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Molecules (Basel, Switzerland) May 2021Microorganisms are highly regarded as a prominent source of natural products that have significant importance in many fields such as medicine, farming, environmental... (Review)
Review
Microorganisms are highly regarded as a prominent source of natural products that have significant importance in many fields such as medicine, farming, environmental safety, and material production. Due to this, only tiny amounts of microorganisms can be cultivated under standard laboratory conditions, and the bulk of microorganisms in the ecosystems are still unidentified, which restricts our knowledge of uncultured microbial metabolism. However, they could hypothetically provide a large collection of innovative natural products. Culture-independent metagenomics study has the ability to address core questions in the potential of NP production by cloning and analysis of microbial DNA derived directly from environmental samples. Latest advancements in next generation sequencing and genetic engineering tools for genome assembly have broadened the scope of metagenomics to offer perspectives into the life of uncultured microorganisms. In this review, we cover the methods of metagenomic library construction, and heterologous expression for the exploration and development of the environmental metabolome and focus on the function-based metagenomics, sequencing-based metagenomics, and single-cell metagenomics of uncultured microorganisms.
Topics: Bacteria; Biological Products; Ecosystem; High-Throughput Nucleotide Sequencing; Metagenome; Metagenomics
PubMed: 34067778
DOI: 10.3390/molecules26102977 -
Current Opinion in Virology Jun 2022Despite the growing interest in the microbiome in recent years, the study of the virome, the major part of which is made up of bacteriophages, is relatively... (Review)
Review
Despite the growing interest in the microbiome in recent years, the study of the virome, the major part of which is made up of bacteriophages, is relatively underdeveloped compared with their bacterial counterparts. This is due in part to the lack of a universally conserved marker such as the 16S rRNA gene. For this reason, the development of metagenomic approaches was a major milestone in the study of the viruses in the microbiome or virome. However, it has become increasingly clear that these wet-lab methods have not yet been able to detect the full range of viruses present, and our understanding of the composition of the virome remains incomplete. In recent years, a range of new technologies has been developed to further our understanding. Direct RNA-Seq technologies bypass the need for cDNA synthesis, thus avoiding biases subjected to this step, which further expands our understanding of RNA viruses. The new generation of amplification methods could solve the low biomass issue relevant to most virome samples while reducing the error rate and biases caused by whole genome amplification. The application of long-read sequencing to virome samples can resolve the shortcomings of short-read sequencing in generating complete viral genomes and avoid the biases introduced by the assembly. Novel experimental methods developed to measure viruses' host range can help overcome the challenges of assigning hosts to many phages, specifically unculturable ones.
Topics: Bacteriophages; Metagenome; Metagenomics; RNA, Ribosomal, 16S; Virome; Viruses
PubMed: 35643020
DOI: 10.1016/j.coviro.2022.101231 -
STAR Protocols Sep 2023The analysis of metagenomic data obtained via high-throughput DNA sequencing is primarily carried out by a dedicated binning process involving clustering contigs,...
The analysis of metagenomic data obtained via high-throughput DNA sequencing is primarily carried out by a dedicated binning process involving clustering contigs, presumably belonging to the same species. Here, we present a protocol for improving the quality of binning using BinSPreader. We describe steps for typical metagenome assembly and binning workflow. We then detail binning refining, its variants, output, and possible caveats. This protocol optimizes the process of reconstructing more complete genomes of microorganisms that make up the metagenome. For complete details on the use and execution of this protocol, please refer to Tolstoganov et al..
Topics: Metagenome; Sequence Analysis, DNA; Metagenomics; Cluster Analysis; High-Throughput Nucleotide Sequencing
PubMed: 37405923
DOI: 10.1016/j.xpro.2023.102417 -
BMC Bioinformatics May 2020Microorganisms are important occupants of many different environments. Identifying the composition of microbes and estimating their abundance promote understanding of...
BACKGROUND
Microorganisms are important occupants of many different environments. Identifying the composition of microbes and estimating their abundance promote understanding of interactions of microbes in environmental samples. To understand their environments more deeply, the composition of microorganisms in environmental samples has been studied using metagenomes, which are the collections of genomes of the microorganisms. Although many tools have been developed for taxonomy analysis based on different algorithms, variability of analysis outputs of existing tools from the same input metagenome datasets is the main obstacle for many researchers in this field.
RESULTS
Here, we present a novel meta-analysis tool for metagenome taxonomy analysis, called TAMA, by intelligently integrating outputs from three different taxonomy analysis tools. Using an integrated reference database, TAMA performs taxonomy assignment for input metagenome reads based on a meta-score by integrating scores of taxonomy assignment from different taxonomy classification tools. TAMA outperformed existing tools when evaluated using various benchmark datasets. It was also successfully applied to obtain relative species abundance profiles and difference in composition of microorganisms in two types of cheese metagenome and human gut metagenome.
CONCLUSION
TAMA can be easily installed and used for metagenome read classification and the prediction of relative species abundance from multiple numbers and types of metagenome read samples. TAMA can be used to more accurately uncover the composition of microorganisms in metagenome samples collected from various environments, especially when the use of a single taxonomy analysis tool is unreliable. TAMA is an open source tool, and can be downloaded at https://github.com/jkimlab/TAMA.
Topics: Bacteria; Classification; Databases, Genetic; Datasets as Topic; High-Throughput Nucleotide Sequencing; Metagenome; Metagenomics; Models, Genetic; Phylogeny
PubMed: 32397982
DOI: 10.1186/s12859-020-3533-7 -
Microbiological Research Dec 2022Microbial cells attached to inert or living surfaces adopt biofilm mode with self-produced exopolysaccharide matrix containing polysaccharides, proteins, and... (Review)
Review
Microbial cells attached to inert or living surfaces adopt biofilm mode with self-produced exopolysaccharide matrix containing polysaccharides, proteins, and extracellular DNA, for protection from adverse external stimuli. Biofilms in hospitals and industries serve as a breeding ground for drug-resistant pathogens and ARG enrichment that are linked to pathogenicity and also impede industrial production process. Biofilm formation, including virulence and pathogenicity, is regulated through quorum sensing (QS), a means of bacterial cell to cell communication for cooperative physiological processes. Hence, QS inhibition through quorum quenching (QQ) is a feasible approach to inhibit biofilm formation. In contrast, biofilms have beneficial roles in promoting plant growth, biocontrol, and wastewater treatment. Furthermore, polymicrobial biofilms can harbour novel compounds and species of industrial and pharmaceutical interest. Hence, surveillance of biofilm microbiome structure and functional attributes is crucial to determine the extent of the risk it poses and to harness its bioactive potential. One of the most preferred approaches to delineate the microbiome is culture-independent metagenomics. In this context, this review article explores the biofilm microbiome in built and natural settings such as agriculture, household appliances, wastewater treatment plants, hospitals, microplastics, and dental biofilm. We have also discussed the recent reports on discoveries of novel QS and biofilm inhibitors through conventional, metagenomics, and machine learning approaches. Finally, we present biofilm-derived novel metagenome-assembled genomes (MAGs), genomes, and taxa of medical and industrial interest.
Topics: Biofilms; Metagenome; Metagenomics; Microplastics; Pharmaceutical Preparations; Plastics; Quorum Sensing
PubMed: 36194989
DOI: 10.1016/j.micres.2022.127207 -
Bioinformatics (Oxford, England) Jan 2023The Metagenomic Intra-Species Diversity Analysis System (MIDAS) is a scalable metagenomic pipeline that identifies single nucleotide variants (SNVs) and gene copy number...
SUMMARY
The Metagenomic Intra-Species Diversity Analysis System (MIDAS) is a scalable metagenomic pipeline that identifies single nucleotide variants (SNVs) and gene copy number variants in microbial populations. Here, we present MIDAS2, which addresses the computational challenges presented by increasingly large reference genome databases, while adding functionality for building custom databases and leveraging paired-end reads to improve SNV accuracy. This fast and scalable reengineering of the MIDAS pipeline enables thousands of metagenomic samples to be efficiently genotyped.
AVAILABILITY AND IMPLEMENTATION
The source code is available at https://github.com/czbiohub/MIDAS2.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
Topics: Metagenome; Software; Metagenomics; Genotype; Databases, Factual
PubMed: 36321886
DOI: 10.1093/bioinformatics/btac713 -
GigaScience Jan 2020The number of microbial genome sequences is increasing exponentially, especially thanks to recent advances in recovering complete or near-complete genomes from...
BACKGROUND
The number of microbial genome sequences is increasing exponentially, especially thanks to recent advances in recovering complete or near-complete genomes from metagenomes and single cells. Assigning reliable taxon labels to genomes is key and often a prerequisite for downstream analyses.
FINDINGS
We introduce CAMITAX, a scalable and reproducible workflow for the taxonomic labelling of microbial genomes recovered from isolates, single cells, and metagenomes. CAMITAX combines genome distance-, 16S ribosomal RNA gene-, and gene homology-based taxonomic assignments with phylogenetic placement. It uses Nextflow to orchestrate reference databases and software containers and thus combines ease of installation and use with computational reproducibility. We evaluated the method on several hundred metagenome-assembled genomes with high-quality taxonomic annotations from the TARA Oceans project, and we show that the ensemble classification method in CAMITAX improved on all individual methods across tested ranks.
CONCLUSIONS
While we initially developed CAMITAX to aid the Critical Assessment of Metagenome Interpretation (CAMI) initiative, it evolved into a comprehensive software package to reliably assign taxon labels to microbial genomes. CAMITAX is available under Apache License 2.0 at https://github.com/CAMI-challenge/CAMITAX.
Topics: Algorithms; Computational Biology; DNA Barcoding, Taxonomic; Databases, Genetic; Genome, Microbial; Metagenome; Metagenomics; Phylogeny; RNA, Ribosomal, 16S
PubMed: 31909794
DOI: 10.1093/gigascience/giz154 -
Viruses Jun 2023Blood transfusion safety is an essential element of public health. Current blood screening strategies rely on targeted techniques that could miss unknown or unexpected...
Blood transfusion safety is an essential element of public health. Current blood screening strategies rely on targeted techniques that could miss unknown or unexpected pathogens. Recent studies have demonstrated the presence of a viral community (virobiota/virome) in the blood of healthy individuals. Here, we characterized the blood virome in patients frequently exposed to blood transfusion by using Illumina metagenomic sequencing. The virome of these patients was compared to viruses present in healthy blood donors. A total number of 155 beta-thalassemia, 149 hemodialysis, and 100 healthy blood donors were pooled with five samples per pool. Members of the and family were most frequently observed. Interestingly, samples of healthy blood donors harbored traces of potentially pathogenic viruses, including adeno-, rota-, and Merkel cell polyomavirus. Viruses of the family were most abundant in the blood of hemodialysis patients and displayed a higher anellovirus richness. Pegiviruses () were only observed in patient populations. An overall trend of higher eukaryotic read abundance in both patient groups was observed. This might be associated with increased exposure through blood transfusion. Overall, the findings in this study demonstrated the presence of various viruses in the blood of Iranian multiple-transfused patients and healthy blood donors.
Topics: Humans; Iran; Virome; Viruses; Anelloviridae; Metagenome; Metagenomics
PubMed: 37515113
DOI: 10.3390/v15071425 -
NPJ Biofilms and Microbiomes Aug 2022Dogs have a key role in law enforcement and military work, and research with the goal of improving working dog performance is ongoing. While there have been intriguing...
Dogs have a key role in law enforcement and military work, and research with the goal of improving working dog performance is ongoing. While there have been intriguing studies from lab animal models showing a potential connection between the gut microbiome and behavior or mental health there is a dearth of studies investigating the microbiome-behavior relationship in working dogs. The overall objective of this study was to characterize the microbiota of working dogs and to determine if the composition of the microbiota is associated with behavioral and performance outcomes. Freshly passed stools from each working canine (Total n = 134) were collected and subject to shotgun metagenomic sequencing using Illumina technology. Behavior, performance, and demographic metadata were collected. Descriptive statistics and prediction models of behavioral/phenotypic outcomes using gradient boosting classification based on Xgboost were used to study associations between the microbiome and outcomes. Regarding machine learning methodology, only microbiome features were used for training and predictors were estimated in cross-validation. Microbiome markers were statistically associated with motivation, aggression, cowardice/hesitation, sociability, obedience to one trainer vs many, and body condition score (BCS). When prediction models were developed based on machine learning, moderate predictive power was observed for motivation, sociability, and gastrointestinal issues. Findings from this study suggest potential gut microbiome markers of performance and could potentially advance care for working canines.
Topics: Animals; Dogs; Gastrointestinal Microbiome; Metagenome; Metagenomics; Microbiota; Working Dogs
PubMed: 35995802
DOI: 10.1038/s41522-022-00329-5 -
MSystems Aug 2022Metagenome-assembled genomes (MAGs) represent individual genomes recovered from metagenomic data. MAGs are extremely useful to analyze uncultured microbial genomic...
Metagenome-assembled genomes (MAGs) represent individual genomes recovered from metagenomic data. MAGs are extremely useful to analyze uncultured microbial genomic diversity, as well as to characterize associated functional and metabolic potential in natural environments. Recent computational developments have considerably improved MAG reconstruction but also emphasized several limitations, such as the nonbinning of sequence regions with repetitions or distinct nucleotidic composition. Different assembly and binning strategies are often used; however, it still remains unclear which assembly strategy, in combination with which binning approach, offers the best performance for MAG recovery. Several workflows have been proposed in order to reconstruct MAGs, but users are usually limited to single-metagenome assembly or need to manually define sets of metagenomes to coassemble prior to genome binning. Here, we present MAGNETO, an automated workflow dedicated to MAG reconstruction, which includes a fully-automated coassembly step informed by optimal clustering of metagenomic distances, and implements complementary genome binning strategies, for improving MAG recovery. MAGNETO is implemented as a Snakemake workflow and is available at: https://gitlab.univ-nantes.fr/bird_pipeline_registry/magneto. Genome-resolved metagenomics has led to the discovery of previously untapped biodiversity within the microbial world. As the development of computational methods for the recovery of genomes from metagenomes continues, existing strategies need to be evaluated and compared to eventually lead to standardized computational workflows. In this study, we compared commonly used assembly and binning strategies and assessed their performance using both simulated and real metagenomic data sets. We propose a novel approach to automate coassembly, avoiding the requirement for knowledge to combine metagenomic information. The comparison against a previous coassembly approach demonstrates a strong impact of this step on genome binning results, but also the benefits of informing coassembly for improving the quality of recovered genomes. MAGNETO integrates complementary assembly-binning strategies to optimize genome reconstruction and provides a complete reads-to-genomes workflow for the growing microbiome research community.
Topics: Workflow; Metagenomics; Metagenome; Microbiota; Genome, Microbial
PubMed: 35703559
DOI: 10.1128/msystems.00432-22