A quantitative comparison of urine centrifugation and filtration for the isolation and analysis of urinary nucleic acid biomarkers.

Urine is a rich source of nucleic acid biomarkers including cell-free DNA (cfDNA) and RNA for monitoring the health of kidney allografts. In this study, we aimed to evaluate whether urine filtration can serve as an alternative to the commonly used method of centrifugation to collect urinary fluid and cell pellets for isolating cfDNA and cellular messenger RNA (mRNA). We collected urine specimens from kidney allograft recipients and obtained the urine supernatant and cell pellet from each specimen using both filtration and centrifugation for paired analyses. We performed DNA sequencing to characterize the origin and properties of cfDNA, as well as quantitative PCR of mRNAs extracted from cell fractions. Our results showed that the biophysical properties of cfDNA, the microbial DNA content, and the tissues of origin of cfDNA were comparable between samples processed using filtration and centrifugation method. Similarly, mRNA quality and quantity obtained using both methods met our criteria for downstream application and the Ct values for each mRNA were comparable between the two techniques.The Ct values demonstrated a high degree of correlation. These findings suggest that urine filtration is a viable alternative to urine centrifugation for isolation of nucleic acid biomarkers from urine specimens.

Metagenomic DNA sequencing to quantify Mycobacterium tuberculosis DNA and diagnose tuberculosis.

Tuberculosis (TB) remains a significant cause of mortality worldwide. Metagenomic next-generation sequencing has the potential to reveal biomarkers of active disease, identify coinfection, and improve detection for sputum-scarce or culture-negative cases. We conducted a large-scale comparative study of 428 plasma, urine, and oral swab samples from 334 individuals from TB endemic and non-endemic regions to evaluate the utility of a shotgun metagenomic DNA sequencing assay for tuberculosis diagnosis. We found that the composition of the control population had a strong impact on the measured performance of the diagnostic test: the use of a control population composed of individuals from a TB non-endemic region led to a test with nearly 100% specificity and sensitivity, whereas a control group composed of individuals from TB endemic regions exhibited a high background of nontuberculous mycobacterial DNA, limiting the diagnostic performance of the test. Using mathematical modeling and quantitative comparisons to matched qPCR data, we found that the burden of Mycobacterium tuberculosis DNA constitutes a very small fraction (0.04 or less) of the total abundance of DNA originating from mycobacteria in samples from TB endemic regions. Our findings suggest that the utility of a minimally invasive metagenomic sequencing assay for pulmonary tuberculosis diagnostics is limited by the low burden of M. tuberculosis and an overwhelming biological background of nontuberculous mycobacterial DNA.

A metagenomic DNA sequencing assay that is robust against environmental DNA contamination.

Metagenomic DNA sequencing is a powerful tool to characterize microbial communities but is sensitive to environmental DNA contamination, in particular when applied to samples with low microbial biomass. Here, we present Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) a metagenomic sequencing assay that is robust against environmental DNA contamination introduced during sample preparation. The core idea of SIFT-seq is to tag the DNA in the sample prior to DNA isolation and library preparation with a label that can be recorded by DNA sequencing. Any contaminating DNA that is introduced in the sample after tagging can then be bioinformatically identified and removed. We applied SIFT-seq to screen for infections from microorganisms with low burden in blood and urine, to identify COVID-19 co-infection, to characterize the urinary microbiome, and to identify microbial DNA signatures of sepsis and inflammatory bowel disease in blood.

Cell-free DNA profiling informs all major complications of hematopoietic cell transplantation.

Allogeneic hematopoietic cell transplantation (HCT) provides effective treatment for hematologic malignancies and immune disorders. Monitoring of posttransplant complications is critical, yet current diagnostic options are limited. Here, we show that cell-free DNA (cfDNA) in blood is a versatile analyte for monitoring of the most important complications that occur after HCT: graft-versus-host disease (GVHD), a frequent immune complication of HCT, infection, relapse of underlying disease, and graft failure. We demonstrate that these therapeutic complications are informed from a single assay, low-coverage bisulfite sequencing of cfDNA, followed by disease-specific bioinformatic analyses. To inform GVHD, we profile cfDNA methylation marks to trace the cfDNA tissues-of-origin and to quantify tissue-specific injury. To inform infection, we implement metagenomic cfDNA profiling. To inform cancer relapse, we implement analyses of tumor-specific genomic aberrations. Finally, to detect graft failure, we quantify the proportion of donor- and recipient-specific cfDNA. We applied this assay to 170 plasma samples collected from 27 HCT recipients at predetermined timepoints before and after allogeneic HCT. We found that the abundance of solid-organ-derived cfDNA in the blood at 1 mo after HCT is predictive of acute GVHD (area under the curve, 0.88). Metagenomic profiling of cfDNA revealed the frequent occurrence of viral reactivation in this patient population. The fraction of donor-specific cfDNA was indicative of relapse and remission, and the fraction of tumor-specific cfDNA was informative of cancer relapse. This proof-of-principle study shows that cfDNA has the potential to improve the care of allogeneic HCT recipients by enabling earlier detection and better prediction of the complex array of complications that occur after HCT.

Highly multiplexed spatial mapping of microbial communities.

Mapping the complex biogeography of microbial communities in situ with high taxonomic and spatial resolution poses a major challenge because of the high density1 and rich diversity2 of species in environmental microbiomes and the limitations of optical imaging technology3-6. Here we introduce high-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH), a versatile technology that uses binary encoding, spectral imaging and decoding based on machine learning to create micrometre-scale maps of the locations and identities of hundreds of microbial species in complex communities. We show that 10-bit HiPR-FISH can distinguish between 1,023 isolates of Escherichia coli, each fluorescently labelled with a unique binary barcode. HiPR-FISH, in conjunction with custom algorithms for automated probe design and analysis of single-cell images, reveals the disruption of spatial networks in the mouse gut microbiome in response to treatment with antibiotics, and the longitudinal stability of spatial architectures in the human oral plaque microbiome. Combined with super-resolution imaging, HiPR-FISH shows the diverse strategies of ribosome organization that are exhibited by taxa in the human oral microbiome. HiPR-FISH provides a framework for analysing the spatial ecology of environmental microbial communities at single-cell resolution.

Cell-Free DNA in Blood Reveals Significant Cell, Tissue and Organ Specific injury and Predicts COVID-19 Severity.

COVID-19 primarily affects the lungs, but evidence of systemic disease with multi-organ involvement is emerging. Here, we developed a blood test to broadly quantify cell, tissue, and organ specific injury due to COVID-19, using genome-wide methylation profiling of circulating cell-free DNA in plasma. We assessed the utility of this test to identify subjects with severe disease in two independent, longitudinal cohorts of hospitalized patients. Cell-free DNA profiling was performed on 104 plasma samples from 33 COVID-19 patients and compared to samples from patients with other viral infections and healthy controls. We found evidence of injury to the lung and liver and involvement of red blood cell progenitors associated with severe COVID-19. The concentration of cfDNA correlated with the WHO ordinal scale for disease progression and was significantly increased in patients requiring intubation. This study points to the utility of cell-free DNA as an analyte to monitor and study COVID-19.

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

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.