Biology subjects

Trebes, A.

Publications and source records attributed to Trebes, A..

6 recordsLinked to original sources

bioRxiv2024

Castanet: a pipeline for rapid analysis of targeted multi-pathogen genomic data

MotivationTarget enrichment strategies generate genomic data from multiple pathogens in a single process, greatly improving sensitivity over metagenomic sequencing and enabling cost-effective, high throughput surveillance and clinical applications. However, uptake by research and clinical laboratories is constrained by an absence of computational tools that are specifically designed for the analysis of multi-pathogen enrichment sequence data. Here we present the Castanet pipeline: an analysis pipeline for end-to-end processing and consensus sequence generation for use with multi-pathogen enrichment sequencing data. Castanet is designed to work with short-read data produced by existing targeted enrichment strategies, but can be readily deployed on any BAM file generated by another methodology. It is packaged with usability features, including graphical interface and installer script. ResultsIn addition to genome reconstruction, Castanet reports method-specific metrics that enable quantification of capture efficiency, estimation of pathogen load, differentiation of low-level positives from contamination, and assessment of sequencing quality. Castanet can be used as a traditional end-to-end pipeline for consensus generation, but its strength lies in the ability to process a flexible, pre-defined set of pathogens of interest directly from multi-pathogen enrichment experiments. In our tests, Castanet consensus sequences were accurate reconstructions of reference sequences, including in instances where multiple strains of the same pathogen were present. Castanet performs effectively on standard laptop computers and can process the entire output of a 96-sample enrichment sequencing run (50M reads) using a single batch process command, in < 2 h. Availability and ImplementationSource code freely available under GPL-3 license at https://github.com/MultipathogenGenomics/castanet, implemented in Python 3.10 and supported in Ubuntu Linux 22.04 and other Bash-like environments. The data for this study have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI under accession number PRJEB77004.

bioinformatics↗

bioRxiv2023

Pan-genotypic probe-based enrichment to improve efficiency of Hepatitis B virus sequencing

Hepatitis B Virus (HBV) genome sequencing can be used to provide more complete genetic information at the population and individual level to shed light on the limitations of current interventions, and inform new strategies for elimination. HBV sequencing is challenging due to the partially dsDNA genome, high diversity, low viral loads and presence of large amounts of host genetic material in clinical samples. Here we describe the design and use of a pan-genotypic panel of 74 HBV specific capture-probes and nuclease treatment in improving sequencing efficiency. We processed 20 plasma samples (viral loads 1.98 to 4.07 log10, genotypes A-E) and three positive controls (human total brain RNA and bacteriophage lambda DNA) in triplicate to compare DNAse vs. RNAse vs. no nuclease treatment. We prepared libraries using the Takara Bio SMARTer Stranded Total RNA-Seq Kit v3, split the library in two, enriching half with the custom-designed probe panel and xGen Hybridization and Wash Kit (IDT), the other half was not enriched. Both libraries were sequenced on the NovaSeq6000 platform with 2x150nt paired-end reads. Capture resulted in a 47,970 fold increase in the number of reads mapped to the HBV genome in the "no nuclease" arm (243 HBV reads per million reads sequenced in the capture pool vs. 5x10-3 reads per million in the no-capture pool). Out of 20 samples, only 1 without capture generated HBV reads (viral load 3.89 log10 IU/ml) vs. 19 samples with capture. HBV sequence yield was increased in the capture arm and resulted in 2.30 log10 (95% confidence interval 1.99 - 2.48 log10) increase in HBV reads (per million reads sequenced) per log10 increase in viral load. The proportion of HBV reads increased a median of 12 fold with RNAse treatment. We developed a targeted pan-genotypic sequencing method using a custom panel of biotinylated oligos that increases the sequencing efficacy of HBV. This method will allow us to gain a better insight into HBV diversity.

genomics↗

bioRxiv2022

Viral burdens are associated with age and viral variant in a population-representative study of SARS-CoV-2 that accounts for time-since-infection related sampling bias.

In this study, we evaluated the impact of viral variant, in addition to other variables, on within-host viral burdens, by analysing cycle threshold (Ct) values derived from nose and throat swabs, collected as part of the UK COVID-19 Infection Survey. Because viral burden distributions determined from community survey data can be biased due to the impact of variant epidemiology on the time-since-infection of samples, we developed a method to explicitly adjust observed Ct value distributions to account for the expected bias. Analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior infection, the average Ct value was 0.94 lower among Alpha variant infections, compared those with the predecessor strain, B.1.177. However, among vaccinated individuals, it was 0.34 lower among Delta variant infections, compared to those with the Alpha variant. In addition, the average Ct value decreased by 0.20 for every 10 year age increment of the infected individual. In summary, within-host viral burdens are associated with age, in addition to the interplay of vaccination status and viral variant.

genetics↗

bioRxiv2020

SARS-CoV-2 genomics beyond the consensus sequence: evidence for circulating mixed viral populations

Extensive global sampling and whole genome sequencing of the pandemic virus SARS-CoV-2 have enabled researchers to characterise its spread, and to identify mutations that may increase transmission or enable the virus to escape therapies or vaccines. Two important components of viral spread are how frequently variants arise within individuals, and how likely they are to be transmitted. Here, we characterise the within-host diversity of SARS-CoV-2, and the extent to which genetic diversity is transmitted, by quantifying variant frequencies in 1390 clinical samples from the UK, many from individuals in known epidemiological clusters. We show that SARS-CoV-2 infections are characterised by low levels of within-host diversity across the entire viral genome, with evidence of strong evolutionary constraint in Spike, a key target of vaccines and antibody-based therapies. Although within-host variants can be observed in multiple individuals in the same phylogenetic or epidemiological cluster, highly infectious individuals with high viral load carry only a limited repertoire of viral diversity. Most viral variants are either lost, or occasionally fixed, at the point of transmission, consistent with a narrow transmission bottleneck. These results suggest potential vaccine-escape mutations are likely to be rare in infectious individuals. Nonetheless, we identified Spike variants present in multiple individuals that may affect receptor binding or neutralisation by antibodies. Since the fitness advantage of escape mutations in highly-vaccinated populations is likely to be substantial, resulting in rapid spread if and when they do emerge, these findings underline the need for continued vigilance and monitoring.

genomics↗

bioRxiv2019

Targeted metagenomic sequencing enhances the identification of pathogens associated with acute infection.

The routine identification of pathogens during infection remains challenging because it relies on multiple modalities such as culture and nucleic acid amplification and tests that tend to be specific for very few of an enormous number of possible infectious agents. Metagenomics promises single-test identification, but shotgun sequencing remains unwieldy and expensive or in many cases insufficiently sensitive to detect the amount of pathogen material in a clinical sample. Here we present the validation and application of Castanet, a method for metagenomic sequencing with enrichment that exploits clinical knowledge to construct a broad panel of relevant organisms for detection at low cost with sensitivity comparable to PCR. Castanet targets both DNA and RNA, works with small sample volumes, and can be implemented in a high-throughput diagnostic setting. We used Castanet to analyse plasma samples from 573 patients from the GAinS sepsis cohort and CSF samples from 243 patients from the ChiMES meningitis cohort that had been evaluated using standard clinical microbiology methods, identifying relevant pathogens in many cases where no pathogen had previously been detected. Castanet is intended for use in defining the distribution of pathogens in samples, diseases and populations, for large-scale clinical studies and for verifying the performance of routine testing regimens. By providing sequence as output, Castanet combines pathogen identification directly with subtyping and phylo-epidemiology.

microbiology↗

bioRxiv2018

Interferon lambda 4 impacts broadly on hepatitis C virus diversity.

Type III interferons (IFN-{lambda}) are part of the innate immune response to hepatitis C virus (HCV) infection however the specific role of IFN-{lambda}4 and the nature of the viral adaption to this pressure have not been defined. Here we use paired genome-wide human and viral genetic data in 485 patients infected with HCV genotype 3a to explore the role of IFN-{lambda}4 on HCV evolution during chronic infection. We show that genetic variations within the host IFNL4 locus have a broad and systematic impact on HCV amino acid diversity. We also demonstrate that this impact is larger in patients producing a more active form of IFN-{lambda}4 protein compared to the less active form. A similar observation was noted for viral load. We conclude that IFN-{lambda}4 protein is a likely causal agent driving widespread HCV amino acid changes and associated with viral load and possibly other clinical and biological outcomes of HCV infection.

genomics↗