Dataset Information

Separating the signal from the noise in metagenomic cell-free DNA sequencing.

ABSTRACT:

Background

Cell-free DNA (cfDNA) in blood, urine, and other biofluids provides a unique window into human health. A proportion of cfDNA is derived from bacteria and viruses, creating opportunities for the diagnosis of infection via metagenomic sequencing. The total biomass of microbial-derived cfDNA in clinical isolates is low, which makes metagenomic cfDNA sequencing susceptible to contamination and alignment noise.

Results

Here, we report low biomass background correction (LBBC), a bioinformatics noise filtering tool informed by the uniformity of the coverage of microbial genomes and the batch variation in the absolute abundance of microbial cfDNA. We demonstrate that LBBC leads to a dramatic reduction in false positive rate while minimally affecting the true positive rate for a cfDNA test to screen for urinary tract infection. We next performed high-throughput sequencing of cfDNA in amniotic fluid collected from term uncomplicated pregnancies or those complicated with clinical chorioamnionitis with and without intra-amniotic infection.

Conclusions

The data provide unique insight into the properties of fetal and maternal cfDNA in amniotic fluid, demonstrate the utility of cfDNA to screen for intra-amniotic infection, support the view that the amniotic fluid is sterile during normal pregnancy, and reveal cases of intra-amniotic inflammation without infection at term. Video abstract.

SUBMITTER: Burnham P

PROVIDER: S-EPMC7014780 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Publications

Separating the signal from the noise in metagenomic cell-free DNA sequencing.

Burnham Philip P Gomez-Lopez Nardhy N Heyang Michael M Cheng Alexandre Pellan AP Lenz Joan Sesing JS Dadhania Darshana M DM Lee John Richard JR Suthanthiran Manikkam M Romero Roberto R De Vlaminck Iwijn I

Microbiome 20200211 1

<h4>Background</h4>Cell-free DNA (cfDNA) in blood, urine, and other biofluids provides a unique window into human health. A proportion of cfDNA is derived from bacteria and viruses, creating opportunities for the diagnosis of infection via metagenomic sequencing. The total biomass of microbial-derived cfDNA in clinical isolates is low, which makes metagenomic cfDNA sequencing susceptible to contamination and alignment noise.<h4>Results</h4>Here, we report low biomass background correction (LBBC) ...[more]

PMID: 32046792

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Project description:BackgroundMetagenomic next-generation sequencing (mNGS) could improve the diagnosed efficiency of pathogens in bloodstream infections or sepsis. Little is known about the clinical impact of mNGS test when used for the early diagnosis of suspected infections. Herein, our main objective was to assess the clinical efficacy of utilizing blood samples to perform mNGS for early diagnosis of suspected infections, as well as to evaluate its potential in guiding antimicrobial therapy decisions.MethodsIn this study, 212 adult hospitalized patients who underwent blood mNGS test in the early stage of suspected infections were enrolled. Diagnostic efficacy of mNGS test and blood culture was compared, and the clinical impact of mNGS on clinical care was analyzed.ResultsIn our study, the total detection rate of blood mNGS was significantly higher than that of culture method (74.4% vs. 12.1%, P < 0.001) in the paired mNGS test and blood culture. Blood stream infection (107, 67.3%) comprised the largest component of all the diseases in our patients, and the detection rate of single blood sample subgroup was similar with that of multiple type of samples subgroup. Among the 187 patients complained with fever, there was no difference in the diagnostic efficacy of mNGS when blood specimens or additional other specimens were used in cases presenting only with fever. While, when patients had other symptoms except fever, the performance of mNGS was superior in cases with specimens of suspected infected sites and blood collected at the same time. Guided by mNGS results, therapeutic regimens for 70.3% cases (149/212) were changed, and the average hospitalized days were significantly shortened in cases with the earlier sampling time of admission.ConclusionIn this study, we emphasized the importance of blood mNGS in early infectious patients with mild and non-specific symptoms. Blood mNGS can be used as a supplement to conventional laboratory examination, and should be performed as soon as possible to guide clinicians to perform appropriate anti-infection treatment timely and effectively. Additionally, combining the contemporaneous samples from suspected infection sites could improve disease diagnosis and prognoses. Further research needs to be better validated in large-scale clinical trials to optimize diagnostic protocol, and the cost-utility analysis should be performed.

Project description:UnlabelledBackgroundThe metagenomics approach allows the simultaneous sequencing of all genomes in an environmental sample. This results in high complexity datasets, where in addition to repeats and sequencing errors, the number of genomes and their abundance ratios are unknown. Recently developed next-generation sequencing (NGS) technologies significantly improve the sequencing efficiency and cost. On the other hand, they result in shorter reads, which makes the separation of reads from different species harder. Among the existing computational tools for metagenomic analysis, there are similarity-based methods that use reference databases to align reads and composition-based methods that use composition patterns (i.e., frequencies of short words or l-mers) to cluster reads. Similarity-based methods are unable to classify reads from unknown species without close references (which constitute the majority of reads). Since composition patterns are preserved only in significantly large fragments, composition-based tools cannot be used for very short reads, which becomes a significant limitation with the development of NGS. A recently proposed algorithm, AbundanceBin, introduced another method that bins reads based on predicted abundances of the genomes sequenced. However, it does not separate reads from genomes of similar abundance levels.ResultsIn this work, we present a two-phase heuristic algorithm for separating short paired-end reads from different genomes in a metagenomic dataset. We use the observation that most of the l-mers belong to unique genomes when l is sufficiently large. The first phase of the algorithm results in clusters of l-mers each of which belongs to one genome. During the second phase, clusters are merged based on l-mer repeat information. These final clusters are used to assign reads. The algorithm could handle very short reads and sequencing errors. It is initially designed for genomes with similar abundance levels and then extended to handle arbitrary abundance ratios. The software can be download for free at http://www.cs.ucr.edu/∼tanaseio/toss.htm.ConclusionsOur tests on a large number of simulated metagenomic datasets concerning species at various phylogenetic distances demonstrate that genomes can be separated if the number of common repeats is smaller than the number of genome-specific repeats. For such genomes, our method can separate NGS reads with a high precision and sensitivity.

Dataset Information

Separating the signal from the noise in metagenomic cell-free DNA sequencing.

Background

Results

Conclusions

Publications

Separating the signal from the noise in metagenomic cell-free DNA sequencing.

Similar Datasets

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