Showing papers by "Thomas Bell published in 2020"

Bacterial adaptation is constrained in complex communities

Abstract: A major unresolved question is how bacteria living in complex communities respond to environmental changes. In communities, biotic interactions may either facilitate or constrain evolution depending on whether the interactions expand or contract the range of ecological opportunities. A fundamental challenge is to understand how the surrounding biotic community modifies evolutionary trajectories as species adapt to novel environmental conditions. Here we show that community context can dramatically alter evolutionary dynamics using a novel approach that ‘cages’ individual focal strains within complex communities. We find that evolution of focal bacterial strains depends on properties both of the focal strain and of the surrounding community. In particular, there is a stronger evolutionary response in low-diversity communities, and when the focal species have a larger genome and are initially poorly adapted. We see how community context affects resource usage and detect genetic changes involved in carbon metabolism and inter-specific interaction. The findings demonstrate that adaptation to new environmental conditions should be investigated in the context of interspecific interactions. A species’ ability to adapt to a new environment may be influenced by both intrinsic factors and extrinsic factors. Here, Scheuerl et al. show that bacterial adaptation to low pH depends on not only its genome size and initial level of adaptation, but also the diversity of the community.

Community-level signatures of ecological succession in natural bacterial communities.

Abstract: A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units. We profiled (16S rRNA sequencing) > 700 semi-aquatic bacterial communities while measuring their functional capacity when grown in laboratory conditions. This approach allowed us to investigate the relationship between composition and function excluding confounding environmental factors. Simulated data allowed us to reject the hypothesis that stochastic processes were responsible for community assembly, suggesting that niche effects prevailed. Consistent with this idea we identified six distinct community classes that contained samples collected from distant locations. Structural equation models showed there was a functional signature associated with each community class. We obtained a more mechanistic understanding of the classes using metagenomic predictions (PiCRUST). This approach allowed us to show that the classes contained distinct genetic repertoires reflecting community-level ecological strategies. The ecological strategies resemble the classical distinction between r- and K-strategists, suggesting that bacterial community assembly may be explained by simple ecological mechanisms. Metagenome approaches can unravel relationships between environment, community composition, and ecological functions. Here, the authors show that bacterial communities sampled from rainwater pools can be clustered into few classes with distinct functional capacities and genetic repertoires, the assembly of which is likely driven by local conditions.

Metabolically cohesive microbial consortia and ecosystem functioning

Abstract: Recent theory and experiments have reported a reproducible tendency for the coexistence of microbial species under controlled environmental conditions. This observation has been explained in the context of competition for resources and metabolic complementarity given that, in microbial communities (MCs), many excreted by-products of metabolism may also be resources. MCs therefore play a key role in promoting their own stability and in shaping the niches of the constituent taxa. We suggest that an intermediate level of organization between the species and the community level may be pervasive, where tightly knit metabolic interactions create discrete consortia that are stably maintained. We call these units Metabolically Cohesive Consortia (MeCoCos) and we discuss the environmental context in which we expect their formation, and the ecological and evolutionary consequences of their existence. We argue that the ability to identify MeCoCos would open new avenues to link the species-, community- and ecosystem-level properties, with consequences for our understanding of microbial ecology and evolution, and an improved ability to predict ecosystem functioning in the wild. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

functionInk: An efficient method to detect functional groups in multidimensional networks reveals the hidden structure of ecological communities

Abstract: 1. Complex networks have been useful to link experimental data with mechanistic models, and have become widely used across many scientific disciplines. Recently, the increasing amount and complexity of data, particularly in biology, has prompted the development of multidimensional networks, where dimensions reflect the multiple qualitative properties of nodes, links, or both. As a consequence, traditional quantities computed in single dimensional networks should be adapted to incorporate this new information. A particularly important problem is the detection of communities, namely sets of nodes sharing certain properties, which reduces the complexity of the networks, hence facilitating its interpretation. 2. In this work, we propose an operative definition of function for the nodes in multidimensional networks, and we exploit this definition to show that it is possible to detect two types of communities: i) modules, which are communities more densely connected within their members than with nodes belonging to other communities, and ii) guilds, which are sets of nodes connected with the same neighbours, even if they are not connected themselves. We provide two quantities to optimally detect both types of communities, whose relative values reflect their importance in the network. 3. The flexibility of the method allowed us to analyze different ecological examples encompassing mutualistic, trophic and microbial networks. We showed that by considering both metrics we were able to obtain deeper ecological insights about how these different ecological communities were structured. The method mapped pools of species with properties that were known in advance, such as plants and pollinators. Other types of communities found, when contrasted with external data, turned out to be ecologically meaningful, allowing us to identify species with important functional roles or the influence of environmental variables. Furthermore, we found the method was sensitive to community-level topological properties like the nestedness. 4. In ecology there is often a need to identify groupings including trophic levels, guilds, functional groups, or ecotypes.The method is therefore important in providing an objective means of distinguishing modules and guilds. The method we developed, functionInk (functional linkage), is computationally efficient at handling large multidimensional networks since it does not require optimization procedures or tests of robustness. The method is available at: https://github.com/apascualgarcia/functionInk.

Systematic variation in the temperature dependence of bacterial carbon use efficiency

Abstract: Understanding the temperature dependence of carbon use efficiency (CUE) is critical for understanding microbial physiology, population dynamics, and community-level responses to changing environmental temperatures 1,2. Currently, microbial CUE is widely assumed to decrease with temperature 3,4. However, this assumption is based largely on community-level data, which are influenced by many confounding factors 5, with little empirical evidence at the level of individual strains. Here, we experimentally characterise the CUE thermal response for a diverse set of environmental bacterial isolates. We find that contrary to current thinking, bacterial CUE typically responds either positively to temperature, or has no discernible temperature response, within biologically meaningful temperature ranges. Using a global data-synthesis, we show that our empirical results are generalisable across a much wider diversity of bacteria than have previously been tested. This systematic variation in the thermal responses of bacterial CUE stems from the fact that relative to respiration rates, bacterial population growth rates typically respond more strongly to temperature, and are also subject to weaker evolutionary constraints. Our results provide fundamental new insights into microbial physiology, and a basis for more accurately modelling the effects of shorter-term thermal fluctuations as well as longer-term climatic warming on microbial communities.