Biology subjects

Murall, C. L.

Publications and source records attributed to Murall, C. L..

9 recordsLinked to original sources

bioRxiv2024

Resource landscape shapes the composition and stability of the human vaginal microbiota

The vaginal microbiota is associated with the health of women and newborns alike. Despite its comparatively simple composition relative to other human microbiota systems, the mechanisms underpinning the dynamics and stability of vaginal microbial communities remain elusive. A crucial, yet so far underexplored, aspect of vaginal microbiota ecology is the role played by nutritional resources. Glycogen and its derivatives, produced by vaginal epithelia, are accessible to all bacterial constituents of the microbiota. Concurrently, free sialic acid and fucose offer supplementary nutritional resources to bacterial strains capable of cleaving them from glycans, which are structurally integral to mucus. Notably, bacteria adept at sialic acid exploitation are often correlated with adverse clinical outcomes and are frequently implicated in bacterial vaginosis (BV). In this study, we introduce a novel mathematical model tailored to human vaginal microbiota dynamics to explore the interactions between bacteria and their respective nutritional landscape. Our resource-based model examines the impact of the relative availability of glycogen derivatives (accessible to all bacterial species) and sialic acid (exclusive to some BV-associated bacteria) on the composition of the vaginal microbiota. Our findings elucidate that the success of BV-associated bacteria is intricately linked to their exclusive access to specific nutritional resources. This private access fortifies communities dominated by BV-associated bacteria, rendering them resilient to compositional transitions. We empirically corroborate our model prediction with longitudinal clinical data on microbiota composition and previously unpublished metabolomic profiles obtained from a North American cohort. The insights gleaned from this study shed light on potential pathways for BV prevention and treatment. Significance statementThe vaginal microbiota has a notable impact on womens health at various stages of life, namely puberty, infection protection, sexual health, fertility, pregnancy, and menopausal changes. At present, most non-anti-microbial products developed to mitigate adverse vaginal symptoms emphasise competitive interactions through acids (boric or lactic acid) or probiotics as a means to "rebalance" microbiota communities. Despite recent advances in profiling the composition of vaginal microbiota communities, there remains a major gap in our mechanistic understanding of how to maintain or reinstate a resilient Lactobacillus-dominated microbiota that improves vaginal health and outcomes. This study explores the role of nutritional resources in the vaginal microbiota by introducing a mathematical model that analyses how access to specific nutrients like glycogen derivatives and sialic acid affects the balance of bacterial vaginosis (BV) and non-BV-associated bacteria. Our findings, supported by original cohort-derived microbiological and metabolomics data, demonstrate that exclusive access to these nutrients is linked to the dominance and resilience of BV-associated bacteria, providing new insights for BV prevention and treatment.

microbiology↗

bioRxiv2023

Towards Pandemic-Scale Ancestral Recombination Graphs of SARS-CoV-2

Millions of SARS-CoV-2 genome sequences were collected during the COVID-19 pandemic, forming a dataset of unprecedented richness. Estimated genealogies are fundamental to understanding this ocean of data and form the primary input to many downstream analyses. A basic assumption of methods to infer genealogies from viral genetic data is that recombination is negligible and the genealogy is a tree. However, recombinant lineages have risen to global prevalence, and simple tree representations are therefore incomplete and potentially misleading. We present sc2ts, a method to infer reticulate genealogies as an Ancestral Recombination Graph (ARG) in real time at pandemic scale. We infer an ARG for 2.48 million SARS-CoV-2 genomes, which leverages the widely used tskit software ecosystem to support further analyses and visualisation. This rich and validated resource clarifies the relationships among recombinant lineages, quantifies the rate of recombination over time, and provides a lower bound on detectable recombination.

evolutionary biology↗

bioRxiv2022

Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including selection of adaptive mutations and emergence of new variant lineages. Here we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, [~][2/3] were plausibly introduced into these animal species from local human populations, while the remaining [~][1/3] were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health. ImportanceSARS-CoV-2, the causative agent of COVID-19, can infect many animal species, making eradication difficult because it can be reseeded from different reservoirs. When viruses replicate in different species, they may be faced with different evolutionary pressures and acquire new mutations, with unknown consequences for transmission and virulence in humans. Here we analyzed SARS-CoV-2 genome sequences from cats, dogs, deer, and mink to estimate transmission between each of these species and humans. We found several transmission events from humans to each animal, but relatively few detectable transmissions from animals back to humans, with the exception of mink. We also identified three mutations more likely to be found in mink than humans, and 26 in deer. These mutations could help the virus adapt to life in these different species. Ongoing surveillance of SARS-CoV-2 from animals will be important to understand their potential impacts on both human and animal health.

genomics↗

bioRxiv2021

Data-driven approaches for genetic characterization of SARS-CoV-2 lineages

The genome of the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), has been sequenced at an unprecedented scale, leading to a tremendous amount of viral genome sequencing data. To understand the evolution of this virus in humans, and to assist in tracing infection pathways and designing preventive strategies, we present a set of computational tools that span phylogenomics, population genetics and machine learning approaches. To illustrate the utility of this toolbox, we detail an in depth analysis of the genetic diversity of SARS-CoV-2 in first year of the COVID-19 pandemic, using 329,854 high-quality consensus sequences published in the GISAID database during the pre-vaccination phase. We demonstrate that, compared to standard phylogenetic approaches, haplotype networks can be computed efficiently on much larger datasets, enabling real-time analyses. Furthermore, time series change of Tajimas D provides a powerful metric of population expansion. Unsupervised learning techniques further highlight key steps in variant detection and facilitate the study of the role of this genomic variation in the context of SARS-CoV-2 infection, with Multiscale PHATE methodology identifying fine-scale structure in the SARS-CoV-2 genetic data that underlies the emergence of key lineages. The computational framework presented here is useful for real-time genomic surveillance of SARS-CoV-2 and could be applied to any pathogen that threatens the health of worldwide populations of humans and other organisms.

bioinformatics↗

bioRxiv2019

Modelling the evolution of viral oncogenesis

Most human oncogenic viruses share several characteristics, such as being DNA viruses, having long (co)evolutionary histories with their hosts and causing either latent or chronic infections. They can reach high prevalences while causing relatively low case mortality, which makes them quite fit according to virulence evolution theory. After analysing the life-histories of DNA oncoviruses, we use a mathematical modelling approach to investigate how the virus life cycle may generate selective pressures favouring or acting against oncogenesis at the within-host or at the between-host level. In particular, we focus on two oncoprotein activities, namely extending cell life expectancy and increasing cell proliferation rate. These have immediate benefits (increasing viral population size) but can be associated with fitness costs at the epidemiological level (increasing recovery rate or risk of cancer) thus creating evolutionary trade-offs. We interpret the results of our nested model in the light of the biological features and identify future perspectives for modelling oncovirus dynamics and evolution.

evolutionary biology↗

bioRxiv2018

Modelling coinfections to detect within-host interactions from genotype combination prevalences

Parasite genetic diversity can provide information on disease transmission dynamics but most methods ignore the exact combinations of genotypes in infections. We introduce and validate a new method that combines explicit epidemiological modelling of coinfections and regression Approximate Bayesian Computing (ABC) to detect within-host interactions. Using genital infections by different types of Human Papillomaviruses (HPVs) as a test case, we show that, if sufficiently strong, within-host parasite interactions can be detected from epidemiological data and that this detection is robust even in the face of host heterogeneity in behaviour. These results suggest that the combination of mathematical modelling and sophisticated inference techniques is promising to extract additional epidemiological information from existing datasets.

epidemiology↗

bioRxiv2017

Epithelial stratification shapes infection dynamics

Infections of stratified epithelia collectively represent a large burden on global health. Experimental models provide a means to understand how the cell dynamics themselves influence the outcomes of these infections. Mathematical approaches are needed to improve quantification and theoretical advancement of these complex systems. Here, we develop a general ecology-inspired model for stratified epithelial dynamics, which allows us to simulate infections and to estimate parameters that are difficult to measure with organotypic cell cultures. To explore how epithelial cell dynamics affect infection dynamics, we focus on two contrasting pathogens of the cervicovaginal epithelium: Chlamydia trachomatis and Human papillomaviruses. We find that key infection symptoms stem from differential interactions with the layers, while clearance and pathogen burden are bottom-up processes. Cell protective responses to infections (e.g. increased cell proliferation) generally lowered pathogen load but there were specific effects based on infection strategies. These generic responses by the epithelium, then, will have varying results depending on the pathogens infection strategy. Our modeling approach opens new perspectives for 3D tissue culture experimental systems of infections and, more generally, for developing and testing hypotheses related to infections of stratified epithelia.

systems biology↗

bioRxiv2017

Macroecology suggests cancer-causing papillomaviruses form non-neutral communities

Chronic infection by oncogenic Human papillomaviruses (HPVs) leads to cancers. Public health interventions, such as cancer screening and mass vaccination, radically change the ecological conditions encountered by circulating viruses. It is currently unclear how HPVs communities may respond to these environmental changes, because little is known about their ecology. Predicting the impact on viral diversity by the introduction of HPV vaccines requires answering the unresolved question of how HPVs interact. Although it is commonly believed that they do not interact (neutral theory), there are suggestions that HPV types may compete for resources or via the immune response (niche-based or non-neutral theory). Here, we applied for the first time established biodiversity measures and methods to epidemiological data in order to assess whether niche-partitioning or neutral processes are shaping HPV diversity patterns at the population level. We find that as infections progress toward cancer, HPVs communities become more uneven and a few HPVs play a stronger dominance role. By fitting species abundance distributions, we found that neutral models were always out-performed by non-neutral distributions, both in asymptomatic infections and in cancers. Our results suggest that temporally moving from a more even to a less even community implies an increase in competition, probably due to environmental changes linked to infection progression. More ecological thinking will be required to understand present-day interactions and to anticipate the future of the long lasting interactions between HPVs and humans.\n\nSIGNIFICANCE STATEMENTHuman papillomaviruses (HPVs) are very diverse. Infections by HPVs are very common and chronic infections may lead to cancers. The more oncogenic HPVs are now targetted by effective vaccines, and this has raised the question of whether there may be a viral replacement if these dominant types were removed. This is a medical version of a classical ecological controversy, namely how much biodiversity distributions and community dynamics are explained by neutral theory plays out across ecosystems. For HPVs, epidemiologic studies before and after the vaccination have led to the widespread belief that these viruses do not interact. Here, we apply different methods developed in macroecology to the best available epidemiologic data to address this issue. Consistently, we find that HPVs form non-neutral communities. Instead, competitive niche-partitioning process and dominance explain best HPVs communities. We also find that the vaccine might not change such competitive niche processes. Beyond clinical implications, this garners support that niche processes often best explain biodiversity patterns, even in human viral communities.

ecology↗

bioRxiv2017

The underestimated importance of acute infections by human papillomaviruses

Most infections by human papillomaviruses (HPVs) are acute, that is non-persistent. Yet, for HPVs, as for many other oncoviruses, there is a striking gap between our detailed understanding of chronic infections and our limited data on the early stages of infection. Here we argue that studying HPV acute infections is necessary and timely. Focusing on early interactions will help explain why certain infections are cleared while others become chronic or latent. From a molecular perspective, descriptions of immune effectors and pro-inflammatory pathways during the initial stages of infections have the potential to lead to novel treatments or to improved handling algorithms. From a dynamical perspective, adopting concepts from spatial ecology, such as meta-populations or meta-communities, can help explain why HPV acute infections sometimes last for years. Furthermore, cervical cancer screening and vaccines impose novel iatrogenic pressures on HPVs, implying that anticipating any viral evolutionary response remain essential. Finally, hints at the associations between HPV acute infections and fertility deserve further investigation given their high worldwide prevalence. Overall, understanding asymptomatic and benign infections may be instrumental in reducing HPV virulence.

epidemiology↗