scholarly journals A Gastrointestinal Metagenomic Study On Mudskippers Supports Their Terrestrial Adaptation

2022 ◽  
Author(s):  
Bo Dong ◽  
Jing Liu ◽  
Bing Chen ◽  
Yuqi Huang ◽  
Peng Ai ◽  
...  
Keyword(s):  
Fish Species ◽  
Life Style ◽  
Potential Functions ◽  
Metagenomic Data ◽  
Literature Mining ◽  
Microbial Composition ◽  
Terrestrial Life ◽  
Metagenomic Study ◽  
Amphibious Fishes ◽  
Genome Level

Abstract -Purpose: The adaptability of blue-spotted mudskipper (Boleophthalmus Periophthalmodon; BP) and giant-fin mudskipper (Periophthalmus magnuspinnatus; PM), has been previously reported at the genome level to explain their amphibious life. However, the roles of GI microbiota in their adaptation to the terrestrial life are worth exploring. -Methods: In this study, we mainly utilized metagenomic data from these two representative mudskippers and typical aquicolous fish species to obtain microbial composition, diversity, abundance and potential functions of GI microbiota for comparisons between amphibious and aquicolous fishes. Meanwhile, we summarized the GI microbiota results of representative seawater fishes, freshwater fishes, amphibians, and terrestrial animals by literature mining for comparing those of the mudskippers. -Result: Interestingly the content for each dominant phylum was strikingly different among BP, PM and aquicolous fishes. We also observed that the profile of GI microbiota in mudskippers owned the typical bacterial families for the terrestrial animals, (freshwater and seawater) fishes, and amphibians at the same time, which is consistent with their life style of water-to-land and freshwater to seawater transition. More interestingly, certain bacteria strains like S24-7, previously thought to be specific in terrestrial animals, were also identified in both BP and PM. -Conclusion: The various composite and diversity of mudskipper GI microflora are therefore considered to conduce to their terrestrial adaptation in these amphibious fishes.

Aspects of the Physiology of Terrestrial Life in Amphibious Fishes

1969 ◽  
Vol 50 (1) ◽  
pp. 141-149 ◽  
Author(s):  
MALCOLM S. GORDON ◽  
INGE BOËTIUS ◽  
DAVID H. EVANS ◽  
ROSEMARY McCARTHY ◽  
LARRY C. OGLESBY
Keyword(s):  
Thermal Stresses ◽  
Severe Dehydration ◽  
Evaporative Water ◽  
Lethal Temperatures ◽  
Physiological Adaptations ◽  
Urea Production ◽  
Terrestrial Life ◽  
Production Increase ◽  
Amphibious Fishes ◽  
Environmental Temperatures

1. A study has been carried out of major aspects of the physiological adaptations for terrestrial life possessed by the amphibious mudskipper fish, Periophthalmus sobrinus, on the island of Nosy Bé, Madagascar. 2. These fish can survive for approximately 1½ days out of water, if not exposed to severe dehydration or thermal stresses. Evaporative water-loss rates while out of water are relatively low. Upper lethal temperatures are only a few degrees above normal midday environmental temperatures. 3. These fish lack the symptoms of the ‘diving syndrome’. Metabolic rates (oxygen consumption), heart rates, and blood lactic acid concentrations are not affected by shifts of fish between water and air. 4. Rates of ammonia and urea production increase in fish out of water. The ratio of urea/ammonia also increases. 5. The generality of the results, also their physiological significance, are discussed.

scholarly journals Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples

2017 ◽  
Author(s):  
Feiqiao Brian Yu ◽  
Paul C. Blainey ◽  
Frederik Schulz ◽  
Tanja Woyke ◽  
Mark A. Horowitz ◽  
...  
Keyword(s):  
Single Cell ◽  
Statistical Power ◽  
Ad Hoc ◽  
Hot Spring ◽  
Genomic Structure ◽  
Metagenomic Data ◽  
Rigorous Approach ◽  
Environmental Selection ◽  
Wide Range ◽  
Genome Level

AbstractMetagenomics and single-cell genomics have enabled the discovery of many new genomes from previously unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and in many respects represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes from complex samples. In addition, by generating 96 sub-samples from each environmental sample, this method maintains high throughput, reduces sample complexity, and preserves single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes larger than 0.5 Mbps. These genomes represent novel lineages at different taxonomic levels, including three deeply branching lineages. Functional analysis revealed that these organisms utilize diverse pathways for energy metabolism. The resolution of this mini-metagenomic method enabled accurate quantification of genome abundance, even for genomes less than 1% in relative abundance. Our analyses also revealed a wide range of genome level single nucleotide polymorphism (SNP) distributions with nonsynonymous to synonymous ratio indicative of low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomic make it a powerful tool to dissect the genomic structure microbial communities while effectively preserving the fundamental unit of biology, the single cell.

scholarly journals Tamock: simulation of habitat-specific benchmark data in metagenomics

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Samuel M. Gerner ◽  
Alexandra B. Graf ◽  
Thomas Rattei
Keyword(s):  
Sequence Data ◽  
Metagenomic Data ◽  
Real Sequence ◽  
Method Performance ◽  
Additional Information ◽  
Benchmark Data ◽  
Metagenomic Study ◽  
Ncbi Refseq ◽  
Automated Simulation ◽  
User Friendly

Abstract Background Simulated metagenomic reads are widely used to benchmark software and workflows for metagenome interpretation. The results of metagenomic benchmarks depend on the assumptions about their underlying ecosystems. Conclusions from benchmark studies are therefore limited to the ecosystems they mimic. Ideally, simulations are therefore based on genomes, which resemble particular metagenomic communities realistically. Results We developed Tamock to facilitate the realistic simulation of metagenomic reads according to a metagenomic community, based on real sequence data. Benchmarks samples can be created from all genomes and taxonomic domains present in NCBI RefSeq. Tamock automatically determines taxonomic profiles from shotgun sequence data, selects reference genomes accordingly and uses them to simulate metagenomic reads. We present an example use case for Tamock by assessing assembly and binning method performance for selected microbiomes. Conclusions Tamock facilitates automated simulation of habitat-specific benchmark metagenomic data based on real sequence data and is implemented as a user-friendly command-line application, providing extensive additional information along with the simulated benchmark data. Resulting benchmarks enable an assessment of computational methods, workflows, and parameters specifically for a metagenomic habitat or ecosystem of a metagenomic study. Availability Source code, documentation and install instructions are freely available at GitHub (https://github.com/gerners/tamock).

scholarly journals BiomeSeq: A Tool for the Characterization of Animal Microbiomes from Metagenomic Data

2021 ◽  
Author(s):  
Kelly A. Mulholland ◽  
Calvin L. Keeler
Keyword(s):  
Relative Abundance ◽  
Performance Metrics ◽  
Complete Characterization ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Microbial Composition ◽  
Additional Species ◽  
User Friendly

Abstract BackgroundThe complete characterization of a microbiome is critical in elucidating the complex ecology of the microbial composition within healthy and diseased animals. Many microbiome studies characterize only the bacterial component, for which there are several well-developed sequencing methods, bioinformatics tools and databases available. The lack of comprehensive bioinformatics workflows and databases have limited efforts to characterize the other components existing in a microbiome. BiomeSeq is a tool for the analysis of the complete animal microbiome using metagenomic sequencing data. With its comprehensive workflow and customizable parameters and microbial databases, BiomeSeq can rapidly quantify the viral, fungal, bacteriophage and bacterial components of a sample and produce informative tables for analysis. ResultsSimulated datasets were constructed, which contained known abundances of microbial sequences, and several performance metrics were analyzed, including correlation of predicted abundance with known abundance, root mean square error and rate of speed. BiomeSeq demonstrated high precision (average of 99.52%) and sensitivity (average of 93.01%). BiomeSeq was employed in detecting and quantifying the respiratory microbiome of a commercial poultry broiler flock throughout its grow-out cycle from hatching to processing and successfully processed 780 million reads. For each microbial species detected, BiomeSeq calculated the normalized abundance, percent relative abundance, and coverage as well as the diversity for each sample. Rate of speed for each step in the pipeline, precision and accuracy were calculated to examine BiomeSeq’s performance using in silico sequencing datasets. When compared to bacterial results generated by the commonly used 16S rRNA sequencing method, BiomeSeq detected the same most abundant bacteria, including Gallibacterium, Corynebacterium and Staphylococcus, as well as several additional species. ConclusionsBiomeSeq provides for the detection and quantification of the microbiome from next-generation metagenomic sequencing data. This tool is implemented into a user-friendly container that requires one command and generates a table containing taxonomical information for each microbe detected. It also determines normalized abundance, percent relative abundance, genome coverage and sample diversity calculations for each sample.

scholarly journals A Statistical Framework for Data Purification with Application to Microbiome Data Analysis

2021 ◽  
Author(s):  
Zequn Sun ◽  
Jing Zhao ◽  
Zhaoqian Liu ◽  
Qin Ma ◽  
Dongjun Chung
Keyword(s):  
Statistical Power ◽  
Metagenomic Data ◽  
Microbial Composition ◽  
Microbial Species ◽  
Statistical Framework ◽  
Clinical Interest ◽  
Complex Relationships ◽  
Colorectal Cancer Patients ◽  
Microbiome Data ◽  
Microbiome Data Analysis

AbstractIdentification of disease-associated microbial species is of great biological and clinical interest. However, this investigation still remains challenges due to heterogeneity in microbial composition between individuals, data quality issues, and complex relationships among species. In this paper, we propose a novel data purification algorithm that allows elimination of noise observations, which leads to increased statistical power to detect disease-associated microbial species. We illustrate the proposed algorithm using the metagenomic data generated from colorectal cancer patients.

scholarly journals nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning

2021 ◽  
Author(s):  
Sabrina Krakau ◽  
Daniel Straub ◽  
Hadrien Gourlé ◽  
Gisela Gabernet ◽  
Sven Nahnsen
Keyword(s):  
Microbial Communities ◽  
Best Practice ◽  
Metagenomic Data ◽  
Hybrid Assembly ◽  
Individual Genome ◽  
Long Reads ◽  
Metagenome Assembly ◽  
Group Information ◽  
Genome Level ◽  
Reference Genomes

The analysis of shotgun metagenomic data provides valuable insights into microbial communities, while allowing resolution at individual genome level. In absence of complete reference genomes, this requires the reconstruction of metagenome assembled genomes (MAGs) from sequencing reads. We present the nf-core/mag pipeline for metagenome assembly, binning and taxonomic classification. It can optionally combine short and long reads to increase assembly continuity and utilize sample-wise group-information for co-assembly and genome binning. The pipeline is easy to install - all dependencies are provided within containers -, portable and reproducible. It is written in Nextflow and developed as part of the nf-core initiative for best-practice pipeline development. All code is hosted on GitHub under the nf-core organization https://github.com/nf-core/mag and released under the MIT license.

scholarly journals MetaWRAP - a flexible pipeline for genome-resolved metagenomic data analysis

2018 ◽  
Author(s):  
Gherman V Uritskiy ◽  
Jocelyne DiRuggiero ◽  
James Taylor
Keyword(s):  
Data Analysis ◽  
Shotgun Sequencing ◽  
Metagenomic Analysis ◽  
Metagenomic Data ◽  
Sequencing Data ◽  
High Quality ◽  
Single Genome ◽  
Significant Burden ◽  
Versatile Tool ◽  
Genome Level

AbstractBackground: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 datasets. 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.

No detection of the pathogen Batrachochytrium dendrobatidis in Sardinian cave salamanders, genus Hydromantes

2013 ◽  
Vol 34 (1) ◽  
pp. 136-141 ◽  
Author(s):  
Ylenia Chiari ◽  
Arie van der Meijden ◽  
Mauro Mucedda ◽  
Norman Wagner ◽  
Michael Veith
Keyword(s):  
Life Style ◽  
Batrachochytrium Dendrobatidis ◽  
Amphibian Declines ◽  
Occurrence Rate ◽  
Aquatic Species ◽  
Terrestrial Habitat ◽  
Aquatic Fungus ◽  
Multiple Factors ◽  
Terrestrial Life

Amphibian declines have been documented worldwide. Chytridiomycosis, a disease caused by the aquatic fungus Batrachochytrium dendrobatidis (Bd), is one of the causes associated with these declines. Occurrence, rate of infection and mortality due to chytridiomycosis in amphibians depend on multiple factors including habitat and life-style (aquatic/terrestrial). Bd infection is lower in terrestrial than in aquatic species, but a fully terrestrial life-style alone may not explain the absence of Bd in some species. Low individual dispersal, decreasing the occurrence of contact with infected organisms, could also favour lower Bd infection. To survey the occurrence of Bd infection in fully terrestrial salamanders with low dispersal, we sampled the Sardinian Hydromantes species to measure their level of infection. Bd was not detected and likely absent in Sardinian Hydromantes. This phenomenon could be explained by a combination of terrestrial habitat, low dispersal, and occurrence mostly in habitats where other amphibians do not occur.

scholarly journals Unveiling the Biogeography and Potential Functions of the Intestinal Digesta- and Mucosa-Associated Microbiome of Donkeys

2020 ◽  
Vol 11 ◽  
Author(s):  
Ruiyang Zhang ◽  
Junpeng Zhang ◽  
Wanyi Dang ◽  
David M. Irwin ◽  
Zhe Wang ◽  
...  
Keyword(s):  
Small Intestine ◽  
Large Intestine ◽  
Intestinal Microbiota ◽  
Synergistic Effects ◽  
Potential Functions ◽  
Production Performance ◽  
Limited Information ◽  
Microbial Composition ◽  
Metabolic Functions ◽  
Degrading Bacteria

The intestinal microbial composition and metabolic functions under normal physiological conditions in the donkey are crucial for health and production performance. However, compared with other animal species, limited information is currently available regarding the intestinal microbiota of donkeys. In the present study, we characterized the biogeography and potential functions of the intestinal digesta- and mucosa-associated microbiota of different segments of the intestine (jejunum, ileum, cecum, and colon) in the donkey, focusing on the differences in the microbial communities between the small and large intestine. Our results show that, Firmicutes and Bacteroidetes dominate in both the digesta- and mucosa-associated microbiota in different intestinal locations of the donkey. Starch-degrading and acid-producing (butyrate and lactate) microbiota, such as Lactobacillus and Sarcina, were more enriched in the small intestine, while the fiber- and mucin-degrading bacteria, such as Akkermansia, were more enriched in the large intestine. Furthermore, metabolic functions in membrane transport and lipid metabolism were more enriched in the small intestine, while functions for energy metabolism, metabolism of cofactors and vitamins, amino acid metabolism were more enriched in the large intestine. In addition, the microbial composition and functions in the digesta-associated microbiota among intestinal locations differed greatly, while the mucosal differences were smaller, suggesting a more stable and consistent role in the different intestinal locations. This study provides us with new information on the microbial differences between the small and large intestines of the donkey and the synergistic effects of the intestinal microbiota with host functions, which may improve our understanding the evolution of the equine digestive system and contribute to the healthy and efficient breeding of donkeys.

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