scholarly journals Spatial microbial community dynamics using a continuous species interaction model

2021 ◽  
Author(s):  
Anshuman Swain ◽  
Levi Fussell ◽  
William F Fagan
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Mutation Rate ◽  
Community Dynamics ◽  
Evolutionary Game ◽  
Species Interaction ◽  
Higher Order ◽  
Community Formation ◽  
Continuous Space ◽  
Wide Range

AbstractComprehending the assembly and maintenance of microbial diversity in natural communities, despite the abundance of antagonistic interactions, is a major problem of interest in biology. A common framework to study the problem is through cyclic dominance games over pairwise interactions. Recent papers incorporating higher-order interactions in these models have successfully explained high diversity of microbes, especially in communities where antibiotic producing, sensitive, and resistant strains co-exist. But most of these models are based on a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which best represents the highly interlinked, quickly evolving and continuous nature of microbial phenotypic space. Here, we present a model of species in a continuous space, with mutual higher order interactions, to examine the assembly and stability of microbial communities. Specifically, we focus on toxin production, vulnerability, and inhibition among the simulated species. We observe intricate interaction between certain parameters that generates highly divergent patterns of diversity and spatial community dynamics. We find that spatial properties are better predicted by species interaction constraints rather than mobility, and that community formation time, mobility, and mutation rate best explain the patterns of diversity.Significance StatementUnderstanding the assembly and maintenance of diverse microbial communities in nature is a question of great interest to theoretical biologists. Previous works, utilizing evolutionary game theory and other techniques, have explained the role of higher order interactions for the coexistence of diverse microbes in different kinds of environments. But these models are usually based on a small number of discrete species and low//no mutation rate, which is not how many natural microbial communities function. In this work, we explore a new framework which incorporates a continuous species model along with a wide range of mutation rates to comprehend the process of microbial community formation.

scholarly journals Metabolite-mediated modelling of microbial community dynamics captures emergent behaviour more effectively than species–species modelling

2019 ◽  
Vol 16 (159) ◽  
pp. 20190423 ◽  
Author(s):  
J. D. Brunner ◽  
N. Chia
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Composition ◽  
Community Dynamics ◽  
Microbial Community Composition ◽  
Growth Dynamics ◽  
Species Interaction ◽  
Interaction Models ◽  
Emergent Behaviour ◽  
Growth Experiments

Personalized models of the gut microbiome are valuable for disease prevention and treatment. For this, one requires a mathematical model that predicts microbial community composition and the emergent behaviour of microbial communities. We seek a modelling strategy that can capture emergent behaviour when built from sets of universal individual interactions. Our investigation reveals that species–metabolite interaction (SMI) modelling is better able to capture emergent behaviour in community composition dynamics than direct species–species modelling. Using publicly available data, we examine the ability of species–species models and species–metabolite models to predict trio growth experiments from the outcomes of pair growth experiments. We compare quadratic species–species interaction models and quadratic SMI models and conclude that only species–metabolite models have the necessary complexity to explain a wide variety of interdependent growth outcomes. We also show that general species–species interaction models cannot match the patterns observed in community growth dynamics, whereas species–metabolite models can. We conclude that species–metabolite modelling will be important in the development of accurate, clinically useful models of microbial communities.

Effects of Community Versus Single Strain Inoculants on the Biocontrol of Salmonella and Microbial Community Dynamics in Alfalfa Sprouts†

2005 ◽  
Vol 68 (1) ◽  
pp. 40-48 ◽  
Author(s):  
ANABELLE MATOS ◽  
JAY L. GARLAND
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Dynamics ◽  
Community Level ◽  
Microbial Consortia ◽  
Single Strain ◽  
Acridine Orange Staining ◽  
Physiological Profiles ◽  
Alfalfa Sprouts ◽  
Alfalfa Seeds

Potential biological control inoculants, Pseudomonas fluorescens 2-79 and microbial communities derived from market sprouts or laboratory-grown alfalfa sprouts, were introduced into alfalfa seeds with and without a Salmonella inoculum. We examined their ability to inhibit the growth of this foodborne pathogen and assess the relative effects of the inoculants on the alfalfa microbial community structure and function. Alfalfa seeds contaminated with a Salmonella cocktail were soaked for 2 h in bacterial suspensions from each inoculant tested. Inoculated alfalfa seeds were grown for 7 days and sampled during days 1, 3, and 7. At each sampling, alfalfa sprouts were sonicated for 7 min to recover microflora from the surface, and the resulting suspensions were diluted and plated on selective and nonselective media. Total bacterial counts were obtained using acridine orange staining, and the percentage culturability was calculated. Phenotypic potential of sprout-associated microbial communities inoculated with biocontrol treatments was assessed using community-level physiological profiles based on patterns of use of 95 separate carbon sources in Biolog plates. Community-level physiological profiles were also determined using oxygen-sensitive fluorophore in BD microtiter plates to examine functional patterns in these communities. No significant differences in total and mesophilic aerobe microbial cell density or microbial richness resulting from the introduction of inoculants on alfalfa seeds with and without Salmonella were observed. P. fluorescens 2-79 exhibited the greatest reduction in the growth of Salmonella early during alfalfa growth (4.22 log at day 1), while the market sprout inoculum had the reverse effect, resulting in a maximum log reduction (5.48) of Salmonella on day 7. Community-level physiological profiles analyses revealed that market sprout communities peaked higher and faster compared with the other inoculants tested. These results suggest that different modes of actions of single versus microbial consortia biocontrol treatments may be involved.

scholarly journals STRUKTUR KOMUNITAS MIKROBA TANAH DAN IMPLIKASINYA DALAM MEWUJUDKAN SISTEM PERTANIAN BERKELANJUTAN

el–Hayah ◽  
2012 ◽  
Vol 1 (4) ◽  
Author(s):  
Prihastuti Prihastuti
Keyword(s):  
Microbial Community ◽  
Microbial Diversity ◽  
Microbial Communities ◽  
Soil Microbial Community ◽  
Soil Microbial Communities ◽  
Organic Soil ◽  
Plant Type ◽  
Soil Microbial Community Structure ◽  
Soil Microbial ◽  
Wide Range

<p>Soils are made up of organic and an organic material. The organic soil component contains all the living creatures in the soil and the dead ones in various stages of decomposition.  Biological activity in soil helps to recycle nutrients, decompose organic matter making nutrient available for plant uptake, stabilize humus, and form soil particles.<br />The extent of the diversity of microbial in soil is seen to be critical to the maintenance of soil health and quality, as a wide range of microbial is involved in important soil functions.  That ecologically managed soils have a greater quantity and diversity of soil microbial. The two main drivers of soil microbial community structure, i.e., plant type and soil type, are thought to exert their function in a complex manner. The fact that in some situations the soil and in others the plant type is the key factor determining soil microbial diversity is related to their complexity of the microbial interactions in soil, including interactions between microbial and soil and microbial and plants. <br />The basic premise of organic soil stewardship is that all plant nutrients are present in the soil by maintaining a biologically active soil environment. The diversity of microbial communities has on ecological function and resilience to disturbances in soil ecosystems. Relationships are often observed between the extent of microbial diversity in soil, soil and plant quality and ecosystem sustainability. Agricultural management can be directed toward maximizing the quality of the soil microbial community in terms of disease suppression, if it is possible to shift soil microbial communities.</p><p>Keywords: structure, microbial, implication, sustainable agriculture<br /><br /></p>

scholarly journals Visualizing Microbial Community Dynamics via a Controllable Soil Environment

mSystems ◽  
2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Arunima Bhattacharjee ◽  
Dusan Velickovic ◽  
Thomas W. Wietsma ◽  
Sheryl L. Bell ◽  
Janet K. Jansson ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Microbial Community ◽  
Microbial Communities ◽  
Community Dynamics ◽  
Soil Microbial Communities ◽  
Soil Microbiome ◽  
Soil Core ◽  
Soil Microbial ◽  
Functional Relationships ◽  
Microbial Community Dynamics

ABSTRACT Understanding the basic biology that underpins soil microbiome interactions is required to predict the metaphenomic response to environmental shifts. A significant knowledge gap remains in how such changes affect microbial community dynamics and their metabolic landscape at microbially relevant spatial scales. Using a custom-built SoilBox system, here we demonstrated changes in microbial community growth and composition in different soil environments (14%, 24%, and 34% soil moisture), contingent upon access to reservoirs of nutrient sources. The SoilBox emulates the probing depth of a common soil core and enables determination of both the spatial organization of the microbial communities and their metabolites, as shown by confocal microscopy in combination with mass spectrometry imaging (MSI). Using chitin as a nutrient source, we used the SoilBox system to observe increased adhesion of microbial biomass on chitin islands resulting in degradation of chitin into N-acetylglucosamine (NAG) and chitobiose. With matrix-assisted laser desorption/ionization (MALDI)-MSI, we also observed several phospholipid families that are functional biomarkers for microbial growth on the chitin islands. Fungal hyphal networks bridging different chitin islands over distances of 27 mm were observed only in the 14% soil moisture regime, indicating that such bridges may act as nutrient highways under drought conditions. In total, these results illustrate a system that can provide unprecedented spatial information about interactions within soil microbial communities as a function of changing environments. We anticipate that this platform will be invaluable in spatially probing specific intra- and interkingdom functional relationships of microbiomes within soil. IMPORTANCE Microbial communities are key components of the soil ecosystem. Recent advances in metagenomics and other omics capabilities have expanded our ability to characterize the composition and function of the soil microbiome. However, characterizing the spatial metabolic and morphological diversity of microbial communities remains a challenge due to the dynamic and complex nature of soil microenvironments. The SoilBox system, demonstrated in this work, simulates an ∼12-cm soil depth, similar to a typical soil core, and provides a platform that facilitates imaging the molecular and topographical landscape of soil microbial communities as a function of environmental gradients. Moreover, the nondestructive harvesting of soil microbial communities for the imaging experiments can enable simultaneous multiomics analysis throughout the depth of the SoilBox. Our results show that by correlating molecular and optical imaging data obtained using the SoilBox platform, deeper insights into the nature of specific soil microbial interactions can be achieved.

scholarly journals Microbial dynamics in a High-Arctic glacier forefield: a combined field, laboratory, and modelling approach

2016 ◽  
Author(s):  
James A. Bradley ◽  
Sandra Arndt ◽  
Marie Šabacká ◽  
Liane G. Benning ◽  
Gary L. Barker ◽  
...  
Keyword(s):  
Microbial Community ◽  
Numerical Model ◽  
Microbial Communities ◽  
Community Dynamics ◽  
Heterotrophic Bacteria ◽  
High Arctic ◽  
Soil Development ◽  
Arctic Soils ◽  
Field Laboratory ◽  
Modelling Approach

Abstract. Modelling the development of soils in glacier forefields is necessary in order to assess how microbial and geochemical processes interact and shape soil development in response to glacier retreat. Furthermore, such models can help us predict microbial growth and the fate of Arctic soils in an increasingly ice-free future. Here, for the first time, we combined field sampling with laboratory analyses and numerical modelling to investigate microbial community dynamics in oligotrophic proglacial soils in Svalbard. We measured low bacterial growth rates and growth efficiencies (relative to estimates from Alpine glacier forefields), and high sensitivity to soil temperature (relative to temperate soils). We used these laboratory measurements to inform parameter values in a new numerical model and significantly refined predictions of microbial and biogeochemical dynamics of soil development over a period of roughly 120 years. The model predicted the observed accumulation of autotrophic and heterotrophic biomass. Genomic data indicated that initial microbial communities were dominated by bacteria derived from the subglacial environment, whereas older soils hosted a mixed community of autotrophic and heterotrophic bacteria. This finding was validated by the numerical model, which showed that active microbial communities play key roles in fixing and recycling carbon and nutrients. We also demonstrated the role of allochthonous carbon and microbial necromass in sustaining a pool of organic material, despite high heterotrophic activity in older soils. This combined field, laboratory and modelling approach demonstrates the value of integrated model-data studies to understand and quantify the functioning of the microbial community in an emerging High-Arctic soil ecosystem.

scholarly journals Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics

2021 ◽  
Vol 119 (1) ◽  
pp. e2020956119
Author(s):  
Anshuman Swain ◽  
Levi Fussell ◽  
William F. Fagan
Keyword(s):  
Microbial Diversity ◽  
Species Interactions ◽  
Community Dynamics ◽  
Spatial Dynamics ◽  
Higher Order ◽  
Formation Time ◽  
Community Formation ◽  
Order Effects ◽  
Disturbance Regimes ◽  
Antagonistic Interactions

The assembly and maintenance of microbial diversity in natural communities, despite the abundance of toxin-based antagonistic interactions, presents major challenges for biological understanding. A common framework for investigating such antagonistic interactions involves cyclic dominance games with pairwise interactions. The incorporation of higher-order interactions in such models permits increased levels of microbial diversity, especially in communities in which antibiotic-producing, sensitive, and resistant strains coexist. However, most such models involve a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which well represent the highly interlinked, quickly evolving, and continuous nature of microbial phenotypic space. Here, we present an alternative vision of spatial dynamics for microbial communities based on antagonistic interactions—one in which a large number of species interact in continuous phenotypic space, are capable of rapid mutation, and engage in both direct and higher-order interactions mediated by production of and resistance to antibiotics. Focusing on toxin production, vulnerability, and inhibition among species, we observe highly divergent patterns of diversity and spatial community dynamics. We find that species interaction constraints (rather than mobility) best predict spatiotemporal disturbance regimes, whereas community formation time, mobility, and mutation size best explain patterns of diversity. We also report an intriguing relationship among community formation time, spatial disturbance regimes, and diversity dynamics. This relationship, which suggests that both higher-order interactions and rapid evolution are critical for the origin and maintenance of microbial diversity, has broad-ranging links to the maintenance of diversity in other systems.

scholarly journals Which games are growing bacterial populations playing?

2015 ◽  
Vol 12 (108) ◽  
pp. 20150121 ◽  
Author(s):  
Xiang-Yi Li ◽  
Cleo Pietschke ◽  
Sebastian Fraune ◽  
Philipp M. Altrock ◽  
Thomas C. G. Bosch ◽  
...  
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Microbial Communities ◽  
Evolutionary Game Theory ◽  
Community Dynamics ◽  
Growth Parameters ◽  
Evolutionary Game ◽  
Frequency Dependent

Microbial communities display complex population dynamics, both in frequency and absolute density. Evolutionary game theory provides a natural approach to analyse and model this complexity by studying the detailed interactions among players, including competition and conflict, cooperation and coexistence. Classic evolutionary game theory models typically assume constant population size, which often does not hold for microbial populations. Here, we explicitly take into account population growth with frequency-dependent growth parameters, as observed in our experimental system. We study the in vitro population dynamics of the two commensal bacteria ( Curvibacter sp. (AEP1.3) and Duganella sp. (C1.2)) that synergistically protect the metazoan host Hydra vulgaris (AEP) from fungal infection. The frequency-dependent, nonlinear growth rates observed in our experiments indicate that the interactions among bacteria in co-culture are beyond the simple case of direct competition or, equivalently, pairwise games. This is in agreement with the synergistic effect of anti-fungal activity observed in vivo . Our analysis provides new insight into the minimal degree of complexity needed to appropriately understand and predict coexistence or extinction events in this kind of microbial community dynamics. Our approach extends the understanding of microbial communities and points to novel experiments.

scholarly journals Ecological Stability Properties of Microbial Communities Assessed by Flow Cytometry

mSphere ◽  
2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Zishu Liu ◽  
Nicolas Cichocki ◽  
Fabian Bonk ◽  
Susanne Günther ◽  
Florian Schattenberg ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Microbial Community ◽  
Microbial Communities ◽  
Temporal Resolution ◽  
Community Dynamics ◽  
Well Being ◽  
High Temporal Resolution ◽  
Ecological Stability ◽  
Stability Properties ◽  
Microbial Community Dynamics

Microbial communities drive many processes which affect human well-being directly, as in the human microbiome, or indirectly, as in natural environments or in biotechnological applications. Due to their complexity, their dynamics over time is difficult to monitor, and current sequence-based approaches are limited with respect to the temporal resolution. However, in order to eventually control microbial community dynamics, monitoring schemes of high temporal resolution are required. Flow cytometry provides single-cell-based data in the required temporal resolution, and we here use such data to compute stability properties as easy to interpret univariate indicators of microbial community dynamics. Such monitoring tools will allow for a fast, continuous, and cost-effective screening of stability states of microbiomes. Applicable to various environments, including bioreactors, surface water, and the human body, it will contribute to the development of control schemes to manipulate microbial community structures and performances.

scholarly journals Constrained proteome allocation affects coexistence in models of competitive microbial communities

2020 ◽  
Author(s):  
Leonardo Pacciani-Mori ◽  
Samir Suweis ◽  
Amos Maritan ◽  
Andrea Giometto
Keyword(s):  
Population Dynamics ◽  
Microbial Community ◽  
Microbial Communities ◽  
Community Dynamics ◽  
Bacterial Strains ◽  
Theoretical Frameworks ◽  
Microbial Community Dynamics ◽  
Common Resource ◽  
Multiple Species ◽  
Consumer Resource

Microbial communities are ubiquitous and play crucial roles in many natural processes. Despite their importance for the environment, industry and human health, there are still many aspects of microbial community dynamics that we do not understand quantitatively. Recent experiments have shown that the metabolism of species in a community is intertwined with its composition, suggesting that properties at the intracellular level such as the allocation of cellular proteomic resources must be taken into account when describing microbial communities with a population dynamics approach. In this work we reconsider one of the theoretical frameworks most commonly used to model population dynamics in competitive ecosystems, MacArthur’s consumer-resource model, in light of experimental evidence showing how pro-teome allocation affects microbial growth. This new framework allows us to describe community dynamics at an intermediate level of complexity between classical consumer-resource models and biochemical models of microbial metabolism, accounting for temporally-varying proteome allocation subject to constraints on growth and protein synthesis in the presence of multiple resources, while preserving analytical insight into the dynamics of the system. We first show experimentally that proteome allocation needs to be accounted for to properly understand the dynamics of even the simplest microbial community, i.e. two bacterial strains competing for one common resource. We then study the model analytically and numerically to determine the conditions that allow multiple species to coexist in systems with arbitrary numbers of species and resources.

scholarly journals Reproducible microbial community dynamics of two drinking water systems treating similar source waters

2019 ◽  
Author(s):  
Sarah C Potgieter ◽  
Ameet J Pinto ◽  
Minette Havenga ◽  
Makhosazana Sigudu ◽  
Stefanus N Venter
Keyword(s):  
Drinking Water ◽  
Microbial Community ◽  
Microbial Communities ◽  
Surface Waters ◽  
Distribution Systems ◽  
Community Dynamics ◽  
Microbial Community Dynamics ◽  
Two Systems ◽  
The Impact ◽  
Source Waters

AbstractIn addition to containing higher concentrations of organics and bacterial cells, surface waters are often more vulnerable to pollution and microbial contamination with intensive industrial and agricultural activities frequently occurring in areas surrounding the water source. Therefore, surface waters typically require additional treatment, where the choice of treatment strategy is critical for water quality. Using 16S rRNA gene profiling, this study provides a unique opportunity to simultaneously investigate and compare two drinking water treatment plants and their corresponding distribution systems. The two treatment plants treat similar surface waters, from the same river system, with the same sequential treatment strategies. Here, the impact of treatment and distribution on the microbial community within and between each system was compared over an eight-month sampling campaign. Overall, reproducible spatial and temporal dynamics within both DWTPs and their corresponding DWDSs were observed. Although source waters showed some dissimilarity in microbial community structure and composition, pre-disinfection treatments (i.e. coagulation, flocculation, sedimentation and filtration) resulted in highly similar microbial communities between the filter effluent samples. This indicated that the same treatments resulted in the development of similar microbial communities. Conversely, post-disinfection (i.e. chlorination and chloramination) resulted in increased dissimilarity between disinfected samples from the two systems, showing alternative responses of the microbial community to disinfection. Lastly, it was observed that within the distribution system the same dominant taxa were selected where samples increased in similarity with increased residence time. Although, differences were found between the two systems, overall treatment and distribution had a similar impact on the microbial community in each system. This study therefore provides valuable information on the impact of treatment and distribution on the drinking water microbiome.HighlightsSource waters show some dissimilarity in microbial community.Treatment processes increases similarity and selects for the same dominant taxa.Differential response to chlorination causing increased dissimilarity and variation.Stabilisation of DWDS microbial community through selection of same dominant taxa.Microbial community dynamics are reproducible between the two systems.

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