CAMITAX: Taxon labels for microbial genomes

Abstract 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.

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CAMITAX: Taxon labels for microbial genomes

10.1101/532473 ◽

2019 ◽

Author(s):

Andreas Bremges ◽

Adrian Fritz ◽

Alice C. McHardy

Keyword(s):

Single Cells ◽

Ensemble Classification ◽

Rrna Gene ◽

Genome Sequences ◽

Microbial Genomes ◽

Phylogenetic Placement ◽

Gene Homology ◽

Reference Databases ◽

Taxonomic Assignments ◽

Genome Distance

The number of microbial genome sequences is growing exponentially, also 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. We introduce CAMITAX, a scalable and reproducible workflow for the taxonomic labelling of microbial genomes recovered from isolates, single cells, and metagenomes. CAMI-TAX combines genome distance-, 16S rRNA 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 re-producibility. We evaluated the method on several hundred metagenome-assembled genomes with high-quality taxonomic annotations from the TARA Oceans project, and show that the ensemble classification method in CAMITAX improved on all individual methods across tested ranks. While we initially developed CAMITAX to aid the Critical Assessment of Metagenome Interpretation (CAMI) initiative, it evolved into a comprehensive software to reliably assign taxon labels to microbial genomes. CAMITAX is available under the Apache License 2.0 at: https://github.com/CAMI-challenge/CAMITAX

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Questionable 16S ribosomal RNA gene annotations are frequent in completed microbial genomes

Gene ◽

10.1016/j.gene.2008.02.023 ◽

2008 ◽

Vol 416 (1-2) ◽

pp. 44-47 ◽

Cited By ~ 8

Author(s):

Yu-Hsiang Lin ◽

Bill C.H. Chang ◽

Pei-Wen Chiang ◽

Sen-Lin Tang

Keyword(s):

Ribosomal Rna ◽

16S Ribosomal Rna ◽

Microbial Genomes ◽

Ribosomal Rna Gene ◽

Gene Annotations ◽

16S Ribosomal Rna Gene

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Molecular Approaches to Studying Microbial Communities: Targeting the 16S Ribosomal RNA Gene

Journal of UOEH ◽

10.7888/juoeh.38.223 ◽

2016 ◽

Vol 38 (3) ◽

pp. 223-232 ◽

Cited By ~ 14

Author(s):

Kazumasa FUKUDA ◽

Midori OGAWA ◽

Hatsumi TANIGUCHI ◽

Mitsumasa SAITO

Keyword(s):

Microbial Communities ◽

Ribosomal Rna ◽

16S Ribosomal Rna ◽

Approaches To Studying ◽

Ribosomal Rna Gene ◽

Molecular Approaches ◽

16S Ribosomal Rna Gene

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Evaluation of 16S, map1 and pCS20 probes for detection of Cowdria and Ehrlichia species

Epidemiology and Infection ◽

10.1017/s0950268899002101 ◽

1999 ◽

Vol 122 (2) ◽

pp. 323-328 ◽

Cited By ~ 18

Author(s):

M. T. E. P. ALLSOPP ◽

C. M. HATTINGH ◽

S. W. VOGEL ◽

B. A. ALLSOPP

Keyword(s):

16S Rrna ◽

Ribosomal Rna ◽

Pcr Amplification ◽

16S Ribosomal Rna ◽

16S Rrna Genes ◽

Rrna Genes ◽

Amblyomma Hebraeum ◽

Ribosomal Rna Gene ◽

Group Iii ◽

16S Ribosomal Rna Gene

A panel of 16S ribosomal RNA gene probes has been developed for the study of the epidemiology of heartwater; five of these detect different cowdria genotypes, one detects five distinct genotypes; one detects any Group III Ehrlichia species other than Cowdria and one detects any Group II Ehrlichia species. These probes have been used on PCR-amplified rickettsial 16S rRNA genes from over 200 Amblyomma hebraeum ticks. Control ticks were laboratory-reared and either uninfected or fed on sheep experimentally infected with different cowdria isolates, field ticks were collected from animals in heartwater-endemic areas. All tick-derived DNA samples were also examined by PCR amplification and probing for two other cowdria genes (map1 and pCS20) which have previously been used for heartwater epidemiology. This paper describes the first direct comparison of all currently available DNA probes for heartwater-associated organisms.

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A Case of Sepsis in a 92-Year-Old Korean Woman Caused byAerococcus urinaeand Identified by Sequencing the 16S Ribosomal RNA Gene

Laboratory Medicine ◽

10.1093/labmed/lmv030 ◽

2016 ◽

Vol 47 (2) ◽

pp. e15-e17 ◽

Cited By ~ 2

Author(s):

Min Young Lee ◽

Myeong Hee Kim ◽

Woo In Lee ◽

So Young Kang ◽

You La Jeon

Keyword(s):

Ribosomal Rna ◽

16S Ribosomal Rna ◽

Korean Woman ◽

Ribosomal Rna Gene ◽

16S Ribosomal Rna Gene

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Bacterial diversity in aortic aneurysms determined by 16S ribosomal RNA gene analysis

Journal of Vascular Surgery ◽

10.1016/j.jvs.2006.07.021 ◽

2006 ◽

Vol 44 (5) ◽

pp. 1055-1060 ◽

Cited By ~ 70

Author(s):

Rafael Marques da Silva ◽

Dominique A. Caugant ◽

Emenike R.K. Eribe ◽

Jørn A. Aas ◽

Per S. Lingaas ◽

...

Keyword(s):

Bacterial Diversity ◽

Ribosomal Rna ◽

Aortic Aneurysms ◽

16S Ribosomal Rna ◽

Gene Analysis ◽

Ribosomal Rna Gene ◽

16S Ribosomal Rna Gene

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Accurate Reconstruction of Microbial Strains from Metagenomic Sequencing Using Representative Reference Genomes

10.1101/215707 ◽

2017 ◽

Cited By ~ 2

Author(s):

Zhemin Zhou ◽

Nina Luhmann ◽

Nabil-Fareed Alikhan ◽

Christopher Quince ◽

Mark Achtman

Keyword(s):

Evaluation Studies ◽

Species Level ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Reference Databases ◽

Microbial Strains ◽

Taxonomic Assignments ◽

Taxonomic Groups ◽

Reference Genomes ◽

Recent Evaluation

AbstractExploring the genetic diversity of microbes within the environment through metagenomic sequencing first requires classifying these reads into taxonomic groups. Current methods compare these sequencing data with existing biased and limited reference databases. Several recent evaluation studies demonstrate that current methods either lack sufficient sensitivity for species-level assignments or suffer from false positives, overestimating the number of species in the metagenome. Both are especially problematic for the identification of low-abundance microbial species, e. g. detecting pathogens in ancient metagenomic samples. We present a new method, SPARSE, which improves taxonomic assignments of metagenomic reads. SPARSE balances existing biased reference databases by grouping reference genomes into similarity-based hierarchical clusters, implemented as an efficient incremental data structure. SPARSE assigns reads to these clusters using a probabilistic model, which specifically penalizes non-specific mappings of reads from unknown sources and hence reduces false-positive assignments. Our evaluation on simulated datasets from two recent evaluation studies demonstrated the improved precision of SPARSE in comparison to other methods for species-level classification. In a third simulation, our method successfully differentiated multiple co-existing Escherichia coli strains from the same sample. In real archaeological datasets, SPARSE identified ancient pathogens with ≤ 0.02% abundance, consistent with published findings that required additional sequencing data. In these datasets, other methods either missed targeted pathogens or reported non-existent ones. SPARSE and all evaluation scripts are available at https://github.com/zheminzhou/SPARSE.

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High-throughput isolation and sorting of gut microbes reduce biases of traditional cultivation strategies

10.1101/759969 ◽

2019 ◽

Cited By ~ 1

Author(s):

William J. Watterson ◽

Melikhan Tanyeri ◽

Andrea R. Watson ◽

Candace M. Cham ◽

Yue Shan ◽

...

Keyword(s):

Ribosomal Rna ◽

Fold Increase ◽

Taxonomic Composition ◽

Biased Sampling ◽

Human Gut ◽

Rare Taxa ◽

Conventional Culture ◽

16S Ribosomal Rna Gene ◽

Slow Growing ◽

New Strategies

AbstractTraditional cultivation approaches in microbiology are labor-intensive, low-throughput, and often yield biased sampling of taxa due to ecological and evolutionary factors. New strategies are needed to enable ample representation of rare taxa and slow-growers that are outcompeted by fast-growing organisms. We developed a microfluidic platform that anaerobically isolates and cultivates microbial cells in millions of picoliter droplets and automatically sorts droplets based on colony density. We applied our strategy to mouse and human gut microbiomes and used 16S ribosomal RNA gene amplicons to characterize taxonomic composition of cells grown using different media. We found up to 4-fold increase in richness and larger representation of rare taxa among cells grown in droplets compared to conventional culture plates. Automated sorting of droplets for slow-growing colonies further enhanced the relative abundance of rare populations. Our method improves the cultivation and analysis of diverse microbiomes to gain deeper insights into microbial functioning and lifestyles.

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Ileal mucosa-associated microbiota overgrowth associated with pathogenesis of primary biliary cholangitis

Scientific Reports ◽

10.1038/s41598-021-99314-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Shogo Kitahata ◽

Yasunori Yamamoto ◽

Osamu Yoshida ◽

Yoshio Tokumoto ◽

Tomoe Kawamura ◽

...

Keyword(s):

Ribosomal Rna ◽

Primary Biliary Cholangitis ◽

Small Intestinal Mucosa ◽

Ileal Mucosa ◽

16S Ribosomal Rna Gene ◽

Pathological Development ◽

Small Intestinal ◽

Chronic Nonsuppurative Destructive Cholangitis ◽

Independent Association ◽

The Relationship

AbstractThe small intestinal mucosa-associated microbiota (MAM) can potentially impact the etiology of primary biliary cholangitis (PBC). Herein, we investigate the MAM profile to determine its association with liver pathology in patients with PBC. Thirty-four patients with PBC and 21 healthy controls who underwent colonoscopy at our hospital were enrolled in our study. We performed 16S ribosomal RNA gene sequencing of MAM samples obtained from the mucosa of the terminal ileum and examined the relationship between the abundance of ileal MAM and chronic nonsuppurative destructive cholangitis using liver specimens from patients with PBC. There was a significant reduction in microbial diversity within individuals with PBC (P = 0.039). Dysbiosis of ileal MAM was observed in patients with PBC, with a characteristic overgrowth of Sphingomonadaceae and Pseudomonas. Multivariate analysis showed that the overgrowth of Sphingomonadaceae and Pseudomonas is an independent association factor for PBC (P = 0.0429, P = 0.026). Moreover, the abundance of Sphingomonadaceae was associated with chronic nonsuppurative destructive cholangitis in PBC (P = 0.00981). The overgrowth of Sphingomonadaceae and Pseudomonas in ileal MAM was found in patients with PBC. Sphingomonadaceae may be associated with the pathological development of PBC.

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