Genomic and proteomic approaches for dark fermentative biohydrogen production

Pallavi Sinha, Shantonu Roy and Debabrata Das

Renewable and Sustainable Energy Reviews, 2016, vol. 56, issue C, 1308-1321

Abstract: Dark fermentative H2 production is a promising approach since it requires minimal energy input as compared to other conventional methods of hydrogen production. Moreover, a wide variety of low cost-feedstock can be used that are released in the environment, thus providing an added advantage of waste management. This paper reviews the application of genomic and proteomic approaches to heterotrophic hydrogen production that could be useful in improvement of the same. Molecular techniques like polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE) are conventionally used for microbial profiling of mixed consortia. An impending application of molecular techniques like terminal-restriction fragment length polymorphism (T-RFLP), ribosomal intergenic spacer analysis (RISA), quantitative PCR (qPCR), single strand conformation polymorphism (SSCP), fluorescence in situ hybridization (FISH) and fluorescence activated cell sorting (FACS) could be potentially used for advanced and rapid microbial characterization. Molecular techniques like gene overexpression, homologous recombination, gene knockout and antisense RNA are extensively used for improvement of hydrogen production processes. Challenges of applying above contemporary molecular techniques in thermophilic biohydrogen production processes were also studied. Use of proteomics helps in understanding the effect of genetic improvement leading to changes in entire proteome of the organism. Moreover, it is a useful tool for study the functional aspect of overexpression, site directed mutagenesis, random mutagenesis etc. towards improvement of H2 production. Thus the study of genomic and proteomic techniques improve understanding of dark fermentative hydrogen production processes.

Keywords: Biohydrogen; Microbial characterization; Molecular techniques; Over expression; Proteomic study (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.rser.2015.12.035

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