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      Enhanced protein degradation by black soldier fly larvae ( Hermetia illucens L.) and its gut microbes

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          Abstract

          Black soldier fly larvae (BSFL) can convert a variety of organic wastes into biomass, and its gut microbiota are involved in this process. However, the role of gut microbes in the nutrient metabolism of BSFL is unclear. In this study, germ-free BSFL (GF) and gnotobiotic BSFL (GB) were evaluated in a high-protein artificial diet model. We used 16S rDNA sequencing, ITS1 sequencing, and network analysis to study gut microbiota in BSFL that degrade proteins. The protein reduction rate of the GB BSFL group was significantly higher (increased by 73.44%) than that of the GF BSFL group. The activity of gut proteinases, such as trypsin and peptidase, in the GB group was significantly higher than the GF group. The abundances of different gut microbes, including Pseudomonas spp., Orbus spp. and Campylobacter spp., were strongly correlated with amino acid metabolic pathways. Dysgonomonas spp. were strongly correlated with protein digestion and absorption. Issatchenkia spp. had a strong correlation with pepsin activity. Campylobacter spp., Pediococcus spp. and Lactobacillus spp. were strongly correlated with trypsin activity. Lactobacillus spp. and Bacillus spp. were strongly correlated with peptidase activity. Gut microbes such as Issatchenkia spp. may promote the gut proteolytic enzyme activity of BSFL and improve the degradation rate of proteins. BSFL protein digestion and absorption involves gut microbiota that have a variety of functions. In BSFL the core gut microbiota help complete protein degradation. These results demonstrate that core gut microbes in BSFL are important in protein degradation.

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          Most cited references62

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          UPARSE: highly accurate OTU sequences from microbial amplicon reads.

          Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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            Search and clustering orders of magnitude faster than BLAST.

            Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
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              VSEARCH: a versatile open source tool for metagenomics

              Background VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                10 January 2023
                2022
                : 13
                : 1095025
                Affiliations
                [1] 1State Key Laboratory of Agricultural Microbiology, National Engineering Research Center of Microbial Pesticides, College of Life Science and Technology, Huazhong Agricultural University , Wuhan, China
                [2] 2Hubei Hongshan Laboratory , Wuhan, China
                [3] 3Renmin Hospital of Wuhan University , Wuhan, China
                [4] 4Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural University , Wuhan, China
                Author notes

                Edited by: Vinay Kumar, ICAR-National Institute of Biotic Stress Management, India

                Reviewed by: Nikolaos Remmas, Democritus University of Thrace, Greece; Shihua Wang, Fujian Agriculture and Forestry University, China

                *Correspondence: Jibin Zhang, ✉ zhangjb@ 123456mail.hzau.edu.cn

                This article was submitted to Microbial Symbioses, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.1095025
                9871565
                36704554
                7d5eb885-ba1d-4948-9f4d-79487922bf59
                Copyright © 2023 Yu, Zhang, Zhu, Fan, Zheng, Cai, Zheng, Huang, Yu and Zhang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 10 November 2022
                : 16 December 2022
                Page count
                Figures: 8, Tables: 8, Equations: 1, References: 63, Pages: 18, Words: 9606
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                black soldier fly larvae,protein synergistic degradation,16s rdna sequencing,its1 sequencing,artificial diet

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