Project description:Using a public reference data set of 82 unique entities, 382 nanopore-sequenced brain tumor samples were classified based on their methylation status through an ad hoc random forest algorithm. As a measure of confidence, score recalibration was performed and platform-specific thresholds were defined.
Project description:Circulating extracellular vesicles (EVs) have gained significant attention for discovering tumor biomarkers. However, isolating EVs with well-defined homogeneous populations from complex biological samples is challenging. Different methods have been found to derive different EV populations carrying different biomolecules, which significantly confound biomarker discovery for developing clinical diagnostics. Building a rigorous EV isolation and standardizing assessment platform associated with -omics is essential to overcome this challenge. We introduced a novel isolation approach using a pH-responsive peptide conjugated with NanoPom magnetic beads (ExCy) for homogeneous EV isolation. Additionally, we introduced the first statistical algorithm for EV quality assessment (ExoQuality Index, EQI), which enables multi-assay quantification to provide a consistent and accurate definition of EV purity and quality; ExoQuality’s algorithm intakes multi-assay information to deconvolute complex EV heterogeneity. We analyzed our next generation sequencing on EV RNAs from pancreatic cancer patient plasma using four isolation methods; results highlighting ExCy’s isolation and EQI assessment improved biomarker identification. We identified a novel EV tumor biomarker, ATP6V0B, validated with Quantitative PCR (qPCR) by screening a pilot cohort of 23 individuals. With random forest modeling the ATP6V0B cycling threshold, we reported an AUC of 0.91, showcasing an enabling and clinically translatable liquid biopsy approach using circulating EVs.
Project description:The Oxford Nanopore technology has a great potential for the analysis of genome methylation, including full-genome methylome profiling. However, there are certain issues while identifying methylation motif sequences caused by low sensitivity of the currently available motif enrichment algorithms. Here, we present Snapper, a new highly-sensitive approach to extract methylation motif sequences based on a greedy motif selection algorithm. Snapper has shown higher enrichment sensitivity compared with the MEME tool coupled with Tombo or Nanodisco instruments, which was demonstrated on H. pylori strain J99 studied earlier using the PacBio technology. In addition, we used Snapper to characterize the total methylome of a new H.pylori strain A45. The analysis revealed the presence of at least 4 methylation sites that have not been described for H. pylori earlier. We experimentally confirmed a new CCAG-specific methyltransferase and indirectly inferred a new CCAAK-specific methyltransferase.
Project description:We used the nanopore Cas9 targeted sequencing (nCATS) strategy to specifically sequence 125 L1HS-containing loci in parallel and measure their DNA methylation levels using nanopore long-read sequencing. Each targeted locus is sequenced at high coverage (~45X) with unambiguously mapped reads spanning the entire L1 element, as well as its flanking sequences over several kilobases. The genome-wide profile of L1 methylation was also assessed by bs-ATLAS-seq in the same cell lines (E-MTAB-10895).