scholarly journals Improvement of eukaryotic proteins prediction from soil metagenomes

2021 ◽  
Author(s):  
Carole Belliardo ◽  
Georgios Koutsovoulos ◽  
Corinne Rancurel ◽  
Mathilde Clement ◽  
Justine Lipuma ◽  
...  
Keyword(s):  
Automated Analysis ◽  
Metagenomic Data ◽  
Analysis Pipeline ◽  
Shotgun Metagenomics ◽  
Assignment Method ◽  
Eukaryotic Proteins ◽  
Public Repositories ◽  
Soil Proteins ◽  
Taxonomic Annotation

Background | During the last decades, shotgun metagenomics and metabarcoding have highlighted the diversity of microorganisms from environmental or host-associated samples. Most assembled metagenome public repositories use annotation pipelines tailored for prokaryotes regardless of the taxonomic origin of contigs and metagenome-assembled genomes (MAGs). Consequently, eukaryotic contigs and MAGs, with intrinsically different gene features, are not optimally annotated, resulting in an incorrect representation of the eukaryotic component of biodiversity, despite their biological relevance. Results | Using an automated analysis pipeline, we have filtered eukaryotic contigs from 6,873 soil metagenomes from the IMG/M database of the Joint Genome Institute. We have re-annotated genes using eukaryote-tailored methods, yielding 5,6 million eukaryotic proteins. Our pipeline improves eukaryotic proteins completeness, contiguity and quality. Moreover, the better quality of eukaryotic proteins combined with a more comprehensive assignment method improves the taxonomic annotation as well. Conclusions | Using public soil metagenomic data, we provide a dataset of eukaryotic soil proteins with improved completeness and quality as well as a more reliable taxonomic annotation. This unique resource is of interest for any scientist aiming at studying the composition, biological functions and gene flux in soil communities involving eukaryotes.

scholarly journals Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazutoshi Yoshitake ◽  
Gaku Kimura ◽  
Tomoko Sakami ◽  
Tsuyoshi Watanabe ◽  
Yukiko Taniuchi ◽  
...  
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Pacific Coast ◽  
Three Dimensional ◽  
Amplicon Sequencing ◽  
Metagenomic Data ◽  
Shotgun Metagenomics ◽  
Functional Features ◽  
Pacific Coast Of Japan ◽  
Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

scholarly journals High-throughput super-resolution analysis of influenza virus pleomorphism reveals insights into viral spatial organization

2021 ◽  
Author(s):  
Andrew McMahon ◽  
Rebecca Andrews ◽  
Sohail V Ghani ◽  
Thorben Cordes ◽  
Achillefs N Kapanidis ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Organization ◽  
Structural Information ◽  
Virus Assembly ◽  
Super Resolution ◽  
Automated Analysis ◽  
Size Analysis ◽  
Analysis Pipeline ◽  
Single Experiment ◽  
Viral Immunology

Many viruses form highly pleomorphic particles; in influenza, these particles range from spheres of ~ 100 nm in diameter to filaments of several microns in length. Virion structure is of interest, not only in the context of virus assembly, but also because pleomorphic variations may correlate with infectivity and pathogenicity. Detailed images of virus morphology often rely on electron microscopy, which is generally low throughput and limited in molecular identification. We have used fluorescence super-resolution microscopy combined with a rapid automated analysis pipeline to image many thousands of individual influenza virions, gaining information on their size, morphology and the distribution of membrane-embedded and internal proteins. This large-scale analysis revealed that influenza particles can be reliably characterised by length, that no spatial frequency patterning of the surface glycoproteins occurs, and that RNPs are preferentially located towards filament ends within Archetti bodies. Our analysis pipeline is versatile and can be adapted for use on multiple other pathogens, as demonstrated by its application for the size analysis of SARS-CoV-2. The ability to gain nanoscale structural information from many thousands of viruses in just a single experiment is valuable for the study of virus assembly mechanisms, host cell interactions and viral immunology, and should be able to contribute to the development of viral vaccines, anti-viral strategies and diagnostics.

scholarly journals The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

2019 ◽  
Author(s):  
H. Soon Gweon ◽  
Liam P. Shaw ◽  
Jeremy Swann ◽  
Nicola De Maio ◽  
Manal AbuOun ◽  
...  
Keyword(s):  
Data Processing ◽  
Open Source ◽  
Open Source Software ◽  
River Sediment ◽  
Taxonomic Composition ◽  
Sequencing Depth ◽  
Gene Content ◽  
Metagenomic Data ◽  
Software Pipeline ◽  
Shotgun Metagenomics

ABSTRACTBackgroundShotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (∼200 million reads per sample). Alongside this, we cultured single-colony isolates ofEnterobacteriaceaefrom the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, ‘ResPipe’.ResultsTaxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve <1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike ofThermus thermophilusDNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment.ConclusionsSequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available (https://gitlab.com/hsgweon/ResPipe).

scholarly journals Assessing species coverage and assembly quality of rapidly accumulating sequenced genomes

2021 ◽  
Author(s):  
Romain Feron ◽  
Robert Michael Waterhouse
Keyword(s):  
Large Scale ◽  
Automated Analysis ◽  
Single Copy ◽  
The United States ◽  
Community Resource ◽  
Assembly Quality ◽  
Sequencing Technologies ◽  
Analysis Workflow ◽  
Genome Assemblies

Ambitious initiatives to coordinate genome sequencing of Earth's biodiversity mean that the accumulation of genomic data is growing rapidly. In addition to cataloguing biodiversity, these data provide the basis for understanding biological function and evolution. Accurate and complete genome assemblies offer a comprehensive and reliable foundation upon which to advance our understanding of organismal biology at genetic, species, and ecosystem levels. However, ever-changing sequencing technologies and analysis methods mean that available data are often heterogeneous in quality. In order to guide forthcoming genome generation efforts and promote efficient prioritisation of resources, it is thus essential to define and monitor taxonomic coverage and quality of the data. Here we present an automated analysis workflow that surveys genome assemblies from the United States National Center for Biotechnology Information (NCBI), assesses their completeness using the relevant Benchmarking Universal Single-Copy Orthologue (BUSCO) datasets, and collates the results into an interactively browsable resource. We apply our workflow to produce a community resource of available assemblies from the phylum Arthropoda, the Arthropoda Assembly Assessment Catalogue. Using this resource, we survey current taxonomic coverage and assembly quality at the NCBI, we examine how key assembly metrics relate to gene content completeness, and we compare results from using different BUSCO lineage datasets. These results demonstrate how the workflow can be used to build a community resource that enables large-scale assessments to survey species coverage and data quality of available genome assemblies, and to guide prioritisations for ongoing and future sampling, sequencing, and genome generation initiatives.

scholarly journals Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data

2019 ◽  
Vol 3 ◽  
Author(s):  
Shruthi Magesh ◽  
Viktor Jonsson ◽  
Johan Bengtsson-Palme
Keyword(s):  
Microbial Communities ◽  
Point Mutations ◽  
Software Tool ◽  
Metagenomic Data ◽  
Data Sets ◽  
Resistance Mutations ◽  
Shotgun Metagenomics ◽  
Key Factor ◽  
Detection Of Mutations ◽  
And Function

Metagenomics has emerged as a central technique for studying the structure and function of microbial communities. Often the functional analysis is restricted to classification into broad functional categories. However, important phenotypic differences, such as resistance to antibiotics, are often the result of just one or a few point mutations in otherwise identical sequences. Bioinformatic methods for metagenomic analysis have generally been poor at accounting for this fact, resulting in a somewhat limited picture of important aspects of microbial communities. Here, we address this problem by providing a software tool called Mumame, which can distinguish between wildtype and mutated sequences in shotgun metagenomic data and quantify their relative abundances. We demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets. We also identified that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than for most other applications of shotgun metagenomics. Mumame is freely available online (http://microbiology.se/software/mumame).

scholarly journals HumanMetagenomeDB: a public repository of curated and standardized metadata for human metagenomes

2020 ◽  
Vol 49 (D1) ◽  
pp. D743-D750
Author(s):  
Jonas Coelho Kasmanas ◽  
Alexander Bartholomäus ◽  
Felipe Borim Corrêa ◽  
Tamara Tal ◽  
Nico Jehmlich ◽  
...  
Keyword(s):  
Average Length ◽  
Sampling Site ◽  
Human Microbiome ◽  
Metagenomic Data ◽  
Limiting Factor ◽  
Body Parts ◽  
Sequencing Platform ◽  
Public Repositories ◽  
Sequence Quality ◽  
Standard Strategy

Abstract Metagenomics became a standard strategy to comprehend the functional potential of microbial communities, including the human microbiome. Currently, the number of metagenomes in public repositories is increasing exponentially. The Sequence Read Archive (SRA) and the MG-RAST are the two main repositories for metagenomic data. These databases allow scientists to reanalyze samples and explore new hypotheses. However, mining samples from them can be a limiting factor, since the metadata available in these repositories is often misannotated, misleading, and decentralized, creating an overly complex environment for sample reanalysis. The main goal of the HumanMetagenomeDB is to simplify the identification and use of public human metagenomes of interest. HumanMetagenomeDB version 1.0 contains metadata of 69 822 metagenomes. We standardized 203 attributes, based on standardized ontologies, describing host characteristics (e.g. sex, age and body mass index), diagnosis information (e.g. cancer, Crohn's disease and Parkinson), location (e.g. country, longitude and latitude), sampling site (e.g. gut, lung and skin) and sequencing attributes (e.g. sequencing platform, average length and sequence quality). Further, HumanMetagenomeDB version 1.0 metagenomes encompass 58 countries, 9 main sample sites (i.e. body parts), 58 diagnoses and multiple ages, ranging from just born to 91 years old. The HumanMetagenomeDB is publicly available at https://webapp.ufz.de/hmgdb/.

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