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. 2019 Oct 29;4(5):e00550-19.
doi: 10.1128/mSystems.00550-19.

Interrogation of Internal Workings in Microbial Community Assembly: Play a Game through a Behavioral Network?

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Interrogation of Internal Workings in Microbial Community Assembly: Play a Game through a Behavioral Network?

Qian Wang et al. mSystems. .

Abstract

Increasing evidence shows that the influence of microbiota on biogeochemical cycling, plant development, and human health is executed through a complex network of microbe-microbe interactions. However, characterizing how microbes interact and work together within closely packed and highly heterogeneous microbial ecosystems is extremely challenging. Here, we describe a rule-of-thumb framework for visualizing polymicrobial interactions and extracting general principles that underlie microbial communities. We integrate elements of metabolic ecology, behavioral ecology, and game theory to quantify the interactive strategies by which microbes at any taxonomic level compete for resources and cooperate symbiotically with each other to form and stabilize ecological communities. We show how the framework can chart an omnidirectional landscape of microbial cooperation and competition that may drive various natural processes. This framework can be implemented into genome-wide association studies to unravel the genetic mechanisms underlying microbial interaction networks and their evolutionary consequences along spatiotemporal gradients.IMPORTANCE Identifying general biological rules that underlie the complexity and heterogeneity of microbial communities has proven to be highly challenging. We present a rule-of-thumb framework for studying and characterizing how microbes interact with each other across different taxa to determine community behavior and dynamics. This framework is computationally simple but conceptually meaningful, and it can provide a starting point to generate novel biological hypotheses about microbial interactions and explore internal workings of microbial community assembly in depth.

Keywords: competition; cooperation; game theory; microbial interaction network.

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Figures

FIG 1
FIG 1
Quantitative description of mutualism (blue) and parasitism (red). Assume a microbial community in which two microbes A and B, whose abundance is denoted by N1 and N2, respectively, interact with each other. The blue curve, specified by log N1 + log N2, describes how the two microbes cooperate to form mutualism, with arrows indicating the increase of mutualism with increasing equality of their abundance. The red curve, specified by log N1 – log N2, is indicative of parasitism through competition, by which one microbe gains by reducing the fitness of the other, with arrows representing the direction of increasing parasitism. The black circle is the position at which mutualism achieves a maximum degree whereas parasitism is minimum.
FIG 2
FIG 2
The network of mutualism (A) and parasitism (B) among eight phyla (distinguished by colors) derived from 127 hosts of the Hutterites, including 93 in winter and 91 in summer. (Panels 1 and 3) Mutualism (indicated by double arrowed lines) and parasitism (indicated by T-shaped lines) expressed independently in winter and summer. The size of the circles indicates the strength of mutualism or parasitism among different genera within phyla, whereas the thickness of the lines indicates the strength of pairwise mutualism or parasitism among different genera from different phyla. (Panels 2) On the diagonal of the matrix are the signs of within-phylum mutualism or parasitism changes from winter to summer (+ for increase, 0 for no change, and – for decrease). The right bottom part reports the correlation coefficient (with its estimated confidence interval) of mutualism or parasitism between the two seasons, representing the season-dependent similarity of the mutualism or parasitism networks. The left top part reports a colored scale representing the results of the significance test of the season-dependent strength difference of mutualism or parasitism between the same phylum pairs. The more intense the color, the higher the degree of mutualism or parasitism. (Panels 4) Cells on the diagonal of the matrix represent the significance tests of correlations of within-phylum mutualism (A) or parasitism (B) with BMI, each of which is separated into two parts for winter (left top) and summer (right bottom). The left top and right bottom portions represent the significance test of the correlations of between-phylum mutualism or parasitism with BMI. The significance tests of the correlations of the microbial abundance of each phylum with BMI are given in the BMI columns (winter) and the BMI rows (summer).
FIG 3
FIG 3
Correlations between mutualism and parasitism over phylum pairs in winter (A) and summer (B). Single-colored and double-colored circles are within-phylum and between-phylum mutualism or parasitism, respectively. The arrowed line on the diagonal shaded area indicates the change of microbial interaction from maximum mutualism to maximum parasitism.

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