scholarly journals Determinism of microbial community assembly by drastic environmental change

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260591
Author(s):  
Akifumi Nishida ◽  
Mayuko Nakagawa ◽  
Masayuki Yamamura
Keyword(s):  
Microbial Community ◽  
Environmental Change ◽  
Community Assembly ◽  
In Silico ◽  
Ex Situ ◽  
Treated Wastewater ◽  
Rrna Gene ◽  
Microbial Community Assembly ◽  
Carbon Concentrations

Microbial community assembly is shaped by deterministic and stochastic processes, but the relationship between these processes and the environment is not understood. Here we describe a rule for the determinism and stochasticity of microbial community assembly affected by the environment using in silico, in situ, and ex situ experiments. The in silico experiment with a simple mathematical model showed that the existence of essential symbiotic microorganisms caused stochastic microbial community assembly, unless the community was exposed to a non-adapted nutritional concentration. Then, a deterministic assembly occurred due to the low number of microorganisms adapted to the environment. In the in situ experiment in the middle of a river, the microbial community composition was relatively deterministic after the drastic environmental change caused by the treated wastewater contamination, as analyzed by 16S rRNA gene sequencing. Furthermore, by culturing microbial communities collected from the upstream natural area and downstream urban area of the river in test tubes with varying carbon source concentrations, the upstream community assembly became deterministic with high carbon concentrations while the downstream community assembly became deterministic with low carbon concentrations. These results suggest that large environmental changes, which are different from the original environment, result in a deterministic microbial community assembly.

scholarly journals Emergent Simplicity in Microbial Community Assembly

2017 ◽  
Author(s):  
Joshua E. Goldford ◽  
Nanxi Lu ◽  
Djordje Bajic ◽  
Sylvie Estrela ◽  
Mikhail Tikhonov ◽  
...  
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Community Assembly ◽  
Competitive Exclusion ◽  
Ex Situ ◽  
Coarse Grained ◽  
Natural Environments ◽  
Complex Dynamic ◽  
Microbial Community Assembly ◽  
Consumer Resource

AbstractMicrobes assemble into complex, dynamic, and species-rich communities that play critical roles in human health and in the environment. The complexity of natural environments and the large number of niches present in most habitats are often invoked to explain the maintenance of microbial diversity in the presence of competitive exclusion. Here we show that soil and plant-associated microbiota, cultivated ex situ in minimal synthetic environments with a single supplied source of carbon, universally re-assemble into large and dynamically stable communities with strikingly predictable coarse-grained taxonomic and functional compositions. We find that generic, non-specific metabolic cross-feeding leads to the assembly of dense facilitation networks that enable the coexistence of multiple competitors for the supplied carbon source. The inclusion of universal and non-specific cross-feeding in ecological consumer-resource models is sufficient to explain our observations, and predicts a simple determinism in community structure, a property reflected in our experiments.

scholarly journals Hill-based dissimilarity indices and null models for analysis of microbial community assembly

2020 ◽  
Author(s):  
Oskar Modin ◽  
Raquel Liébana ◽  
Soroush Sabeh-Alam ◽  
Britt-Marie Wilén ◽  
Carolina Suarez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Relative Abundance ◽  
Community Assembly ◽  
Null Model ◽  
Amplicon Sequencing ◽  
Marker Genes ◽  
Rrna Gene ◽  
Data Set ◽  
Microbial Community Assembly ◽  
The Impact

Abstract Background: High-throughput amplicon sequencing of marker genes, such as the 16S rRNA gene in Bacteria and Archaea, provides a wealth of information about the composition of microbial communities. To quantify differences between samples and draw conclusions about factors affecting community assembly, dissimilarity indices are typically used. However, results are subject to several biases and data interpretation can be challenging. The Jaccard and Bray-Curtis indices, which are often used to quantify taxonomic dissimilarity, are not necessarily the most logical choices. Instead, we argue that Hill-based indices, which make it possible to systematically investigate the impact of relative abundance on dissimilarity, should be used for robust analysis of data. In combination with a null model, mechanisms of microbial community assembly can be analyzed. Here, we also introduce a new software, qdiv, which enables rapid calculations of Hill-based dissimilarity indices in combination with null models.Results: Using amplicon sequencing data from two experimental systems, aerobic granular sludge (AGS) reactors and microbial fuel cells (MFC), we show that the choices of bioinformatics pipeline and dissimilarity index can have considerable impacts on results and conclusions. Analysis of the AGS data set showed that results are sensitive to bioinformatics choices when dissimilarities between sample groups are compared with incidence-based indices. Analysis of the MFC data set with a combination of Hill-based indices and a null model revealed that random dispersal could explain the distribution of both rare and highly abundant taxa within a glucose-fed MFC whereas the distribution of taxa of intermediate relative abundance was governed by heterogeneous selection.Conclusions: Hill-based indices provides a rational framework for analysis of dissimilarity between microbial community samples. In combination with a null model, the effects of deterministic and stochastic factors on taxa of low-, intermediate-, and high relative abundance during microbial community assembly can be systematically investigated. Calculations of Hill-based dissimilarity indices in combination with a null model can be done in qdiv, which is freely available as a Python package (https://github.com/omvatten/qdiv).

Microbial community assembly and metabolic function during mammalian corpse decomposition

Science ◽  
2015 ◽  
Vol 351 (6269) ◽  
pp. 158-162 ◽  
Author(s):  
J. L. Metcalf ◽  
Z. Z. Xu ◽  
S. Weiss ◽  
S. Lax ◽  
W. Van Treuren ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Assembly ◽  
Metabolic Function ◽  
Microbial Community Assembly

scholarly journals Deterministic Selection Dominates Microbial Community Assembly in Termite Mounds Across a Large Spatial Area

2020 ◽  
Author(s):  
Qing-Lin Chen ◽  
Hang-Wei Hu ◽  
Zhen-Zhen Yan ◽  
Chao-Yu Li ◽  
Bao-Anh Thi Nguyen ◽  
...  
Keyword(s):  
Microbial Community ◽  
Stochastic Processes ◽  
Microbial Communities ◽  
Fungal Community ◽  
Community Assembly ◽  
Distance Decay ◽  
Termite Mounds ◽  
Deterministic Processes ◽  
Microbial Community Assembly

Abstract Background: Termites are ubiquitous insects in tropical and subtropical habitats, where they construct massive mounds from soil, their saliva and excreta. Termite mounds harbor an enormous amount of microbial inhabitants, which regulate multiple ecosystem functions such as mitigating methane emissions and increasing ecosystem resistance to climate change. However, we lack a mechanistic understanding about the role of termite mounds in modulating the microbial community assembly processes, which are essential to unravel the biological interactions of soil fauna and microorganisms, the major components of soil food webs. We conducted a large-scale survey across a >1500 km transect in northern Australia to investigate biogeographical patterns of bacterial and fungal community in 134 termite mounds and the relative importance of deterministic versus stochastic processes in microbial community assembly. Results: Microbial alpha (number of phylotypes) and beta (changes in bacterial and fungal community composition) significantly differed between termite mounds and surrounding soils. Microbial communities in termite mounds exhibited a significant distance-decay pattern, and fungal communities had a stronger distance-decay relationship (slope = -1.91) than bacteria (slope = -0.21). Based on the neutral community model (fitness < 0.7) and normalized stochasticity ratio index (NST) with a value below the 50% boundary point, deterministic selection, rather than stochastic forces, predominated the microbial community assembly in termite mounds. Deterministic processes exhibited significantly weaker impacts on bacteria (NST = 45.23%) than on fungi (NST = 33.72%), probably due to the wider habitat niche breadth and higher potential migration rate of bacteria. The abundance of antibiotic resistance genes (ARGs) was negatively correlated with bacterial/fungal biomass ratios, indicating that ARG content might be an important biotic factor that drove the biogeographic pattern of microbial communities in termite mounds. Conclusions: Deterministic processes play a more important role than stochastic processes in shaping the microbial community assembly in termite mounds, an unique habitat ubiquitously distributed in tropical and subtropical ecosystems. An improved understanding of the biogeographic patterns of microorganisms in termite mounds is crucial to decipher the role of soil faunal activities in shaping microbial community assembly, with implications for their mediated ecosystems functions and services.

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