
AbstractMicrobial retting is a critical step in obtaining fiber bundles from bamboo culm using indigenous microorganisms. A cultivation‐independent technique for monitoring the changes in bacteria community during bamboo retting was applied in this work. This technique involves genetic profiling of PCR‐amplified small‐subunit rRNA and the single‐strand conformation polymorphism (SSCP) gel analysis of the PCR‐amplified 16S rDNA fragments. The study revealed that both the structure and the diversity of investigated communities varied with the incubation periods and sample locations. The bacteria bands from SCCP gel profiles related to Bacillus sp. decreased in intensity, and Phaeospirillum sp. and Azospirillum brasilense completely disappeared during the 4th and 5th month of incubation, while the bands related to the Sphingomonas japonica, Alphaproteobacterium Ellin335 and Microbacterium sp. increased. The bands closely related to Sphingomonads, Brevundimonas brasilense, Pseudoclavibacter sp., Agrococcus jenensis and Oxalophagus oxalicus remained dominant during the whole incubation period. This study showed that the use of PCR assay targeting 16S rRNA and SCCP profiling provided valuable information on monitoring the bacteria dynamic changes occurring in the bacteria community during bamboo retting, which is crucial for controlling the quality of the retting process and improving the retting efficiency, and thus benefits for fiber recovery.
DNA, Bacterial, Bacteria, Plant Stems, Textiles, Bioretting, Sequence Analysis, DNA, Poaceae, Polymerase Chain Reaction, SSCP, PCR, RNA, Ribosomal, 16S, Bacterial community, Metagenomics, Biomass, Polymorphism, Single-Stranded Conformational
DNA, Bacterial, Bacteria, Plant Stems, Textiles, Bioretting, Sequence Analysis, DNA, Poaceae, Polymerase Chain Reaction, SSCP, PCR, RNA, Ribosomal, 16S, Bacterial community, Metagenomics, Biomass, Polymorphism, Single-Stranded Conformational
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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