Microbiome Responses to Perturbations: Understanding, Prediction, and Engineering

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Biological Processes and Systems".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 3736

Special Issue Editors


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Guest Editor
Department of Biological Systems Engineering, Department of Food Science and Technology, Nebraska Food for Health Center, University of Nebraska, 1400 R St, Lincoln, NE 68588, USA
Interests: microbial community modeling; metabolic modeling; metabolic network analysis; system optimization
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Guest Editor
The Arctic Centre for Sustainable Energy, Faculty of Bioscience, Fisheries and Economics, The Arctic University of Norway, Trams, Norway
Interests: microbial communities and bio design

Special Issue Information

Dear Colleagues, 

Harnessing microbial communities to the benefit of our society is considered the next frontier of science in various fields, including agriculture, environmenal science, biotechnology, and biomedical science, due to its huge impact on economy, the environment, and human health, when successful. Controlling or designing community-level properties through either targed interventions or the synthesis of functional consortia is a challenging goal, however, as biotic and abiotic perturbations to the system may lead to significant changes in community-level function, often in an unexpected way. Achieving this goal requires rational approaches that necessarily account for the dependencies of microbial growth, interactions, community function on environmental, genetic, and compositional factors. The utility and development of theoretical, computational, and experimental protocols/platforms and analytical tools in synthetic biology, computational biology, and microbial community ecology are criticially important in this regard. 

This special issue on "Microbiome Responses to Perturbations: Understanding, Prediction, and Engineering" invites experts in the related fields to contrbute original research articles, as well as reviews, to address current challenges and issues in further advancing our understanding to better predict the effect of perturbations on the dynamics and function of microbial communities towards system-level engineering. Topics include, but are not limited to:

  • Experimental studies on a microbial community’s response to perturbations
  • Computational, modeling, or data integration methods for predicting microbial interactions and community dynamics
  • Theoretical studies for revealing the design principles of microbial communities
  • Data-driven modeling for discovering perturbation-specific molecular signatures in microbial communities
  • Synthesis of functional consortia for controllable community function
  • Rational approaches to microbiome engineering
Prof. Dr. Hyun-Seob Song
Prof. Dr. Hans Bernstein
Guest Editors

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Keywords

  • microbial communities
  • modeling
  • synthetic consortia
  • microbial community ecology
  • computational biology

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Published Papers (1 paper)

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Research

14 pages, 1682 KiB  
Article
Investigation of Stress Response Genes in Antimicrobial Resistant Pathogens Sampled from Five Countries
by Rachael Pei, Liz Zhang, Catherine Duan, Michael Gao, Rachel Feng, Qian Jia and Zuyi (Jacky) Huang
Processes 2021, 9(6), 927; https://doi.org/10.3390/pr9060927 - 25 May 2021
Cited by 7 | Viewed by 3196
Abstract
Pathogens, which survive from stressed environmental conditions and evolve with antimicrobial resistance, cause millions of human diseases every year in the world. Fortunately, the NCBI Pathogen Detection Isolates Browser (NPDIB) collects the detected stress response genes and antimicrobial resistance genes in pathogen isolates [...] Read more.
Pathogens, which survive from stressed environmental conditions and evolve with antimicrobial resistance, cause millions of human diseases every year in the world. Fortunately, the NCBI Pathogen Detection Isolates Browser (NPDIB) collects the detected stress response genes and antimicrobial resistance genes in pathogen isolates sampled around the world. While several studies have been conducted to identify important antimicrobial resistance genes, little work has been done to analyze the stress response genes in the NPDIB database. In order to address this, this work conducted the first comprehensive statistical analysis of the stress response genes from five countries of the major residential continents, including the US, the UK, China, Australia, and South Africa. Principal component analysis was first conducted to project the stress response genes onto a two-dimensional space, and hierarchical clustering was then implemented to identify the outlier (i.e., important) genes that show high occurrences in the historical data from 2010 to 2020. Stress response genes and AMR genes were finally analyzed together to investigate the co-occurring relationship between these two types of genes. It turned out that seven genes were commonly found in all five countries (i.e., arsR, asr, merC, merP, merR, merT, and qacdelta1). Pathogens E. coli and Shigella, Salmonella enterica, and Klebsiella pneumoniae were the major pathogens carrying the stress response genes. The hierarchical clustering result showed that certain stress response genes and AMR genes were grouped together, including golT~golS and mdsB~mdsC, ymgB and mdtM, and qacEdelta1 and sul1. The occurrence analysis showed that the samples containing three stress response genes and three AMR genes had the highest detection frequency in the historical data. The findings of this work on the important stress response genes, along with their connection with AMR genes, could inform future drug development that targets stress response genes to weaken antimicrobial resistance pathogens. Full article
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