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

A bloom of a single bacterium shapes the microbiome during outdoor diatom cultivation collapse

Algae-dominated ecosystems are fundamentally influenced by their microbiome. We lack information on the identity and function of bacteria that specialize in consuming algal-derived dissolved organic matter in high algal density ecosystems such as outdoor algal ponds used for biofuel production. Here, we describe the metagenomic and metaproteomic signatures of a single bacterial strain that bloomed during a population-wide crash of the diatom, Phaeodactylum tricornutum, grown in outdoor ponds. 16S rRNA gene data indicated that a single Kordia sp. strain (family Flavobacteriaceae) contributed up to 93% of the bacterial community during P. tricornutum demise. Kordia sp. expressed proteins linked to microbial antagonism and biopolymer breakdown, which likely contributed to its dominance over other microbial taxa during diatom demise. Analysis of accompanying downstream microbiota (primarily of the Rhodobacteraceae family) provided evidence that cross-feeding may be a pathway supporting microbial diversity during diatom demise. In situ and laboratory data with a different strain suggested that Kordia was a primary degrader of biopolymers during algal demise, and co-occurring Rhodobacteraceae exploited degradation molecules for carbon. An analysis of 30 Rhodobacteraceae metagenome assembled genomes suggested that algal pond Rhodobacteraceae commonly harbored pathways to use diverse carbon and energy sources, including carbon monoxide, which may have contributed to the prevalence of this taxonomic group within the ponds. These observations further constrain the roles of functionally distinct heterotrophic bacteria in algal microbiomes, demonstrating how a single dominant bacterium, specialized in processing senescing or dead algal biomass, shapes the microbial community of outdoor algal biofuel ponds.IMPORTANCEAquatic biogeochemical cycles are dictated by the activity of diverse microbes inhabiting the algal microbiome. Outdoor biofuel ponds provide a setting analogous to aquatic algal blooms, where monocultures of fast-growing algae reach high cellular densities. Information on the microbial ecology of this setting is lacking, and so we employed metagenomics and metaproteomics to understand the metabolic roles of bacteria present within four replicated outdoor ponds inoculated with the diatom Phaeodactylum tricornutum. Unexpectedly, after 29 days of cultivation, all four ponds crashed concurrently with a "bloom" of a single taxon assigned to the Kordia bacterial genus. We assessed how this dominant taxon influenced the chemical and microbial fate of the ponds following the crash, with the hypothesis that it was primarily responsible for processing senescent/dead algal biomass and providing the surrounding microbiota with carbon. Overall, these findings provide insight into the roles of microbes specialized in processing algal organic matter and enhance our understanding of biofuel pond microbial ecology.

Branched-chain amino acid metabolism supports Roseobacteraceae positive interactions in marine biofilms

Interspecies interactions are key factors affecting the stability of microbial communities. However, microbial interactions in marine biofilms, which constitute up to 80% of the microbial biomass in certain marine environments, are not well understood. We addressed this knowledge gap by coculturing four marine biofilm-derived Roseobacteraceae strains (Leisingera aquaemixtae M597, Roseibium aggregatum S1616, Alloyangia pacifica T6124, and Sulfitobacter indolifex W002) in 14 single carbon sources. Overall, 140 coculture experiments revealed 39.3% positive interactions compared to 8.3% negative interactions. When the carbon source was consumed by only one strain, the interaction between the strains was more likely to be positive. The interaction between S1616 and M597, when cultured in D-gluconic acid, was further studied as an example. S1616-M597 coculture displayed a higher D-gluconic acid consumption rate than S1616 monoculture, whereas M597 could not use D-gluconic acid as the sole carbon source. The supernatant of S1616 monoculture supported the growth of M597, and branched-chain amino acids in the supernatant were consumed. Transcriptomic analysis suggested that M597 induced the expression of genes for branched-chain amino acid biosynthesis in S1616. Additionally, metagenomic analysis revealed the wide distribution and a strongly correlated co-occurrence of the four strains in global oceanic biofilms. Together, our findings show that interspecies positive interactions are prevalent among marine-biofilm Roseobacteraceae, and the interactions are likely to be mediated by branched-chain amino acids metabolism.

IMPORTANCE

Interspecies interactions are crucial for microbial community structure and function. Despite well-studied social behaviors in model microorganisms, species interactions in natural marine biofilms especially Roseobacteraceae with complex metabolic pathways are not well understood. Our findings suggest that positive microbial interactions, which can be mediated by branched-chain amino acid biosynthesis, are common among marine-biofilm Roseobacteraceae. This study provides new insights into microbial interactions and the ecology of marine biofilms.

The architecture of theory and data in microbiome design: towards an S-matrix for microbiomes

Designing microbiomes for applications in health, bioengineering, and sustainability is intrinsically linked to a fundamental theoretical understanding of the rules governing microbial community assembly. Microbial ecologists have used a range of mathematical models to understand, predict, and control microbiomes, ranging from mechanistic models, putting microbial populations and their interactions as the focus, to purely statistical approaches, searching for patterns in empirical and experimental data. We review the success and limitations of these modeling approaches when designing novel microbiomes, especially when guided by (inevitably) incomplete experimental data. Although successful at predicting generic patterns of community assembly, mechanistic and phenomenological models tend to fall short of the precision needed to design and implement specific functionality in a microbiome. We argue that to effectively design microbiomes with optimal functions in diverse environments, ecologists should combine data-driven techniques with mechanistic models - a middle, third way for using theory to inform design.

Polysaccharide breakdown products drive degradation-dispersal cycles of foraging bacteria through changes in metabolism and motility

Most of Earth's biomass is composed of polysaccharides. During biomass decomposition, polysaccharides are degraded by heterotrophic bacteria as a nutrient and energy source and are thereby partly remineralized into CO2. As polysaccharides are heterogeneously distributed in nature, following the colonization and degradation of a polysaccharide hotspot the cells need to reach new polysaccharide hotspots. Even though many studies indicate that these degradation-dispersal cycles contribute to the carbon flow in marine systems, we know little about how cells alternate between polysaccharide degradation and motility, and which environmental factors trigger this behavioral switch. Here, we studied the growth of the marine bacterium Vibrio cyclitrophicus ZF270 on the abundant marine polysaccharide alginate, both in its soluble polymeric form as well as on its breakdown products. We used microfluidics coupled to time-lapse microscopy to analyze motility and growth of individual cells, and RNA sequencing to study associated changes in gene expression. We found that single cells grow at reduced rate on alginate until they form large groups that cooperatively break down the polymer. Exposing cell groups to digested alginate accelerates cell growth and changes the expression of genes involved in alginate degradation and catabolism, central metabolism, ribosomal biosynthesis, and transport. However, exposure to digested alginate also triggers cells to become motile and disperse from cell groups, proportionally increasing with the group size before the nutrient switch, and this is accompanied by high expression of genes involved in flagellar assembly, chemotaxis, and quorum sensing. The motile cells chemotax toward polymeric but not digested alginate, likely enabling them to find new polysaccharide hotspots. Overall, our findings reveal cellular mechanisms that might also underlie bacterial degradation-dispersal cycles, which influence the remineralization of biomass in marine environments.

Quantifying microbial interactions: concepts, caveats, and applications

Microbial communities are fundamental to every ecosystem on Earth and hold great potential for biotechnological applications. However, their complex nature hampers our ability to study and understand them. A common strategy to tackle this complexity is to abstract the community into a network of interactions between its members - a phenomenological description that captures the overall effects of various chemical and physical mechanisms that underpin these relationships. This approach has proven useful for numerous applications in microbial ecology, including predicting community dynamics and stability and understanding community assembly and evolution. However, care is required in quantifying and interpreting interactions. Here, we clarify the concept of an interaction and discuss when interaction measurements are useful despite their context-dependent nature. Furthermore, we categorize different approaches for quantifying interactions, highlighting the research objectives each approach is best suited for.

Substrate complexity buffers negative interactions in a synthetic community of leaf litter degraders

Leaf litter microbes collectively degrade plant polysaccharides, influencing land-atmosphere carbon exchange. An open question is how substrate complexity-defined as the structure of the saccharide and the amount of external processing by extracellular enzymes-influences species interactions. We tested the hypothesis that monosaccharides (i.e. xylose) promote negative interactions through resource competition, and polysaccharides (i.e. xylan) promote neutral or positive interactions through resource partitioning or synergism among extracellular enzymes. We assembled a three-species community of leaf litter-degrading bacteria isolated from a grassland site in Southern California. In the polysaccharide xylan, pairs of species stably coexisted and grew equally in coculture and in monoculture. Conversely, in the monosaccharide xylose, competitive exclusion and negative interactions prevailed. These pairwise dynamics remained consistent in a three-species community: all three species coexisted in xylan, while only two species coexisted in xylose, with one species capable of using peptone. A mathematical model showed that in xylose these dynamics could be explained by resource competition. Instead, the model could not predict the coexistence patterns in xylan, suggesting other interactions exist during biopolymer degradation. Overall, our study shows that substrate complexity influences species interactions and patterns of coexistence in a synthetic microbial community of leaf litter degraders.

Constructions of quorum sensing signaling network for activated sludge microbial community

In wastewater treatment systems, the interactions among various microbes based on chemical signals, namely quorum sensing (QS), play critical roles in influencing microbial structure and function. However, it is challenging to understand the QS-controlled behaviors and the underlying mechanisms in complex microbial communities. In this study, we constructed a QS signaling network, providing insights into the intra- and interspecies interactions of activated sludge microbial communities based on diverse QS signal molecules. Our research underscores the role of diffusible signal factors in both intra- and interspecies communication among activated sludge microorganisms, and signal molecules commonly considered to mediate intraspecies communication may also participate in interspecies communication. QS signaling molecules play an important role as communal resources among the entire microbial group. The communication network within the microbial community is highly redundant, significantly contributing to the stability of natural microbial systems. This work contributes to the establishment of QS signaling network for activated sludge microbial communities, which may complement metabolic exchanges in explaining activated sludge microbial community structure and may help with a variety of future applications, such as making the dynamics and resilience of highly complex ecosystems more predictable.