Biology subjects

Daneshpajouh, H.

Publications and source records attributed to Daneshpajouh, H..

4 recordsLinked to original sources

bioRxiv2026

ONETest PathoGenome: A Multi-Cohort Evaluation of an Optimized NGS Assay for Detection of Lower Respiratory Pathogens in Bronchoalveolar Lavage

BackgroundLower respiratory tract infections (LRTIs) remain diagnostically challenging when culture and molecular assays are negative or delayed. We evaluated ONETest Pathogenome (OT), an automated hybrid-capture metagenomic assay with core-genome enrichment probes, for direct pathogen detection in bronchoalveolar lavage (BAL). MethodsAnalytical performance (LoD, precision, continuity) was assessed using whole-cell spike-ins into culture-negative BAL fluid. Technical performance was assessed in 119 specimens profiled by OT and whole-metagenome shotgun sequencing (WmGS, cohort 1). Clinical accuracy was evaluated in 360 specimens (cohort 2) benchmarked against routine bacterial and acid-fast bacillus (AFB) culture. Laboratory-developed test (LDT) validation included 43 specimens (cohort 3) benchmarked to bacterial and AFB culture. ResultsOT uses 6.2 million probes covering core genomes across 50 microbial families (>250 respiratory pathogens). In BAL specimens, OT increased normalized on-target microbial abundance 26-fold versus that of WmGS while preserving within-sample microbial diversity. In cohort 2, OT achieved species-level sensitivity of 80% and specificity of 99% across culture-confirmed isolates and detected [≥]1 culture-confirmed organism in 100/115 culture-positive specimens (87%), while applying species-specific background baselines to mitigate overcalling. Additive yield was 21% (76/360), with 7.5% (27/360) of specimens having [≥]1 additional finding supported by orthogonal testing. In LDT validation, OT identified [≥]1 culture-confirmed organism in 34/40 culture-positive specimens (85%) with one OT-positive/culture-negative specimen. ConclusionsOT is an assay with a turnaround time <24 h complementary to culture that improves pathogen detection and expands microbiologic findings through additional detections and co-detections, including slow-growing organisms that may require prolonged incubation by conventional methods.

microbiology↗

bioRxiv2025

Pan-cell type continuous chromatin state annotation of all IHEC epigenomes

The International Human Epigenome Consortium has generated thousands of epigenomic datasets that mea-sure various biochemical activities in the genome, including transcription factor binding, histone modification, and DNA accessibility. Currently, the predominant methods for integrating these datasets to annotate regu-latory elements are segmentation and genome annotation (SAGA) algorithms. The majority of annotations by these methods are cell type-specific. However, as the number of profiled cell types has grown into the thousands, using thousands of cell type-specific chromatin state annotations proves undesirable for many applications. Here, we present a pan-cell type annotation that summarizes all IHEC epigenomes using the recently-developed method, epigenome-ssm.

genomics↗

bioRxiv2023

Integrative chromatin state annotation of 234 human ENCODE4 cell types using Segway reveals disease drivers

Towards the goal of identifying functional elements in the human genome, the fourth and final phase of the ENCODE consortium has newly profiled hundreds of human tissues using sequencing-based measurements of genomic activity such as ChIP-seq measures of transcription factor binding and histone modification. Chromatin state annotations created by segmentation and genome annotation (SAGA) methods such as Segway have emerged as the predominant integrative summary of such epigenomic data sets. Here, we present the ENCODE4 catalog of Segway annotations, a set of sample-specific genome-wide Segway chromatin state annotations for 234 ENCODE human biosamples inferred from 1,794 functional genomics experiments. We define an updated vocabulary of chromatin state terms that includes patterns of activity present only in a subset of samples or identified only with rarely-performed assays. We show that these ENCODE4 Segway annotations accurately capture both general and cell-type-specific regulatory patterns, and do so with substantially improved sensitivity relative to prior large-scale chromatin annotation sets. This catalog facilitates the downstream discovery of regulatory mechanisms which underlie diseases and traits identified by genome-wide association studies.

genomics↗

bioRxiv2021

Target Capture Sequencing of SARS-CoV-2 Genomes Using the ONETest Coronaviruses Plus

BackgroundGenomic sequencing is important to track and monitor genetic changes in SARS-CoV-2. We introduce a target capture next-generation sequencing methodology, the ONETest Coronaviruses Plus, to sequence SARS-CoV-2 genomes and select genes of other respiratory viruses simultaneously. MethodsWe applied the ONETest on 70 respiratory samples (collected in Florida, USA between May and July, 2020), in which SARS-CoV-2 had been detected by a qualitative PCR assay. For 48 (69%) of the samples, we also applied the ARTIC protocol for Illumina sequencing. All the libraries were sequenced as 2x150 nucleotide reads on an Illumina instrument. The ONETest data were analyzed using an in-house pipeline and the ARTIC data using a published pipeline to produce consensus SARS-CoV-2 genome sequences, to which lineages were assigned using pangolin. ResultsOf the 70 ONETest libraries, 45 (64%) had a complete or near-complete SARS-CoV-2 genome sequence (> 29,000 bases and with > 90% of its bases covered by at least 10 reads). Of the 48 ARTIC libraries, 25 (52%) had a complete or near-complete SARS-CoV-2 genome sequence. In 24 out of 34 (71%) samples in which both the ONETest and ARTIC sequences were complete or near-complete and in which lineage could be assigned to both the ONETest and ARTIC sequences, the SARS-CoV-2 lineage identified was the same. ConclusionsThe ONETest can be used to sequence the SARS-CoV-2 genomes in archived samples and thereby enable detection of circulating and emerging SARS-CoV-2 variants. Target capture approaches, such as the ONETest, are less prone to loss of sequence coverage probably due to amplicon dropouts encountered in amplicon approaches, such as ARTIC. With its added value of characterizing other major respiratory pathogens, although not assessed in this study, the ONETest can help to better understand the epidemiology of infectious respiratory disease in the post COVID-19 era.

genomics↗