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.