Biology subjects

Harker, C. M.

Publications and source records attributed to Harker, C. M..

4 recordsLinked to original sources

bioRxiv2026

Application of metagenomic sequencing to improve sessile serrated lesion detection using the faecal immunochemical test

Most population colorectal cancer (CRC) screening programs use the faecal immunochemical test (FIT), which quantifies occult haemoglobin in faeces and has proven to be effective in detecting and reducing CRC incidence and mortality. Sessile serrated lesions (SSLs) account for up to 30% of sporadic CRC, yet FIT has low sensitivity to detect them. Faecal microbial biomarkers may improve their detection, but FIT samples have not previously been used to study the SSL microbiome. We asked whether FIT samples preserve the faecal microbiome as accurately as fresh collection, and whether they can reveal a microbial signature of SSL. We first reanalysed a published dataset of paired FIT and fresh faecal samples from the same participants. Donor identity explained 63.5% of compositional variance compared with 16.7% for collection method, indicating that FIT preserves the donor-specific signature on which biomarker discovery depends. We then generated shotgun metagenomes from FIT samples of 24 adults scheduled for diagnostic colonoscopy, twelve with at least one clinically significant SSL and twelve with no neoplasia (NN) and compared each group with a published fresh faeces cohort matched on colonoscopy outcome. Collection method explained 6.3% to 7.6% of variance, and no individual species was significantly differentially abundant between methods. Between SSL and NN FIT samples, community structure did not significantly differ, and conservative differential abundance analysis returned no results. More permissive count-based models suggested a depletion of fermentative commensals in SSL. Functionally, SSL samples encoded significantly fewer KEGG orthologs and less polyamine biosynthesis capacity, while orthologs carried by several Bifidobacterium species were more abundant. Many depleted functions reflected Enterobacteriaceae gene content concentrated in a few control samples. No single feature was diagnostic on its own. A multi-feature signature, confirmed in larger cohorts and applied to samples that screening programs already collect, may increase the detection rate of SSLs.

bioinformatics↗

bioRxiv2026

Host species background, defence systems, and phage tail gene architecture shape phage infectivity in cystic fibrosis-associated Achromobacter

Achromobacter species are emerging multidrug-resistant (MDR) pathogens in people with cystic fibrosis. Their increasing resistance has grown an interest in phage therapy as an alternative treatment strategy. However, the factors governing phage susceptibility remain poorly understood, thereby limiting the rational selection of phage candidates. Using 15 strictly lytic Achromobacter phages and 7 clinical cystic fibrosis isolates representing Achromobacter insolitus and Achromobacter xylosoxidans, we demonstrate substantial variation in infection efficiency across all 105 phage-host combinations, variation that could not be discerned from qualitative plaque assays alone. We integrated complete bacterial and phage genomes with quantitative efficiency-of-plating (EOP) assays and lineage-aware Bayesian mixed-effects modelling to show that phage infectivity in Achromobacter is governed predominantly by bacterial lineage and strain identity, accounting for 90% of total variance in log-normalised EOP, with individual strains varying substantially in permissiveness irrespective of species membership. After accounting for this lineage structure, no individual defence system, antimicrobial resistance gene class, or phage tail cluster retained a statistically significant independent or interaction association with infectivity. Together, these findings demonstrate that bacterial strain identity is the primary driver of infection outcome. Host defence systems and phage tail-associated genes remain biologically plausible contributors; their independent effect could not be resolved after accounting for lineage structure, indicating that infection outcomes are largely strain-dependent. This work shifts the question from which individual traits predict infection to how strain lineage and specific host-phage combinations jointly determine infectivity, and argues that quantitative phenotyping of individual phage-host pairs is essential for guiding phage candidate selection and supporting rational cocktail design against multidrug-resistant Achromobacter infections in cystic fibrosis. Impact statementChronic Achromobacter infections in cystic fibrosis are increasingly difficult to treat due to multidrug resistance and biofilm formation. Although phage therapy is a promising alternative, its development is limited by poorly understood and highly variable infectivity. Here, we show that infectivity within a phage host range spans a broad quantitative continuum spanning several orders of magnitude that cannot be captured by qualitative plaque assays. These infection efficiencies are primarily structured by bacterial lineage and strain identity, while the contributions of individual genomic features remain unresolved, given the current sample size. This work provides a framework for predicting phage-host compatibility and supports a shift from empirical screening toward rational, evidence-based phage selection for MDR Achromobacter infections.

molecular biology↗

bioRxiv2026

OpusTaxa: A Unified Workflow for Taxonomic Profiling, Assembly, and Functional Analysis of Shotgun Metagenomes

Shotgun metagenomics has become a cornerstone of microbiome research, yet the complexity of existing workflows remains a major barrier for life scientists without dedicated bioinformatics support. Manual database setup, detailed sample sheet preparation, and management of software dependencies can make routine analysis difficult and time-consuming. Cross-study comparisons are further hampered by inconsistent processing pipelines, database versions, and profiling strategies, limiting reproducibility and the potential for large-scale meta-analyses. We present OpusTaxa, an open-source Snakemake workflow that provides end-to-end processing of short paired-end shotgun metagenomic data with minimal configuration. Users provide either FASTQ files or Sequence Read Archive accessions; OpusTaxa automatically downloads required databases, performs quality control, removes host reads, and executes taxonomic profiling, metagenome assembly, and functional analysis. All analysis modules can be independently toggled, and per-sample outputs are automatically merged into harmonised, cross-sample tables ready for downstream exploration. Across two public datasets, we demonstrate how OpusTaxa can be used to compare consistency across complementary taxonomic profilers and to estimate microbial load in addition to standard metagenomic workflows. AvailabilityOpusTaxa is freely available at https://github.com/yenkaiC/OpusTaxa. Documentation, test data, and example configurations are included in the repository.

bioinformatics↗

bioRxiv2024

Sphae: An automated toolkit for predicting phage therapy candidates from sequencing data

MotivationPhage therapy is a viable alternative for treating bacterial infections amidst the escalating threat of antimicrobial resistance. However, the therapeutic success of phage therapy depends on selecting safe and effective phage candidates. While experimental methods focus on isolating phages and determining their lifecycle and host range, comprehensive genomic screening is critical to identify markers that indicate potential risks, such as toxins, antimicrobial resistance, or temperate lifecycle traits. These analyses are often labor-intensive and time-consuming, limiting the rapid deployment of phage in clinical settings. ResultsWe developed Sphae, an automated bioinformatics pipeline designed to streamline therapeutic potential of a phage in under ten minutes. Using Snakemake workflow manager, Sphae integrates tools for quality control, assembly, genome assessment, and annotation tailored specifically for phage biology. Sphae automates the detection of key genomic markers, including virulence factors, antimicrobial resistance genes, and lysogeny indicators like integrase, recombinase, and transposase, which could preclude therapeutic use. Benchmarked on 65 phage sequences, 28 phage samples showed therapeutic potential, 8 failed during assembly due to low sequencing depth, 22 samples included prophage or virulent markers, and the remaining 23 samples included multiple phage genomes per sample. This workflow outputs a comprehensive report, enabling rapid assessment of phage safety and suitability for phage therapy under these criteria. Sphae is scalable, portable, facilitating efficient deployment across most high-performance computing (HPC) and cloud platforms, expediting the genomic evaluation process. AvailabilitySphae is source code and freely available at https://github.com/linsalrob/sphae, with installation supported on Conda, PyPi, Docker containers.

bioinformatics↗