bacteria, mycobacteria and fungi. Nat. Rev. Microbiol. 13: 620-630.

657

658 Burdman, S., Jurkevitch, E., Schwartsburd, B., Hampel, M. and Okon, Y. (1998). Aggregation in

659 Azospirillum brasilense: Effects of chemical and physical factors and involvement of extracellular

660 components. Microbiology 144: 1989-1999.

661

662 Butaite, E., Kramer, J. and Kümmerli, R. (2021). Local adaptation, geographical distance and

663 phylogenetic relatedness: Assessing the drivers of siderophore-mediated social interactions in natural

664 bacterial communities. J. Evol. Biol. 34: 1266-1278.

665

666 Cadotte, M. W., Davies, T. J. and Peres-Neto, P. R. (2017). Why phylogenies do not always predict

667 ecological differences. Ecol. Monogr. 87: 535-551.

668

669 Cao, P., Dey, A., Vassallo, C. N. and Wall, D. (2015). How myxobacteria cooperate. J. Mol. Biol. 427:

670 3709-3721.

671

672 Cao, P. and Wall, D. (2017). Self-identity reprogrammed by a single residue switch in a cell surface

673 receptor of a social bacterium. PNAS 114: 3732-3737.

674

675 Cao, Z., Casabona, M. G., Kneuper, H., Chalmers, J. D. and Palmer, T. (2016). The type VII secretion

676 system of Staphylococcus aureus secretes a nuclease toxin that targets competitor bacteria. Nat.

677 Microbiol. 2: 1-11.

678

27
679 Caspi, R., Helinski, D. R., Pacek, M. and Konieczny, I. (2000). Interactions of DnaA proteins from

680 distantly related bacteria with the replication origin of the broad host range plasmid RK2. J. Biol. Chem.

681 275: 18454-18461.

682

683 Charubin, K., Modla, S., Caplan, J. L. and Papoutsakis, E. T. (2020). Interspecies microbial fusion and

684 large-scale exchange of cytoplasmic proteins and RNA in a syntrophic Clostridium coculture. mBio 11:

685 e02030-02020.

686

687 Cheng, Q. and Call, D. F. (2016). Hardwiring microbes via direct interspecies electron transfer:

688 Mechanisms and applications. Environ. Sci.: Process. Impacts 18: 968-980.

689

690 Cook, L. C. and Federle, M. J. (2014). Peptide pheromone signaling in Streptococcus and Enterococcus.

691 FEMS Microbiol. Rev. 38: 473-492.

692

693 Cordero, O. X. and Datta, M. S. (2016). Microbial interactions and community assembly at microscales.

694 Curr. Opin. in Microbiol. 31: 227-234.

695

696 Crisan, C. V. and Hammer, B. K. (2020). The Vibrio cholerae type VI secretion system: toxins, regulators

697 and consequences. Environ. Microbiol. 22: 4112-4122.

698

699 Cubillos-Ruiz, A., Alcantar, M. A., Donghia, N. M., Cárdenas, P., Avila-Pacheco, J. and Collins, J. J.

700 (2022). An engineered live biotherapeutic for the prevention of antibiotic-induced dysbiosis. Nat.

701 Biomed. Eng. 6: 910–921.

702

703 Culotti, A. and Packman, A. I. (2014). Pseudomonas aeruginosa promotes Escherichia coli biofilm

704 formation in nutrient-limited medium. PLoS One 9: e107186.

705

706 D'Souza, G., Shitut, S., Preussger, D., Yousif, G., Waschina, S. and Kost, C. (2018). Ecology and

707 evolution of metabolic cross-feeding interactions in bacteria. Nat. Prod. Rep. 35: 455-488.

708

28
709 Dahl, P. J., Yi, S. M., Gu, Y., Acharya, A., Shipps, C., Neu, J., O’Brien, J. P., Morzan, U. N., Chaudhuri,

710 S. and Guberman-Pfeffer, M. J. (2022). A 300-fold conductivity increase in microbial cytochrome

711 nanowires due to temperature-induced restructuring of hydrogen bonding networks. Sci. adv. 8:

712 eabm7193.

713

714 Delgado-Baquerizo, M., Maestre, F. T., Reich, P. B., Jeffries, T. C., Gaitan, J. J., Encinar, D., Berdugo,

715 M., Campbell, C. D. and Singh, B. K. (2016). Microbial diversity drives multifunctionality in terrestrial

716 ecosystems. Nat. Commun. 7: 1-8.

717

718 Dell’Annunziata, F., Folliero, V., Giugliano, R., De Filippis, A., Santarcangelo, C., Izzo, V., Daglia, M.,

719 Galdiero, M., Arciola, C. R. and Franci, G. (2021). Gene transfer potential of outer membrane vesicles

720 of gram-negative bacteria. Int. J. Mol. Sci. 22: 5985.

721

722 Drescher, K., Nadell, C. D., Stone, H. A., Wingreen, N. S. and Bassler, B. L. (2014). Solutions to the

723 public goods dilemma in bacterial biofilms. Curr. Biol. 24: 50-55.

724 Dragoš, A., Kiesewalter, H., Martin, M., Hsu, C.-Y., Hartmann, R., Wechsler, T., Eriksen, C., Brix, S.,

725 Drescher, K. and Stanley-Wall, N. (2018). Division of labor during biofilm matrix production. Curr. Biol.

726 28: 1903-1913. e1905.

727

728 Dubey, G. P. and Ben-Yehuda, S. (2011). Intercellular nanotubes mediate bacterial communication. Cell

729 144: 590-600.

730

731 Dubey, G. P., Malli Mohan, G. B., Dubrovsky, A., Amen, T., Tsipshtein, S., Rouvinski, A., Rosenberg,

732 A., Kaganovich, D., Sherman, E., Medalia, O., et al. (2016). Architecture and characteristics of bacterial

733 nanotubes. Dev. Cell 36: 453-461.

734

735 Ducret, A., Fleuchot, B., Bergam, P. and Mignot, T. (2013). Direct live imaging of cell-cell protein transfer

736 by transient outer membrane fusion in Myxococcus xanthus. Elife 2: e00868.

737

738 Federle, M. J. and Bassler, B. L. (2003). Interspecies communication in bacteria. J. Clin. Investig. 112:

739 1291-1299.

29
740 Fischer, T., Schorb, M., Reintjes, G., Kolovou, A., Santarella-Mellwig, R., Markert, S., Rhiel, E., Littmann,

741 S., Becher, D. and Schweder, T. (2019). Biopearling of interconnected outer membrane vesicle chains

742 by a marine flavobacterium. Appl. Environ. Microbiol. 85: e00829-00819.

743

744 Flemming, H.-C. and Wingender, J. (2010). The biofilm matrix. Nat. Rev. Microbiol. 8: 623-633.

745

746 Friedlander, R. S., Vlamakis, H., Kim, P., Khan, M., Kolter, R. and Aizenberg, J. (2013). Bacterial flagella

747 explore microscale hummocks and hollows to increase adhesion. PNAS 110: 5624-5629.

748

749 Fritts, R. K., McCully, A. L. and McKinlay, J. B. (2021). Extracellular metabolism sets the table for

750 microbial cross-feeding. Microbiol. Mol. Biol. Rev. 85: e00135-20.

751

752 Fritschie, K. J., Cardinale, B. J., Alexandrou, M. A. and Oakley, T. H. (2014). Evolutionary history and

753 the strength of species interactions: Testing the phylogenetic limiting similarity hypothesis. Ecology 95:

754 1407-1417.

755

756 Fronzes, R., Remaut, H. and Waksman, G. (2008). Architectures and biogenesis of non-flagellar protein

757 appendages in Gram-negative bacteria. The EMBO J. 27: 2271-2280.

758

759 Ghoul, M. and Mitri, S. (2016). The ecology and evolution of microbial competition. Trends Microbiol.

760 24: 833-845.

761

762 Gilbertie, J. M., Schnabel, L. V., Hickok, N. J., Jacob, M. E., Conlon, B. P., Shapiro, I. M., Parvizi, J. and

763 Schaer, T. P. (2019). Equine or porcine synovial fluid as a novel ex vivo model for the study of bacterial

764 free-floating biofilms that form in human joint infections. PLoS One 14: e0221012.

765

766 Giri, S., Ona, L., Waschina, S., Shitut, S., Yousif, G., Kaleta, C. and Kost, C. (2021). Metabolic

767 dissimilarity determines the establishment of cross-feeding interactions in bacteria. Curr. Biol. 31: 5547-

768 5557 e5546.

769

30
770 Giri, S., Shitut, S. and Kost, C. (2020). Harnessing ecological and evolutionary principles to guide the

771 design of microbial production consortia. Curr. Opin. Biotechnol. 62: 228-238.

772

773 Goberna, M., Montesinos-Navarro, A., Valiente-Banuet, A., Colin, Y., Gómez-Fernández, A., Donat, S.,

774 Navarro-Cano, J. A. and Verdú, M. (2019). Incorporating phylogenetic metrics to microbial co-

775 occurrence networks based on amplicon sequences to discern community assembly processes. Mol.

776 Ecol. Resour. 19: 1552-1564.

777

778 Gogarten, J. P., Doolittle, W. F. and Lawrence, J. G. (2002). Prokaryotic evolution in light of gene

779 transfer. Mol. Biol. Evol. 19: 2226-2238.

780

781 Granato, E. T. and Foster, K. R. (2020). The evolution of mass cell suicide in bacterial warfare. Curr.

782 Biol. 30: 2836-2843. e2833.

783

784 Grandclement, C., Tannieres, M., Morera, S., Dessaux, Y. and Faure, D. (2016). Quorum quenching:

785 Role in nature and applied developments. FEMS Microbiol. Rev. 40: 86-116.

786

787 Griffith, F. (1928). The significance of pneumococcal types. Epidemiol. Infect. 27: 113-159.

788

789 Harcombe, W. R., Riehl, W. J., Dukovski, I., Granger, B. R., Betts, A., Lang, A. H., Bonilla, G., Kar, A.,

790 Leiby, N. and Mehta, P. (2014). Metabolic resource allocation in individual microbes determines

791 ecosystem interactions and spatial dynamics. Cell Rep. 7: 1104-1115.

792

793 Hawver, L. A., Jung, S. A. and Ng, W.-L. (2016). Specificity and complexity in bacterial quorum-sensing

794 systems. FEMS Microbiol. Rev. 40: 738-752.

795

796 Hobley, L., Harkins, C., MacPhee, C. E. and Stanley-Wall, N. R. (2015). Giving structure to the biofilm

797 matrix: An overview of individual strategies and emerging common themes. FEMS Microbiol. Rev. 39:

798 649-669.

799

31
800 Horner-Devine, M. C. and Bohannan, B. J. (2006). Phylogenetic clustering and overdispersion in

801 bacterial communities. Ecology 87: S100-S108.

802

803 Ishii, S. i., Kosaka, T., Hori, K., Hotta, Y. and Watanabe, K. (2005). Coaggregation facilitates interspecies

804 hydrogen transfer between Pelotomaculum thermopropionicum and Methanothermobacter

805 thermautotrophicus. Appl. Environ. Microbiol. 71: 7838-7845.

806

807 Jiang, Z., Zhang, S., Klausen, L. H., Song, J., Li, Q., Wang, Z., Stokke, B. T., Huang, Y., Besenbacher,

808 F. and Nielsen, L. P. (2018). In vitro single-cell dissection revealing the interior structure of cable

809 bacteria. PNAS 115: 8517-8522.

810

811 John, M., Trzcinski, A. P., Zhou, Y. and Ng, W. J. (2017). Microbial stress mediated intercellular

812 nanotubes in an anaerobic microbial consortium digesting cellulose. Sci. Rep. 7: 18006.

813

814 Kalamara, M., Spacapan, M., Mandic-Mulec, I. and Stanley-Wall, N. R. (2018). Social behaviours by

815 Bacillus subtilis: quorum sensing, kin discrimination and beyond. Mol. Microbiol. 110: 863-878.

816

817 Kaplan, M., Chreifi, G., Metskas, L. A., Liedtke, J., Wood, C. R., Oikonomou, C. M., Nicolas, W. J.,

818 Subramanian, P., Zacharoff, L. A. and Wang, Y. (2021). In situ imaging of bacterial outer membrane

819 projections and associated protein complexes using electron cryo-tomography. Elife 10: e73099.

820

821 Kato, S., Hashimoto, K. and Watanabe, K. (2012). Microbial interspecies electron transfer via electric

822 currents through conductive minerals. PNAS 109: 10042-10046.

823

824 Keegstra, J. M., Carrara, F. and Stocker, R. (2022). The ecological roles of bacterial chemotaxis. Nat.

825 Rev. Microbiol. 20: 491-504.

826

827 Kehe, J., Ortiz, A., Kulesa, A., Gore, J., Blainey, P. C. and Friedman, J. (2021). Positive interactions are

828 common among culturable bacteria. Sci. Adv. 7: eabi7159.

829

32
830 Kent, A. G., Vill, A. C., Shi, Q., Satlin, M. J. and Brito, I. L. (2020). Widespread transfer of mobile antibiotic

831 resistance genes within individual gut microbiomes revealed through bacterial Hi-C. Nat. Commun. 11:

832 1-9.

833

834 Kim, H. J., Boedicker, J. Q., Choi, J. W. and Ismagilov, R. F. (2008). Defined spatial structure stabilizes

835 a synthetic multispecies bacterial community. PNAS 105: 18188-18193.

836

837 Kim, J. H., Lee, J., Park, J. and Gho, Y. S. (2015). Gram-negative and Gram-positive bacterial

838 extracellular vesicles. Semin. Cell. Dev. Biol. 40: 97-104.

839

840 Kline, K. A., Dodson, K. W., Caparon, M. G. and Hultgren, S. J. (2010). A tale of two pili: Assembly and

841 function of pili in bacteria. Trends Microbiol. 18: 224-232.

842

843 Kolenbrander, P. E., Palmer Jr, R. J., Rickard, A. H., Jakubovics, N. S., Chalmers, N. I. and Diaz, P. I.

844 (2006). Bacterial interactions and successions during plaque development. Periodontol. 2000 42: 47-

845 79.

846

847 Kraigher, B., Butolen, M., Stefanic, P. and Mandic Mulec, I. (2022). Kin discrimination drives territorial

848 exclusion during Bacillus subtilis swarming and restrains exploitation of surfactin. ISME J. 16: 833-841.

849

850 Laganenka, L. and Sourjik, V. (2018). Autoinducer 2-dependent Escherichia coli biofilm formation is

851 enhanced in a dual-species coculture. Appl. Environ. Microbiol. 84: e02638-02617.

852

853 Lambert, B. S., Fernandez, V. I. and Stocker, R. (2019). Motility drives bacterial encounter with particles

854 responsible for carbon export throughout the ocean. Limnol. Oceanogr. Lett. 4: 113-118.

855

856 Lawrence, J. G. and Hendrickson, H. (2003). Lateral gene transfer: When will adolescence end? Mol.

857 Microbiol. 50: 739-749.

858

859 Lederberg, J. (1952). Cell genetics and hereditary symbiosis. Physiological reviews 32: 403-430.

860

33
861 Lederberg, J. and Tatum, E. L. (1946). Gene recombination in Escherichia coli. Nature 158: 558.

862

863 Lilja, E. E. and Johnson, D. R. (2016). Segregating metabolic processes into different microbial cells

864 accelerates the consumption of inhibitory substrates. ISME J. 10: 1568-1578.

865

866 López-García, P. and Moreira, D. (2021). Physical connections: Prokaryotes parasitizing their kin.

867 Environ. Microbiol.Reports 13: 54-61.

868

869 Lovley, D. R. (2017). Happy together: microbial communities that hook up to swap electrons. ISME J.

870 11: 327-336.

871

872 Low, W. W., Wong, J. L., Beltran, L. C., Seddon, C., David, S., Kwong, H.-S., Bizeau, T., Wang, F.,

873 Peña, A. and Costa, T. R. (2022). Mating pair stabilization mediates bacterial conjugation species

874 specificity. Nat. Microbiol. 7: 1016-1027.

875

876 Madsen, J. S., Roder, H. L., Russel, J., Sorensen, H., Burmølle, M. and Sørensen, S. J. (2016).

877 Coexistence facilitates interspecific biofilm formation in complex microbial communities. Environ.

878 Microbiol. 18: 2565-2574.

879

880 Mahon, M. B., Jennings, D. E., Civitello, D. J., Lajeunesse, M. J. and Rohr, J. R. (2021). Functional

881 similarity, not phylogenetic relatedness, predicts the relative strength of competition. bioRxiv,

882 https://doi.org/10.1101/2021.07.21.453226.

883

884 Marchal, M., Goldschmidt, F., Derksen-Muller, S. N., Panke, S., Ackermann, M. and Johnson, D. R.

885 (2017). A passive mutualistic interaction promotes the evolution of spatial structure within microbial

886 populations. BMC Evol. Biol. 17: 106.

887

888 Marx, C. J. (2009). Getting in touch with your friends. Science 324: 1150-1151.

889

890 McCaig, W. D., Koller, A. and Thanassi, D. G. (2013). Production of outer membrane vesicles and outer

891 membrane tubes by Francisella novicida. J. Bacteriol. 195: 1120-1132.

34
892

893 McNally, L., Bernardy, E., Thomas, J., Kalziqi, A., Pentz, J., Brown, S. P., Hammer, B. K., Yunker, P. J.

894 and Ratcliff, W. C. (2017). Killing by Type VI secretion drives genetic phase separation and correlates

895 with increased cooperation. Nat. commun. 8: 1-11.

896

897 Meysman, F. J., Cornelissen, R., Trashin, S., Bonné, R., Martinez, S. H., van der Veen, J., Blom, C. J.,

898 Karman, C., Hou, J.-L. and Eachambadi, R. T. (2019). A highly conductive fibre network enables

899 centimetre-scale electron transport in multicellular cable bacteria. Nat. Commun. 10: 1-8.

900

901 Meysman, F. J. R. (2018). Cable bacteria take a new breath using long-distance electricity. Trends

902 Microbiol. 26: 411-422.

903

904 Moore-Ott, J. A., Chiu, S., Amchin, D. B., Bhattacharjee, T. and Datta, S. S. (2022). A biophysical

905 threshold for biofilm formation. eLife 11: e76380.

906

907 Morris, B. E., Henneberger, R., Huber, H. and Moissl-Eichinger, C. (2013). Microbial syntrophy:

908 Interaction for the common good. FEMS Microbiol. Rev. 37: 384-406.

909

910 Mould, D. L., Botelho, N. J. and Hogan, D. A. (2020). Intraspecies signaling between common variants

911 of Pseudomonas aeruginosa increases production of quorum-sensing-controlled virulence factors. mBio

912 11: e01865-01820.

913

914 Muok, A. R., Claessen, D. and Briegel, A. (2021). Microbial hitchhiking: How Streptomyces spores are

915 transported by motile soil bacteria. ISME J. 15: 2591-2600.

916

917 Nadell, C. D., Drescher, K. and Foster, K. R. (2016). Spatial structure, cooperation and competition in

918 biofilms. Nat. Rev. Microbiol. 14: 589-600.

919

920 Netzker, T., Shepherdson, E. M., Zambri, M. P. and Elliot, M. A. (2020). Bacterial volatile compounds:

921 Functions in communication, cooperation, and competition. Annu. Rev. Microbiol. 74: 409-430.

922

35
923 Niehus, R., Oliveira, N. M., Li, A., Fletcher, A. G. and Foster, K. R. (2021). The evolution of strategy in

924 bacterial warfare via the regulation of bacteriocins and antibiotics. eLife 10: e69756.

925

926 Odom, J. M. and Wall, J. D. (1983). Photoproduction of H2 from cellulose by an anaerobic bacterial

927 coculture. Appl. Environ. Microbiol. 45: 1300-1305.

928

929 Ona, L., Giri, S., Avermann, N., Kreienbaum, M., Thormann, K. M. and Kost, C. (2021). Obligate cross-

930 feeding expands the metabolic niche of bacteria. Nat. Ecol. Evol. 5: 1224-1232.

931

932 Pacheco, A. R., Moel, M. and Segre, D. (2019). Costless metabolic secretions as drivers of interspecies

933 interactions in microbial ecosystems. Nat. Commun. 10: 103.

934

935 Palmer Jr, R. J., Kazmerzak, K., Hansen, M. C. and Kolenbrander, P. E. (2001). Mutualism versus

936 independence: Strategies of mixed-species oral biofilms in vitro using saliva as the sole nutrient source.

937 Infect. Iimmun. 69: 5794-5804.

938

939 Pande, S., Kaftan, F., Lang, S., Svatos, A., Germerodt, S. and Kost, C. (2016). Privatization of

940 cooperative benefits stabilizes mutualistic cross-feeding interactions in spatially structured

941 environments. ISME J. 10: 1413-1423.

942

943 Pande, S. and Kost, C. (2017). Bacterial unculturability and the formation of intercellular metabolic

944 networks. Trends Microbiol. 25: 349-361.

945

946 Pande, S., Shitut, S., Freund, L., Westermann, M., Bertels, F., Colesie, C., Bischofs, I. B. and Kost, C.

947 (2015). Metabolic cross-feeding via intercellular nanotubes among bacteria. Nat. Commun. 6: 6238.

948

949 Peterson, S. B., Bertolli, S. K. and Mougous, J. D. (2020). The central role of interbacterial antagonism

950 in bacterial life. Curr. Biol. 30: R1203-R1214.

951

36
952 Pfeffer, C., Larsen, S., Song, J., Dong, M., Besenbacher, F., Meyer, R. L., Kjeldsen, K. U., Schreiber,

953 L., Gorby, Y. A. and El-Naggar, M. Y. (2012). Filamentous bacteria transport electrons over centimetre

954 distances. Nature 491: 218-221.

955

956 Pirbadian, S., Barchinger, S. E., Leung, K. M., Byun, H. S., Jangir, Y., Bouhenni, R. A., Reed, S. B.,

957 Romine, M. F., Saffarini, D. A., Shi, L., et al. (2014). Shewanella oneidensis MR-1 nanowires are outer

958 membrane and periplasmic extensions of the extracellular electron transport components. PNAS 111:

959 12883-12888.

960

961 Polz, M. F., Alm, E. J. and Hanage, W. P. (2013). Horizontal gene transfer and the evolution of bacterial

962 and archaeal population structure. Trends Genet. 29: 170-175.

963

964 Ranava, D., Backes, C., Karthikeyan, G., Ouari, O., Soric, A., Guiral, M., Cárdenas, M. L. and Giudici-

965 Orticoni, M. T. (2021). Metabolic exchange and energetic coupling between nutritionally stressed

966 bacterial species: role of quorum-sensing molecules. mBio 12: e02758-02720.

967

968 Rees, D. C., Johnson, E. and Lewinson, O. (2009). ABC transporters: The power to change. Nat. Rev.

969 Mol. Cell Biol.10: 218-227.

970

971 Reguera, G., McCarthy, K. D., Mehta, T., Nicoll, J. S., Tuominen, M. T. and Lovley, D. R. (2005).

972 Extracellular electron transfer via microbial nanowires. Nature 435: 1098-1101.

973

974 Remis, J. P., Wei, D., Gorur, A., Zemla, M., Haraga, J., Allen, S., Witkowska, H. E., Costerton, J. W.,

975 Berleman, J. E. and Auer, M. (2014). Bacterial social networks: Structure and composition of

976 Myxococcus xanthus outer membrane vesicle chains. Environ. Microbiol. 16: 598-610.

977

978 Ren, D., Madsen, J. S., Sørensen, S. J. and Burmølle, M. (2015). High prevalence of biofilm synergy

979 among bacterial soil isolates in cocultures indicates bacterial interspecific cooperation. ISME J. 9: 81-

980 89.

981

37
982 Rendueles, O. and Ghigo, J.-M. (2012). Multi-species biofilms: How to avoid unfriendly neighbors. FEMS

983 Microbiol. Rev. 36: 972-989.

984

985 Rickard, A. H., Gilbert, P., High, N. J., Kolenbrander, P. E. and Handley, P. S. (2003). Bacterial

986 coaggregation: An integral process in the development of multi-species biofilms. Trends Microbiol. 11:

987 94-100.

988

989 Russel, J., Roder, H. L., Madsen, J. S., Burmølle, M. and Sørensen, S. J. (2017). Antagonism correlates

990 with metabolic similarity in diverse bacteria. PNAS 114: 10684-10688.

991

992 Sah, G. P. and Wall, D. (2020). Kin recognition and outer membrane exchange (OME) in myxobacteria.

993 Curr. Opin. Microbiol. 56: 81-88.

994

995 Salles, J. F., Le Roux, X. and Poly, F. (2012). Relating phylogenetic and functional diversity among

996 denitrifiers and quantifying their capacity to predict community functioning. Front. Microbiol. 3: 209.

997

998 San Millan, A. and Maclean, R. C. (2017). Fitness costs of plasmids: A limit to plasmid transmission.

999 Microbiol. Spectr. 5: 5.5. 02.

1000

1001 Sandy, M. and Butler, A. (2009). Microbial iron acquisition: Marine and terrestrial siderophores. Chem.

1002 Rev. 109: 4580-4595.

1003

1004 Schwechheimer, C. and Kuehn, M. J. (2015). Outer-membrane vesicles from Gram-negative bacteria:

1005 Biogenesis and functions. Nat. Rev. Microbiol. 13: 605-619.

1006

1007 Sher, D., Thompson, J. W., Kashtan, N., Croal, L. and Chisholm, S. W. (2011). Response of

1008 Prochlorococcus ecotypes to co-culture with diverse marine bacteria. ISME J. 5: 1125-1132.

1009

1010 Shi, L., Dong, H., Reguera, G., Beyenal, H., Lu, A., Liu, J., Yu, H. Q. and Fredrickson, J. K. (2016).

1011 Extracellular electron transfer mechanisms between microorganisms and minerals. Nat. Rev. Microbiol.

1012 14: 651-662.

38
1013

1014 Shimoyama, T., Kato, S., Ishii, S. i. and Watanabe, K. (2009). Flagellum mediates symbiosis. Science

1015 323: 1574-1574.

1016

1017 Silverman, M. and Simon, M. I. (1977). Bacterial flagella. Annu. Rev. Microbiol. 31: 397-419.

1018

1019 Smith, P. and Schuster, M. (2019). Public goods and cheating in microbes. Curr. Biol. 29: R442-R447.

1020

1021 Sokolovskaya, O. M., Shelton, A. N. and Taga, M. E. (2020). Sharing vitamins: Cobamides unveil

1022 microbial interactions. Science 369.

1023

1024 Sorg, R. A., Lin, L., Van Doorn, G. S., Sorg, M., Olson, J., Nizet, V. and Veening, J.-W. (2016). Collective

1025 resistance in microbial communities by intracellular antibiotic deactivation. PLoS Biol. 14: e2000631.

1026

1027 Souza, D. P., Oka, G. U., Alvarez-Martinez, C. E., Bisson-Filho, A. W., Dunger, G., Hobeika, L.,

1028 Cavalcante, N. S., Alegria, M. C., Barbosa, L. R. and Salinas, R. K. (2015). Bacterial killing via a type

1029 IV secretion system. Nat. Commun. 6: 1-9.

1030

1031 Stams, A. J., De Bok, F. A., Plugge, C. M., Van Eekert, M. H., Dolfing, J. and Schraa, G. (2006).

1032 Exocellular electron transfer in anaerobic microbial communities. Environ. Microbiol.8: 371-382.

1033

1034 Stams, A. J. and Plugge, C. M. (2009). Electron transfer in syntrophic communities of anaerobic bacteria

1035 and archaea. Nat. Rev. Microbiol. 7: 568-577.

1036

1037 Strickland, M., Lauber, C., Fierer, N. and Bradford, M. A. (2009). Testing the functional significance of

1038 microbial community composition. Ecology 90: 441-451.

1039

1040 Stempler, O., Baidya, A. K., Bhattacharya, S., Malli Mohan, G. B., Tzipilevich, E., Sinai, L., Mamou, G.

1041 and Ben-Yehuda, S. (2017). Interspecies nutrient extraction and toxin delivery between bacteria. Nat.

1042 commun. 8: 1-9.

1043

39
1044 Summers, Z. M., Fogarty, H. E., Leang, C., Franks, A. E., Malvankar, N. S. and Lovley, D. R. (2010).

1045 Direct exchange of electrons within aggregates of an evolved syntrophic coculture of anaerobic bacteria.

1046 Science 330: 1413-1415.

1047

1048 Tait, K. and Sutherland, I. (2002). Antagonistic interactions amongst bacteriocin-producing enteric

1049 bacteria in dual species biofilms. J. Appl. Microbiol. 93: 345-352.

1050

1051 Tashiro, Y., Hasegawa, Y., Shintani, M., Takaki, K., Ohkuma, M., Kimbara, K. and Futamata, H. (2017).

1052 Interaction of bacterial membrane vesicles with specific species and their potential for delivery to target

1053 cells. Front. Microbiol. 8: 571.

1054

1055 Taylor, J. R. and Stocker, R. (2012). Trade-offs of chemotactic foraging in turbulent water. Science 338:

1056 675-679.

1057

1058 Toyofuku, M., Morinaga, K., Hashimoto, Y., Uhl, J., Shimamura, H., Inaba, H., Schmitt-Kopplin, P., Eberl,

1059 L. and Nomura, N. (2017). Membrane vesicle-mediated bacterial communication. ISME J. 11: 1504-

1060 1509.

1061

1062 Toyofuku, M., Nomura, N. and Eberl, L. (2019). Types and origins of bacterial membrane vesicles. Nat.

1063 Rev. Microbiol. 17: 13-24.

1064

1065 Troselj, V., Cao, P. and Wall, D. (2018). Cell-cell recognition and social networking in bacteria. Environ.

1066 Microbiol.20: 923-933.

1067

1068 Valdes, A. M., Walter, J., Segal, E. and Spector, T. D. (2018). Role of the gut microbiota in nutrition and

1069 health. The BMJ 361: k2179.

1070

1071 van Tatenhove-Pel, R. J., de Groot, D. H., Bisseswar, A. S., Teusink, B. and Bachmann, H. (2021).

1072 Population dynamics of microbial cross-feeding are determined by co-localization probabilities and

1073 cooperation-independent cheater growth. ISME J. 15: 3050-3061.

1074

40
1075 van Tatenhove-Pel, R. J., Rijavec, T., Lapanje, A., van Swam, I., Zwering, E., Hernandez-Valdes, J. A.,

1076 Kuipers, O. P., Picioreanu, C., Teusink, B. and Bachmann, H. (2021). Microbial competition reduces

1077 metabolic interaction distances to the low µm-range. ISME J.l 15: 688-701.

1078

1079 Vassallo, C., Cao, P., Conklin, A., Finkelstein, H., Hayes, C. and Wall, D. (2018). Correction: Infectious

1080 polymorphic toxins delivered by outer membrane exchange discriminate kin in myxobacteria. eLife 7:

1081 e37049.

1082

1083 Venail, P. A., Narwani, A., Fritschie, K., Alexandrou, M. A., Oakley, T. H., Cardinale, B. J. and Cahill, J.

1084 (2014). The influence of phylogenetic relatedness on species interactions among freshwater green

1085 algae in a mesocosm experiment. J. Ecol. 102: 1288-1299.

1086

1087 Venail, P. A. and Vives, M. J. (2013). Phylogenetic distance and species richness interactively affect the

1088 productivity of bacterial communities. Ecology 94: 2529-2536.

1089

1090 Vicuña, R. (1988). Bacterial degradation of lignin. Enzyme Microb. Technol. 10: 646-655.

1091

1092 Vijay, A. and Valdes, A. M. (2022). Role of the gut microbiome in chronic diseases: A narrative review.

1093 Eur. J. Clin. Nutr. 76: 489-501.

1094

1095 Virolle, C., Goldlust, K., Djermoun, S., Bigot, S. and Lesterlin, C. (2020). Plasmid transfer by conjugation

1096 in gram-negative bacteria: From the cellular to the community level. Genes 11: 1239.

1097

1098 Wagg, C., Hautier, Y., Pellkofer, S., Banerjee, S., Schmid, B. and van der Heijden, M. G. (2021).

1099 Diversity and asynchrony in soil microbial communities stabilizes ecosystem functioning. eLife 10:

1100 e62813.

1101

1102 Walker, D. J. F., Nevin, K. P., Holmes, D. E., Rotaru, A. E., Ward, J. E., Woodard, T. L., Zhu, J., Ueki,

1103 T., Nonnenmann, S. S., McInerney, M. J., et al. (2020). Syntrophus conductive pili demonstrate that

1104 common hydrogen-donating syntrophs can have a direct electron transfer option. ISME J. 14: 837-846.

1105

41
1106 Wang, F., Gu, Y., O'Brien, J. P., Yi, S. M., Yalcin, S. E., Srikanth, V., Shen, C., Vu, D., Ing, N. L.,

1107 Hochbaum, A. I., et al. (2019). Structure of microbial nanowires reveals stacked hemes that transport

1108 electrons over micrometers. Cell 177: 361-369 e310.

1109

1110 Wang, J., Karnati, P. K., Takacs, C. M., Kowalski, J. C. and Derbyshire, K. M. (2005). Chromosomal

1111 DNA transfer in Mycobacterium smegmatis is mechanistically different from classical Hfr chromosomal

1112 DNA transfer. Mol. Microbiol. 58: 280-288.

1113

1114 Wegener, G., Krukenberg, V., Riedel, D., Tegetmeyer, H. E. and Boetius, A. (2015). Intercellular wiring

1115 enables electron transfer between methanotrophic archaea and bacteria. Nature 526: 587-590.

1116

1117 Wei, X., Vassallo, C. N., Pathak, D. T. and Wall, D. (2014). Myxobacteria produce outer membrane-

1118 enclosed tubes in unstructured environments. J. bacteriol. 196: 1807-1814.

1119

1120 Woith, E., Fuhrmann, G. and Melzig, M. F. (2019). Extracellular vesicles-connecting kingdoms. Int. J.

1121 Mol. Sci. 22: 5695

1122

1123 Yawata, Y., Carrara, F., Menolascina, F. and Stocker, R. (2020). Constrained optimal foraging by marine

1124 bacterioplankton on particulate organic matter. PNAS 117: 25571-25579.

1125

1126 Yurtsev, E. A., Conwill, A. and Gore, J. (2016). Oscillatory dynamics in a bacterial cross-protection

1127 mutualism. PNAS 113: 6236-6241.

1128

1129 Zhang, Z., Du, C., de Barsy, F., Liem, M., Liakopoulos, A., van Wezel, G. P., Choi, Y. H., Claessen, D.

1130 and Rozen, D. E. (2020). Antibiotic production in Streptomyces is organized by a division of labor

1131 through terminal genomic differentiation. Sci. Adv. 6: eaay5781.

1132

1133 Zhu, H., Conibear, T. C., Bandara, R., Aliwarga, Y., Stapleton, F. and Willcox, M. D. (2006). Type III

1134 secretion system-associated toxins, proteases, serotypes, and antibiotic resistance of Pseudomonas

1135 aeruginosa isolates associated with keratitis. Curr. eye Res. 31: 297-306.

1136

42
1137 Zinder, N. D. and Lederberg, J. (1952). Genetic exchange in Salmonella. J. bacteriol. 64: 679-699.

43
Supplementary information

Determinants of synergistic cell-cell interactions in bacteria

Benedikt Pauli1‡, Shiksha Ajmera1‡, Christian Kost1,2*

1 Department of Ecology, School of Biology/Chemistry, Osnabrück University, 49076

Osnabrück, Germany

2 Center of Cellular Nanoanalytics CellNanOs, Osnabrück University, Barbarastrasse

11, 49076 Osnabrück, Germany

‡ These authors contributed equally to this work.

* For correspondence: christiankost@gmail.com

1
Supplementary Table 1: Examples of synergistic benefits exchanged by bacteria.

Exchanged Traded Transfer Within Between Species Reference

benefit commodity mechanism species species number
Acetate, Diffusion  Escherichia coli, 1
Metabolites methionine, Salmonella enterica,
ammonia Methylobacterium
extorquens
Acetate, Diffusion  Desulfovibrio vulgaris, 2
carbon Methanococcus
dioxide, maripaludis
hydrogen
Organic Diffusion  Escherichia coli, 3
acids, Rhodopseudomonas
ammonia palustris
Vitamins Diffusion  Lobomonas rostrate, 4
Mesorhizobium loti
Nucleotides Diffusion  Saccharomyces 5
cerevisiae
Amino acids, Nanotubes   Acinetobacter baylyi, 6
proteins Escherichia coli
Amino acids Cell-cell   Acinetobacter baylyi, 7
attachment Escherichia coli
Amino acids Cell-cell  Escherichia coli 8
attachment
ATP Cell-cell   Ignicoccus hospitalis, 9
contact Nanoarchaeum
observed equitans
Industry Diffusion  Escherichia coli 10
intermediates
coniferol,
caffeate
Cobamides Active  Several bacterial and 11
transport eukaryotic species
Glucose as Diffusion,  Lactococus lactis 12
carbon source cell-cell
attachment
Vesicles as Vesicles  Prochlorococcus 13
carbon source
Biofilm as Biofilm  Cyanobacterium sp. 14
carbon source
Carbon and Cell-cell  Azotobacter vinelandii, 15
Nitrogen attachment Bacillus licheniformis,
source Paenibacillus
curdlanolyticus
Carbon and Physical  Cyanobacterium sp. 16
Nitrogen contact
source observed
Proteins Vesicles   Myxococcus xanthus 17
Proteins Cell-cell  Clostridium 18
attachment acetobutylicum,
Desulfovibrio vulgaris
Hildenborough
Membrane Cell-cell   Myxococcus xanthus 19
proteins attachment
Membrane Cell-cell   Myxococcus xanthus 20
proteins attachment
Electrons Physical  Cable bacteria 21
Electrons contact
Electrons e-Pili,  Geobacter 22
nanowires, metallireducens,
physical Geobacter
contact sulfurreducens
Electrons e-Pili  Syntrophus 23
aciditrophicus,

2
 Geobacter
sulfurreducens
Electrons Nanowires  Shewanella oneidensis 24
Electrons Nanowires  Lysinibacillus varians 25
Electrons Diffusion,   Several species 26
nanowires,
cell-cell
attachment
Electrons Nanowires  ANME-1 archaea, 27
SRB HotSeep-1
Electrons Nanowires  Geobacter 28
sulfurreducens
Electrons Conductive  Geobacter 29
minerals sulfurreducens,
Thiobacillus
denitrificans
Electrons Conductive  Geobacter 30
minerals metallireducens,
Methanosarcina barkeri
Antibiotic Diffusion  Lactococcus lactis, gut 31
Services protection, microbiota
β-lactam
Antibiotic Diffusion  Streptococcus 32
protection, pneumoniae
chlorampheni
col
Siderophore Diffusion  Marinobacter sp., 33
coccolithophores,
dinoflagellates
pH change Diffusion  Acetobacter sp., 34
Lactobacillus plantarum
Cellulose Diffusion  Cellulomonas sp., 35
degradation Rhodopseudomonas
capsulata
Siderophore Active  Pseudomonas sp. 36
transport
Hitchhiking Flagella  Streptomyces spores, 37
attachment gram-positive and
negative bacteria
Aggregate Flagella  Pelotomaculum 38
formation attachment thermopropionicum,
Methanothermobacter
thermautotrophicus,
21 methanogens
genera
Aggregate Flagella  Pelotomaculum 39
formation attachment thermopropionicum,
Methanothermobacter
thermautotrophicus
Aggregate Flagella  Pelotomaculum 40
formation attachment thermopropionicum,
Methanothermobacter
thermautotrophicus
Adhesion Flagella  Escherichia coli 41
attachment
CAI-1 and AI- Diffusion  Vibrio cholerae 42
Information 2
N- Vesicles  Paracoccus sp. 43
hexadecanoyl
-L-
homoserine
lactone
Signalling Nanotubes   Anaerobic sludge 44
molecules microbiota

3
 Quorum Diffusion  Vibrio fischeri 45
sensing
Quorum Diffusion   Streptococci 46
sensing
Quorum Diffusion,   Several bacterial 47
sensing active species
transport
Quorum Diffusion,   Several bacterial 48
sensing active species
transport
Bacterial Diffusion   Bacillus subtilis, 49
volatile Escherichia coli,
ammonia Pseudomonas
aeruginosa,
Staphylococcus aureus
Chromosomal Conjugation   Mycobacterium 50
DNA pili smegmatis
DNA Vesicles   Alteromonas sp., 13
Halomonas sp.,
Prochlorococcus sp.
Plasmid Conjugation   Gram-negative bacteria 51
pili
Plasmid Nanotubes   Bacillus subtilis, 52
Staphylococcus
aureus,
Escherichia coli

Supplementary References
1. Harcombe, W. R., Riehl, W. J., Dukovski, I., Granger, B. R., Betts, A., Lang, A. H., Bonilla, G., Kar,
A., Leiby, N. and Mehta, P. 2014. Metabolic resource allocation in individual microbes determines
ecosystem interactions and spatial dynamics. Cell Rep. 7: 1104-1115.

2. Hillesland, K. L. and Stahl, D. A. 2010. Rapid evolution of stability and productivity at the origin of
a microbial mutualism. PNAS 107: 2124-2129.

3. LaSarre, B., McCully, A. L., Lennon, J. T. and McKinlay, J. B. 2017. Microbial mutualism dynamics
governed by dose-dependent toxicity of cross-fed nutrients. ISME J. 11: 337-348.

4. Kazamia, E., Czesnick, H., Nguyen, T. T. V., Croft, M. T., Sherwood, E., Sasso, S., Hodson, S. J.,
Warren, M. J. and Smith, A. G. 2012. Mutualistic interactions between vitamin B12‐dependent algae
and heterotrophic bacteria exhibit regulation. Environ. Microbiol. 14: 1466-1476.

5. Shou, W., Ram, S. and Vilar, J. M. 2007. Synthetic cooperation in engineered yeast populations.
PNAS 104: 1877-1882.

6. Pande, S., Shitut, S., Freund, L., Westermann, M., Bertels, F., Colesie, C., Bischofs, I. B. and Kost,
C. 2015. Metabolic cross-feeding via intercellular nanotubes among bacteria. Nat. Commun. 6:
6238.

7. Pande, S., Kaftan, F., Lang, S., Svatos, A., Germerodt, S. and Kost, C. 2016. Privatization of
cooperative benefits stabilizes mutualistic cross-feeding interactions in spatially structured
environments. ISME J. 10: 1413-1423.

8. Marchal, M., Goldschmidt, F., Derksen-Muller, S. N., Panke, S., Ackermann, M. and Johnson, D.
R. 2017. A passive mutualistic interaction promotes the evolution of spatial structure within
microbial populations. BMC Evol. Biol. 17: 106.

9. Huber, H., Küper, U., Daxer, S. and Rachel, R. 2012. The unusual cell biology of the
hyperthermophilic Crenarchaeon Ignicoccus hospitalis. Antonie Leeuwenhoek 102: 203-219.

4
10. Li, X., Zhou, Z., Li, W., Yan, Y., Shen, X., Wang, J., Sun, X. and Yuan, Q. 2022. Design of stable
and self-regulated microbial consortia for chemical synthesis. Nat. Commun. 13: 1-9.

11. Sokolovskaya, O. M., Shelton, A. N. and Taga, M. E. 2020. Sharing vitamins: Cobamides unveil
microbial interactions. Science 369.

12. van Tatenhove-Pel, R. J., Rijavec, T., Lapanje, A., van Swam, I., Zwering, E., Hernandez-Valdes,
J. A., Kuipers, O. P., Picioreanu, C., Teusink, B. and Bachmann, H. 2021. Microbial competition
reduces metabolic interaction distances to the low µm-range. ISME J. 15: 688-701.

13. Biller, S. J., Schubotz, F., Roggensack, S. E., Thompson, A. W., Summons, R. E. and Chisholm,
S. W. 2014. Bacterial vesicles in marine ecosystems. Science 343: 183-186.

14. Stuart, R. K., Mayali, X., Lee, J. Z., Craig Everroad, R., Hwang, M., Bebout, B. M., Weber, P. K.,
Pett-Ridge, J. and Thelen, M. P. 2016. Cyanobacterial reuse of extracellular organic carbon in
microbial mats. ISME J. 10: 1240-1251.

15. Kim, H. J., Boedicker, J. Q., Choi, J. W. and Ismagilov, R. F. 2008. Defined spatial structure
stabilizes a synthetic multispecies bacterial community. PNAS 105: 18188-18193.

16. Herrero, A., Stavans, J. and Flores, E. 2016. The multicellular nature of filamentous heterocyst-
forming cyanobacteria. FEMS Microbiol. Rev.40: 831-854.

17. Berleman, J. E., Allen, S., Danielewicz, M. A., Remis, J. P., Gorur, A., Cunha, J., Hadi, M. Z.,
Zusman, D. R., Northen, T. R., Witkowska, H. E. et al. 2014. The lethal cargo of Myxococcus
xanthus outer membrane vesicles. Front. Microbiol. 5: 474.

18. Benomar, S., Ranava, D., Cardenas, M. L., Trably, E., Rafrafi, Y., Ducret, A., Hamelin, J., Lojou,
E., Steyer, J. P. and Giudici-Orticoni, M. T. 2015. Nutritional stress induces exchange of cell
material and energetic coupling between bacterial species. Nat. Commun. 6: 6283.

19. Sah, G. P. and Wall, D. 2020. Kin recognition and outer membrane exchange OME in
myxobacteria. Curr. Opin. Microbiol. 56: 81-88.

20. Cao, P., Dey, A., Vassallo, C. N. and Wall, D. 2015. How myxobacteria cooperate. J. Mol. Biol.
427: 3709-3721.

21. Pfeffer, C., Larsen, S., Song, J., Dong, M., Besenbacher, F., Meyer, R. L., Kjeldsen, K. U.,
Schreiber, L., Gorby, Y. A. and El-Naggar, M. Y. 2012. Filamentous bacteria transport electrons
over centimetre distances. Nature 491: 218-221.

22. Summers, Z. M., Fogarty, H. E., Leang, C., Franks, A. E., Malvankar, N. S. and Lovley, D. R. 2010.
Direct exchange of electrons within aggregates of an evolved syntrophic coculture of anaerobic
bacteria. Science 330: 1413-1415.

23. Walker, D. J. F., Nevin, K. P., Holmes, D. E., Rotaru, A. E., Ward, J. E., Woodard, T. L., Zhu, J.,
Ueki, T., Nonnenmann, S. S., McInerney, M. J. et al. 2020. Syntrophus conductive pili demonstrate
that common hydrogen-donating syntrophs can have a direct electron transfer option. ISME J. 14:
837-846.

24. Pirbadian, S., Barchinger, S. E., Leung, K. M., Byun, H. S., Jangir, Y., Bouhenni, R. A., Reed, S.
B., Romine, M. F., Saffarini, D. A., Shi, L. et al. 2014. Shewanella oneidensis MR-1 nanowires are
outer membrane and periplasmic extensions of the extracellular electron transport components.
PNAS 111: 12883-12888.

25. Yang, Y., Wang, Z., Gan, C., Klausen, L. H., Bonné, R., Kong, G., Luo, D., Meert, M., Zhu, C. and
Sun, G. 2021. Long-distance electron transfer in a filamentous Gram-positive bacterium. Nat.
Commun. 12: 1-9.

26. Shi, L., Dong, H., Reguera, G., Beyenal, H., Lu, A., Liu, J., Yu, H. Q. and Fredrickson, J. K. 2016.
Extracellular electron transfer mechanisms between microorganisms and minerals. Nat. Rev.
Microbiol. 14: 651-662.

5
27. Wegener, G., Krukenberg, V., Riedel, D., Tegetmeyer, H. E. and Boetius, A. 2015. Intercellular
wiring enables electron transfer between methanotrophic archaea and bacteria. Nature 526: 587-
590.

28. Wang, F., Gu, Y., O'Brien, J. P., Yi, S. M., Yalcin, S. E., Srikanth, V., Shen, C., Vu, D., Ing, N. L.,
Hochbaum, A. I. et al. 2019. Structure of microbial nanowires reveals stacked hemes that transport
electrons over micrometers. Cell 177: 361-369.

29. Kato, S., Hashimoto, K. and Watanabe, K. 2012. Microbial interspecies electron transfer via electric
currents through conductive minerals. PNAS 109: 10042-10046.

30. Igarashi, K., Miyako, E. and Kato, S. 2020. Direct interspecies electron transfer mediated by
graphene oxide-based materials. Front. Microbiol. 10: 3068.

31. Cubillos-Ruiz, A., Alcantar, M. A., Donghia, N. M., Cárdenas, P., Avila-Pacheco, J. and Collins, J.
J. 2022. An engineered live biotherapeutic for the prevention of antibiotic-induced dysbiosis. Nat.
Biomed. Eng. 1-12.

32. Sorg, R. A., Lin, L., Van Doorn, G. S., Sorg, M., Olson, J., Nizet, V. and Veening, J.-W. 2016.
Collective resistance in microbial communities by intracellular antibiotic deactivation. PLoS Biol.
14: e2000631.

33. Amin, S. A., Green, D. H., Hart, M. C., Küpper, F. C., Sunda, W. G. and Carrano, C. J. 2009.
Photolysis of iron-siderophore chelates promotes bacterial-algal mutualism. PNAS 106: 17071-
17076.

34. Aranda-Díaz, A., Obadia, B., Dodge, R., Thomsen, T., Hallberg, Z. F., Güvener, Z. T., Ludington,
W. B. and Huang, K. C. 2020. Bacterial interspecies interactions modulate pH-mediated antibiotic
tolerance. eLife 9: e51493.

35. Odom, J. M. and Wall, J. D. 1983. Photoproduction of H 2 from cellulose by an anaerobic bacterial
coculture. Applied and Environ. Microbiol. 45: 1300-1305.

36. Butaite, E., Kramer, J. and Kummerli, R. 2021. Local adaptation, geographical distance, and
phylogenetic relatedness: Assessing the drivers of siderophore-mediated social interactions in
natural bacterial communities. J. Evol. Biol. 34: 1266-1278.

37. Muok, A. R., Claessen, D. and Briegel, A. 2021. Microbial hitchhiking: How Streptomyces spores
are transported by motile soil bacteria. ISME J. 15: 2591-2600.

38. Marx, C. J. 2009. Getting in touch with your friends. Science 324: 1150-1151.

39. Shimoyama, T., Kato, S., Ishii, S. i. and Watanabe, K. 2009. Flagellum mediates symbiosis.
Science 323: 1574-1574.

40. Ishii, S. i., Kosaka, T., Hori, K., Hotta, Y. and Watanabe, K. 2005. Coaggregation facilitates
interspecies hydrogen transfer between Pelotomaculum thermopropionicum and
Methanothermobacter thermautotrophicus. Appl. Environ. Microbiol.71: 7838-7845.

41. Friedlander, R. S., Vlamakis, H., Kim, P., Khan, M., Kolter, R. and Aizenberg, J. 2013. Bacterial
flagella explore microscale hummocks and hollows to increase adhesion. PNAS 110: 5624-5629.

42. Bridges, A. A. and Bassler, B. L. 2019. The intragenus and interspecies quorum-sensing
autoinducers exert distinct control over Vibrio cholerae biofilm formation and dispersal. PLoS Biol.
17: e3000429.

43. Toyofuku, M., Morinaga, K., Hashimoto, Y., Uhl, J., Shimamura, H., Inaba, H., Schmitt-Kopplin, P.,
Eberl, L. and Nomura, N. 2017. Membrane vesicle-mediated bacterial communication. ISME J 11:
1504-1509.

6
 44. John, M., Trzcinski, A. P., Zhou, Y. and Ng, W. J. 2017. Microbial stress mediated intercellular
nanotubes in an anaerobic microbial consortium digesting cellulose. Sci. Rep. 7: 1-14.

45. Pérez, P. D. and Hagen, S. J. 2010. Heterogeneous response to a quorum-sensing signal in the
luminescence of individual Vibrio fischeri. PLoS One 5: e15473.

46. Cvitkovitch, D. G., Li, Y.-H. and Ellen, R. P. 2003. Quorum sensing and biofilm formation in
Streptococcal infections. J. Clin. Investig. 112: 1626-1632.

47. Grandclement, C., Tannieres, M., Morera, S., Dessaux, Y. and Faure, D. 2016. Quorum quenching:
Role in nature and applied developments. FEMS Microbiol. Rev. 40: 86-116.

48. Abisado, R. G., Benomar, S., Klaus, J. R., Dandekar, A. A. and Chandler, J. R. 2018. Bacterial
quorum sensing and microbial community interactions. mBio 9.

49. Bernier, S. P., Létoffé, S., Delepierre, M. and Ghigo, J. M. 2011. Biogenic ammonia modifies
antibiotic resistance at a distance in physically separated bacteria. Mol. Microbiol. 81: 705-716.

50. Wang, J., Karnati, P. K., Takacs, C. M., Kowalski, J. C. and Derbyshire, K. M. 2005. Chromosomal
DNA transfer in Mycobacterium smegmatis is mechanistically different from classical Hfr
chromosomal DNA transfer. Mol. Microbiol. 58: 280-288.

51. Virolle, C., Goldlust, K., Djermoun, S., Bigot, S. and Lesterlin, C. 2020. Plasmid transfer by
conjugation in gram-negative bacteria: From the cellular to the community level. Genes 11: 1239.

52. Dubey, G. P. and Ben-Yehuda, S. 2011. Intercellular nanotubes mediate bacterial communication.
Cell 144: 590-600.

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