Strong inter-population cooperation leads to partner intermixing in microbial communities

Patterns of spatial positioning of individuals within microbial communities are often critical to community function. However, understanding patterning in natural communities is hampered by the multitude of cell–cell and cell–environment interactions as well as environmental variability. Here, through simulations and experiments on communities in defined environments, we examined how ecological interactions between two distinct partners impacted community patterning. We found that in strong cooperation with spatially localized large fitness benefits to both partners, a unique pattern is generated: partners spatially intermixed by appearing successively on top of each other, insensitive to initial conditions and interaction dynamics. Intermixing was experimentally observed in two obligatory cooperative systems: an engineered yeast community cooperating through metabolite-exchanges and a methane-producing community cooperating through redox-coupling. Even in simulated communities consisting of several species, most of the strongly-cooperating pairs appeared intermixed. Thus, when ecological interactions are the major patterning force, strong cooperation leads to partner intermixing.

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Distinct niche partitioning of marine and freshwater microbes during colonisation

FEMS Microbiology Ecology ◽

10.1093/femsec/fiz098 ◽

2019 ◽

Vol 95 (8) ◽

Cited By ~ 2

Author(s):

Lisa M Dann ◽

Michelle Clanahan ◽

James S Paterson ◽

James G Mitchell

Keyword(s):

Microbial Communities ◽

Initial Conditions ◽

Niche Partitioning ◽

Bacterial Chemotaxis ◽

Physical Factors ◽

Mixed Species ◽

Viral Abundance ◽

Strong Negative Association ◽

Taxonomic Groups ◽

Natural Communities

ABSTRACTBacteria are ubiquitous on the Earth, and many use chemotaxis to colonise favourable microenvironments. The colonisation process is continuous, where animals, plants, protists, viruses and chemical and physical factors frequently remove bacteria from wide volume ranges. Colonisation processes are poorly understood in natural communities. Here, we investigated niche partitioning during colonisation in aquatic microbial communities using bands of bacterial chemotaxis in petri dishes from mixed-species communities. The community partitioned into loiterers, primary and secondary colonisers, each having distinct abundances and taxonomy. Within marine samples, Shewanella dominated the primary colonisers, whilst Enterobacteriaceae dominated this group within the freshwater samples. Whether the success of these specific groups translates to what occurs within natural communities is uncertain, but here we show these taxa have the capacity to colonise new, unexplored environments. A strong negative association existed between the primary colonisers and viral abundance, suggesting that successful colonisers simultaneously move toward areas of heightened resources, which correlated with lower virus-like particles. Here, we show that microbial communities constantly sort themselves into distinct taxonomic groups as they move into new environments. This sorting during colonisation may be fundamental to microbial ecology, industry, technology, and disease development by setting the initial conditions that determine the winners as a community develops.

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Steering ecological-evolutionary dynamics during artificial selection of microbial communities

10.1101/264697 ◽

2018 ◽

Cited By ~ 4

Author(s):

Li Xie ◽

Wenying Shou

Keyword(s):

Microbial Communities ◽

Artificial Selection ◽

Evolutionary Dynamics ◽

Ecological Interactions ◽

Evolutionary Trajectory ◽

Community Function ◽

Selection Strategies ◽

Effective Selection ◽

Orthogonal Components ◽

Selection Of

AbstractMicrobial communities often perform important functions that arise from interactions among member species. Community functions can be improved via artificial selection: Many communities are repeatedly grown, mutations arise, and communities with the highest desired function are chosen to reproduce where each is partitioned into multiple offspring communities for the next cycle. Since selection efficacy is often unimpressive in published experiments and since multiple experimental parameters need to be tuned, we sought to use computer simulations to learn how to design effective selection strategies. We simulated community selection to improve a community function that requires two species and imposes a fitness cost on one of the species. This simplified case allowed us to distill community function down to two fundamental and orthogonal components: a heritable determinant and a nonheritable determinant. We then visualize a “community function landscape” relating community function to these two determinants, and demonstrate that the evolutionary trajectory on the landscape is restricted along a path designated by ecological interactions. This path can prevent the attainment of maximal community function, and trap communities in landscape locations where community function has low heritability. Exploiting these observations, we devise a species spiking approach to shift the path to improve community function heritability and consequently selection efficacy. We show that our approach is applicable to communities with complex and unknown function landscapes.

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

10.1101/2022.01.14.476316 ◽

2022 ◽

Author(s):

Gayathri Sambamoorthy ◽

Karthik Raman

Keyword(s):

Microbial Communities ◽

In Silico ◽

Microbial Interactions ◽

Interaction Patterns ◽

Wild Type ◽

Community Function ◽

Evolutionary Forces ◽

In Silico Studies ◽

Wide Range ◽

In The Wild

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.

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An equation-free method reveals the ecological interaction networks within complex microbial ecosystems

10.1101/080697 ◽

2016 ◽

Author(s):

Kenta Suzuki ◽

Katsuhiko Yoshida ◽

Yumiko Nakanishi ◽

Shinji Fukuda

Keyword(s):

Time Series ◽

Microbial Communities ◽

Microbial Processes ◽

Interaction Networks ◽

List Type ◽

Metagenomic Sequencing ◽

Ecological Interactions ◽

Microbial Interaction ◽

Ecological Interaction ◽

Dataset Size

AbstractMapping the network of ecological interactions is key to understanding the composition, stability, function and dynamics of microbial communities. In recent years various approaches have been used to reveal microbial interaction networks from metagenomic sequencing data, such as time-series analysis, machine learning and statistical techniques. Despite these efforts it is still not possible to capture details of the ecological interactions behind complex microbial dynamics.We developed the sparse S-map method (SSM), which generates a sparse interaction network from a multivariate ecological time-series without presuming any mathematical formulation for the underlying microbial processes. The advantage of the SSM over alternative methodologies is that it fully utilizes the observed data using a framework of empirical dynamic modelling. This makes the SSM robust to non-equilibrium dynamics and underlying complexity (nonlinearity) in microbial processes.We showed that an increase in dataset size or a decrease in observational error improved the accuracy of SSM whereas, the accuracy of a comparative equation-based method was almost unchanged for both cases and equivalent to the SSM at best. Hence, the SSM outperformed a comparative equation-based method when datasets were large and the magnitude of observational errors were small. The results were robust to the magnitude of process noise and the functional forms of inter-specific interactions that we tested. We applied the method to a microbiome data of six mice and found that there were different microbial interaction regimes between young to middle age (4-40 week-old) and middle to old age (36-72 week-old) mice.The complexity of microbial relationships impedes detailed equation-based modeling. Our method provides a powerful alternative framework to infer ecological interaction networks of microbial communities in various environments and will be improved by further developments in metagenomics sequencing technologies leading to increased dataset size and improved accuracy and precision.

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Agricultural constraints on microbial resource use and niche breadth in drainage ditches

10.7287/peerj.preprints.3221 ◽

2017 ◽

Author(s):

Ellard R Hunting ◽

Henrik Barmentlo ◽

Maarten Schrama ◽

Peter van Bodegom ◽

Yujia Zhai ◽

...

Keyword(s):

Organic Matter ◽

Microbial Communities ◽

Resource Utilization ◽

Agricultural Land ◽

Niche Breadth ◽

Niche Differentiation ◽

Drainage Ditches ◽

Substrate Quality ◽

Degradation Rates ◽

Natural Communities

Background. Microorganisms govern important ecosystems processes, in particular the degradation of organic matter (OM). However, microorganisms are rarely considered in efforts to monitor ecosystem health and functioning. Evidence suggests that environmental perturbations can adversely affect microbial communities and and their ability to use available substrates. However, whether impacted microbial efficiencies in extracting and utilizing the available resources (resource niche breadth) translate to changes in organic matter (OM) degradation in natural systems remains poorly understood. Methods. Here we evaluated effects of differences in organic matter (OM) related to agricultural land use (OM derived from ditches adjacent to grasslands, bulb fields and a pristine dune area) on microbial functioning. We specifically assessed 1) resource niche breadths of microbial communities during initial community assembly in laboratory microcosms and already established natural communities, and 2) how changes in community resource niche breadth translates to the degradation of natural OM. Results. A disparity existed between microbial resource niche breadth in laboratory incubations and natural microbial communities. Resource utilization and niche breadth of natural microbial communities was observed to be constrained in drainage ditches adjacent to agricultural fields. This outcome coincides with retarded degradation of natural OM collected from ditches adjacent to hyacinth bulb fields. Microbial communities in bulb field ditches further showed functional redundancy when offered grassland OM of seemingly higher substrate quality. Discussion. Results presented in this study suggest that agricultural practices can impose constraints on microbial functional diversity by reducing OM resource quality, which can subsequently translate to confined microbial resource niche differentiation and reduced organic matter degradation rates. This hints that assessments of actual microbial resource utilization and niche differentiation could potentially be used to assess the ecological health and functioning of natural communities.

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Comparison of Extracellular Enzyme Activities and Community Composition of Attached and Free-Living Bacteria in Porous Medium Columns

Applied and Environmental Microbiology ◽

10.1128/aem.68.4.1569-1575.2002 ◽

2002 ◽

Vol 68 (4) ◽

pp. 1569-1575 ◽

Cited By ~ 50

Author(s):

R. Michael Lehman ◽

Seán P. O'Connell

Keyword(s):

Porous Medium ◽

Microbial Communities ◽

Enzyme Activities ◽

Denaturing Gradient Gel Electrophoresis ◽

Solid Phase ◽

Pcr Amplification ◽

Extracellular Enzyme ◽

Free Living ◽

Extracellular Enzyme Activities ◽

Community Function

ABSTRACT Free-living and surface-associated microbial communities in sand-packed columns perfused with groundwater were compared by examination of compositional and functional characteristics. The composition of the microbial communities was assessed by bulk DNA extraction, PCR amplification of 16S ribosomal DNA fragments, separation of these fragments by denaturing gradient gel electrophoresis, and sequence analysis. Community function was assessed by measurement of β-glucosidase and aminopeptidase extracellular enzyme activities. Free-living populations in the aqueous phase exhibited a greater diversity of phylotypes than populations associated with the solid phase. The attached bacterial community displayed significantly greater β-glucosidase and aminopeptidase enzyme activities per volume of porous medium than those of the free-living community. On a per-cell basis, the attached community had a significantly higher cell-specific aminopeptidase enzyme activity (1.07 × 10−7 nmol cell−1 h−1) than the free-living community (5.02 × 10−8 nmol cell−1 h−1). Conversely, the free-living community had a significantly higher cell-specific β-glucosidase activity (1.92 × 10−6 nmol cell−1 h−1) than the surface-associated community (6.08 × 10−7 nmol cell−1 h−1). The compositional and functional differences observed between these two communities may reflect different roles for these distinct but interacting communities in the decomposition of natural organic matter or biodegradation of xenobiotics in aquifers.

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Microbial Community Function in Electroactive Biofilm-based Constructed Wetlands

10.5194/bg-2018-428 ◽

2018 ◽

Cited By ~ 1

Author(s):

Carlos A. Ramírez-Vargas ◽

Carlos A. Arias ◽

Liang Zhang ◽

Hans Brix

Keyword(s):

Microbial Communities ◽

Constructed Wetlands ◽

Petroleum Coke ◽

Performance Enhancement ◽

Carbon Sources ◽

Spatial Dynamics ◽

Community Function ◽

Microbial Characterization ◽

Calcined Petroleum Coke

Abstract. The performance enhancement of constructed wetlands can be achieved through the coupling with microbial electrochemical technologies (MET). MET is a setup designed to mimic metabolic electrons exchange with insoluble donors and acceptors with the aid of electroactive bacteria and external electrical circuits. An alternative MET that dispenses of electrodes and circuits but uses an electro-conductive biofilter is called Microbial Electrochemical-based Constructed Wetland (METland). Previously it has been demonstrated that a METland has higher biodegradation rates than horizontal flow constructed wetlands, however given its novelty there are still uncertainties related to the removal of pollutants, including their microbial activity. The genetic characterization of microbial communities of a METland is desirable, but is time and resource consuming, then a characterization alternative could be based on functional analysis of the microbial communities. Community-level physiological profile (CLPP) is a useful method to evaluate the functional diversity of microbial communities based on the carbon source utilization pattern (CSUP). Therefore, this study was focused on the microbial characterization of laboratory scale METland based on CLPP analysis. The study included the characterization of microbial communities attached to two carbon-based electro-conductive materials (calcined petroleum coke from crushed electrodes – PK-A; calcined petroleum coke with low sulphur and nitrogen content – PK-LSN), in planted and non-planted set-ups. Variations on the metabolic activity of tested systems were identified and it seems to be related to the characteristics of the material, rather than the presence/absence of plants. In general, CSUP show differences along flow pathway, as well as among the tested systems, being carbohydrates and carboxylic/acetic acids the most consumed carbon sources, followed by polymers, amides/amines and amino acids. Also, were established some correlations between the utilization of carbon sources and the removal of pollutants. The obtained results provide useful insight into the spatial dynamics of METland systems.

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Copper affects composition and functions of microbial communities in marine biofilms at environmentally relevant concentrations

10.7287/peerj.preprints.27129 ◽

2018 ◽

Author(s):

Natàlia Corcoll ◽

Jianghua Yang ◽

Thomas Backhaus ◽

Xiaowei Zhang ◽

Martin Karl Eriksson ◽

...

Keyword(s):

Community Structure ◽

Primary Production ◽

Microbial Communities ◽

Algal Biomass ◽

Amplicon Sequencing ◽

Quality Standard ◽

Aquatic Communities ◽

Static Test ◽

Community Function ◽

Eukaryotic Organisms

Cu pollution in coastal areas is a worldwide threat for aquatic communities. This study assesses the effects of Cu exposure on microbial diversity, community structure and functions of microbial communities in marine periphyton biofilms at environmental relevant concentrations. Periphyton was exposed for 18 days to five Cu concentrations, between 0.01 and 10 μM, in a semi-static test. Diversity and community structure of prokaryotic and eukaryotic organisms were assessed by 16S and 18S amplicon sequencing, respectively. Community function was studied as impacts on algal biomass and primary production. Additionally, we studied Pollution-Induced Community Tolerance (PICT) using photosynthesis as the endpoint. Sequencing results detected an average of 9504 and 1242 OTUs for 16S and 18S, respectively, reflecting the huge biodiversity of marine periphytic biofilms. Eukaryotes represent the most Cu-sensitive kingdom, where effects were seen already at concentrations as low as 10 nM. The structure of the prokaryotic part of the community was impacted at slightly higher concentrations (60 nM), which is still in the range of the Cu concentrations observed in the area (80 nM).The current environmental quality standard for Cu of 70 nM therefore does not seem to be sufficiently protective for periphyton. Cu exposure resulted in a more Cu-tolerant community, which was accompanied by a reduced total algal biomass, increased relative abundance of diatoms and a reduction of primary production. Cu exposure changed the network of associations between taxa in the communities. A total of 23 taxa, including species within Proteobacteria, Bacteroidetes, Stramenopiles and Hacrobia, were identified as being particularly sensitive to Cu. DNA metabarcoding is presented as a sensitive tool for community-level ecotoxicological studies that allows to observe impacts simultaneously on a multitude of pro- and eukaryotic species, and therefore to identify particularly sensitive, non-cultivable species and taxa.

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

Nature Communications ◽

10.1038/s41467-021-26647-4 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Li Xie ◽

Wenying Shou

Keyword(s):

Microbial Communities ◽

Artificial Selection ◽

Species Interactions ◽

Evolutionary Dynamics ◽

Species Coexistence ◽

Evolutionary Trajectory ◽

Community Function ◽

Link Type ◽

Selection Strategies ◽

Effective Selection

AbstractMicrobial 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/.

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Ecology dictates evolution? About the importance of genetic and ecological constraints in adaptation

10.31219/osf.io/qkzb5 ◽

2018 ◽

Author(s):

Marjon G. J. de Vos ◽

Sijmen E Schoustra ◽

J. Arjan G. M. de Visser

Keyword(s):

Microbial Communities ◽

Major Determinant ◽

Model Systems ◽

Adaptive Landscape ◽

Ecological Interactions ◽

Ecological Constraints ◽

Adaptive Constraints

The topography of the adaptive landscape is a major determinant of the course of evolution. In this review we use the adaptive landscape metaphor to highlight the effect of ecology on evolution. We describe how ecological interactions modulate the shape of the adaptive landscape, and how this affects adaptive constraints. We focus on microbial communities as model systems.

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