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.

Simultaneous multiplexed amplicon sequencing and transcriptome profiling in single cells.

We describe droplet-assisted RNA targeting by single-cell sequencing (DART-seq), a versatile technology that enables multiplexed amplicon sequencing and transcriptome profiling in single cells. We applied DART-seq to simultaneously characterize the non-A-tailed transcripts of a segmented dsRNA virus and the transcriptome of the infected cell. In addition, we used DART-seq to simultaneously determine the natively paired, variable region heavy and light chain amplicons and the transcriptome of B lymphocytes.

A cell-free DNA metagenomic sequencing assay that integrates the host injury response to infection.

High-throughput metagenomic sequencing offers an unbiased approach to identify pathogens in clinical samples. Conventional metagenomic sequencing, however, does not integrate information about the host, which is often critical to distinguish infection from infectious disease, and to assess the severity of disease. Here, we explore the utility of high-throughput sequencing of cell-free DNA (cfDNA) after bisulfite conversion to map the tissue and cell types of origin of host-derived cfDNA, and to profile the bacterial and viral metagenome. We applied this assay to 51 urinary cfDNA isolates collected from a cohort of kidney transplant recipients with and without bacterial and viral infection of the urinary tract. We find that the cell and tissue types of origin of urinary cfDNA can be derived from its genome-wide profile of methylation marks, and strongly depend on infection status. We find evidence of kidney and bladder tissue damage due to viral and bacterial infection, respectively, and of the recruitment of neutrophils to the urinary tract during infection. Through direct comparison to conventional metagenomic sequencing as well as clinical tests of infection, we find this assay accurately captures the bacterial and viral composition of the sample. The assay presented here is straightforward to implement, offers a systems view into bacterial and viral infections of the urinary tract, and can find future use as a tool for the differential diagnosis of infection.

Measurement Biases Distort Cell-Free DNA Fragmentation Profiles and Define the Sensitivity of Metagenomic Cell-Free DNA Sequencing Assays.

BACKGROUND: Metagenomic sequencing of microbial cell-free DNA (cfDNA) in blood and urine is increasingly used as a tool for unbiased infection screening. The sensitivity of metagenomic cfDNA sequencing assays is determined by the efficiency by which the assay recovers microbial cfDNA vs host-specific cfDNA. We hypothesized that the choice of methods used for DNA isolation, DNA sequencing library preparation, and sequencing would affect the sensitivity of metagenomic cfDNA sequencing. METHODS: We characterized the fragment length biases inherent to select DNA isolation and library preparation procedures and developed a model to correct for these biases. We analyzed 305 cfDNA sequencing data sets, including publicly available data sets and 124 newly generated data sets, to evaluate the dependence of the sensitivity of metagenomic cfDNA sequencing on pre-analytical variables. RESULTS: Length bias correction of fragment length distributions measured from different experimental procedures revealed the ultrashort (<100 bp) nature of microbial-, mitochondrial-, and host-specific urinary cfDNA. The sensitivity of metagenomic sequencing assays to detect the clinically reported microorganism differed by more than 5-fold depending on the combination of DNA isolation and library preparation used. CONCLUSIONS: Substantial gains in the sensitivity of microbial and other short fragment recovery can be achieved by easy-to-implement changes in the sample preparation protocol, which highlights the need for standardization in the liquid biopsy field.

Development of a comprehensive noninvasive prenatal test.

Our aim was to develop and apply a comprehensive noninvasive prenatal test (NIPT) by using high-coverage targeted next-generation sequencing to estimate fetal fraction, determine fetal sex, and detect trisomy and monogenic disease without parental genotype information. We analyzed 45 pregnancies, 40 mock samples, and eight mother-child pairs to generate 35 simulated datasets. Fetal fraction (FF) was estimated based on analysis of the single nucleotide polymorphism (SNP) allele fraction distribution. A Z-score was calculated for trisomy of chromosome 21 (T21), and fetal sex detection. Monogenic disease detection was performed through variant analysis. Model validation was performed using the simulated datasets. The novel model to estimate FF was robust and accurate (r2= 0.994, p-value < 2.2e-16). For samples with FF > 0.04, T21 detection had 100% sensitivity (95% CI: 63.06 to 100%) and 98.53% specificity (95% CI: 92.08 to 99.96%). Fetal sex was determined with 100% accuracy. We later performed a proof of concept for monogenic disease diagnosis of 5/7 skeletal dysplasia cases. In conclusion, it is feasible to perform a comprehensive NIPT by using only data from high coverage targeted sequencing, which, in addition to detecting trisomies, also make it possible to identify pathogenic variants of the candidate genes for monogenic diseases.

Image-based profiling: a powerful and challenging new data type.

Software has provided cell biologists the power to quantify specific cellular features in cell images at scale. Before long, these biologists also recognized the potential to extract much more biological information from the same images. From here, the field of image-based profiling, the process of extracting unbiased representations that capture morphological cell state, was born. We are still in the early days of image-based profiling, and it is clear that the many opportunities to interrogate biological systems come with significant challenges. These challenges include building expressive and biologically-relevant representations, adjusting for technical noise, writing generalizable software infrastructure, continuing to foster a culture of open science, and promoting FAIR (findable, accessible, interoperable, and reusable) data. We present a workshop at the Pacific Symposium on Biocomputing 2022 to introduce the field of image-based profiling to the broader computational biology community. In the following document, we introduce image-based profiling, discuss current state-of-the-art methods and limitations, and provide rationale for why now is the perfect time for the field to expand. We also introduce our invited speakers and agenda, which together provide an introduction to the field complemented by in-depth application areas in industry and academia. We also include five lightning talks to complement the invited speakers on various methodological and discovery advances.

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.

Peritoneal Effluent Cell-Free DNA Sequencing in Peritoneal Dialysis Patients With and Without Peritonitis.

RATIONALE & OBJECTIVE: Conventional culture can be insensitive for the detection of rare infections and for the detection of common infections in the setting of recent antibiotic usage. Patients receiving peritoneal dialysis (PD) with suspected peritonitis have a significant proportion of negative conventional cultures. This study examines the utility of metagenomic sequencing of peritoneal effluent cell-free DNA (cfDNA) for evaluating the peritoneal effluent in PD patients with and without peritonitis. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: We prospectively characterized cfDNA in 68 peritoneal effluent samples obtained from 33 patients receiving PD at a single center from September 2016 to July 2018. OUTCOMES: Peritoneal effluent, microbial, and human cfDNA characteristics were evaluated in culture-confirmed peritonitis and culture-negative peritonitis. ANALYTICAL APPROACH: Descriptive statistics were analyzed and microbial cfDNA was detected in culture-confirmed peritonitis and culture-negative peritonitis. RESULTS: Metagenomic sequencing of cfDNA was able to detect and identify bacterial, viral, and eukaryotic pathogens in the peritoneal effluent from PD patients with culture-confirmed peritonitis, as well as patients with recent antibiotic usage and in cases of culture-negative peritonitis. LIMITATIONS: Parallel cultures were not obtained in all the peritoneal effluent specimens. CONCLUSIONS: Metagenomic cfDNA sequencing of the peritoneal effluent can identify pathogens in PD patients with peritonitis, including culture-negative peritonitis.

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.

Cell-free DNA (cfDNA) and Exosome Profiling from a Year-Long Human Spaceflight Reveals Circulating Biomarkers.

Liquid biopsies based on cell-free DNA (cfDNA) or exosomes provide a noninvasive approach to monitor human health and disease but have not been utilized for astronauts. Here, we profile cfDNA characteristics, including fragment size, cellular deconvolution, and nucleosome positioning, in an astronaut during a year-long mission on the International Space Station, compared to his identical twin on Earth and healthy donors. We observed a significant increase in the proportion of cell-free mitochondrial DNA (cf-mtDNA) inflight, and analysis of post-flight exosomes in plasma revealed a 30-fold increase in circulating exosomes and patient-specific protein cargo (including brain-derived peptides) after the year-long mission. This longitudinal analysis of astronaut cfDNA during spaceflight and the exosome profiles highlights their utility for astronaut health monitoring, as well as cf-mtDNA levels as a potential biomarker for physiological stress or immune system responses related to microgravity, radiation exposure, and the other unique environmental conditions of spaceflight.

Gut uropathogen abundance is a risk factor for development of bacteriuria and urinary tract infection.

The origin of most bacterial infections in the urinary tract is often presumed to be the gut. Herein, we investigate the relationship between the gut microbiota and future development of bacteriuria and urinary tract infection (UTI). We perform gut microbial profiling using 16S rRNA gene deep sequencing on 510 fecal specimens from 168 kidney transplant recipients and metagenomic sequencing on a subset of fecal specimens and urine supernatant specimens. We report that a 1% relative gut abundance of Escherichia is an independent risk factor for Escherichia bacteriuria and UTI and a 1% relative gut abundance of Enterococcus is an independent risk factor for Enterococcus bacteriuria. Strain analysis establishes a close strain level alignment between species found in the gut and in the urine in the same subjects. Our results support a gut microbiota-UTI axis, suggesting that modulating the gut microbiota may be a potential novel strategy to prevent UTIs.

Urinary cell-free DNA is a versatile analyte for monitoring infections of the urinary tract.

Urinary tract infections are one of the most common infections in humans. Here we tested the utility of urinary cell-free DNA (cfDNA) to comprehensively monitor host and pathogen dynamics in bacterial and viral urinary tract infections. We isolated cfDNA from 141 urine samples from a cohort of 82 kidney transplant recipients and performed next-generation sequencing. We found that urinary cfDNA is highly informative about bacterial and viral composition of the microbiome, antimicrobial susceptibility, bacterial growth dynamics, kidney allograft injury, and 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 with conventional diagnostic protocols. Our work identifies urinary cfDNA as a highly versatile analyte to monitor infections of the urinary tract.

Myriad Applications of Circulating Cell-Free DNA in Precision Organ Transplant Monitoring.

Solid organ transplantation remains the preferred treatment for many end-stage organ diseases, but complications due to acute rejection and infection occur frequently and undermine its long-term benefits. Monitoring of the health of the allograft is therefore a critically important component of post-transplant therapy. Here, we review several emerging applications of circulating cell-free DNA (cfDNA) in the post-transplant monitoring of rejection, infection, and immunosuppression. We further discuss the cellular origins and salient biophysical properties of cfDNA. A property of cfDNA that has been prominent since its discovery in the late 1940s is its ability to yield surprises. We review recent insights into the epigenetic features of cfDNA that yet again provide novel opportunities for transplant monitoring.

Single-stranded DNA library preparation uncovers the origin and diversity of ultrashort cell-free DNA in plasma.

Circulating cell-free DNA (cfDNA) is emerging as a powerful monitoring tool in cancer, pregnancy and organ transplantation. Nucleosomal DNA, the predominant form of plasma cfDNA, can be adapted for sequencing via ligation of double-stranded DNA (dsDNA) adapters. dsDNA library preparations, however, are insensitive to ultrashort, degraded cfDNA. Drawing inspiration from advances in paleogenomics, we have applied a single-stranded DNA (ssDNA) library preparation method to sequencing of cfDNA in the plasma of lung transplant recipients (40 samples, six patients). We found that ssDNA library preparation yields a greater portion of sub-100 bp nuclear genomic cfDNA (p 10(-5), Mann-Whitney U Test), and an increased relative abundance of mitochondrial (10.7x, p 10(-5)) and microbial cfDNA (71.3x, p 10(-5)). The higher yield of microbial sequences from this method increases the sensitivity of cfDNA-based monitoring for infections following transplantation. We detail the fragmentation pattern of mitochondrial, nuclear genomic and microbial cfDNA over a broad fragment length range. We report the observation of donor-specific mitochondrial cfDNA in the circulation of lung transplant recipients. A ssDNA library preparation method provides a more informative window into understudied forms of cfDNA, including mitochondrial and microbial derived cfDNA and short nuclear genomic cfDNA, while retaining information provided by standard dsDNA library preparation methods.