Biology subjects

Foster, C. S. P.

Publications and source records attributed to Foster, C. S. P..

8 recordsLinked to original sources

bioRxiv2026

vartracker: an end-to-end tool for pathogen longitudinal variant analysis and visualisation

Longitudinal sequencing can reveal fine-grained pathogen evolution during acute and chronic infections and inform public health responses. However, integrating ordered pathogen genomic data into a coherent evolutionary and clinical framework can be tedious and error-prone. We present vartracker, an open-source tool for longitudinal pathogen variant analysis and visualisation. Given an ordered sample manifest, vartracker supports three entry points: raw sequence reads, reference-aligned BAM files, or user-supplied VCF and coverage inputs. Raw-read and BAM inputs are processed through an integrated Snakemake workflow, whereas VCF mode starts from precomputed files. Variants are normalised and annotated relative to a reference genome, tracked across timepoints, and classified as original or newly emerging and as transient or persistent. Inferred amino acid changes are reported, and for SARS-CoV-2 analyses, relevant published literature for key mutations can be automatically linked through a functional database. vartracker outputs a schema-documented results table, provenance metadata for reproducibility, publication-quality static figures, and an interactive heatmap for data exploration. Although packaged with SARS-CoV-2 reference assets and initially developed for SARS-CoV-2 datasets, vartracker is pathogen-agnostic when appropriate reference data are supplied. We demonstrate its utility using SARS-CoV-2 and respiratory syncytial virus A (RSV-A) datasets. vartracker is freely available through GitHub, PyPI and Bioconda.

bioinformatics↗

bioRxiv2026

Antiviral efficacy versus host recovery: contrasting transcriptional footprints of four antivirals in human cytomegalovirus-infected brain organoids

Infection with human cytomegalovirus (HCMV) is common and usually asymptomatic in healthy individuals, but can cause severe neurological injury, particularly following congenital transmission. For symptomatic congenital infection, standard antiviral treatment is ganciclovir, with maribavir and letermovir as alternative direct-acting agents. However, their relative antiviral activity in reducing HCMV RNA abundance and restoring the host transcriptome towards an uninfected state has not been directly assessed in a neural model. We infected human cerebral organoids with Merlin-strain HCMV and treated them for 14 days with aciclovir, ganciclovir, letermovir, or maribavir, comparing each with untreated infected organoids (NO). Relative to NO, antiviral treatment reduced viral load 3.3-fold with aciclovir, 20.1-fold with ganciclovir, 65.4-fold with letermovir, and 6.9-fold with maribavir. We identified >2,500 differentially expressed host genes in infected versus uninfected organoids, with enrichment of neurodevelopmental and metabolic stress pathways. Aciclovir, ganciclovir, and maribavir produced few differentially expressed host genes relative to NO and no significant GO or KEGG enrichment. In contrast, letermovir altered 312 genes enriched for glycolysis and related metabolic processes. An MSigDB Hallmark pathway analysis showed minimal perturbation with aciclovir and letermovir, whereas ganciclovir and maribavir produced small, coordinated pathway-level shifts. This was partly in the same direction as control uninfected organoids but also with additional perturbations not seen in controls. Collectively, antiviral choice influenced both the magnitude of reduction in HCMV RNA abundance and the gene expression profile of infected neural tissue. The results support further evaluation of ganciclovir and letermovir in therapy of neural damage resulting from HCMV infection.

microbiology↗

bioRxiv2023

Long-term serial passaging of SARS-CoV-2 reveals signatures of convergent evolution

Understanding viral evolutionary dynamics is crucial to pandemic responses, prediction of virus adaptation over time, and virus surveillance for public health strategies. Whole-genome sequencing (WGS) of SARS-CoV-2 has enabled fine-grained studies of virus evolution in the human population. Serial passaging in vitro offers a complementary controlled environment to investigate the emergence and persistence of genetic variants that may confer selective advantage. In this study, nine virus lineages, including four "variants of concern" and three former "variants under investigation", were sampled over [≥]33 serial passages (range 33-100) in Vero E6 cells. WGS was used to examine virus evolutionary dynamics and identify key mutations with implications for fitness and/or transmissibility. Viruses accumulated mutations regularly during serial passaging. Many low-frequency variants were lost but others became fixed, suggesting either in vitro benefits, or at least a lack of deleterious effect. Mutations arose convergently both across passage lines, and when compared with contemporaneous SARS-CoV-2 clinical sequences. These mutations included some hypothesised to drive lineage success through host immune evasion (e.g. S:A67V, S:H655Y). The appearance of these mutations in vitro suggested key mutations can arise convergently even in the absence of a multicellular host immune response through mechanisms other than immune-driven mutation. Such mutations may provide other benefits to the viruses in vitro, or arise stochastically. Our quantitative investigation into SARS-CoV-2 evolutionary dynamics spans the greatest number of serial passages to date, and will inform measures to reduce the effects of SARS-CoV-2 infection on the human population. ImportanceThe ongoing evolution of SARS-CoV-2 remains a challenge for long term public health efforts to minimise the effects of COVID-19. Whole-genome sequencing of outbreak cases has enabled global contact tracing efforts and the identification of mutations of concern within the virus genome. However, complementary approaches are necessary to inform our understanding of virus evolution and clinical outcomes. Here we charted evolution of the virus within a controlled cell culture environment, focusing on nine different virus lineages. Our approach demonstrates how SARS-CoV-2 continues to evolve readily in vitro, with changes mirroring those seen in outbreak cases globally. Findings of the study are important for i) investigating the mechanisms of how mutations arise, ii) predicting the future evolutionary trajectory of SARS-CoV-2, and iii) informing treatment and prevention design.

evolutionary biology↗

bioRxiv2023

Shrinking in the dark: Parallel endosymbiont genome erosions are associated with repeated host transitions to an underground life

Microbial symbioses have had profound impacts on the evolution of animals. Conversely, changes in host biology may impact the evolutionary trajectory of symbionts themselves. Blattabacterium cuenoti is present in almost all cockroach species and enables hosts to subsist on a nutrient-poor diet. To investigate if host biology has impacted Blattabacterium at the genomic level, we sequenced and analysed 25 genomes from Australian soil-burrowing cockroaches (Blaberidae: Panesthiinae) which have undergone at least seven independent subterranean transitions from above-ground, wood-feeding ancestors. We find at least three independent instances of genome erosion have occurred in Blattabacterium strains exclusive to Australian soil-burrowing cockroaches. Such shrinkages have involved the repeated inactivation of genes involved in amino acid biosynthesis and nitrogen recycling, the core role of Blattabacterium in the host-symbiont relationship. The most drastic of these erosions have occurred in hosts thought to have transitioned underground the earliest relative to other lineages. As Blattabacterium is unable to fulfil its core function in such host groups, our findings suggest soil-burrowing cockroaches must acquire these nutrients from novel sources. Our study represents one of the first cases, to our knowledge, of parallel host adaptations leading to concomitant parallelism in their mutualistic symbionts, further underscoring the intimate relationship between these two partners.

genomics↗

bioRxiv2023

Bioinformatic investigation of discordant sequence data for SARS-CoV-2: insights for robust genomic analysis during pandemic surveillance

The COVID-19 pandemic has necessitated the rapid development and implementation of whole genome sequencing (WGS) and bioinformatic methods for managing the pandemic. However, variability in methods and capabilities between laboratories has posed challenges in ensuring data accuracy. A national working group comprising 18 laboratory scientists and bioinformaticians from Australia and New Zealand was formed to improve data concordance across public health laboratories (PHLs). One effort, presented in this study, sought to understand the impact of methodology on consensus genome concordance and interpretation. Data were retrospectively obtained from the 2021 Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP) SARS-CoV-2 WGS proficiency testing program (PTP), which included 11 participating Australian laboratories. The submitted consensus genomes and reads from eight contrived specimen were investigated, focusing on discordant sequence data, and findings were presented to the working group to inform best practices. Despite using a variety of laboratory and bioinformatic methods for SARS-CoV-2 WGS, participants largely produced concordant genomes. Two participants returned five discordant sites in a high Ct replicate which could be resolved with reasonable bioinformatic quality thresholds. We noted ten discrepancies in genome assessment that arose from nucleotide heterogeneity at three different sites in three cell-culture derived control specimen. While these sites were ultimately accurate after considering the participants bioinformatic parameters, it presented an interesting challenge for developing standards to account for intrahost single nucleotide variation (iSNV). Observed differences had little to no impact on key surveillance metrics, lineage assignment and phylogenetic clustering, while genome coverage <90% affected both. We recommend PHLs bioinformatically generate two consensus genomes with and without ambiguity thresholds for quality control and downstream analysis, respectively, and adhere to a minimum 90% genome coverage threshold for inclusion in surveillance interpretations. We also suggest additional PTP assessment criteria, including primer efficiency, detection of iSNVs, and minimum genome coverage of 90%. This study underscores the importance of multidisciplinary national working groups in informing guidelines in real time for bioinformatic quality acceptance criteria. It demonstrates the potential for enhancing public health responses through improved data concordance and quality control in SARS-CoV-2 genomic analysis during pandemic surveillance. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Impact statementAmidst the COVID-19 pandemic, a unique collaboration between a national multidisciplinary working group and a quality assurance program facilitated ongoing development of standardized quality control criteria and analysis methods for high-quality SARS-CoV-2 genomic approaches across Australia. With this article, we shed light on the robustness of amplicon sequencing and analysis methods to produce highly concordant genomes, while also presenting additional assessment criteria to guide laboratories in identifying areas for improvement. Insights from this nationwide collaboration underscore the need for real-time knowledge-sharing and iterative refinements to quality standards, particularly as situations and methods evolve during a pandemic. While the spotlight is on SARS-CoV-2, the analyses and findings have universal implications for genomic surveillance during infectious disease outbreaks. As WGS becomes increasingly central in outbreak surveillance, continuous evaluation and collaboration, like that described here, are vital to ensure data accuracy and inform future public health responses.

genomics↗

bioRxiv2021

Stressed out underground?: Transcriptomics illuminates the genome-wide response to heat stress in surface and subterranean diving beetles

Subterranean habitats are generally very stable environments, and as such evolutionary transitions of organisms from surface to subterranean lifestyles may cause considerable shifts in physiology, particularly with respect to thermal tolerance. In this study we compared responses to heat shock at the molecular level in a geographically widespread, surface-dwelling water beetle to a congeneric subterranean species restricted to a single aquifer (Dytiscidae: Hydroporinae). The obligate subterranean beetle Paroster macrosturtensis is known to have a lower thermal tolerance compared to surface lineages (CTmax 38{degrees}C cf. 42-46 {degrees}C), but the genetic basis of this physiological difference has not been characterized. We experimentally manipulated the thermal environment of 24 individuals to demonstrate that both species can mount a heat shock response at high temperatures (35{degrees}C), as determined by comparative transcriptomics. However, genes involved in these responses differ between species and a far greater number were differentially expressed in the surface taxon, suggesting it can mount a more robust heat shock response; these data may underpin its higher thermal tolerance compared to subterranean relatives. In contrast, the subterranean species examined not only differentially expressed fewer genes in response to increasing temperatures, but also in the presence of the experimental setup employed here alone. Our results suggest P. macrosturtensis may be comparatively poorly equipped to respond to both thermally induced stress and environmental disturbances more broadly. The molecular findings presented here have conservation implications for P. macrosturtensis and contribute to a growing narrative concerning weakened thermal tolerances in obligate subterranean organisms at the molecular level.

evolutionary biology↗

bioRxiv2018

Linking Branch Lengths Across Loci Provides the Best Fit for Phylogenetic Inference

Evolution leaves heterogeneous patterns of nucleotide variation across the genome, with different loci subject to varying degrees of mutation, selection, and drift. Appropriately modelling this heterogeneity is important for reliable phylogenetic inference. One modelling approach in statistical phylogenetics is to apply independent models of molecular evolution to different groups of sites, where the groups are usually defined by locus, codon position, or combinations of the two. The potential impacts of partitioning data for the assignment of substitution models are well appreciated. Meanwhile, the treatment of branch lengths has received far less attention. In this study, we examined the effects of linking and unlinking branch-length parameters across loci. By analysing a range of empirical data sets, we find that the best-fitting model for phylogenetic inference is consistently one in which branch lengths are proportionally linked: gene trees have the same pattern of branch-length variation, but with varying absolute tree lengths. This model provided a substantially better fit than those that either assumed identical branch lengths across gene trees or that allowed each gene tree to have its own distinct set of branch lengths. Using simulations, we show that the fit of the three different models of branch lengths varies with the length of the sequence alignment and with the number of taxa in the data set. Our findings suggest that a model with proportionally linked branch lengths across loci is likely to provide the best fit under the conditions that are most commonly seen in practice. In future work, improvements in fit might be afforded by models with levels of complexity intermediate to proportional and free branch lengths. The results of our study have implications for model selection, computational efficiency, and experimental design in phylogenomics.

evolutionary biology↗

bioRxiv2017

Strategies For Partitioning Clock Models In Phylogenomic Dating: Application To The Angiosperm Evolutionary Timescale

Evolutionary timescales can be inferred from molecular sequence data using a Bayesian phylogenetic approach. In these methods, the molecular clock is often calibrated using fossil data. The uncertainty in these fossil calibrations is important because it determines the limiting posterior distribution for divergence-time estimates as the sequence length tends to infinity. Here we investigate how the accuracy and precision of Bayesian divergence-time estimates improve with the increased clock-partitioning of genome-scale data into clock-subsets. We focus on a data set comprising plastome-scale sequences of 52 angiosperm taxa. There was little difference among the Bayesian date estimates whether we chose clock-subsets based on patterns of among-lineage rate heterogeneity or relative rates across genes, or by random assignment. Increasing the degree of clock-partitioning usually led to an improvement in the precision of divergence-time estimates, but this increase was asymptotic to a limit presumably imposed by fossil calibrations. Our clock-partitioning approaches yielded highly precise age estimates for several key nodes in the angiosperm phylogeny. For example, when partitioning the data into 20 clock-subsets based on patterns of among-lineage rate heterogeneity, we inferred crown angiosperms to have arisen 198-178 Ma. This demonstrates that judicious clock-partitioning can improve the precision of molecular dating based on phylogenomic data, but the meaning of this increased precision should be considered critically.

evolutionary biology↗