Otto Cordero
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Researcher at Massachusetts Institute of Technology
Environmental Microbiology, 2019-12-10
Marine microorganisms play a fundamental role in the global carbon cycle by mediating the sequestration of organic matter in ocean waters and sediments. A better understanding of how biological factors, such as microbial community composition, influence the lability and fate of organic matter is needed. Here, we explored the extent to which organic matter remineralization is influenced by species-specific metabolic capabilities. We carried out aerobic time-series incubations of Guaymas basin sediments to quantify the dynamics of carbon utilization by two different heterotrophic marine isolates. Continuous measurement of respiratory CO2 production and its carbon isotopic compositions (13C and 14C) shows species-specific differences in the rate, quantity, and type of organic matter remineralized. Each species was incubated with hydrothermally-influenced vs. unimpacted sediments, resulting in a ~3-fold difference in respiratory CO2 yield across the experiments. Genomic analysis indicated that the observed carbon utilization patterns may be attributed in part to the number of gene copies encoding for extracellular hydrolytic enzymes. Our results demonstrate that the lability and remineralization of organic matter in marine environments is not only a function of chemical composition and/or environmental conditions, but also a function of the microorganisms that are present and active.
Many complex biological systems such as metabolic networks can be divided into functional and organizational subunits, called modules, which provide the flexibility to assemble novel multi-functional hierarchies by a mix and match of simpler components. Here we show that polysaccharide-degrading microbial communities in the ocean can also assemble in a modular fashion. Using synthetic particles made of a variety of polysaccharides commonly found in the ocean, we showed that the particle colonization dynamics of natural bacterioplankton assemblages can be understood as the aggregation of species modules of two main types: a first module type made of narrow niche-range primary degraders, whose dynamics are controlled by particle polysaccharide composition, and a second module type containing broad niche-range, substrate-independent taxa whose dynamics are controlled by interspecific interactions, in particular cross-feeding via organic acids, amino acids and other metabolic byproducts. As a consequence of this modular logic, communities can be predicted to assemble by a sum of substrate-specific primary degrader modules, one for each complex polysaccharide in the particle, connected to a single broad-niche range consumer module. We validate this model by showing that a linear combination of the communities on single-polysaccharide particles accurately predicts community composition on mixed-polysaccharide particles. Our results suggest thus that the assembly of heterotrophic communities that degrade complex organic materials follow simple design principles that can be exploited to engineer heterotrophic microbiomes.
Nature Microbiology, 2018-09-24
Microbial communities are often highly diverse in their composition, both at the level of coarse-grained taxa such as genera as well as at the level of strains within species. This variability can be driven by both extrinsic factors like temperature, pH, etc., as well as by intrinsic ones, such as demographic fluctuations or ecological interactions. The relative contributions of these factors and the taxonomic level at which they influence community structure remain poorly understood, in part because of the difficulty of identifying true community replicates assembled under the same environmental parameters. Here, we address this problem using an activated granular sludge reactor in which millimeter scale biofilm granules represent true community replicates whose differences in composition are expected to be driven primarily by biotic factors. Using 142 shotgun metagenomes of single biofilm granules we found that, at the commonly used genus-level resolution, community replicates varied much more in their composition than would be expected from neutral assembly processes. This variation, however, did not translate into any clear partitioning into discrete community types, i.e. the equivalent of enterotypes in the human gut. However, a strong partition into community types did emerge at the strain level for the most abundant organism: strains of Candidatus Accumulibacter that coexisted in the metacommunity---i.e. the reactor---excluded each other within community replicates. Single-granule communities maintained a significant lineage structure, whereby the strain phylogeny of Accumulibacter correlated with the overall species composition of the community, indicating high potential for co-diversification among species and communities. Our results suggest that due to the high functional redundancy and competition between close relatives, alternative community types are most likely observed at the level of recently differentiated genotypes but not higher orders of genetic resolution.
Public good exploitation has been studied extensively from an evolutionary lens, but little is known about the occurrence and impact of public good exploiters in natural communities. Here, we develop a reverse ecology approach to systematically identify bacteria that can exploit public goods produced during the degradation of polysaccharides. Focusing on chitin - the second most abundant biopolymer on the planet, we show that public good exploiters hinder the growth of degraders and invade marine microbial communities during early stages of colonization. Unlike cheaters in social evolution, exploiters and polysaccharide degraders (cooperators) come together by a process of community assembly, belong to distant lineages and can stably coexist. Thus, our approach opens novel avenues to interpret the wealth of genomic data through an ecological lens.
Recent work on microbial communities from various environments has shown that coexisting microorganisms with similar metabolic functions can be combined into high level “functional groups”, which explain a larger proportion of variance in abiotic parameters than any individual taxon. However, the general rules by which taxa should be aggregated into functional groups remain elusive. Here, we show that two conditions are required for species-assemblages to explain a higher percentage of variance in abiotic factors than single taxa. 1) consistent taxa-environment correlations, and 2) weak or negative correlations (i.e. complementarity) between taxa. Applying this recipe to the ocean microbiome, we found that the best grouping of taxa is one that partitions it into only two groups, a core and a flexible assemblage. The core assemblage is enriched in Cyanobacteria and oligotrophic heterotrophs, and was strongly correlated to the first principal component of the taxa-sample matrix. The flexible assemblage instead was enriched in metabolically versatile copiotrophs, abundant at higher depths. This simple core / flexible bipartition explained the most variance in abiotic parameters and outperformed annotation-based functional groups as well as individual taxa. It therefore represents the simplest and best grouping of taxa that can be extracted from current ocean microbiome surveys.
Niche construction through interspecific interactions can condition future community states on past ones. However, the extent to which such history dependency can steer communities towards functionally different states remains a subject of active debate. Using bacterial communities collected from wild pitchers of the carnivorous pitcher plant, Sarracenia purpurea , we tested the effects of history on composition and function across communities assembled in synthetic pitcher plant microcosms. We found that the diversity of assembled communities was determined by the diversity of the system at early, pre-assembly stages. Species composition was also contingent on early community states, not only because of differences in the species pool, but also because the same species had different dynamics in different community contexts. Importantly, compositional differences were proportional to differences in function, as profiles of resource use were strongly correlated with composition, despite convergence in respiration rates. Early differences in community structure can thus propagate to mature communities, conditioning their functional repertoire.