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Microbiome Evolution, Molecular Recognition and Interaction Webs: the PLOS Comp Biol July Issue

Here are our highlights from July’s PLOS Computational Biology

 

Neutral Models of Microbiome Evolution

There has been an explosion of research on host-associated microbial communities (i.e.,microbiomes) and how they correlate with host health, disease, phenotype, physiology and ecology. However, few studies have focused on how these microbiomes may have evolved. Qinglong Zeng and colleagues develop an agent-based framework to study the dynamics of microbiome evolution. Their framework incorporates neutral models of how hosts acquire their microbiomes, and how the environmental microbial community that is available to the hosts is assembled.

 

Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein

July Issue Image: Hydrophobic Gating of Ion Permeation in Magnesium Channel CorA. Credit: Pomès et al.
July Issue Image: Hydrophobic Gating of Ion Permeation in Magnesium Channel CorA. Credit: Pomès et al.

Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA interference, which is a key cellular mechanism for sequence-specific gene silencing. Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain largely elusive. Xuhui Huang and colleagues propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement. Their results hold the potential to be widely applied in the studies of other molecular recognition systems.

 

What Can Interaction Webs Tell Us About Species Roles?

Matrix structure of complete Tatoosh network, organized by groups. Credit: Sander et al.
Matrix structure of complete Tatoosh network, organized by groups. Credit: Sander et al.

Ecological interactions are highly diverse, even when considering a single species: the species might feed on a first, disperse the seeds of a second, and pollinate a third. Elizabeth L. Sander and colleagues extend the group model – a method for identifying broad patterns of interaction across a food web – to networks which contain multiple types of interactions. Using this new method, the authors test whether combining different interaction types leads to a better definition of the roles species play in ecological communities.

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