Biology subjects

Farrell, S.

Publications and source records attributed to Farrell, S..

6 recordsLinked to original sources

bioRxiv2026

Oral Actinobacteria sense and defend against parasitic epibionts

Bacteria contend with a wide range of antagonistic interactions from neighboring microbes. One widespread but poorly understood threat is posed by Patescibacteria, which proliferate by colonizing host bacteria surfaces and extracting cellular resources. Despite the ubiquity of Patescibacteria in the environment, how hosts defend against these epibionts remains unknown. Here we show that Actinomycetota fend off Patescibacteria using the Esx secretion system. We identify a secreted effector protein that mediates this defensive behavior and demonstrate that Esx induction is part of a multifaceted, epibiont-specific response that includes multiple predicted cell surface modifications. Finally, we show that this response occurs at the transcriptional level and is mediated by a previously undescribed threat sensing pathway whose activation leads to threonine phosphorylation of an FHA domain-containing output protein. Together with bioinformatic evidence linking this threat sensing pathway to Esx across Actinomycetales, our experimental findings establish a functional role for the elusive and broadly distributed Esx pathway in defense against epibionts. Furthermore, they help resolve the ecological relationship between Patescibacteria and their hosts as one of antagonism, not mutualism.

microbiology↗

bioRxiv2023

Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity.

While animal models have provided key insights into conserved mechanisms of how the lung forms during development, human-specific developmental mechanisms are not always captured. To fully appreciate how developmental defects and disease states alter the function of the lungs, studies in human lung models are important. Here, we sequenced >150,000 single single-cells from 19 healthy human fetal lung tissues from gestational weeks 10-19 and identified at least 58 unique cell types/states contributing to the developing lung. We captured novel dynamic developmental trajectories from various progenitor cells that give rise to club, ciliated, and pulmonary neuroendocrine cells. We also identified four CFTR-expressing progenitor cell types and pinpointed the temporal emergence of these cell types. These developmental dynamics reveal broader epithelial cell plasticity and novel lineage hierarchies that were not previously reported. Combined with spatial transcriptomics, we identified both cell autonomous and non-cell autonomous signalling pathways that may dictate the temporal and spatial emergence of cell lineages. Finally, we showed that human pluripotent stem cell-derived fetal lung models capture cell lineage trajectories specifically through CFTR-expressing progenitor cells, that were also observed in the native fetal tissue. Overall, this study provides a comprehensive single-cell atlas of the developing human lung, outlining the temporal and spatial complexities of cell lineage development. HighlightsO_LISingle-cell transcriptomics atlas from 19 human fetal lungs reveals cellular heterogeneity and previously unappreciated cellular plasticity in the epithelial compartment. C_LIO_LIIdentification of novel CFTR-expressing progenitor cells that gives rise to club, ciliated and PNEC. C_LIO_LINovel RNA velocity facilitated the identification of dynamic lineage trajectories in the epithelial compartment. C_LIO_LITemporally regulated cell signaling through promiscuous interactions between sender and receiving cells may dictate cell lineage fates. C_LIO_LIIntegration of human pluripotent stem cell (hPSC)-derived fetal lung cells and organoids with primary lung dataset show hPSC-differentiations captures key developmental trajectories of fetal epithelial cell states. C_LI

developmental biology↗

bioRxiv2022

Inferring single-cell dynamics with structured dynamical representations of RNA velocity

Gene expression dynamics provide directional information for trajectory inference from single-cell RNA-sequencing data. Traditional approaches compute local RNA velocity using strict assumptions about the equations describing transcription and splicing of RNA. Not surprisingly, these approaches fail where these assumptions are violated, such as in multiple lineages with distinct gene dynamics or time-dependent kinetic rates of transcription and splicing. In this work we present "LatentVelo", a novel approach to compute a low-dimensional representation of gene dynamics with deep learning. Our approach embeds cells into a latent space with a variational auto-encoder, and describes differentiation dynamics on this latent space with neural ordinary differential equations. These more general dynamics enable accurate trajectory inference, and the latent space approach enables the generation of a latent "dynamics-based" embedding of cell states. To model multiple distinct lineages, LatentVelo infers a latent regulatory state that controls the dynamics of an individual cell. With these lineage-specific dynamics LatentVelo can predict latent trajectories, describing global inferred developmental path for individual cells, rather than just outputting local RNA velocity vectors. The dynamics-based embedding also enables concurrent batch correction of cell states and RNA velocity, outperforming comparable auto-encoder based batch correction methods that do not consider gene expression dynamics. Finally, the flexible structure of LatentVelo enables additional of new regulatory constraints required to integrate multiomic data. LatentVelo is available at https://github.com/Spencerfar/LatentVelo.

bioinformatics↗

bioRxiv2022

Measurements of damage and repair in aging mice and humans reveals that robustness and resilience decrease with age, operate over broad timescales, and are affected differently by interventions

As an organism ages, its health-state is determined by a balance between the processes of damage and repair. Measuring these processes requires longitudinal data. We extract damage and repair rates from repeated observations of health deficits in mice and humans to explore the contribution of robustness and resilience, which respectively decrease damage rates and increase repair rates, to aging health. We find a conserved decline with age in robustness and resilience in mice and humans, implying that both contribute to worsening health in aging. A decline in robustness, however, has a greater effect than a decline in resilience on accelerating damage accumulation with age, and a greater association with reduced survival. We also find that deficits are damaged and repaired over a wide range of timescales ranging from the shortest measurement scales towards organismal lifetime timescales. We explore the effect of systemic interventions that have been shown to improve health, including the angiotensin-converting enzyme inhibitor enalapril and voluntary exercise for mice, and household wealth for humans. We find that these interventions affect both damage and repair rates - but in different proportions for different interventions. These findings have implications for how health in aging, and interventions targeting health, are conceptualized and assessed.

systems biology↗

bioRxiv2021

SARS-CoV-2 neutralising antibodies in Dogs and Cats in the United Kingdom

Companion animals are susceptible to SARS-CoV-2 infection and sporadic cases of pet infections have occurred in the United Kingdom. Here we present the first large-scale serological survey of SARS-CoV-2 neutralising antibodies in dogs and cats in the UK. Results are reported for 688 sera (454 canine, 234 feline) collected by a large veterinary diagnostic laboratory for routine haematology during three time periods; pre-COVID-19 (January 2020), during the first wave of UK human infections (April-May 2020) and during the second wave of UK human infections (September 2020-February 2021). Both pre-COVID-19 sera and those from the first wave tested negative. However, in sera collected during the second wave, 1.4% (n=4) of dogs and 2.2% (n=2) cats tested positive for neutralising antibodies. The low numbers of animals testing positive suggests pet animals are unlikely to be a major reservoir for human infection in the UK. However, continued surveillance of in-contact susceptible animals should be performed as part of ongoing population health surveillance initiatives.

microbiology↗

bioRxiv2020

Generating individual aging trajectories with a network model using cross-sectional data

We develop a computational model of human aging that generates individual health trajectories with a set of observed health attributes. Our model consists of a network of interacting health attributes that stochastically damage with age to form health deficits, leading to eventual mortality. We train and test the model for two different cross-sectional observational aging studies that include simple binarized clinical indicators of health. In both studies, we find that cohorts of simulated individuals generated from the model resemble the observed cross-sectional data in both health characteristics and mortality. We can generate large numbers of synthetic individual aging trajectories with our weighted network model. Predicted average health trajectories and survival probabilities agree well with the observed data.

systems biology↗