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      Microecological Koch’s postulates reveal that intestinal microbiota dysbiosis contributes to shrimp white feces syndrome

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          Abstract

          Background

          Recently, increasing evidence supports that some complex diseases are not attributed to a given pathogen, but dysbiosis in the host intestinal microbiota (IM). The full intestinal ecosystem alterations, rather than a single pathogen, are associated with white feces syndrome (WFS), a globally severe non-infectious shrimp disease, while no experimental evidence to explore the causality. Herein, we conducted comprehensive metagenomic and metabolomic analysis, and intestinal microbiota transplantation (IMT) to investigate the causal relationship between IM dysbiosis and WFS.

          Results

          Compared to the Control shrimp, we found dramatically decreased microbial richness and diversity in WFS shrimp. Ten genera, such as Vibrio, Candidatus Bacilloplasma, Photobacterium, and Aeromonas, were overrepresented in WFS, whereas 11 genera, including Shewanella, Chitinibacter, and Rhodobacter were enriched in control. The divergent changes in these populations might contribute the observation that a decline of pathways conferring lipoic acid metabolism and mineral absorption in WFS. Meanwhile, some sorts of metabolites, especially lipids and organic acids, were found to be related to the IM alteration in WFS. Integrated with multiomics and IMT, we demonstrated that significant alterations in the community composition, functional potentials, and metabolites of IM were closely linked to shrimp WFS. The distinguished metabolites which were attributed to the IM dysbiosis were validated by feed-supplementary challenge. Both homogenous selection and heterogeneous selection process were less pronounced in WFS microbial community assembly. Notably, IMT shrimp from WFS donors eventually developed WFS clinical signs, while the dysbiotic IM can be recharacterized in recipient shrimp.

          Conclusions

          Collectively, our findings offer solid evidence of the causality between IM dysbiosis and shrimp WFS, which exemplify the ‘microecological Koch’s postulates’ (an intestinal microbiota dysbiosis, a disease) in disease etiology, and inspire our cogitation on etiology from an ecological perspective.

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          Most cited references31

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          FLASH: fast length adjustment of short reads to improve genome assemblies.

          Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
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            Stochastic Community Assembly: Does It Matter in Microbial Ecology?

            Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.
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              Quantifying community assembly processes and identifying features that impose them.

              Spatial turnover in the composition of biological communities is governed by (ecological) Drift, Selection and Dispersal. Commonly applied statistical tools cannot quantitatively estimate these processes, nor identify abiotic features that impose these processes. For interrogation of subsurface microbial communities distributed across two geologically distinct formations of the unconfined aquifer underlying the Hanford Site in southeastern Washington State, we developed an analytical framework that advances ecological understanding in two primary ways. First, we quantitatively estimate influences of Drift, Selection and Dispersal. Second, ecological patterns are used to characterize measured and unmeasured abiotic variables that impose Selection or that result in low levels of Dispersal. We find that (i) Drift alone consistently governs ∼25% of spatial turnover in community composition; (ii) in deeper, finer-grained sediments, Selection is strong (governing ∼60% of turnover), being imposed by an unmeasured but spatially structured environmental variable; (iii) in shallower, coarser-grained sediments, Selection is weaker (governing ∼30% of turnover), being imposed by vertically and horizontally structured hydrological factors;(iv) low levels of Dispersal can govern nearly 30% of turnover and be caused primarily by spatial isolation resulting from limited exchange between finer and coarser-grain sediments; and (v) highly permeable sediments are associated with high levels of Dispersal that homogenize community composition and govern over 20% of turnover. We further show that our framework provides inferences that cannot be achieved using preexisting approaches, and suggest that their broad application will facilitate a unified understanding of microbial communities.
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                Author and article information

                Contributors
                lsshzhj@mail.sysu.edu.cn
                735580213@qq.com
                xiongjinbo@nbu.edu.cn
                714482872@qq.com
                zhourenj@mail2.sysu.edu.cn
                1505043889@qq.com
                406215797@qq.com
                385831942@qq.com
                1114750275@qq.com
                wh19950622@vip.qq.com
                190232791@qq.com
                lsswsp@mail.sysu.edu.cn
                ksatapornvanit@gmail.com
                ningdaliang@ou.edu
                jzhou@ou.edu
                lsshjg@mail.sysu.edu.cn
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                10 March 2020
                10 March 2020
                2020
                : 8
                : 32
                Affiliations
                [1 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, School of Marine Sciences, , Sun Yat-sen University, ; Guangzhou, Guangdong People’s Republic of China
                [2 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, State Key Laboratory of Biocontrol, School of Life Sciences, , Sun Yat-sen University, ; Guangzhou, Guangdong People’s Republic of China
                [3 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, Southern Marine Sciences and Engineering Guangdong Laboratory (Zhuhai), , Sun Yat-sen University, ; Guangzhou, Guangdong People’s Republic of China
                [4 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, South China Sea Resource Exploitation and Protection Collaborative Innovation Center, School of Marine Sciences, , Sun Yat-sen University, ; Guangzhou, Guangdong People’s Republic of China
                [5 ]GRID grid.203507.3, ISNI 0000 0000 8950 5267, School of Marine Sciences, , Ningbo University, ; Ningbo, People’s Republic of China
                [6 ]GRID grid.9723.f, ISNI 0000 0001 0944 049X, Department of Fishery Biology, Faculty of Fisheries, , Kasetsart University, ; Bangkok, Thailand
                [7 ]GRID grid.266900.b, ISNI 0000 0004 0447 0018, Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, , University of Oklahoma, ; Norman, OK USA
                Author information
                http://orcid.org/0000-0003-1601-3802
                Article
                802
                10.1186/s40168-020-00802-3
                7065354
                32156316
                8e2340a2-d8da-4bb5-a944-2fc382879c40
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 6 August 2019
                : 10 February 2020
                Funding
                Funded by: the China Agriculture Research System
                Award ID: CARS-48
                Award Recipient :
                Funded by: China-ASEAN Maritime Cooperation Fund
                Award ID: 0
                Award Recipient :
                Funded by: Guangdong MEPP Fund
                Award ID: NO.GDOE (2019) A21
                Award Recipient :
                Funded by: the Guangzhou Science Technology and Innovation Commission Project
                Award ID: 201510010071
                Award Recipient :
                Funded by: the Guangdong Ocean and Fishery Bureau Project
                Award ID: 20164200042090023
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                pacific white shrimp,intestinal microbiota,intestinal microbiota transplantation,white feces syndrome,microecological koch’s postulates

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