Multiplex Picoliter-Droplet Digital PCR for Quantitative Assessment of DNA Integrity in Clinical Samples

BACKGROUND Assessment of DNA integrity and quantity remains a bottleneck for high-throughput molecular genotyping technologies, including next-generation sequencing. In particular, DNA extracted from paraffin-embedded tissues, a major potential source of tumor DNA, varies widely in quality, leading to unpredictable sequencing data. We describe a picoliter droplet–based digital PCR method that enables simultaneous detection of DNA integrity and the quantity of amplifiable DNA. METHODS Using a multiplex assay, we detected 4 different target lengths (78, 159, 197, and 550 bp). Assays were validated with human genomic DNA fragmented to sizes of 170 bp to 3000 bp. The technique was validated with DNA quantities as low as 1 ng. We evaluated 12 DNA samples extracted from paraffin-embedded lung adenocarcinoma tissues. RESULTS One sample contained no amplifiable DNA. The fractions of amplifiable DNA for the 11 other samples were between 0.05% and 10.1% for 78-bp fragments and ≤1% for longer fragments. Four samples were chosen for enrichment and next-generation sequencing. The quality of the sequencing data was in agreement with the results of the DNA-integrity test. Specifically, DNA with low integrity yielded sequencing results with lower levels of coverage and uniformity and had higher levels of false-positive variants. CONCLUSIONS The development of DNA-quality assays will enable researchers to downselect samples or process more DNA to achieve reliable genome sequencing with the highest possible efficiency of cost and effort, as well as minimize the waste of precious samples.

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

Journal of Clinical Microbiology ◽

10.1128/jcm.02723-15 ◽

2016 ◽

Vol 54 (4) ◽

pp. 980-987 ◽

Cited By ~ 50

Author(s):

Sarah Mollerup ◽

Jens Friis-Nielsen ◽

Lasse Vinner ◽

Thomas Arn Hansen ◽

Stine Raith Richter ◽

...

Keyword(s):

Next Generation Sequencing ◽

Propionibacterium Acnes ◽

Opportunistic Pathogen ◽

Next Generation Sequencing Data ◽

Clinical Samples ◽

Next Generation ◽

Sequencing Data ◽

Tissue Samples ◽

Content Type ◽

Generation Sequencing

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.

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Evaluation of the Use of Formalin-Fixed and Paraffin-Embedded Archive Gastric Tissues for Microbiota Characterization Using Next-Generation Sequencing

International Journal of Molecular Sciences ◽

10.3390/ijms21031096 ◽

2020 ◽

Vol 21 (3) ◽

pp. 1096 ◽

Cited By ~ 1

Author(s):

Ines Pinto-Ribeiro ◽

Rui M. Ferreira ◽

Joana Pereira-Marques ◽

Vanessa Pinto ◽

Guilherme Macedo ◽

...

Keyword(s):

Next Generation Sequencing ◽

Tissue Sample ◽

Clinical Samples ◽

Rrna Gene ◽

Next Generation ◽

Sequencing Data ◽

Ffpe Tissues ◽

The Times ◽

Generation Sequencing ◽

Formalin Fixed

Large numbers of well-characterized clinical samples are fundamental to establish relevant associations between the microbiota and disease. Formalin-fixed and paraffin-embedded (FFPE) tissues are routinely used and are widely available clinical materials. Since current approaches to study the microbiota are based on next-generation sequencing (NGS) targeting the bacterial 16S rRNA gene, our aim was to evaluate the feasibility of FFPE gastric tissues for NGS-based microbiota characterization. Analysis of sequencing data revealed the presence of bacteria in the paraffin control. After the subtraction of the operational taxonomic units (OTUs) present in the paraffin control to the FFPE tissue sample dataset, we evaluated the microbiota profiles between paired FFPE and frozen gastric tissues, and between different times of archiving. Compared with frozen gastric tissues, we detected a lower number of OTUs in the microbiota of paired FFPE tissues, regardless of the time of archiving. No major differences in microbial diversity were identified, but taxonomic variation in the relative abundance of phyla and orders was observed between the two preservation methods. This variation was also evident in each case and throughout the times of FFPE archiving. The use of FFPE tissues for NGS-based microbiota characterization should be considered carefully, as biases can be introduced by the embedding process and the time of tissue archiving.

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Clinical Metagenomic Next-Generation Sequencing for Pathogen Detection

Annual Review of Pathology Mechanisms of Disease ◽

10.1146/annurev-pathmechdis-012418-012751 ◽

2019 ◽

Vol 14 (1) ◽

pp. 319-338 ◽

Cited By ~ 110

Author(s):

Wei Gu ◽

Steve Miller ◽

Charles Y. Chiu

Keyword(s):

Next Generation Sequencing ◽

Infectious Diseases ◽

Pathogen Detection ◽

Case Reports ◽

Next Generation Sequencing Data ◽

Clinical Samples ◽

Clinical Microbiology Laboratory ◽

Next Generation ◽

Sequencing Data ◽

Generation Sequencing

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.

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Evaluation of targeted next-generation sequencing for detection of equine pathogens in clinical samples

Journal of Veterinary Diagnostic Investigation ◽

10.1177/1040638720978381 ◽

2020 ◽

pp. 104063872097838

Author(s):

Eman Anis ◽

Marcia R. S. Ilha ◽

Julie B. Engiles ◽

Rebecca P. Wilkes

Keyword(s):

Next Generation Sequencing ◽

Simultaneous Detection ◽

Clinical Samples ◽

Next Generation ◽

Diagnostic Laboratory ◽

Percent Agreement ◽

Moderate Agreement ◽

Targeted Ngs ◽

Parasitic Pathogens ◽

Generation Sequencing

Equine infectious disease outbreaks may have profound economic impact, resulting in losses of millions of dollars of revenue as a result of horse loss, quarantine, and cancelled events. Early and accurate diagnosis is essential to limit the spread of infectious diseases. However, laboratory detection of infectious agents, especially the simultaneous detection of multiple agents, can be challenging to the clinician and diagnostic laboratory. Next-generation sequencing (NGS), which allows millions of DNA templates to be sequenced simultaneously in a single reaction, is an ideal technology for comprehensive testing. We conducted a proof-of-concept study of targeted NGS to detect 62 common equine bacterial, viral, and parasitic pathogens in clinical samples. We designed 264 primers and constructed a bioinformatics tool for the detection of targeted pathogens. The designed primers were able to specifically detect the intended pathogens. Results of testing 27 clinical samples with our targeted NGS assay compared with results of routine tests (assessed as a group) yielded positive percent agreement of 81% and negative percent agreement of 83%, overall agreement of 81%, and kappa of 0.56 (moderate agreement). This moderate agreement was likely the result of low sensitivity of some primers. However, our NGS assay successfully detected multiple pathogens in the clinical samples, including some pathogens missed by routine techniques.

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Faculty Opinions recommendation of VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718272765.793499663 ◽

2014 ◽

Author(s):

Gary Bader ◽

Mohamed Helmy

Keyword(s):

Next Generation Sequencing ◽

Network Analysis ◽

Next Generation Sequencing Data ◽

Cancer Genes ◽

Next Generation ◽

Sequencing Data ◽

Generation Sequencing

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Faculty Opinions recommendation of Bioinformatory-assisted analysis of next-generation sequencing data for precision medicine in pancreatic cancer.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.727775566.793536095 ◽

2017 ◽

Author(s):

Steve Pereira

Keyword(s):

Pancreatic Cancer ◽

Next Generation Sequencing ◽

Precision Medicine ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Assisted Analysis ◽

Generation Sequencing

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NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab174 ◽

2021 ◽

Author(s):

Anne Krogh Nøhr ◽

Kristian Hanghøj ◽

Genis Garcia Erill ◽

Zilong Li ◽

Ida Moltke ◽

...

Keyword(s):

Next Generation Sequencing ◽

Genetic Research ◽

Likelihood Estimation ◽

Software Tool ◽

Estimation Methods ◽

Next Generation Sequencing Data ◽

Next Generation ◽

Sequencing Data ◽

Ngs Data ◽

Generation Sequencing

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.

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recoup: flexible and versatile signal visualization from next generation sequencing

BMC Bioinformatics ◽

10.1186/s12859-020-03902-x ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Panagiotis Moulos

Keyword(s):

Next Generation Sequencing ◽

Next Generation Sequencing Data ◽

Special Focus ◽

Next Generation ◽

Sequencing Data ◽

User Friendliness ◽

Computational Environment ◽

Level Data ◽

Data Signal ◽

Generation Sequencing

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.

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