scholarly journals Novel Approach for Microbiome Analysis Using Bacterial Replication Rates and Causal Inference with Applications

2020 ◽  
Author(s):  
Vitalii Stebliankin ◽  
Musfiqur Rahman Sazal ◽  
Camilo Valdes ◽  
Kalai Mathee ◽  
Giri Narasimhan
Keyword(s):  
Gut Microbiome ◽  
Sequence Data ◽  
Causality Analysis ◽  
Metagenomic Sequence ◽  
Novel Approach ◽  
Infant Gut Microbiome ◽  
Abundance Profile ◽  
Bacterial Replication ◽  
Antibiotic Response ◽  
Metagenomic Sequence Data

Motivation: Metagenomics sequencing data can be used to compute not just the relative abundance profile, but also the replication rates of every taxon in the microbiome sample. We investigate how the dynamics implied by the replication rates can be used to understand the antibiotic response in microbiomes, given the significant variation in the types of antibiotics and the types of response by different taxa. The analysis is further expanded by factoring in the resistome of the microbiomes, which can be readily profiled from the metagenomic sequence data. The fact that some antibiotics such as β -lactams target replicating cells makes it even more critical to use replication rates to analyze the antibiotic response. Results: We introduce a novel approach for metagenomic analysis that integrates microbial community profiling, replication rate calculation, and causal structural learning to analyze the antibiotic response. First, we developed PeTRi, which involves efficient cluster computation of bacterial replication rates from metagenomic sequence data. Second, we integrate the abundance profile, replication profile, resistome profile, and environmental variables to perform causality analysis. Finally, we applied the integrated analysis to the data from an infant gut microbiome study. Conclusions from our analysis are as follows: (i) Microbes tend to lower their replication rates in response to β -lactams; (ii) The presence of antibiotic resistance genes combined with the causality analysis strongly suggest that genes fosA5, oqxA, kpnF, arnA, and acrA provides resistance for the taxon K. pneumoniae, allowing it to replicate and dominate the microbiome after the drug ticarcillin-clavulanate was administered; and (iii) Human and donor milk strongly influence the resistome of the infant gut microbiome.

scholarly journals Metagenomics: a path to understanding the gut microbiome

2021 ◽  
Author(s):  
Sandi Yen ◽  
Jethro S. Johnson
Keyword(s):  
Gut Microbiome ◽  
Sequence Data ◽  
Metagenomic Sequence ◽  
Sequencing Technologies ◽  
Host Health ◽  
Technological Developments ◽  
Viral Components ◽  
Metagenomic Sequence Data ◽  
Insight Into ◽  
Generation Sequencing

AbstractThe gut microbiome is a major determinant of host health, yet it is only in the last 2 decades that the advent of next-generation sequencing has enabled it to be studied at a genomic level. Shotgun sequencing is beginning to provide insight into the prokaryotic as well as eukaryotic and viral components of the gut community, revealing not just their taxonomy, but also the functions encoded by their collective metagenome. This revolution in understanding is being driven by continued development of sequencing technologies and in consequence necessitates reciprocal development of computational approaches that can adapt to the evolving nature of sequence datasets. In this review, we provide an overview of current bioinformatic strategies for handling metagenomic sequence data and discuss their strengths and limitations. We then go on to discuss key technological developments that have the potential to once again revolutionise the way we are able to view and hence understand the microbiome.

scholarly journals Occurrence and Expression of Gene Transfer Agent Genes in Marine Bacterioplankton

2008 ◽  
Vol 74 (10) ◽  
pp. 2933-2939 ◽  
Author(s):  
Erin J. Biers ◽  
Kui Wang ◽  
Catherine Pennington ◽  
Robert Belas ◽  
Feng Chen ◽  
...  
Keyword(s):  
Gene Transfer ◽  
Sequence Data ◽  
Genome Sequences ◽  
Metagenomic Sequence ◽  
Marine Bacterioplankton ◽  
Extracellular Release ◽  
Gene Transfer Agent ◽  
Metagenomic Sequence Data ◽  
Search For Homologs

ABSTRACT Genes with homology to the transduction-like gene transfer agent (GTA) were observed in genome sequences of three cultured members of the marine Roseobacter clade. A broader search for homologs for this host-controlled virus-like gene transfer system identified likely GTA systems in cultured Alphaproteobacteria, and particularly in marine bacterioplankton representatives. Expression of GTA genes and extracellular release of GTA particles (∼50 to 70 nm) was demonstrated experimentally for the Roseobacter clade member Silicibacter pomeroyi DSS-3, and intraspecific gene transfer was documented. GTA homologs are surprisingly infrequent in marine metagenomic sequence data, however, and the role of this lateral gene transfer mechanism in ocean bacterioplankton communities remains unclear.

scholarly journals The composition and functional protein subsystems of the human nasal microbiome in granulomatosis with polyangiitis: a pilot study

Microbiome ◽  
2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Josef Wagner ◽  
Ewan M. Harrison ◽  
Marcos Martinez Del Pero ◽  
Beth Blane ◽  
Gert Mayer ◽  
...  
Keyword(s):  
Granulomatosis With Polyangiitis ◽  
Sequence Data ◽  
Bacterial Species ◽  
Vitamin B ◽  
Diversity Analysis ◽  
Healthy Controls ◽  
Functional Protein ◽  
Metagenomic Sequence ◽  
Metagenomic Sequence Data ◽  
Nasal Microbiota

Abstract Background Ear, nose and throat involvement in granulomatosis with polyangiitis (GPA) is frequently the initial disease manifestation. Previous investigations have observed a higher prevalence of Staphylococcus aureus in patients with GPA, and chronic nasal carriage has been linked with an increased risk of disease relapse. In this cross-sectional study, we investigated changes in the nasal microbiota including a detailed analysis of Staphylococcus spp. by shotgun metagenomics in patients with active and inactive granulomatosis with polyangiitis (GPA). Shotgun metagenomic sequence data were also used to identify protein-encoding genes within the SEED database, and the abundance of proteins then correlated with the presence of bacterial species on an annotated heatmap. Results The presence of S. aureus in the nose as assessed by culture was more frequently detected in patients with active GPA (66.7%) compared with inactive GPA (34.1%). Beta diversity analysis of nasal microbiota by bacterial 16S rRNA profiling revealed a different composition between GPA patients and healthy controls (P = 0.039). Beta diversity analysis of shotgun metagenomic sequence data for Staphylococcus spp. revealed a different composition between active GPA patients and healthy controls and disease controls (P = 0.0007 and P = 0.0023, respectively), and between healthy controls and inactive GPA patients and household controls (P = 0.0168 and P = 0.0168, respectively). Patients with active GPA had a higher abundance of S. aureus, mirroring the culture data, while healthy controls had a higher abundance of S. epidermidis. Staphylococcus pseudintermedius, generally assumed to be a pathogen of cats and dogs, showed an abundance of 13% among the Staphylococcus spp. in our cohort. During long-term follow-up of patients with inactive GPA at baseline, a higher S. aureus abundance was not associated with an increased relapse risk. Functional analyses identified ten SEED protein subsystems that differed between the groups. Most significant associations were related to chorismate synthesis and involved in the vitamin B12 pathway. Conclusion Our data revealed a distinct dysbiosis of the nasal microbiota in GPA patients compared with disease and healthy controls. Metagenomic sequencing demonstrated that this dysbiosis in active GPA patients is manifested by increased abundance of S. aureus and a depletion of S. epidermidis, further demonstrating the antagonist relationships between these species. SEED functional protein subsystem analysis identified an association between the unique bacterial nasal microbiota clusters seen mainly in GPA patients and an elevated abundance of genes associated with chorismate synthesis and vitamin B12 pathways. Further studies are required to further elucidate the relationship between the biosynthesis genes and the associated bacterial species.

scholarly journals A Need for Improved Cellulase Identification from Metagenomic Sequence Data

2020 ◽  
Vol 87 (1) ◽  
Author(s):  
Rebecca Co ◽  
Laura A. Hug
Keyword(s):  
Sequence Data ◽  
Industrial Applications ◽  
Data Sets ◽  
Metagenomic Sequence ◽  
Environmental Sequence ◽  
Sequencing Technologies ◽  
Current Classification ◽  
Applied Microbiology ◽  
Environmental Surveys ◽  
Metagenomic Sequence Data

ABSTRACT Improved sequencing technologies and the maturation of metagenomic approaches allow the identification of gene variants with potential industrial applications, including cellulases. Cellulase identification from metagenomic environmental surveys is complicated by inconsistent nomenclature and multiple categorization systems. Here, we summarize the current classification and nomenclature systems, with recommendations for improvements to these systems. Addressing the issues described will strengthen the annotation of cellulose-active enzymes from environmental sequence data sets—a rapidly growing resource in environmental and applied microbiology.

scholarly journals Correction: TreeSeq, a Fast and Intuitive Tool for Analysis of Whole Genome and Metagenomic Sequence Data

PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0131379
Author(s):  
Bastiaan B. Wintermans ◽  
Bernd W. Brandt ◽  
Christina M. J. E. Vandenbroucke-Grauls ◽  
Andries E. Budding
Keyword(s):  
Sequence Data ◽  
Whole Genome ◽  
Metagenomic Sequence ◽  
Metagenomic Sequence Data

scholarly journals Assembling metagenomes, one community at a time

2017 ◽  
Author(s):  
Andries J. van der Walt ◽  
Marc W. Van Goethem ◽  
Jean-Baptiste Ramond ◽  
Thulani P. Makhalanyane ◽  
Oleg Reva ◽  
...  
Keyword(s):  
Sequence Data ◽  
Gene Prediction ◽  
Metagenomic Sequence ◽  
Scientific Question ◽  
Critical Step ◽  
Metagenomic Sequence Data ◽  
Complex Dataset ◽  
Assembly Tool ◽  
Selection Of ◽  
Available Resources

AbstractBackgroundMetagenomics allows unprecedented access to uncultured environmental microorganisms. The analysis of metagenomic sequences facilitates gene prediction and annotation, and enables the assembly of draft genomes, including uncultured members of a community. However, while several platforms have been developed for this critical step, there is currently no clear framework for the assembly of metagenomic sequence data.ResultsTo assist with selection of an appropriate metagenome assembler we evaluated the capabilities of nine prominent assembly tools on nine publicly-available environmental metagenomes, as well as three simulated datasets. Overall, we found that SPAdes provided the largest contigs and highest N50 values across 6 of the 9 environmental datasets, followed by MEGAHIT and metaSPAdes. MEGAHIT emerged as a computationally inexpensive alternative to SPAdes, assembling the most complex dataset using less than 500 GB of RAM and within 10 hours.ConclusionsWe found that assembler choice ultimately depends on the scientific question, the available resources and the bioinformatic competence of the researcher. We provide a concise workflow for the selection of the best assembly tool.

scholarly journals Improved metagenomic analysis with Kraken 2

2019 ◽  
Author(s):  
Derrick E. Wood ◽  
Jennifer Lu ◽  
Ben Langmead
Keyword(s):  
Sequence Data ◽  
High Accuracy ◽  
Viral Metagenomics ◽  
Search Mode ◽  
Metagenomic Sequence ◽  
Large Memory ◽  
Increased Sensitivity ◽  
Metagenomic Sequence Data ◽  
Metagenomics Analysis

Although Kraken’s k-mer-based approach provides fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed five-fold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.

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