Deciphering the evolution of microbial interactions: in silico studies of two-member microbial communities

Microbes thrive in communities, embedded in a complex web of interactions. These interactions, particularly metabolic interactions, play a crucial role in maintaining the community structure and function. As the organisms thrive and evolve, a variety of evolutionary processes alter the interactions among the organisms in the community, although the community function remains intact. In this work, we simulate the evolution of two-member microbial communities in silico to study how evolutionary forces can shape the interactions between organisms. We employ genomescale metabolic models of organisms from the human gut, which exhibit a range of interaction patterns, from mutualism to parasitism. We observe that the evolution of microbial interactions varies depending upon the starting interaction and also on the metabolic capabilities of the organisms in the community. We find that evolutionary constraints play a significant role in shaping the dependencies of organisms in the community. Evolution of microbial communities yields fitness benefits in only a small fraction of the communities, and is also dependent on the interaction type of the wild-type communities. The metabolites cross-fed in the wild-type communities appear in only less than 50% of the evolved communities. A wide range of new metabolites are cross-fed as the communities evolve. Further, the dynamics of microbial interactions are not specific to the interaction of the wild-type community but vary depending on the organisms present in the community. Our approach of evolving microbial communities in silico provides an exciting glimpse of the dynamics of microbial interactions and offers several avenues for future investigations.

Ecological landscapes guide the assembly of optimal microbial communities

Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia.

STRUCTURAL SOCIAL CAPITAL OF PARENTS HAVING PERSONS WITH DISABILITY IN CHANDIGARH

Structural social capital is understood as maintenance of connections, immense trust, following of certain rules and fulfilling certain commitments. It is pertinent to improve quality of life. The present research aimed to study the structural social capital of parents having persons with disability living in Chandigarh. The descriptive survey method with convenient sampling technique was employed. Twenty-five parents of persons with disability (N=25) having age group 20 to 55 years were in the sample. The questionnaire comprised of six statements and each statement had sub-items with the options of yes and no. Results showed that parents having persons with disabilities hadgood network ties with relatives, neighbours and friends but a few parents having persons with disabilities did not have good bondings. Besides, majority did not participate in the activities such as social and cultural clubs, religious organisation, government schemes, local community function and political organisation.The authors recommend that support from government, non-government organisation and community to provide financial, moral and psychologicalhelp to families of PWD is important for healthy development of all individuals of society.

Steering ecological-evolutionary dynamics to improve artificial selection of microbial communities

Microbial communities often perform important functions that depend on inter-species interactions. To improve community function via artificial selection, one can repeatedly grow many communities to allow mutations to arise, and “reproduce” the highest-functioning communities by partitioning each into multiple offspring communities for the next cycle. Since improvement is often unimpressive in experiments, we study how to design effective selection strategies in silico. Specifically, we simulate community selection to improve a function that requires two species. With a “community function landscape”, we visualize how community function depends on species and genotype compositions. Due to ecological interactions that promote species coexistence, the evolutionary trajectory of communities is restricted to a path on the landscape. This restriction can generate counter-intuitive evolutionary dynamics, prevent the attainment of maximal function, and importantly, hinder selection by trapping communities in locations of low community function heritability. We devise experimentally-implementable manipulations to shift the path to higher heritability, which speeds up community function improvement even when landscapes are high dimensional or unknown. Video walkthroughs: https://go.nature.com/3GWwS6j; https://online.kitp.ucsb.edu/online/ecoevo21/shou2/.

Synthetic periphyton as a model community to examine species dynamics in complex microbial consortia

Phototrophic biofilms, also known as periphyton, drive crucial ecosystem processes and are subject to alterations due to a multitude of biotic and abiotic factors. In this context, understanding species dynamics in periphyton is a fundamental, yet challenging, requirement to accurately predict outcomes on functions and properties of complex communities. To address this challenge, we developed a workflow applying rational design based on existing knowledge on natural periphyton, to successfully obtain a stable, diverse and highly reproducible synthetic periphyton. We show that by using our synthetic community, with a known microbial composition, we are able to monitor dynamics of single species during periphyton development and their specific response to stressors such as increased temperature and herbicides. Importantly, we clearly demonstrate that these responses are mainly driven by species interactions and how they link to changes of community function and structure. Our synthetic periphyton is a powerful tool to perform mechanistic studies on periphyton structural and functional responses, as well as on species propagation, to any biotic and abiotic stressors and their combinations.

Metagenomic analysis provides functional insights into seasonal change of a non-cyanobacterial prokaryotic community in temperate coastal waters

The taxonomic compositions of marine prokaryotic communities are known to follow seasonal cycles, but functional metagenomic insights into this seasonality is still limited. We analyzed a total of 22 metagenomes collected at 11 time points over a 14-month period from two sites in Sendai Bay, Japan to obtain seasonal snapshots of predicted functional profiles of the non-cyanobacterial prokaryotic community. Along with taxonomic composition, functional gene composition varied seasonally and was related to chlorophyll a concentration, water temperature, and salinity. Spring phytoplankton bloom stimulated increased abundances of putative genes that encode enzymes in amino acid metabolism pathways. Several groups of functional genes, including those related to signal transduction and cellular communication, increased in abundance during the mid- to post-bloom period, which seemed to be associated with a particle-attached lifestyle. Alternatively, genes in carbon metabolism pathways were generally more abundant in the low chlorophyll a period than the bloom period. These results indicate that changes in trophic condition associated with seasonal phytoplankton succession altered the community function of prokaryotes. Our findings on seasonal changes of predicted function provide fundamental information for future research on the mechanisms that shape marine microbial communities.

Maintenance of community function through compensation breaks down over time in a desert rodent community

Understanding the ecological processes that maintain community function in systems experiencing species loss, and how these processes change over time, is key to understanding the relationship between community structure and function and predicting how communities may respond to perturbations in the Anthropocene. Using a 30-year experiment on desert rodents, we show that the impact of species loss on community-level energy use has changed dramatically over time, due to changes in both species composition and in the degree of functional redundancy among the same set of species. Although strong compensation, initially driven by the dispersal of functionally redundant species to the local community, occurred in this system from 1996-2010, since 2010, compensation has broken down due to decreasing functional overlap within the same set of species. Simultaneously, long-term changes in sitewide community composition due to niche complementarity have decoupled the dynamics of compensation from the overall impact of species loss on community-level energy use. These results highlight the importance of explicitly long-term, metacommunity, and eco-evolutionary perspectives on compensatory dynamics, zero-sum constraints, and the link between species-level fluctuations and community function in a changing world.Original submissionThis submission analyzes long-term data on rodent community abundance and energy use from the Portal Project. Sections of this timeseries have been analyzed in numerous other publications, but this is the first to analyze data from 2007-2020 on compensation on experimental and control plots.No prior publicationThis submission is posted as a preprint on bioRxiv at [bioRxiv].Animal welfareRodent censuses were conducted with IACUC approval, most recently under protocol 201808839_01 at the University of Florida.Open researchAll data and code to reproduce these analyses are archived on Zenodo at https://doi.org/10.5281/zenodo.5544362 and https://doi.org/10.5281/zenodo.5539881.Analytic methodsAll analyses were conducted in R version 4.0.3.

NetCom: A Network-Based Tool for Predicting Metabolic Activities of Microbial Communities Based on Interpretation of Metagenomics Data

The study of microbial activity can be viewed as a triangle with three sides: environment (dominant resources in a specific habitat), community (species dictating a repertoire of metabolic conversions) and function (production and/or utilization of resources and compounds). Advances in metagenomics enable a high-resolution description of complex microbial communities in their natural environments and support a systematic study of environment-community-function associations. NetCom is a web-tool for predicting metabolic activities of microbial communities based on network-based interpretation of assembled and annotated metagenomics data. The algorithm takes as an input, lists of differentially abundant enzymatic reactions and generates the following outputs: (i) pathway associations of differently abundant enzymes; (ii) prediction of environmental resources that are unique to each treatment, and their pathway associations; (iii) prediction of compounds that are produced by the microbial community, and pathway association of compounds that are treatment-specific; (iv) network visualization of enzymes, environmental resources and produced compounds, that are treatment specific (2 and 3D). The tool is demonstrated on metagenomic data from rhizosphere and bulk soil samples. By predicting root-specific activities, we illustrate the relevance of our framework for forecasting the impact of soil amendments on the corresponding microbial communities. NetCom is available online.