scholarly journals Propionibacterium acnes: Disease-Causing Agent or Common Contaminant? Detection in Diverse Patient Samples by Next-Generation Sequencing

2016 ◽  
Vol 54 (4) ◽  
pp. 980-987 ◽  
Author(s):  
Sarah Mollerup ◽  
Jens Friis-Nielsen ◽  
Lasse Vinner ◽  
Thomas Arn Hansen ◽  
Stine Raith Richter ◽  
...  

Propionibacterium acnesis the most abundant bacterium on human skin, particularly in sebaceous areas.P. acnesis suggested to be an opportunistic pathogen involved in the development of diverse medical conditions but is also a proven contaminant of human clinical samples and surgical wounds. Its significance as a pathogen is consequently a matter of debate. In the present study, we investigated the presence ofP. acnesDNA in 250 next-generation sequencing data sets generated from 180 samples of 20 different sample types, mostly of cancerous origin. The samples were subjected to either microbial enrichment, involving nuclease treatment to reduce the amount of host nucleic acids, or shotgun sequencing. We detected high proportions ofP. acnesDNA in enriched samples, particularly skin tissue-derived and other tissue samples, with the levels being higher in enriched samples than in shotgun-sequenced samples.P. acnesreads were detected in most samples analyzed, though the proportions in most shotgun-sequenced samples were low. Our results show thatP. acnescan be detected in practically all sample types when molecular methods, such as next-generation sequencing, are employed. The possibility of contamination from the patient or other sources, including laboratory reagents or environment, should therefore always be considered carefully whenP. acnesis detected in clinical samples. We advocate that detection ofP. acnesalways be accompanied by experiments validating the association between this bacterium and any clinical condition.

Author(s):  
Wei Gu ◽  
Steve Miller ◽  
Charles Y. Chiu

Nearly all infectious agents contain DNA or RNA genomes, making sequencing an attractive approach for pathogen detection. The cost of high-throughput or next-generation sequencing has been reduced by several orders of magnitude since its advent in 2004, and it has emerged as an enabling technological platform for the detection and taxonomic characterization of microorganisms in clinical samples from patients. This review focuses on the application of untargeted metagenomic next-generation sequencing to the clinical diagnosis of infectious diseases, particularly in areas in which conventional diagnostic approaches have limitations. The review covers ( a) next-generation sequencing technologies and common platforms, ( b) next-generation sequencing assay workflows in the clinical microbiology laboratory, ( c) bioinformatics analysis of metagenomic next-generation sequencing data, ( d) validation and use of metagenomic next-generation sequencing for diagnosing infectious diseases, and ( e) significant case reports and studies in this area. Next-generation sequencing is a new technology that has the promise to enhance our ability to diagnose, interrogate, and track infectious diseases.


Author(s):  
Anne Krogh Nøhr ◽  
Kristian Hanghøj ◽  
Genis Garcia Erill ◽  
Zilong Li ◽  
Ida Moltke ◽  
...  

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Panagiotis Moulos

Abstract Background The relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging. Results recoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations. Conclusion While some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.


2011 ◽  
Vol 9 (6) ◽  
pp. 238-244 ◽  
Author(s):  
Tongwu Zhang ◽  
Yingfeng Luo ◽  
Kan Liu ◽  
Linlin Pan ◽  
Bing Zhang ◽  
...  

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