Bacteria play many important roles in animal digestive systems, including the provision of enzymes critical to digestion. Typically, complex communities of bacteria reside in the gut lumen in direct contact with the ingested materials they help to digest. Here, we demonstrate a previously undescribed digestive strategy in the wood-eating marine bivalve Bankia setacea, wherein digestive bacteria are housed in a location remote from the gut. These bivalves, commonly known as shipworms, lack a resident microbiota in the gut compartment where wood is digested but harbor endosymbiotic bacteria within specialized cells in their gills. We show that this comparatively simple bacterial community produces wood-degrading enzymes that are selectively translocated from gill to gut. These enzymes, which include just a small subset of the predicted wood-degrading enzymes encoded in the endosymbiont genomes, accumulate in the gut to the near exclusion of other endosymbiont-made proteins. This strategy of remote enzyme production provides the shipworm with a mechanism to capture liberated sugars from wood without competition from an endogenous gut microbiota. Because only those proteins required for wood digestion are translocated to the gut, this newly described system reveals which of many possible enzymes and enzyme combinations are minimally required for wood degradation. Thus, although it has historically had negative impacts on human welfare, the shipworm digestive process now has the potential to have a positive impact on industries that convert wood and other plant biomass to renewable fuels, fine chemicals, food, feeds, textiles, and paper products.Teredinidae | endosymbionts | symbiosis | xylotrophy | carbohydrate-active enzymes

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Many microbial functions happen within communities of interacting species. Explaining how species with disparate growth rates can coexist is important for applications such as manipulating host-associated microbiota or engineering industrial communities. Here, we ask how microbes interacting through their chemical environment can achieve coexistence in a continuous growth setup (similar to an industrial bioreactor or gut microbiota) where external resources are being supplied. We formulate and experimentally constrain a model in which mediators of interactions (e.g. metabolites or waste-products) are explicitly incorporated. Our model highlights facilitation and self-restraint as interactions that contribute to coexistence, consistent with our intuition. When interactions are strong, we observe that coexistence is determined primarily by the topology of facilitation and inhibition influences not their strengths. Importantly, we show that consumption or degradation of chemical mediators moderates interaction strengths and promotes coexistence. Our results offer insights into how to build or restructure microbial communities of interest.

The interaction between an antibiotic and bacterium is not merely restricted to the drug and its direct target, rather antibiotic induced stress seems to resonate through the bacterium, creating selective pressures that drive the emergence of adaptive mutations not only in the direct target, but in genes involved in many different fundamental processes as well. Surprisingly, it has been shown that adaptive mutations do not necessarily have the same effect in all species, indicating that the genetic background influences how phenotypes are manifested. However, to what extent the genetic background affects the manner in which a bacterium experiences antibiotic stress, and how this stress is processed is unclear. Here we employ the genome-wide tool Tn-Seq to construct daptomycin-sensitivity profiles for two strains of the bacterial pathogen Streptococcus pneumoniae. Remarkably, over half of the genes that are important for dealing with antibiotic-induced stress in one strain are dispensable in another. By confirming over 100 genotype-phenotype relationships, probing potassium-loss, employing genetic interaction mapping as well as temporal gene-expression experiments we reveal genome-wide conditionally important/essential genes, we discover roles for genes with unknown function, and uncover parts of the antibiotic’s mode-of-action. Moreover, by mapping the underlying genomic network for two query genes we encounter little conservation in network connectivity between strains as well as profound differences in regulatory relationships. Our approach uniquely enables genome-wide fitness comparisons across strains, facilitating the discovery that antibiotic responses are complex events that can vary widely between strains, which suggests that in some cases the emergence of resistance could be strain specific and at least for species with a large pan-genome less predictable.

Teredinibacter turnerae is a cultivable intracellular endosymbiont of xylotrophic (wood-feeding) bivalves of the Family Teredinidae (shipworms). Although T. turnerae has been isolated from many shipworm taxa collected in many locations, no systematic effort has been made to explore genetic diversity within this symbiont species across the taxonomic and geographic range of its hosts. The mode of symbiont transmission is unknown. Here we examine sequence diversity in fragments of six genes (16S rRNA, gyrB, sseA, recA, rpoB, and celAB) among 25 isolates of T. turnerae cultured from 13 shipworm species collected in 15 locations in the Atlantic, Pacific and Indian Oceans. While 16S rRNA sequences are nearly invariant among all examined isolates (maximum pairwise difference <0.26%) variation among examined protein coding loci is greater (mean pairwise difference 2.2-5.9%). Phylogenetic analyses based on each protein-coding locus differentiate the 25 isolates into two distinct and well-supported clades. With five exceptions, clade assignments for each isolate were supported by analysis of alleles of each of the five protein coding loci. These exceptions include (1) putative recombinant alleles of the celAB and gyrB loci in two isolates (PMS-535T.S.1b.3 and T8510), suggesting homologous recombination between members of the two clades, and (2) evidence for a putative lateral gene transfer event affecting a second locus (recA) in three isolates (T8412, T8503 and T8513). These results demonstrate that T. turnerae isolates do not represent a homogeneous global population. Instead they indicate the emergence of two lineages that, although distinct, likely experience some level of genetic exchange with each other and with other bacterial species.

Many microbial functions happen within communities of interacting species. Explaining how species with intrinsically disparate fitness can coexist is important for applications such as manipulating hostassociated microbiota or engineering industrial communities. Previous coexistence studies have often neglected interaction mechanisms. Here, we formulate and experimentally constrain a model in which chemical mediators of microbial interactions (e.g. metabolites or waste-products) are explicitly incorporated. We construct many instances of coexistence by simulating community assembly through enrichment and ask how species interactions can explain coexistence. We show that growth-facilitating influences between members are favored in assembled communities. Among negative influences, selfrestraint, such as production of self-inhibiting waste, contributes to coexistence, whereas inhibition of other species disrupts coexistence. Coexistence is also favored when interactions are mediated by depletable chemicals that get consumed or degraded, rather than by reusable chemicals that are unaffected by recipients. Our model creates null predictions for coexistence driven by chemicalmediated interactions.

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With our growing understanding of the impact of microbial communities, understanding how such communities function has become a priority. The influence of microbial communities is widespread. Human-associated microbiota impacts health, environmental microbes determine ecosystem sustainability, and microbe-driven industrial processes are expanding. This broad range of applications has led to a wide range of approaches to analyze and describe microbial communities. In particular, theoretical work based on mathematical modeling has been a steady source of inspiration for explaining and predicting microbial community processes. Here, we survey some of the modeling approaches used in different contexts. We promote classifying different approaches using a unified platform, and encourage cataloging the findings in a database. We believe that the synergy emerging from a coherent collection facilitates a better understanding of important processes that determine microbial community functions. We emphasize the importance of close collaboration between theoreticians and experimentalists in formulating, classifying, and improving models of microbial communities.