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      Genome-centric metagenomics provides insights into the core microbial community and functional profiles of biofloc aquaculture

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          ABSTRACT

          Bioflocs are microbial aggregates that play a pivotal role in shaping animal health, gut microbiota, and water quality in biofloc technology (BFT)-based aquaculture systems. Despite the worldwide application of BFT in aquaculture industries, our comprehension of the community composition and functional potential of the floc-associated microbiota (FAB community; ≥3 µm size fractions) remains rudimentary. Here, we utilized genome-centric metagenomic approach to investigate the FAB community in shrimp aquaculture systems, resulting in the reconstruction of 520 metagenome-assembled genomes (MAGs) spanning both bacterial and archaeal domains. Taxonomic analysis identified Pseudomonadota and Bacteroidota as core community members, with approximately 93% of recovered MAGs unclassified at the species level, indicating a large uncharacterized phylogenetic diversity hidden in the FAB community. Functional annotation of these MAGs unveiled their complex carbohydrate-degrading potential and involvement in carbon, nitrogen, and sulfur metabolisms. Specifically, genomic evidence supported ammonium assimilation, autotrophic nitrification, denitrification, dissimilatory nitrate reduction to ammonia, thiosulfate oxidation, and sulfide oxidation pathways, suggesting the FAB community’s versatility for both aerobic and anaerobic metabolisms. Conversely, genes associated with heterotrophic nitrification, anaerobic ammonium oxidation, assimilatory nitrate reduction, and sulfate reduction were undetected. Members of Rhodobacteraceae emerged as the most abundant and metabolically versatile taxa in this intriguing community. Our MAGs compendium is expected to expand the available genome collection from such underexplored aquaculture environments. By elucidating the microbial community structure and metabolic capabilities, this study provides valuable insights into the key biogeochemical processes occurring in biofloc aquacultures and the major microbial contributors driving these processes.

          IMPORTANCE

          Biofloc technology has emerged as a sustainable aquaculture approach, utilizing microbial aggregates (bioflocs) to improve water quality and animal health. However, the specific microbial taxa within this intriguing community responsible for these benefits are largely unknown. Compounding this challenge, many bacterial taxa resist laboratory cultivation, hindering taxonomic and genomic analyses. To address these gaps, we employed metagenomic binning approach to recover over 500 microbial genomes from floc-associated microbiota of biofloc aquaculture systems operating in South Korea and China. Through taxonomic and genomic analyses, we deciphered the functional gene content of diverse microbial taxa, shedding light on their potential roles in key biogeochemical processes like nitrogen and sulfur metabolisms. Notably, our findings underscore the taxa-specific contributions of microbes in aquaculture environments, particularly in complex carbon degradation and the removal of toxic substances like ammonia, nitrate, and sulfide.

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          metaSPAdes: a new versatile metagenomic assembler

          While metagenomics has emerged as a technology of choice for analyzing bacterial populations, the assembly of metagenomic data remains challenging, thus stifling biological discoveries. Moreover, recent studies revealed that complex bacterial populations may be composed from dozens of related strains, thus further amplifying the challenge of metagenomic assembly. metaSPAdes addresses various challenges of metagenomic assembly by capitalizing on computational ideas that proved to be useful in assemblies of single cells and highly polymorphic diploid genomes. We benchmark metaSPAdes against other state-of-the-art metagenome assemblers and demonstrate that it results in high-quality assemblies across diverse data sets.
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            dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication.

            The number of microbial genomes sequenced each year is expanding rapidly, in part due to genome-resolved metagenomic studies that routinely recover hundreds of draft-quality genomes. Rapid algorithms have been developed to comprehensively compare large genome sets, but they are not accurate with draft-quality genomes. Here we present dRep, a program that reduces the computational time for pairwise genome comparisons by sequentially applying a fast, inaccurate estimation of genome distance, and a slow, accurate measure of average nucleotide identity. dRep achieves a 28 × increase in speed with perfect recall and precision when benchmarked against previously developed algorithms. We demonstrate the use of dRep for genome recovery from time-series datasets. Each metagenome was assembled separately, and dRep was used to identify groups of essentially identical genomes and select the best genome from each replicate set. This resulted in recovery of significantly more and higher-quality genomes compared to the set recovered using co-assembly.
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              MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis

              Background The study of microbiomes using whole-metagenome shotgun sequencing enables the analysis of uncultivated microbial populations that may have important roles in their environments. Extracting individual draft genomes (bins) facilitates metagenomic analysis at the single genome level. Software and pipelines for such analysis have become diverse and sophisticated, resulting in a significant burden for biologists to access and use them. Furthermore, while bin extraction algorithms are rapidly improving, there is still a lack of tools for their evaluation and visualization. Results To address these challenges, we present metaWRAP, a modular pipeline software for shotgun metagenomic data analysis. MetaWRAP deploys state-of-the-art software to handle metagenomic data processing starting from raw sequencing reads and ending in metagenomic bins and their analysis. MetaWRAP is flexible enough to give investigators control over the analysis, while still being easy-to-install and easy-to-use. It includes hybrid algorithms that leverage the strengths of a variety of software to extract and refine high-quality bins from metagenomic data through bin consolidation and reassembly. MetaWRAP’s hybrid bin extraction algorithm outperforms individual binning approaches and other bin consolidation programs in both synthetic and real data sets. Finally, metaWRAP comes with numerous modules for the analysis of metagenomic bins, including taxonomy assignment, abundance estimation, functional annotation, and visualization. Conclusions MetaWRAP is an easy-to-use modular pipeline that automates the core tasks in metagenomic analysis, while contributing significant improvements to the extraction and interpretation of high-quality metagenomic bins. The bin refinement and reassembly modules of metaWRAP consistently outperform other binning approaches. Each module of metaWRAP is also a standalone component, making it a flexible and versatile tool for tackling metagenomic shotgun sequencing data. MetaWRAP is open-source software available at https://github.com/bxlab/metaWRAP. Electronic supplementary material The online version of this article (10.1186/s40168-018-0541-1) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                mSystems
                mSystems
                msystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                October 2024
                24 September 2024
                24 September 2024
                : 9
                : 10
                : e00782-24
                Affiliations
                [1 ]Department of Biological Sciences and Bioengineering, Inha University; , Incheon, South Korea
                [2 ]Institute for Specialized Teaching and Research, Inha University; , Incheon, South Korea
                [3 ]Center for Molecular and Cell Biology, Inha University; , Incheon, South Korea
                University of Illinois at Chicago; , Chicago, Illinois, USA
                Author notes
                Address correspondence to Jang-Cheon Cho, chojc@ 123456inha.ac.kr

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0001-9902-7454
                https://orcid.org/0000-0003-2815-1735
                https://orcid.org/0000-0002-0666-3791
                Article
                msystems00782-24 msystems.00782-24
                10.1128/msystems.00782-24
                11494986
                39315779
                2a8c9455-a86f-4aad-89f9-591d9ae5122d
                Copyright © 2024 Meora et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 07 June 2024
                : 06 September 2024
                Page count
                supplementary-material: 2, authors: 4, Figures: 5, References: 79, Pages: 19, Words: 10761
                Funding
                Funded by: Korea Institute of Marine Science and Technology promotion (KIMST);
                Award ID: KIMST-20210646
                Award Recipient :
                Funded by: National Research Foundation of Korea (NRF);
                Award ID: NRF-2022R1A2C3008502,NRF-2018R1A5A1025077
                Award Recipient :
                Categories
                Research Article
                microbial-ecology, Microbial Ecology
                Custom metadata
                October 2024

                biofloc technology,floc-associated microbiota,metagenomics,metagenome-assembled genomes,functional composition,nitrogen cycling

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