Biology subjects

Andrews, T.

Publications and source records attributed to Andrews, T..

13 recordsLinked to original sources

bioRxiv2026

A Patient-Derived Ex Vivo Tissue Model of Cholangiocarcinoma Using Precision-Cut Tissue Slices

Background & Aims: Cholangiocarcinoma (CCA) is an aggressive malignancy with poor five-year survival. Improving outcomes requires preclinical models that faithfully recapitulate the native tumour microenvironment. Precision-Cut Tissue Slices (PCTS) retain in-vivo architecture and represent a promising candidate. We aimed to establish a patient-derived PCTS model of CCA, characterise its response to ex-vivo culture, and assess its use as a platform for therapeutic testing. Methods: PCTS were generated from 25 patients undergoing curative-intent resection for presumed CCA (2022-2024) and cultured for up to 15 days. Viability and histological architecture were assessed serially. Quantitative proteomics (SWATH-DIA) was performed at Days 0, 3, 7 and 15. A subset were treated with staurosporine or clinically relevant chemotherapy (5'-deoxy-5-fluorouridine, gemcitabine {+/-} cisplatin). Results: PCTS viability was maintained to Day 15, with no significant reduction from baseline. PCTS retain tumour architecture, cytokeratin-19-positivity and resident CD3+/CD68+ immune cells during culture. Proteomic profiling quantified 4,578 proteins and identified a staged response, with differentially abundant proteins increasing from 8 (Day 3) to 127 (Day 7) and 180 (Day 15), stabilising thereafter. This comprised of an early loss of inflammatory and stromal proteins, sustained cellular stress responses and metabolic reprogramming. CCA subtype-specific proteomic signatures were preserved throughout culture. Staurosporine produced dose-dependent cytotoxicity whilst chemotherapy responses were variable. Conclusions: Patient-derived CCA PCTS maintain viability, tumour architecture and subtype identity for 15 days while undergoing a defined proteomic response to culture, and retain pharmacological responsiveness,

cancer biology↗

bioRxiv2026

HLiCA: An integrated cell atlas of the healthy human liver

The human liver is composed of a heterogeneous mix of cell types. How these distinct populations contribute individually and collectively to liver function remains poorly understood. Although single-cell technologies have advanced our understanding of liver biology, individual studies have often been limited by small donor cohorts and inconsistent cell type annotations. Integrating multiple datasets can overcome these challenges and better capture biological variability. We present the Human Liver Cell Atlas (HLiCA), an integrated reference of non-disease liver cells assembled from eight datasets across six research centers, encompassing more than 525,000 cells from 110 donors. Developed in collaboration with the Human Cell Atlas Liver Bionetwork, the HLiCA incorporates expert-curated cell annotations refined through community feedback and dedicated cell type annotation meetings. The HLiCA classifies cells into six lineages and expands the cell type resolution to include 47 distinct cell types. Starting from raw sequencing reads, we realigned all data and performed rigorous benchmarking to ensure robust integration across technical and biological variables. Genetic ancestry was inferred for all samples to evaluate the range of ancestral backgrounds represented in the atlas. The expanded cell type annotation enabled identification of previously unrecognized liver cell types, including NRXN1+ stromal cells. Their presence was validated using spatial transcriptomics, which localized NRXN1+ stromal cells to periportal regions. With the number of donors included in the HLiCA we were able to examine cell type specific associations with demographic covariates. In hepatocytes, drug metabolism genes showed differential expression between sexes, and in cholangiocytes, mucus-production genes varied with age. As the largest and most genetically diverse human liver cell atlas to date, the HLiCA provides a comprehensive, well-annotated reference for the field, annotated by expert consensus. This resource will enable deeper interrogation of liver cellular diversity, architecture, and function in the healthy human liver and serve as a reference to understand changes that occur with disease.

genomics↗

bioRxiv2026

An Integrated Pipeline for Cell-Type Annotation, Metabolic Profiling, and Spatial Communication Analysis in the Liver using Spatial Transcriptomics

The liver acts as a central metabolic hub, integrating systemic signals through a spatially organized pattern known as zonation, driven by the coordinated activity of diverse cell types including hepatocytes, stellate cells, Kupffer cells, endothelial cells, and immune populations. Spatial transcriptomics (ST) enables the profiling of thousands of cells with spatial resolution in a single experiment, facilitating the identification of novel gene markers, cell types, cellular states, and tissue neighborhoods across diverse tissues and organisms. By simultaneously capturing transcriptional and spatial heterogeneity, ST has become a powerful tool for understanding cellular and tissue biology. Given its advantages, there is growing demand for applying ST to uncover novel biological insights in the liver under various physiological and pathological conditions including obesity, diabetes, and metabolic dysfunction-associated steatotic liver disease (MASLD). However, to date no comprehensive and practical protocols currently exist for analyzing ST data specifically in the context of liver metabolism. Herein, we present a systematic and detailed protocol for ST data analysis using liver tissues from MASLD mouse models. This guide offers practical support for metabolic based researchers without advanced expertise in coding, mathematics and statistics enabling single-cell RNA-seq referencing for deconvolution-based annotation, curated liver cell type markers for manual annotation, and a GMT file of metabolic gene sets and flux balance analysis to analyze liver metabolic activity. This framework and integrated computational resources for decoding metabolic reprogramming and cellular heterogeneity will empower researchers to uncover novel biological pathways regulating liver metabolism in health and disease.

bioinformatics↗

bioRxiv2025

The growth-promoting protein TMEM263 is an ER resident that controls early stages of lipid droplet biogenesis

Cell and organismal growth is controlled not only by the availability of nutrients, but also the ability to dynamically sense and respond to changes in metabolic demand. We have identified a protein, TMEM263 (also known as C12orf23) as a new mechanistic link between growth and lipid metabolism. TMEM263 was discovered in a screen as an ER-resident protein, and we have characterised its role as both necessary and sufficient for lipid droplet formation. TMEM263 has two transmembrane domains that fold into a hairpin structure which are essential for its localisation to the ER and to lipid droplets. Functionally, we propose that TMEM263 can interact with and support the condensation of neutral lipids in a bilayer to promote lipid droplet formation and growth. Consistently, loss of TMEM263 in cells and in zebrafish significantly impairs lipid droplet formation. Loss of TMEM263 protein function in vivo is associated with organismal growth defects and proportional dwarfism and our study provides a mechanistic understanding linking these phenotypes to impaired lipid droplet biology.

cell biology↗

bioRxiv2025

Narrowed host ranges do not constrain future host range expansion in RNA phage phi6

RNA viruses frequently shift between infecting different hosts and emerge on novel hosts. Part of this evolutionary process can involve specialization, when viruses adapt to increase their fitness on a particular host, often at the expense of their ability to infect other hosts. This trajectory has the potential to lead to extreme host narrowing which excludes all other previously accessible hosts. The consequences of the genetic architecture of host specialization on a viruss future evolutionary potential are understudied. In this study, we explored the ability of extreme specialists to re-expand their host ranges, particularly the ease and mutational mechanisms by which they might accomplish this such as reversion of host-range-narrowing mutations or mutations at other sites. Using previously evolved specialized strains of model dsRNA bacteriophage phi6 which had lost their ability to infect some hosts, we challenged specialists to adapt to their ancestral and other challenge hosts and identified resulting mutations. We found that these specialists readily re-gained their broader host ranges, at rates comparable to previously observed emergence events in phi6, indicating a lack of potential constraint from their mutational backgrounds due to epistasis. While some viral strains achieved host range re-expansion by reversing the original host-narrowing mutations gained during specialization, others used secondary mutations which were found to be parallel mutations previously associated with phi6 entry into those host species. This study contributes to our understanding of the evolutionary dynamics of host shifting in RNA viruses and their strategies to re-expand following specialization, which is relevant to spillback events and recurring host shifts that are observed in nature.

evolutionary biology↗

bioRxiv2024

Interpretable single-cell factor decomposition using sciRED

Single-cell RNA sequencing (scRNA-seq) maps gene expression heterogeneity within a tissue. However, identifying biological signals in this data is challenging due to confounding technical factors, sparsity, and high dimensionality. Data factorization methods address this by separating and identifying signals in the data, such as gene expression programs, but the resulting factors must be manually interpreted. We developed Single-Cell Interpretable REsidual Decomposition (sciRED) to improve the interpretation of scRNA-seq factor analysis. sciRED removes known confounding effects, uses rotations to improve factor interpretability, maps factors to known covariates, identifies unexplained factors that may capture hidden biological phenomena and determines the genes and biological processes represented by the resulting factors. We apply sciRED to multiple scRNA-seq datasets and identify sex-specific variation in a kidney map, discern strong and weak immune stimulation signals in a PBMC dataset, reduce ambient RNA contamination in a rat liver atlas to help identify strain variation, and reveal rare cell type signatures and anatomical zonation gene programs in a healthy human liver map. These demonstrate that sciRED is useful in characterizing diverse biological signals within scRNA-seq data.

bioinformatics↗

bioRxiv2023

4R-Tau seeding activity unravels molecular subtypes in patients with Progressive Supranuclear Palsy

Progressive Supranuclear palsy (PSP) is a 4-repeat (4-R) tauopathy. We hypothesized that the molecular diversity of tau could explain the heterogeneity seen in PSP disease progression. To test this hypothesis, we performed an extensive biochemical characterisation of the high molecular weight tau species (HMW-Tau) in 20 different brain regions of 25 PSP patients. We found a correlation between the HMW-Tau species and tau seeding capacity in the primary motor cortex, where we confirmed that an elevated 4R-Tau seeding activity correlates with a shorter disease duration. To identify factors that contribute to these differences, we performed proteomic and spatial transcriptomic analysis that revealed key mechanistic pathways, in particular those involving the immune system, that defined patients demonstrating high and low tau seeding capacity. These observations suggest that differences in the tau seeding activity may contribute to the considerable heterogeneity seen in disease progression of patients suffering from PSP.

neuroscience↗

bioRxiv2022

A Transducing Bacteriophage Infecting Staphylococcus epidermidis Contributes to the Expansion of aNovel Siphovirus Genus and Implies Genus is Inappropriate for Phage Therapy

The effort to discover novel phages infecting Staphylococcus epidermidis contributes to both the development of phage therapy and the expansion of genome-based phage phylogeny. Here, we report the genome of an S. epidermidis-infecting phage SEP1 and compare its genome with five other sequenced phages with high sequence identity. These phages represent a novel siphovirus genus, which was recently reported in the literature. The published member of this group was favorably evaluated as a phage therapeutic agent, but SEP1 is capable of transducing antibiotic resistance. Members of this genus may be maintained within their host as extrachromosomal plasmid prophages, through stable lysogeny or pseudolysogeny. Therefore, we conclude that SEP1 may be temperate and members of this novel genus are not suitable for phage therapy.

microbiology↗

bioRxiv2021

Interferon-stimulated and metallothionein-expressing macrophages are associated with acute and chronic allograft dysfunction after lung transplantation

Lung transplant (LT) recipients experience episodes of immune-mediated acute lung allograft dysfunction (ALAD). ALAD episodes are a risk factor for chronic lung allograft dysfunction (CLAD), the major cause of death after LT. We have applied single-cell RNA sequencing (scRNAseq) to bronchoalveolar lavage (BAL) cells from stable and ALAD patients and to cells from explanted CLAD lung tissue to determine key cellular elements in dysfunctional lung allografts, with a focus on macrophages. We identified two alveolar macrophage (AM) subsets uniquely represented in ALAD. Using pathway analysis and differentially expressed genes, we annotated these as pro-inflammatory interferon-stimulated gene (ISG) and metallothionein-mediated inflammatory (MT) AMs. Functional analysis of an independent set of AMs in vitro revealed that ALAD AMs exhibited a higher expression of CXCL10, a marker of ISG AMs, and increased secretion of pro-inflammatory cytokines compared to AMs from stable patients. Using publicly available BAL scRNAseq datasets, we found that ISG and MT AMs are associated with more severe inflammation in COVID-19 patients. Analysis of cells from four explanted CLAD lungs revealed similar macrophage populations. Using a single nucleotide variation calling algorithm, we also demonstrated contributions of donor and recipient cells to all AM subsets early post-transplant, with loss of donor-derived cells over time. Our data reveals extensive heterogeneity among lung macrophages after LT and indicates that specific sub-populations may be associated with allograft dysfunction, raising the possibility that these cells may represent important therapeutic targets.

immunology↗

bioRxiv2019

Single-cell atlas of the first intra-mammalian developmental stage of the human parasite Schistosoma mansoni

Over 250 million people suffer from schistosomiasis, a tropical disease caused by parasitic flatworms known as schistosomes. Humans become infected by free-swimming, water-borne larvae, which penetrate the skin. The earliest intra-mammalian stage, called the schistosomulum, undergoes a series of developmental transitions. These changes are critical for the parasite to adapt to its new environment as it navigates through host tissues to reach its niche, where it will grow to reproductive maturity. Unravelling the mechanisms that drive intra-mammalian development requires knowledge of the spatial organisation and transcriptional dynamics of different cell types that comprise the schistomulum body. To fill these important knowledge gaps, we performed single-cell RNA sequencing on two-day old schistosomula of Schistosoma mansoni. We identified likely gene expression profiles for muscle, nervous system, tegument, parenchymal/primordial gut cells, and stem cells. In addition, we validated cell markers for all these clusters by in situ hybridisation in schistosomula and adult parasites. Taken together, this study provides a comprehensive cell-type atlas for the early intra-mammalian stage of this devastating metazoan parasite.

genomics↗

bioRxiv2019

The Malaria Cell Atlas: a comprehensive reference of single parasite transcriptomes across the complete Plasmodium life cycle

Malaria parasites adopt a remarkable variety of morphological life stages as they transition through multiple mammalian host and mosquito vector environments. Here we profile the single-cell transcriptomes of thousands of individual parasites, deriving the first high-resolution transcriptional atlas of the entire Plasmodium berghei life cycle. We then use our atlas to precisely define developmental stages of single cells from three different human malaria parasite species, including parasites isolated directly from infected individuals. The Malaria Cell Atlas provides both a comprehensive view of gene usage in a complex eukaryotic parasite and an open access reference data set for the study of malaria parasites.

genomics↗

bioRxiv2018

Climate or disturbance: temperate forest structural change and carbon sink potential

Anticipating forest responses to changing climate and disturbance regimes requires understanding long-term successional processes and aggregating these local processes into global relevance. Estimates of existing forest structure and biomass are improving globally; however, vegetation models continue to show substantial spread in predictions of future land carbon uptake and the roles of forest structural change and demography are increasingly being recognized as important. To identify mechanisms that drive change in tree size, density, and carbon, we need a better understanding of forest structural trajectories and the factors that affect those trajectories. Here we reveal a coherent, cyclic pattern of structural change in temperate forests, as predicted by successional theory, and identify significant sensitivity to climatic precipitation and temperature anomalies using large datasets and empirical modeling. For example, in the eastern US above average temperature (+1{degrees}C) was associated with a 27% (-0.4{+/-}0.1 Mg C ha-1 yr-1) reduction in productivity attributed to higher rates of disease (+23%), weather disturbance (+57%), and sapling mortality. Projections of future vegetative carbon sink potential suggests biomass would be lowest on managed lands (72{+/-}2 Mg C ha-1) and highest when larger trees survive in undisturbed conditions (153{+/-}21 Mg C ha-1). Overall, the indirect effects of disturbance and mortality were considerably larger than the direct effects of climate on productivity when predicting future vegetative carbon sinks. Results provide robust comparisons for global vegetation models, and valuable projections for management and carbon mitigation efforts.

ecology↗

bioRxiv2018

Distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data

Droplet-based single-cell RNA sequencing protocols have dramatically increased the throughput and efficiency of single-cell transcriptomics studies. A key computational challenge when processing these data is to distinguish libraries for real cells from empty droplets. Existing methods for cell calling set a minimum threshold on the total unique molecular identifier (UMI) count for each library, which indiscriminately discards cell libraries with low UMI counts. Here, we describe a new statistical method for calling cells from droplet-based data, based on detecting significant deviations from the expression profile of the ambient solution. Using simulations, we demonstrate that our method has greater power than existing approaches for detecting cell libraries with low UMI counts, while controlling the false discovery rate among detected cells. We also apply our method to real data, where we show that the use of our method results in the retention of distinct cell types that would otherwise have been discarded.

bioinformatics↗