scholarly journals 1210. K-mer Profiling Powered by Reference-assisted Assembly of NGS Data: A Highly Sensitive Protocol to Infer the Plasma Microbiome Using Cell-free DNA Sequence Data

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S626-S627
Author(s):  
Rohita Sinha ◽  
Steve Kleiboeker ◽  
Michelle Altrich ◽  
Ellis Bixler
Keyword(s):  
Sequence Data ◽  
Clinical Specimen ◽  
Clinical Samples ◽  
Cell Free Dna ◽  
Antibody Mediated Rejection ◽  
Free Dna ◽  
Specificity And Sensitivity ◽  
Highly Sensitive ◽  
Ngs Data ◽  
Taxonomic Annotation

Abstract Background Cell-free DNA (cfDNA) has emerged as an important clinical specimen to probe for pathogenic microbes, especially in organ transplant patients where the same data can be used to predict allograft rejection. Recent reports described viral, bacterial or the complete microbial diversity in plasma following cfDNA sequencing. The prevalence of certain viral families (anelloviridae) is associated with immunosuppressant dosage and the risk of antibody mediated rejection. While being informative, the cfDNA reads are inherently shorter in length (~160bp or 2x75bp) and predominated by the host DNA (~97-99%), causing challenges in their taxonomic annotation and lower specificity. Here we present a computational protocol which minimizes these challenges by merging the concept of “Reference-assisted Assembly” with K-mer profiles of NGS data, for highly sensitive and specific microbial detection. Methods We developed a pipeline in which non-host NGS data (reads not mapped to the human genome) undergo a reference-assisted assembly operation and then taxonomic annotation using KrakenUneq (a K-mer based classifier). We trained the KrakenUneq on an in-house and curated database of ~12,000 viral genomes. We used three different K-mer values (16, 21, 31) to train KrakenUneq, and final predictions are made by applying a majority-wins rule. Currently the default KrakenUneq database is used for bacterial & fungal metagenome analysis. We tested our method on 30 simulated and 124 clinical samples obtained from a biorepository. Results Our protocol currently screens for a targeted list of pathogens (15 viral species, 16 bacterial and 10 fungal genera). On a simulated set of viral sample mixes, our protocol had 100% accuracy. For 124 clinical samples, predictions were evaluated for specificity and sensitivity using qPCR assays for the following viral species: EBV, BKV, JCV, HSV1/2, HHV7, and CMV. Total 33/38 computational predictions (87%) were confirmed by qPCR. The prediction sensitivity in terms of cps/ml ranged from 6 - 106 copies/mL. Conclusion Our efforts to perform ‘Reference-assisted assembly’ followed by K-mer based taxonomic annotation of cfDNA data, led to development of a novel and accurate pathogen detection protocol. Disclosures Rohita Sinha, PhD, Viracor-Eurofins (Employee) Steve Kleiboeker, DVM, PhD, Viracor-Eurofins (Employee) Michelle Altrich, PhD, Viracor-Eurofins (Employee) Ellis Bixler, MS, Viracor-Eurofins (Employee)

scholarly journals Numerous uncharacterized and highly divergent microbes which colonize humans are revealed by circulating cell-free DNA

2017 ◽  
Vol 114 (36) ◽  
pp. 9623-9628 ◽  
Author(s):  
Mark Kowarsky ◽  
Joan Camunas-Soler ◽  
Michael Kertesz ◽  
Iwijn De Vlaminck ◽  
Winston Koh ◽  
...  
Keyword(s):  
Human Body ◽  
Sequence Data ◽  
Human Microbiome ◽  
Pcr Amplification ◽  
The Body ◽  
Direct Pcr ◽  
Cell Free Dna ◽  
Free Dna ◽  
Novel Taxa ◽  
Circulating Cell Free Dna

Blood circulates throughout the human body and contains molecules drawn from virtually every tissue, including the microbes and viruses which colonize the body. Through massive shotgun sequencing of circulating cell-free DNA from the blood, we identified hundreds of new bacteria and viruses which represent previously unidentified members of the human microbiome. Analyzing cumulative sequence data from 1,351 blood samples collected from 188 patients enabled us to assemble 7,190 contiguous regions (contigs) larger than 1 kbp, of which 3,761 are novel with little or no sequence homology in any existing databases. The vast majority of these novel contigs possess coding sequences, and we have validated their existence both by finding their presence in independent experiments and by performing direct PCR amplification. When their nearest neighbors are located in the tree of life, many of the organisms represent entirely novel taxa, showing that microbial diversity within the human body is substantially broader than previously appreciated.

scholarly journals A cell-free DNA metagenomic sequencing assay that integrates the damage response to infection

2019 ◽  
Author(s):  
Alexandre Pellan Cheng ◽  
Philip Burnham ◽  
John Richard Lee ◽  
Matthew Pellan Cheng ◽  
Manikkam Suthanthiran ◽  
...  
Keyword(s):  
Urinary Tract ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Viral Infections ◽  
Clinical Samples ◽  
Metagenomic Sequencing ◽  
Kidney Transplant Recipients ◽  
Bladder Tissue ◽  
Cell Free Dna ◽  
Free Dna

ABSTRACTHigh-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 after bisulfite conversion to map the tissue and cell types of origin of host-derived cell-free DNA, 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 cell-free DNA 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 infections.

scholarly journals Prospective evaluation of donor-derived cell-free DNA as a potential biomarker for cardiac allograft vasculopathy

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
M Jimenez-Blanco Bravo ◽  
L Perez Gomez ◽  
C Arellano Serrano ◽  
F.J Hernandez Perez ◽  
M Gomez Bueno ◽  
...  
Keyword(s):  
Unmet Need ◽  
Cardiac Allograft Vasculopathy ◽  
Cardiac Allograft ◽  
Allograft Vasculopathy ◽  
Cell Free Dna ◽  
Antibody Mediated Rejection ◽  
Free Dna ◽  
Asymptomatic Patients ◽  
Potential Biomarker ◽  
Coronary Angiograms

Abstract Background Cardiac allograft vasculopathy (CAV) remains a major cause of morbidity and mortality among long-term heart transplant (HT) recipients. There is clearly an unmet need for a noninvasive biomarker of CAV that could obviate the need to perform surveillance coronary angiograms in these patients. Purpose Our aim was to evaluate the performance of Donor-derived Cell Free DNA (dd-cfDNA) as a biomarker of CAV. Methods We prospectively measured dd-cfDNA levels in all consecutive asymptomatic patients undergoing surveillance coronary angiography >1 year after HT at a single center, between Jan 2019 and Jan 2021. Endpoints included the association between dd-cfDNA levels and the presence CAV, according to ISHLT 2010 classification. Patients with history of acute cellular rejection ≥1R or antibody mediated rejection in the previous 6 months were excluded. Results We included 94 HT recipients, median age 57 years (IQR 50–67), 67% men, a median of 10.9 years after transplant. Coronary angiogram revealed CAV0, CAV1, CAV2 and CAV3 in 61%, 19%, 14% and 6% of patients, respectively. Median dd-cfDNA values for each CAV group were: CAV0 0.92% (IQR 0.46–2.0), CAV1 1.4% (0.38–2.8), CAV2 0.17% (0.07–0.52) and CAV3 0.24% (0.057–0.87); p=0.0535. Figure 1 summarizes baseline characteristics of the cohort and results. Comparison of dd-cfDNA levels in patients with CAV0 and CAV1–2-3 did not show significant differences (0.92%, IQR 0.46–2.0 vs 0.46%, IQR 0.075–1.5, p=0.059) (Figure 2A), nor did the comparison between patients with stable CAV (no new coronary lesions since previous angiogram, n=77) and progressive CAV (patients with new coronary stenoses, n=17); median dd-cfDNA values were 0.735% (IQR 0.195–2.0) vs 0.9% (IQR 0.12–1.8), p=0.76 (Figure 2B). A subanalysis according to time after HT was also found non-significant: less than 5 years (p=0.95), 5 to 10 years (p=0.14) and more than 10 years after HT (p=0.16) (Figure 2C). The AUC ROC curve for the diagnosis of CAV revealed the lack of ability to predict the presence of any degree of CAV (AUC ROC = 0.38). Conclusion In our experience, dd-cfDNA did not perform as a useful biomarker to avoid surveillance coronary angiograms for CAV diagnosis. FUNDunding Acknowledgement Type of funding sources: Other. Main funding source(s): Sociedad Madrileña de Trasplantes

Plasma cell-free DNA-based prognosis in metastatic hormone sensitive prostate cancer.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 242-242
Author(s):  
Manish Kohli ◽  
Siddhartha Yadav ◽  
Winston Tan ◽  
Irbaz Bin Riaz ◽  
Tiantian Zheng ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Plasma Cell ◽  
Univariate Analysis ◽  
Newly Diagnosed ◽  
Illumina Hiseq ◽  
Cell Free Dna ◽  
Free Dna ◽  
Genomic Aberrations ◽  
Hormone Sensitive ◽  
Ngs Data

242 Background: We evaluated plasma cell free based genomic aberrations for prognosticating survival of newly diagnosed metastatic hormone sensitive prostate cancer (mHSPC) patients (pts). Methods: Plasma was collected from mHSPC pts enrolled between 2009-2014. Platelet poor plasma (PPP) fractions were processed uniformly and cell free DNA (cfDNA) extracted using Qiagen kits. Pts were followed after initiating hormonal therapy until death. Next Gen Sequencing (NGS) of cfDNA was performed using Illumina HiSeq X for a preselected panel of 128 genes (PredicineDDR-77 cancer driver genes; 29 genes in BRCA-FA homologous recombination deficiency (HRD) pathway; 22 DNA damage repair pathway genes). Statistical analyses of plasma genome based aberrations with overall survival (OS) were performed in R 3.5.1. Cox proportional-hazard models were used for survival analysis. Results: An average of 2.5 ml PPP from 99 pts yielded a median of 10.5 ng (range: 2.8-702) cfDNA per sample. 15/99 pt samples with a yield < 5 ng were excluded from sequencing; 9/99 samples failed NGS. Median follow-up time was 80.2 months (mths) (Range: 74.7, 87]); median OS was 69.1 mths (range: 54,NR). 29 pts with full NGS data had high volume metastatic disease. cfDNA yield correlated with metastatic volume (P = 0.01). Univariate analysis revealed both variables prognostic for OS (Metastatic volume: log-rank P=0.01, HR=2.1, 95% CI: 1.1-3.8; cfDNA yield: P =0.04, HR = 1.3, 95% CI: 1.03-1.7). Multivariate regression showed prognostic value of cfDNA yield remained independent of metastatic volume (P = 0.03, HR = 1.34, 95% CI: 1.02-1.76). 54/67 samples with NGS data had at least one mutation/copy number variation detected. Top mutated genes included TP53 (N=18), ATM (N=9), CHEK2 (N=7), FANCM (N=6), RB1 (N=6), BRCA2 (N=5), PIK3CA (N=4) and 37/67 pts harbored 1≥ variant in HDR pathways. These pts had a shorter survival (median: 58.6 mths) (P=0.04, HR= 2.28, 95% CI: 1.01-5.18) and pts with ATM mutations did significantly worse (median survival: 47.4 mths) (HR=4.03, P=0.0005, 95% CI: 1.73-9.37). Conclusions: Plasma cfDNA yield is prognostic for survival in newly diagnosed mHSPC state and presence of HRD pathway genomic aberrations in plasma cfDNA are associated with poor survival.

The Role of Donor-Derived Cell-Free DNA in the Identification of Injury in Kidney Allografts with Antibody-Mediated Rejection or De Novo DSA

2018 ◽  
Vol 102 ◽  
pp. S5-S6
Author(s):  
Huanxi Zhang ◽  
Longshan Liu ◽  
Chunting Zheng ◽  
Xirui Li ◽  
Qian Fu ◽  
...  
Keyword(s):  
De Novo ◽  
Cell Free Dna ◽  
Antibody Mediated Rejection ◽  
Free Dna

scholarly journals The Use of Donor-Derived Cell-Free DNA for Assessment of Allograft Rejection and Injury Status

2020 ◽  
Vol 9 (5) ◽  
pp. 1480 ◽  
Author(s):  
Charat Thongprayoon ◽  
Pradeep Vaitla ◽  
Iasmina M. Craici ◽  
Napat Leeaphorn ◽  
Panupong Hansrivijit ◽  
...  
Keyword(s):  
Serum Creatinine ◽  
Allograft Rejection ◽  
Surrogate Marker ◽  
Diagnostic Tools ◽  
Cell Free Dna ◽  
Antibody Mediated Rejection ◽  
Acute Renal Allograft Rejection ◽  
Free Dna ◽  
Allograft Loss ◽  
Injury Status

Patient monitoring after kidney transplantation (KT) for early detection of allograft rejection remains key in preventing allograft loss. Serum creatinine has poor predictive value to detect ongoing active rejection as its increase is not sensitive, nor specific for acute renal allograft rejection. Diagnosis of acute rejection requires allograft biopsy and histological assessment, which can be logistically challenging in some cases and carries inherent risk for complications related to procedure. Donor-derived cell-free DNA (dd-cfDNA), DNA of donor origin in the blood of KT recipient arising from cells undergoing injury and death, has been examined as a potential surrogate marker for allograft rejection. A rise in dd-cfDNA levels precedes changes in serum creatinine allows early detections and use as a screening tool for allograft rejection. In addition, when used in conjunction with donor-specific antibodies (DSA), it increases the pre-biopsy probability of antibody-mediated rejection (ABMR) aiding the decision-making process. Advancements in noninvasive biomarker assays such as dd-cfDNA may offer the opportunity to improve and expand the spectrum of available diagnostic tools to monitor and detect risk for rejection and positively impact outcomes for KT recipients. In this this article, we discussed the evolution of dd-cfDNA assays and recent evidence of assessment of allograft rejection and injury status of KT by the use of dd-cfDNA.

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