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Microbial communities play key roles across diverse environments. Predicting their function and dynamics is a key goal of microbial ecology, but detailed microscopic descriptions of these systems can be prohibitively complex. One approach to deal with this complexity is to resort to coarser representations. Several approaches have sought to identify useful groupings of microbial species in a data-driven way. Of these, recent work has claimed some empirical success at de novo discovery of coarse representations predictive of a given function using methods as simple as a linear regression, against multiple groups of species or even a single such group (the ensemble quotient optimization (EQO) approach). Modeling community function as a linear combination of individual species’ contributions appears simplistic. However, the task of identifying a predictive coarsening of an ecosystem is distinct from the task of predicting the function well, and it is conceivable that the former could be accomplished by a simpler methodology than the latter. Here, we use the resource competition framework to design a model where the “correct” grouping to be discovered is well-defined, and use synthetic data to evaluate and compare three regression-based methods, namely, two proposed previously and one we introduce. We find that regression-based methods can recover the groupings even when the function is manifestly nonlinear; that multi-group methods offer an advantage over a single-group EQO; and crucially, that simpler (linear) methods can outperform more complex ones. 

Climate change is having increasingly profound effects on human health, notably those associated with the occurrence, distribution, and transmission of infectious diseases. The number of disparate ecological parameters and pathogens affected by climate change are vast and expansive. Disentangling the complex relationship between these variables is critical for the development of effective countermeasures against its effects. The pathogenVibrio vulnificus, a naturally occurring aquatic bacterium that causes fulminant septicemia, represents a quintessential climate-sensitive organism. In this review, we useV.vulnificusas a model organism to elucidate the intricate network of interactions between climatic factors and pathogens, with the objective of identifying common patterns by which climate change is affecting their disease burden. Recent findings indicate that in regions native toV.vulnificusor related pathogens, climate-driven natural disasters are the chief contributors to their disease outbreaks. Concurrently, climate change is increasing the environmental suitability of areas non-endemic to their diseases, promoting a surge in their natural populations and transmission dynamics, thus elevating the risk of new outbreaks. We highlight potential risk factors and climatic drivers aggravating the threat ofV.vulnificustransmission under both scenarios and propose potential measures for mitigating its impact. By defining the mechanisms by which climate change influencesV.vulnificusdisease burden, we aim to shed light on the transmission dynamics of related disease-causing agents, thereby laying the groundwork for early warning systems and broadly applicable control measures. 

Abstract Metabolic cross-feeding plays vital roles in promoting ecological diversity. While some microbes depend on exchanges of essential nutrients for growth, the forces driving the extensive cross-feeding needed to support the coexistence of free-living microbes are poorly understood. Here we characterize bacterial physiology under self-acidification and establish that extensive excretion of key metabolites following growth arrest provides a collaborative, inter-species mechanism of stress resistance. This collaboration occurs not only between species isolated from the same community, but also between unrelated species with complementary (glycolytic vs. gluconeogenic) modes of metabolism. Cultures of such communities progress through distinct phases of growth-dilution cycles, comprising of exponential growth, acidification-triggered growth arrest, collaborative deacidification, and growth recovery, with each phase involving different combinations of physiological states of individual species. Our findings challenge the steady-state view of ecosystems commonly portrayed in ecological models, offering an alternative dynamical view based on growth advantages of complementary species in different phases. 

Abstract The degradation of particulate organic matter in the ocean is a central process in the global carbon cycle, the mode and tempo of which is determined by the bacterial communities that assemble on particle surfaces. Here, we find that the capacity of communities to degrade particles is highly dependent on community composition using a collection of marine bacteria cultured from different stages of succession on chitin microparticles. Different particle degrading taxa display characteristic particle half-lives that differ by ~170 h, comparable to the residence time of particles in the ocean’s mixed layer. Particle half-lives are in general longer in multispecies communities, where the growth of obligate cross-feeders hinders the ability of degraders to colonize and consume particles in a dose dependent manner. Our results suggest that the microscale community ecology of bacteria on particle surfaces can impact the rates of carbon turnover in the ocean.