Published February 2019 | Version v1
Journal article

Bioinformatics analysis of metagenomics data of biogas-producing microbial communities in anaerobic digesters: A review

  • 1. Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, S117576 Singapore (Singapore)
  • 2. NUS Environmental Research Institute, National University of Singapore, 1 Create Way, Create Tower 15-02, S138602 Singapore (Singapore)

Description

Highlights: • Biogas-producing microbial communities were analyzed using bioinformatic tools. • Comprehensive microbial community investigation aimed to optimize digestion process. • Challenges involved data storage, processing technique, reliability and application. • Collaboration of biological and computer sciences can contribute to problem solving. • A big-data-based fermentation platform by artificial neural network was proposed. -- Abstract: Complex microbial communities in anaerobic digestion (AD) system play a vital role in the production of biogas. An in-depth understanding of the microbial compositions, diversity/similarity, metabolic networks, functional gene patterns, and relations between biodiversity and system functions at the genome level could help to optimize microbial productivity and contribute to enhancement of AD process. The study of microbial communities has been revolutionized in recent years with the development of high-throughput sequencing technologies. Analysis of high-throughput sequencing data and a suitable bioinformatics analysis approach therefore plays a very critical role in the investigation of microbial metagenome. The present article reviews the overall procedure of processing metagenomics data of microbial communities for revealing metagenomics characterization using bioinformatics approaches. This includes (1) introduction of application case summary, (2) DNA extraction and high-throughput pyrosequencing, (3) processing metagenomics data using function-based bioinformatics platforms and tools, and (4) several specific bioinformatics analysis of anaerobic microbial communities. Key findings on anaerobic digestion via bioinformatics analysis are summarized. Limitations and future potential of bioinformatics approaches for analysis of metagenomics information of microbial communities are also discussed, with the hope of promoting its further development. Finally, a big-data-based precision fermentation platform using artificial neural network is proposed for integrating the bioinformatics data of microbial communities with performance of anaerobic digesters to facilitate the usage of huge metagenomics data.

Additional details

Identifiers

DOI
10.1016/j.rser.2018.10.021;
PII
S1364032118307251;

Publishing Information

Journal Title
Renewable and Sustainable Energy Reviews
Journal Volume
100
Journal Page Range
p. 110-126
ISSN
1364-0321

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55020549
Subject category
S09: BIOMASS FUELS;
Descriptors DEI
ANAEROBIC DIGESTION; FERMENTATION; METHANE; NEURAL NETWORKS; PRODUCTIVITY; SPECIES DIVERSITY
Descriptors DEC
ALKANES; BIOCONVERSION; DIGESTION; HYDROCARBONS; ORGANIC COMPOUNDS

Optional Information

Copyright
Copyright (c) 2018 Elsevier Ltd. All rights reserved.