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Heyang, M.

Publications and source records attributed to Heyang, M..

2 recordsLinked to original sources

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

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. 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. 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.

genomics↗

Host-pathogen interactions in urinary tract infection from the structure and diversity of urinary cell-free DNA

Infections of the urinary tract are the most common form of infection in the human population. Here, we tested the utility of urinary cell-free DNA (cfDNA) to comprehensively monitor host and pathogen dynamics in the scope of bacterial and viral urinary tract infections. We assayed cfDNA isolated from 141 urine samples obtained from a cohort of 82 kidney transplant recipients by next-generation sequencing. We find that urinary cfDNA simultaneously informs about the composition of the bacterial and viral components of the microbiome, antimicrobial susceptibility, bacterial growth dynamics, kidney allograft injury, and the host response to infection. These different layers of information are accessible from a single assay and individually agree with corresponding clinical tests based on quantitative PCR, conventional bacterial culture, and urinalysis. In addition, cfDNA reveals the frequent occurrence of pathologies that remain undiagnosed in conventional diagnostic workups. Our work identifies urinary cfDNA as a highly versatile tool to monitor infections of the urinary tract.

genomics↗