Biology subjects

Langhorst, B. W.

Publications and source records attributed to Langhorst, B. W..

7 recordsLinked to original sources

bioRxiv2023

The Omicron variant BQ.1* with mutations at positions 28,311 and 28,312 in the SARS-CoV-2 N gene have minimal impact on CDC N1 target detection

Ensuring COVID-19 testing remains accurate and reliable is of critical importance as the SARS-CoV-2 virus continues to evolve. Currently, a number of Omicron variants are dominating infection across the globe in including BQ.1 and XBB. Both variants and their sublineages (BQ.1* and XBB*) contain a 28,311 C/U mutation inherited from the original Omicron variant (BA.1). This mutation overlaps with a commonly used fluorescent probe for N gene detection in many Emergency Use Authorization (EUA) assays, as this target was originally established by the U.S. Centers for Disease Control and Prevention (CDC) in their EUA test for COVID-19 (2019-nCoV_N1). This C to U mutation was previously shown to have no impact on CDC N1 target detection. The rise of Omicron sublineages has increased the likelihood of additional point mutations occurring within the same assay target. A subpopulation of BQ.1* has an additional 28,312 C/U mutation within the CDC 2019_nCoV_N1 fluorescent probe in addition to the 28,311 C/U mutation. The double mutation could adversely affect the ability of diagnostic assays to detect the virus in patient samples and therefore it is important to verify the impacts of this additional mutation. Using in vitro transcribed (IVT) N gene RNA representing the wildtype (GenBank/GISAID ID MN908947.3) and Omicron BQ.1.1 variant (BQ.1, GISAID ID EPI_ISL_ 15155651), we evaluated the performance of two different amplification protocols, both of which include the CDC 2019-nCoV_N1 primer-probe set. Both assays successfully detected the mutant N gene sequence efficiently even at 10 copies of input, although the double mutation caused a 0.5[~]1 Cq delay on average when compared to the wild-type sequence. These data suggest that circulating BQ.1* lineage viruses with this double mutation likely have minimal impact on diagnostic assays that use the 2019-nCoV-N1 primer-probe.

biochemistry↗

bioRxiv2021

Correcting Methylation Calls in Clinically Relevant Low-Mappability Regions

DNA methylation is an important component in vital biological functions such as embryonic development, carcinogenesis, and heritable regulation. Accurate methods to assess genomic methylation status are crucial to its effective use in many scenarios, especially in the detection and diagnosis of disease. Methylation aligners, such as Bismark and bwa-meth, frequently assign significantly higher MapQ values than can be supported by the uniqueness of the region reads are mapped to. These incorrectly high MapQs result in inappropriate methylation calling in repetitive regions. We observe reads that should map to separate locations (possibly having different methylation states) actually end up mapping to the same locus, causing apparent mixed methylation at such loci. Methylation calling can be improved by using Bismap mappability data to filter out insufficiently unique reads. However, simply filtering out Cs in insufficiently unique regions is not adequate as it is prone to over-filtering Cs in small mappability dips. These Cs can in fact often be called using reads anchored in a nearby mappable region. We have created a new feature for the MethylDackel methylation caller to perform read-based filtering. This new methylation calling method resolves some of the apparent mixed methylation to either 0% or 100% methylation and removes many unsupportable methylation calls. We examined methylation calls with and without read-based filtering in or near the 7830 genes containing ClinVar variants in a methylation sequencing data set from the NA12878 cell line. Use of this improved method corrected 41,143 mixed methylation Cs to 0% methylation, and 22,345 to 100% methylation throughout the genome.

genomics↗

bioRxiv2020

The SEQC2 Epigenomics Quality Control (EpiQC) Study: Comprehensive Characterization of Epigenetic Methods, Reproducibility, and Quantification

Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and a global resource for epigenetics research from the FDAs Epigenomics Quality Control (EpiQC) Group. The study design leverages seven human cell lines that are designated as reference materials and publicly available from the National Institute of Standards and Technology (NIST) and Genome in a Bottle (GIAB) consortium. These samples were subject to a variety of genome-wide methylation interrogation approaches across six independent laboratories, with a primary focus was on 5-methylcytosine modifications. Each sample was processed in two or more technical replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), one enzymatic deamination method (EMseq), targeted methylation sequencing (Illumina Methyl Capture EPIC), and single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, BWAMeth, and GemBS), we found overall high concordance between assays (R=0.87-R0.93), differences in efficency of read mapping and CpG capture and coverage, and platform performance. The data provided herein can guide continued used of these reference materials in epigenomics assays, as well as provide best practices for epigenomics research and experimental design in future studies.

genomics↗

bioRxiv2020

Expanding the Galaxy's reference data

SummaryProperly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows to easily organize, retrieve, and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform. Server administrators are able to configure Galaxy to make use of reference datasets made available on a refgenie instance. Additionally, a Galaxy Data Manager tool has been developed to provide a graphical interface to refgenies remote reference retrieval functionality. A large collection of reference datasets has also been made available using the CVMFS repository from GalaxyProject.org, with mirrors across the United States, Canada, Europe, and Australia, enabling easy use outside of Galaxy. Availability and implementationThe ability of Galaxy to use refgenie assets was added to the core Galaxy framework in version 20.05, which is available from https://github.com/galaxyproject/galaxy under the Academic Free License version 3.0. The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license.

bioinformatics↗

bioRxiv2020

Host, Viral, and Environmental Transcriptome Profiles of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.

molecular biology↗

bioRxiv2019

EM-seq: Detection of DNA Methylation at Single Base Resolution from Picograms of DNA

Bisulfite sequencing is widely used to detect 5mC and 5hmC at single base resolution. However, bisulfite treatment damages DNA resulting in fragmentation, loss of DNA and biased sequencing data. To overcome this, we developed Enzymatic Methyl-seq (EM-seq), an enzymatic based approach that uses as little as 100 pg of DNA. EM-seq outperformed bisulfite converted libraries in all metrics examined including coverage, duplication, sensitivity and nucleotide composition. EM-seq libraries displayed even GC distribution, improved correlation across input amounts as well as increased representation of genomic features. These data indicate that EM-seq is more accurate and reliable than whole genome bisulfite sequencing (WGBS).

genomics↗

bioRxiv2018

Optimization of Golden Gate assembly through application of ligation sequence-dependent fidelity and bias profiling

Modern synthetic biology depends on the manufacture of large DNA constructs from libraries of genes, regulatory elements or other genetic parts. Type IIS restriction enzyme-dependent DNA assembly methods (e.g., Golden Gate) enable rapid one-pot, ordered, multi-fragment DNA assembly, facilitating the generation of high-complexity constructs. The order of assembly of genetic parts is determined by the ligation of flanking Watson-Crick base-paired overhangs. The ligation of mismatched overhangs leads to erroneous assembly, and the need to avoid such pairings has typically been accomplished by using small sets of empirically vetted junction pairs, limiting the number of parts that can be joined in a single reaction. Here, we report the use of a comprehensive method for profiling end-joining ligation fidelity and bias to predict highly accurate sets of connections for ligation-based DNA assembly methods. This data set allows quantification of sequence-dependent ligation efficiency and identification of mismatch-prone pairings. The ligation profile accurately predicted junction fidelity in ten-fragment Golden Gate assembly reactions, and enabled efficient assembly of a lac cassette from up to 24-fragments in a single reaction. Application of the ligation fidelity profile to inform choice of junctions thus enables highly flexible assembly design, with >20 fragments in a single reaction.

synthetic biology↗