Interspecies interactions determine growth dynamics of biopolymer degrading populations in microbial communities

Microbial communities perform essential ecosystem functions such as the remineralization of organic carbon that exists as biopolymers. The first step in mineralization is performed by biopolymer degraders, which harbor enzymes that can break down polymers into constituent oligo- or monomeric forms. The released nutrients not only allow degraders to grow, but also promote growth of cells that either consume the breakdown products, i.e., exploiters, or consume metabolites released by the degraders, i.e., scavengers. It is currently not clear how such remineralizing communities assemble at the microscale – how interactions between the different guilds influence their growth and spatial distribution, and hence the development and dynamics of the community. Here we address this knowledge gap by studying marine microbial communities that grow on the abundant marine biopolymer alginate. We used batch growth assays and microfluidics coupled to time-lapse microscopy to quantitatively investigate growth and spatial distribution of single cells. We found that the presence of exploiters or scavengers alters the spatial distribution of degrader cells. In general, exploiters and scavengers – which we collectively refer to as consumer cells – slowed down the growth of degrader cells. In addition, coexistence with consumers altered the production of the extracellular enzymes that breakdown polymers by degrader cells. Our findings reveal that ecological interactions by non-degrading community members have a profound impact on the functions of microbial communities that remineralize carbon biopolymers in nature. Importance Biopolymers are the most abundant source of carbon on the planet and their breakdown by microbial degraders releases metabolic products that allow cross-feeding cells to grow and fuel the assembly of microbial communities. While it is known that the growth of degraders can facilitate growth of downstream cross-feeders in microbial communities, it has remained generally unclear if and how cross-feeders influence growth of degraders. Bridging this knowledge gap is important because degraders primarily drive the remineralization of carbon, a central process in the carbon cycle. We found that the presence cross-feeders can influence the growth of degraders by altering their spatial distribution as well as extracellular breakdown enzyme activity. Our study sheds light on the role of microbial interactions in shaping the rate of carbon remineralization in nature.


Introduction: 88
Heterotrophic microbial communities drive the remineralization of carbon, which 89 predominantly exist as biopolymers like chitin(1), alginate(2), cellulose(3) and xylan(4) 90 in natural ecosystems, and thus drive a central step in the biogeochemical cycling of 91 carbon(5-7). Within these communities, multiple microbial guilds coexist and engage 92 in metabolic interactions. A key challenge of microbial ecology is to understand how 93 these metabolic interactions influence the rate of carbon remineralization, which is an 94 ecosystem function of major interest (8-11). The assembly of these communities 95 follows intuitive rules (1). The first step in remineralization is carried out by specialized 96 degraders that express and secrete hydrolytic enzymes that degrade biopolymers. 97 The secretion of these enzymes leads to the formation of breakdown products. These 98 products support the growth of the degraders and are also released into the 99 environment, alongside with metabolites released by the growing degraders. The 100 release of these metabolites creates niches for the growth of cross-feeder taxa that 101 lack the ability to produce biopolymer-degrading enzymes but can utilize breakdown 102 products (i.e. "exploiters"), or utilize other metabolites released from degraders and 103 exploiter (i.e. "scavengers"; (9, 10, 12, 13)). Since degrader cells are positioned at the 104 beginning of these food chains, their growth influences the assembly of downstream 105 cross-feeders in biopolymer degrading communities (1,10,13). Therefore, any 106 ecological interaction that impacts the growth of degrader cells is expected to impact 107 the rate of carbon remineralization but the magnitude of these impacts is currently 108

unknown. 109
Degrader cells often aggregate while growing on polysaccharides like chitin(14), 110 alginate(15-17) or xylan(4, 18). Previous experimental and computational studies have established that aggregation, by increasing local cell density, allows degrader 112 cells to benefit from the polysaccharide breakdown activities of neighboring cells (4, 113 15, 19). However, it is generally unclear how growth and collective behaviors of 114 degraders are influenced by the coexistence with cross-feeding species. Since 115 biopolymer breakdown and metabolic byproduct release at the microscale are a 116 consequence of the activities of degraders, it is important to investigate the impacts of 117 cross-feeding at the microscale on degrader taxa, in order to develop a better 118 understanding on how interactions impact the growth of biopolymer degrading taxa 119 and ultimately the rate of remineralization. 120 Here, we sought to address these knowledge gaps using simple two-species microbial 121 communities that degrade alginate, an abundant biopolymer in marine ecosystems, 122 on which the individual behavior of degraders is well characterized(20). We used a 123 combination of batch growth assays and microfluidics coupled to time-lapse 124 microscopy along with spatial analyses in order to quantitatively determine growth and 125 aggregation behaviors of degrader cells when coexisting with cross-feeder cells. We 126 find that the presence of cross-feeder cells influences the growth of degrader cells, 127 indicating that the activity of cross-feeders can substantially alter the function of 128 microbial communities.

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The bars indicate the mean whereas the error bars indicate the standard deviation (sd). Asterisks and 149 'ns' indicate statistically significant or non-significant comparisons, respectively, amongst groups (in B A3M17 cells lack alginate lyases but have a set of genes that could potentially confer 162 the ability to import and utilize simpler oligo-or monomeric products resulting from 163 alginate degradation(2, 10). In line with these predictions, we found that only ZF270 164 cells grew on alginate, whereas the cross-feeders 1F187 and A3M17 could not grow 165 on alginate ( Figure S1). We then grew strains on enzymatically hydrolyzed alginate, 166 i.e. d-alginate, thus creating a scenario where cross-feeders experience byproducts 167 released from alginate breakdown. We found that 1F187 grew to substantially higher 168 levels on d-alginate compared to alginate, whereas A3M17 did not benefit from the 169 hydrolysis products ( Figure S1). These observations suggest that while 1F187 can 170 indeed cross-feed on byproducts of alginate breakdown, A3M17 cannot cross-feed on 171 breakdown byproducts despite encoding potential genes for uptake and utilization. 172

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Based on these growth results we constructed simple two-species communities 174 consisting of the degrader ZF270 and either the oligo-saccharide exploiter 1F187 or the byproduct scavenger A3M17 ( Figure 1A). We then asked if presence of degraders 176 allowed cross-feeders to grow. In addition, this growth assay enabled the 177 quantification of any beneficial or detrimental effects of cross-feeder cells on degrader 178 cells. When we grew degrader and cross-feeder cells in isolation or together on 179 alginate in shaking flasks, we found that both cross-feeding strains 1F187 ( Figure 1B  Cross-feeders can decrease the growth of degraders by consuming metabolites that 195 represent nutrients for degraders, thus reducing the availability of these for degraders, 196 or by producing metabolites that inhibit the growth of degraders(26, 28). Conversely, 197 cross-feeders can increase the growth of degraders by utilizing metabolites that inhibit 198 the growth of degrader cells (13, 24) or by producing metabolites that support degrader growth. To understand the effect of compounds secreted by cross-feeders on the 200 growth of degrader cells, we grew cross-feeder cells, harvested the spent media and 201 grew degraders on this spent-media. Since cross-feeders do not grow on alginate, we 202 grew them on substrates permissive to cross-feeder growth. Oligomer-exploiting 203 1F187 cells were grown on d-alginate for 36 h. A3M17 cells, which scavenge 204 byproducts and did not grow on alginate or d-alginate ( Figure S1), were grown on 205 alginate supplemented with 0.1% marine broth for 36 h. The spent medium in either 206 case was harvested to remove cross-feeder cells and used to monitor growth of 207 degrader cells (Figure 2A and B). The growth of degraders on spent-medium was then 208 compared to the growth of degraders on spent-medium produced by growing degrader 209 cells on cognate fresh medium (Figure 2A       Since the presence of cross-feeders alters the spatial behaviors of degrader cells, and 297 the growth of degrader cells on polymers depends on increased cell densities(4, 17), 298 we expected interactions with cross-feeders to alter growth dynamics of degraders. 299 To quantify these effects, we measured the single-cell growth rates of ZF270 cells that 300 were grown on alginate in the absence or presence of either cross-feeding cell-type

Since the presence of cross-feeders alters the growth dynamics of degrader cells it is 357
plausible that the activity of alginate lyases, enzymes that mediate breakdown of 358 alginate, is also altered. In ZF270 cells, alginate lyases are secreted 359 extracellularly(17). Therefore, quantifying the activity of alginate lyases enabled the  Our findings indicate that cross-feeding, which is a prevalent phenomenon in natural 387 microbial communities(11), can alter the growth of species that remineralize carbon 388 biopolymers. It is known that biopolymer degrading bacteria can alter their surface 389 association in response to changes in environmental nutrient composition(4, 22, 30). 390 Our findings indicate that differences in collective behaviors including the spatial 391 distribution of cells can also arise as a consequence of species interactions. These 392 observations suggest that degraders not only structure microbial food-chains but their 393 activity is also shaped by downstream cross-feeding species.

Spent-medium experiments 476
To generate spent-medium of degraders, Vibrio cyclitrophicus ZF270 cells 477 (∼10 5 CFUs ml −1 ) were grown in 10 mL TR medium with 0.1% alginate for 36 hours. and experience the medium that the diffused through the lateral flow channels. 498 Imaging was performed using IX83 inverted microscope systems (Olympus, Japan) with automated stage controller (Marzhauser Wetzlar, Germany), shutter, and laser-500 based autofocus system (Olympus ZDC 2). Chambers were imaged in parallel on the 501 same PDMS chip, and phase-contrast and fluorescent (mKate2 and/or mCitrine) 502 images of each position were taken every 8 or 10 min. The microscopy unit and PDMS 503 chip was maintained at 25 °C using a cellVivo microscope incubation system (Pecon 504 GmbH, Germany). 505 506 Alginate Lyase assay. 507 We adapted a previously described agarose plate based assay (39) to test the ability 508 of monocultures and cocultures to secrete alginate lyases. For each strain, cultures 509 were growth for 18h in MB medium and 1 ml of cell suspension was centrifuged (13000 510 rpm for 2mins) in a 2ml microfuge tube. The supernatant was discarded and the cell-511 pellet was subject to two rounds of washing with TR medium without any carbon 512 source. The cell pellet was suspended in 1ml of TR medium without carbon source 513 and the optical density measured and adjusted to 0.1OD. For ZF270 monocultures 514 50µl of 0.1OD culture, or for cocultures 50µl of degrader and 50µl of cross-feeder 515 cultures were mixed and spotted on plates that were made using TR medium 516 containing 0.1% (w/v) alginate (Sigma Aldrich) and 1% agarose (Applichem). Colonies 517 were allowed to grow for 30h at 25°C and then the plates were flooded with 2%. 518 Gram's Iodine (Sigma Aldrich). The excess iodine was discarded and the imaged 519 using an iPhone 12 camera. If cells secreted alginate lyases, then a distinct clearance 520 zone was formed, the diameter of which was measured using a standard ruler. 521 522 523

Image analysis 525
Cells within microscopy mages were segmented using a custom built Python based 526 (v3.7) segmentation workflow and tracked with SuperSegger(40). The output of 527 segmentation and tracking were processed using Matlab v2017b or newer and R v4. 528 Phase contrast channel images were used for alignment following which fluorescence 529 channel images were used for segmentation, tracking and linking. Images were 530 cropped at the boundaries of each microfluidic chamber. Growth properties and spatial 531 locations were directly derived from the downstream processing tools of SuperSegger 532 (gateTool and superSeggerViewer). Spatial distances between cells (Fig. 3E) were 533 computed from segmentation data using the R package spatstat(41). 534 535

Datasets and statistical analysis 536
All batch experiments were replicated 3-6 times. Growth curves were analyzed in 537 Python v3.7 using the Amiga package(42) and GraphPad Prism v8 (GraphPad 538 Software, USA). The microscopy dataset set consists of eight, nine and eight 539 chambers, respectively for ZF270, ZF270+1F187 and ZF270 + A3M17. These are 540 grouped into three biological replicates wherein each biological replicate is fed by 541 media through a unique channel in a microfluidic chip. Cells with negative growth rates 542 were excluded from the analysis after visual curation, and represent artefacts, 543 mistakes in linking during the segmentation or tracking process or non-growing 544 deformed cells. Each chamber was treated as an independent. Each figure depicts 545 means or medians of all chambers for each condition. Pre-existing linear or 546 exponential regression models in GraphPad Prism v 8.0 (GraphPad Software, USA) 547 were applied to determine relationships between independent measures such as: 548 number of cells versus time (Fig. 3D) and intercellular distance versus number of 549 nearest neighbors (Fig. 3E). Comparisons were considered statistically significant 550 when P < 0.05 or when False Discovery Rate (FDR) corrected Q < 0.05. FDR 551 corrections were applied when multiple t tests were performed for the same dataset.