Stress and stability: applying the Anna Karenina principle to animal microbiomes

Nature Microbiology, Journal Year: 2017, Volume and Issue: 2(9)

Published: Aug. 23, 2017

Language: Английский

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The Human Gut Microbiome: From Association to Modulation

Cell, Journal Year: 2018, Volume and Issue: 172(6), P. 1198 - 1215

Published: March 1, 2018

Language: Английский

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Disentangling Interactions in the Microbiome: A Network Perspective

Trends in Microbiology, Journal Year: 2016, Volume and Issue: 25(3), P. 217 - 228

Published: Dec. 2, 2016

TrendsPolymicrobial communities (microbiota) are complex, dynamic, and ubiquitous.Microbiota play a central role in host health development. For example, dysbiotic shifts the composition of human microbiome have been linked to wide variety issues, such as obesity, diabetes, eczema, heart disease, asthma, colitis, etc.The complexity microbiomes motivates movement from reductionist approaches that focus on individual pathogens isolation more holistic interactions among members community their hosts.Network theory has emerged an extremely promising approach for modelling complex biological systems with multifaceted between members, microbiota.Networks enhance analysis polymicrobial within microbiota health, development.AbstractMicrobiota now widely recognized being players all organisms ecosystems, subsequently subject intense study. However, analyzing converting data into meaningful insights remain very challenging. In this review, we highlight recent advances network applicability research. We discuss emerging graph theoretical concepts used other research disciplines demonstrate how they well suited enhancing our understanding higher-order occur microbiomes. Network-based analytical potential help disentangle microbe–host interactions, thereby further personalized medicine, public environmental industrial applications, agriculture.

Language: Английский

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Engineering Microbiomes to Improve Plant and Animal Health

Trends in Microbiology, Journal Year: 2015, Volume and Issue: 23(10), P. 606 - 617

Published: Sept. 26, 2015

Language: Английский

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Functional Redundancy-Induced Stability of Gut Microbiota Subjected to Disturbance

Trends in Microbiology, Journal Year: 2016, Volume and Issue: 24(5), P. 402 - 413

Published: March 17, 2016

Language: Английский

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The sponge holobiont in a changing ocean: from microbes to ecosystems

Microbiome, Journal Year: 2018, Volume and Issue: 6(1)

Published: March 9, 2018

The recognition that all macroorganisms live in symbiotic association with microbial communities has opened up a new field biology. Animals, plants, and algae are now considered holobionts, complex ecosystems consisting of the host, microbiota, interactions among them. Accordingly, ecological concepts can be applied to understand host-derived processes govern dynamics interactive networks within holobiont. In marine systems, holobionts further integrated into larger more ecosystems, concept referred as "nested ecosystems." this review, we discuss dynamic interact at multiple scales respond environmental change. We focus on symbiosis sponges their communities—a resulted one most diverse environment. recent years, sponge microbiology remarkably advanced terms curated databases, standardized protocols, information functions microbiota. Like Russian doll, these translated holobiont impact surrounding ecosystem. For example, sponge-associated metabolisms, fueled by high filtering capacity substantially affect biogeochemical cycling key nutrients like carbon, nitrogen, phosphorous. Since increasingly threatened anthropogenic stressors jeopardize stability ecosystem, link between perturbations, dysbiosis, diseases. Experimental studies suggest community composition is tightly linked health, but whether dysbiosis cause or consequence collapse remains unresolved. Moreover, potential role microbiome mediating for acclimate adapt change unknown. Future should aim identify mechanisms underlying scales, from develop management strategies preserve provided our present future oceans.

Language: Английский

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From hairballs to hypotheses–biological insights from microbial networks

FEMS Microbiology Reviews, Journal Year: 2018, Volume and Issue: 42(6), P. 761 - 780

Published: July 25, 2018

Microbial networks are an increasingly popular tool to investigate microbial community structure, as they integrate multiple types of information and may represent systems-level behaviour. Interpreting these is not straightforward, the biological implications network properties unclear. Analysis allows researchers predict hub species interactions. Additionally, such analyses can help identify alternative states niches. Here, we review factors that result in spurious predictions address emergent be meaningful context microbiome. We also give overview studies analyse new hypotheses. Moreover, show a simulation how affected by choice environmental factors. For example, consistent across tools, heterogeneity induces modularity. highlight need for robust inference suggest strategies infer more reliably.

Language: Английский

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CoNet app: inference of biological association networks using Cytoscape

F1000Research, Journal Year: 2016, Volume and Issue: 5, P. 1519 - 1519

Published: Oct. 14, 2016

Here we present the Cytoscape app version of our association network inference tool CoNet. Though CoNet was developed with microbial community data from sequencing experiments in mind, it is designed to be generic and can detect associations any set where biological entities (such as genes, metabolites or species) have been observed repeatedly. The supports 2.x 3.x offers a variety approaches, which also combined. Here briefly describe its main features illustrate use on count obtained by 16S rDNA arctic soil samples. available at: http://apps.cytoscape.org/apps/conet.

Language: Английский

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Microbial interactions and community assembly at microscales

Current Opinion in Microbiology, Journal Year: 2016, Volume and Issue: 31, P. 227 - 234

Published: May 25, 2016

In most environments, microbial interactions take place within microscale cell aggregates. At the scale of these aggregates (∼100 μm), are likely to be dominant driver population structure and dynamics. particular, organisms that exploit interspecific increase ecological performance often co-aggregate. Conversely, antagonize each other will tend spatially segregate, creating distinct micro-communities increased diversity at larger length scales. We argue that, in order understand role biological play community function, it is necessary study spatial organization with enough throughput measure statistical associations between taxa possible alternative states. conclude by proposing strategies tackle this challenge.

Language: Английский

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Species co‐occurrence networks: Can they reveal trophic and non‐trophic interactions in ecological communities?

Ecology, Journal Year: 2018, Volume and Issue: 99(3), P. 690 - 699

Published: Jan. 16, 2018

Abstract Co‐occurrence methods are increasingly utilized in ecology to infer networks of species interactions where detailed knowledge based on empirical studies is difficult obtain. Their use particularly common, but not restricted to, microbial constructed from metagenomic analyses. In this study, we test the efficacy procedure by comparing an inferred network using spatially intensive co‐occurrence data rocky intertidal zone central Chile a well‐resolved, empirically based, interaction same region. We evaluated overlap information provided each and extent which there bias for better detect known trophic or non‐trophic, positive negative interactions. found poor correspondence between with overall sensitivity (probability true link detection) equal 0.469, specificity (true non‐interaction) 0.527. The ability varied type. Positive non‐trophic such as commensalism facilitation were detected at highest rates. These results demonstrate that do represent classical ecological defined direct observations experimental manipulations. provide about joint spatial effects environmental conditions, recruitment, and, some extent, biotic interactions, among latter, they tend niche‐expanding Detection links (sensitivity specificity) was higher well‐known keystone than rest consumers community. Thus, observed previous theoretical studies, patterns must be interpreted caution, especially when extending interaction‐based theory interpret variability stability. may valuable analysis community dynamics blends environment, rather pairwise alone.

Language: Английский

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