Biology subjects

Hall, B. A.

Publications and source records attributed to Hall, B. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Dynamics of the B-Cell gene regulatory network in differentiation determine evolutionary trajectories of childhood leukaemogenesis

B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) is the most frequent paediatric malignancy. Despite extensive molecular and cellular characterization a mechanistic model of leukaemogenesis has not yet been developed. Here we present a multi-valued logical model of B-cell differentiation, centred on a core pentad of transcription factors whose dysregulation results in the developmental arrest characteristic of BCP-ALL. Whilst B-cell maturation follows a fixed and sequential differentiation process, leukaemic transformation is driven by stochastic genetic insults. Integrating BCR-ABL1 as the initiating event, we model alternative evolutionary trajectories by introducing secondary mutations at different time points within synchronous simulations. We demonstrate that the combination, order and timing of secondary mutations dictate maturation arrest points and fitness, explaining how different patterns of mutations seen in patients may arise and in turn influence disease severity. This platform provides a generalisable framework to model driver mutations in their developmental context to predict evolutionary trajectories in cancer.

cancer biology↗

bioRxiv2025

Validating folding energy estimates as a method for variant interpretation

Interpretation of variants of uncertain significance remains a major problem in genomic analysis. Whilst statistical models can be used to predict pathogenicity, they offer no insights into the biophysical mechanism of variant action, and genomic data available for training is biased towards the subpopulations who have access. Protein misfolding has been found to act as a frequent mechanism for loss of gene or domain activity, where it is typically responsible for [~]2/3 of disease-causing variants and somatic mutations. The accuracy of energy predictions however has consistently been challenged by highly variable correlation coefficients reported from different proteins, and the unknown impact of alternative structures where available. Here we address this directly through a systematic analysis of mega-scale folding experimental results, enabled by a fully automated predictive pipeline based on FoldX. We find that whilst absolute correlation coefficients are mediocre for three highly studied proteins (0.30-0.31), the correlation coefficient alone does not capture the full predictive power of the estimates. Specifically, we find a clear linear relationship between experimental and theoretical result, with a small number of outlier residues responsible for reducing the correlation. We show that the quantitative accuracy of predictions can be improved by aggregating estimates taken from different structures, and that the problematic outlier residues can be both empirically and theoretically identified, allowing us to flag low-confidence values. Our findings not only provide a framework for identifying problematic mutations in advance but also offers new insights into potential improvements of the FoldX protocol for more accurate protein stability predictions. Our insights support the use of FoldX in computational saturation screens to support variant analysis.

biophysics↗

bioRxiv2025

OmniPath: integrated knowledgebase for multi-omics analysis

Analysis and interpretation of omics data largely benefit from the use of prior knowledge. However, this knowledge is fragmented across resources and often is not directly accessible for analytical methods. We developed OmniPath (https://omnipathdb.org/), a database combining diverse molecular knowledge from 168 resources. It covers causal protein-protein, gene regulatory, miRNA, and enzyme-PTM (post-translational modification) interactions, cell-cell communication, protein complexes, and information about the function, localization, structure, and many other aspects of biomolecules. It prioritizes literature curated data, and complements it with predictions and large scale databases. To enable interactive browsing of this large corpus of knowledge, we developed OmniPath Explorer, which also includes a large language model (LLM) agent that has direct access to the database. Python and R/Bioconductor client packages and a Cytoscape plugin create easy access to customized prior knowledge for omics analysis environments, such as scverse. OmniPath can be broadly used for the analysis of bulk, single-cell and spatial multi-omics data, especially for mechanistic and causal modeling. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/675512v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@17c2b6borg.highwire.dtl.DTLVardef@1069835org.highwire.dtl.DTLVardef@1f2ce76org.highwire.dtl.DTLVardef@1d0b34f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Recovery of human upper airway epithelium after smoking cessation is driven by a slow-cycling stem cell population and immune surveillance

The upper airway epithelium in humans is maintained in homeostasis by a resident population of basal stem cells. In the presence of tobacco smoke these gain mutations that significantly increase their risk of transformation to lung squamous cell carcinoma. Previous studies show that a small proportion of stem cells avoid the mutational damage caused by carcinogens in tobacco and are more abundant in the lungs of former smokers than ongoing smokers, indicating unexplained tissue-level genomic recovery. This mirrors epidemiological risk, which falls rapidly after quitting smoking. Somatic evolutionary mechanistic hypotheses have been proposed to explain these observations. Here, we present a computational framework to model each of these hypotheses within the upper airway epithelial stem cell population over the entire patient lifetimes of a cohort with diverse smoking histories. Applying a mechanistic learning approach based on a set of biologically informed metrics to single cell-derived whole-genome sequencing data, we identified subtle differences between epithelia modelled under different combinations of hypotheses. A slow-cycling subpopulation of stem cells, combined with suppression of immune predation of highly mutated stem cells while smoking, best matched observed data, a result converged upon by multiple distinct machine learning methodologies. Our findings, drawing on an evolutionary model of mutagen exposure at a whole-lifetime scale that is not feasible to model in vivo, reveal the mechanisms behind reduction in lung squamous cell carcinoma risk on cessation of smoking and inform future therapeutic interventions to prevent lung cancer initiation.

evolutionary biology↗

bioRxiv2025

Selection of pre-leukemic hematopoietic stem cells driven by distinct extracellular matrix molecules

Despite rapid advances in mapping genetic drivers and gene expression changes in hematopoietic stem cells (HSCs), there is a relative paucity of studies at the protein level. Here, we perform a deep, multi-omic characterization (epigenome, transcriptome and proteome) of HSCs carrying a loss-of-function mutation in Tet2, a key driver of increased self-renewal in blood cancers. Using state-of-the-art, multiplexed, low-input mass spectrometry (MS)-based proteomics, we profile wildtype (WT) and TET2-deficient (Tet2-/-) HSCs and show that the proteome captures previously unrecognized molecular processes which define the pre-leukemic HSC molecular landscape. Specifically, we obtain more accurate stratification of WT and Tet2-/- HSCs than transcriptomic approaches and identify extracellular matrix (ECM) molecules as novel points of dysregulation upon TET2 loss. HSC expansion assays using ECM-functionalized hydrogels confirm a selective effect on the expansion of Tet2-mutant HSCs. Taken together, our study represents a comprehensive molecular characterization of Tet2-mutant HSCs and identifies a previously unanticipated role of ECM molecules in regulating self-renewal of disease-driving HSCs.

cell biology↗

bioRxiv2024

Somatic mutant selection is altered by prior NOTCH1 mutation in aging esophageal epithelium

The ageing mid esophagus is progressively colonized by somatic mutations, including oncogenic TP53 and antioncogenic NOTCH1 mutants. Most esophageal squamous carcinomas are TP53 mutant, NOTCH1 wild type. By middle age, much of the esophagus is NOTCH1 mutant. We hypothesised that prior NOTCH1 mutation may alter subsequent mutant selection. Here we show that selection of mutant NOTCH2 was increased and mutant TP53 decreased within NOTCH1 mutant epithelium. Potential mechanisms include spatial competition between adjacent clones and/or epistasis altering the fitness NOTCH1 double mutants. We investigated these possibilities in transgenic mice. Spontaneous Notch2 mutant clones emerged in aged Notch1 null, but not wild type, esophagus, consistent with epistasis increasing Notch1/Notch2 double mutant fitness. However, there was no evidence of epistasis between Notch1 and Trp53, as Notch1 mutation alone increased fitness. In consequence, over time, Trp53 mutant Notch1 wild type clones were outcompeted by expanding Notch1 and Trp53/Notch1 mutants. NOTCH1 mutant takeover of the aging esophagus alters the trajectory of somatic evolution, decreasing selection of TP53 mutants and potentially reducing cancer risk.

genomics↗

bioRxiv2024

Coxiella burnetii-containing vacuoles interact with host recycling-endosomal proteins Rab11a and Rab35 for vacuolar expansion

Coxiella burnetii is a gram-negative obligate intracellular bacterium and a zoonotic pathogen that causes human Q fever. Although acute Q fever manifests as atypical pneumonia, chronic infection may lead to life-threatening endocarditis. The lack of effective antibiotics and a licensed vaccine for Coxiella in the U.S. warrants further research into Coxiella pathogenesis. Within the host cells, Coxiella replicates in an acidic phagolysosome-like vacuole termed Coxiella-containing vacuole (CCV). Previously, we have shown that the CCV pH is critical for Coxiella survival and that the Coxiella Type 4B secretion system regulates CCV pH by inhibiting the host endosomal maturation pathway. However, the trafficking pattern of the immature endosomes in Coxiella-infected cells remained unclear. Our recent CCV localization screen with host Rab proteins revealed that recycling endosome-associated proteins Rab11a and Rab35 localize to the CCV during infection, suggesting that CCV interacts with host recycling endosomes during maturation. Interestingly, only a subset of CCVs were Rab11a or Rab35-positive at any given time point. A quantitation of Rab11a/Rab35-positive CCVs at 3- and 6-days post-infection (dpi) revealed that at 3 dpi, [~]52% of CCVs were positive for Rab11a, whereas only [~]39% CCVs were positive for Rab35. This pattern reversed at 6-dpi, when only [~]22% of CCVs were positive for Rab11a and [~]64% of CCVs were positive for Rab35. These data suggest that the CCV preferentially interacts with Rab11a and Rab35-positive recycling endosomes depending on the stage of maturation. Furthermore, we observed a significant increase in Rab11a and Rab35 fluorescent intensity in Coxiella-infected cells compared to mock cells suggesting that Coxiella increases the recycling endosome content in infected cells. Finally, a siRNA-mediated knockdown of both Rab11a and Rab35 resulted in significantly smaller CCVs, suggesting that recycling endosomal Rab proteins are essential for CCV expansion. Overall, our data, for the first time, show that the CCV dynamically interacts with host recycling endosomes for vacuolar expansion and potentially uncovers novel host cell factors essential for Coxiella pathogenesis.

microbiology↗

bioRxiv2022

p53 mutation in normal esophagus promotes multiple stages of carcinogenesis but is constrained by clonal competition

Aging normal human epithelia, such as the esophagus, accumulate a substantial burden of TP53 mutant clones. These are the origin of most esophageal squamous carcinomas, in which biallelic TP53 disruption is almost frequent. However, the cellular mechanisms by which p53 mutants colonize the esophagus and participate in the subsequent stages of transformation are unclear. Here we show that inducing the p53R245W mutant in single esophageal progenitor cells in transgenic mice confers a proliferative advantage that drives clonal expansion but does not disrupt normal epithelial structure or function. Loss of the remaining p53 allele in mutant cells does not increase their competitive fitness, creating a bottleneck to the development of chromosomally unstable p53R245W/null epithelium. In carcinogenesis, p53 mutation does not initiate tumor formation, but tumors developing from areas with p53 mutation and LOH are larger and show extensive chromosomal instability compared to lesions arising in wild type epithelium. We conclude that p53 has distinct functions at different stages of carcinogenesis and that LOH within p53 mutant clones in normal epithelium is a critical step in malignant transformation.

cancer biology↗

bioRxiv2021

Heterogeneity of the Cancer Cell Line Metabolic Landscape

The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1099 different species using liquid chromatography-mass spectrometry (LC-MS). We correlate known cancer-associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.

cancer biology↗

bioRxiv2021

Precancer: Mutant clones in normal epithelium outcompete and eliminate esophageal micro-tumors

Human epithelial tissues accumulate cancer-driver mutations with age1-7, yet tumor formation remains rare. The positive selection of these mutations argues they alter the behavior and fitness of proliferating cells8-10. Hence, normal adult tissues become a patchwork of mutant clones competing for space and survival, with the fittest clones expanding by eliminating their less-competitive neighbors9-12. However, little is known about how such dynamic competition in normal epithelia impacts early tumorigenesis. Here we show that the majority of newly formed esophageal tumors are eliminated through competition with mutant clones in the surrounding normal epithelium. We followed the fate of microscopic tumors in a mouse model of esophageal carcinogenesis. Most neoplasms are rapidly lost despite no indication of tumor cell death, decreased proliferation, or an anti-tumor immune response. Deep-sequencing of 10-day and 1-year-old tumors shows evidence of genetic selection on the surviving neoplasms. Induction of highly competitive clones in transgenic mice increased tumor removal, while pharmacologically inhibiting clonal competition reduced tumor loss. The results are consistent with a model where survival of early neoplasms depends on their competitive fitness relative to that of mutant clones in the adjacent normal tissue. We have identified an unexpected anti-tumorigenic role for mutant clones in normal epithelium by purging early neoplasms through cell competition, thereby preserving tissue integrity.

cancer biology↗

bioRxiv2021

SARS-CoV-2 Variants are Selecting for Spike Protein Mutations that Increase Protein Stability

The emergence of SARS-CoV-2 in 2019 has caused severe disruption and a huge number of human deaths across the globe. As the pandemic spreads, a natural result is the emergence of variants with a variety of amino acid mutations. Variants of SARS-CoV-2 with mutations in their spike protein may result in an increased infectivity, increased lethality, or immune escape, and whilst many of these properties can be explained through changes to binding affinity or changes to post-translational modification, many mutations have no known biophysical impact on the structure of protein. The Gibbs free energy of a protein represents a measure of protein stability, with an increased stability resulting in a protein that is more thermodynamically stable, and more robust to changes in external environment. Here we show that mutations in the spike proteins of SARS-CoV-2 are selecting for amino acid changes that result in a more stable protein than expected by chance. We calculate all possible mutations in the SARS-CoV-2 spike protein, and show that many variants are more stable than expected when compared to the background, indicating that protein stability is an important consideration for the understanding of SARS-CoV-2 evolution. Variants exhibit a range of stabilities, and we further suggest that some stabilising mutations may be acting as a "counterbalance" to destabilising mutations that have other properties, such as increasing binding site affinity for the human ACE2 receptor. We suggest that protein folding calculations offer a useful tool for early identification of advantageous mutations.

biophysics↗

bioRxiv2021

Notch1 mutation drives clonal expansion in normal esophageal epithelium but impairs tumor growth

NOTCH1 mutant clones occupy the majority of normal human esophagus by middle age, but are comparatively rare in esophageal cancers, suggesting NOTCH1 mutations may promote clonal expansion but impede carcinogenesis1-3. Here we test this hypothesis. Visualizing and sequencing NOTCH1 mutant clones in aging normal human esophagus reveals frequent biallelic mutations that block NOTCH1 signaling. In mouse esophagus, heterozygous Notch1 mutation confers a competitive advantage over wild type cells, an effect enhanced by loss of the second allele. Notch1 loss alters transcription but has minimal effects on epithelial structure and cell dynamics. In a carcinogenesis model, Notch1 mutations were less prevalent in tumors than normal epithelium. Deletion of Notch1 reduced tumor growth, an effect recapitulated by anti-NOTCH1 antibody treatment. We conclude that Notch1 mutations in normal epithelium are beneficial as wild type Notch1 promotes tumor expansion. NOTCH1 blockade may have therapeutic potential in preventing esophageal squamous cancer.

cancer biology↗

bioRxiv2021

HOXA9 acts as a regulatory switch in acute myeloid leukaemia and myeloproliferative neoplasms

Blood malignancies arise from the dysregulation of haematopoiesis. The type of blood cell and the specific order of oncogenic events initiating abnormal growth ultimately determine the cancer subtype and subsequent clinical outcome. HOXA9 plays an important role in acute myeloid leukaemia (AML) prognosis by promoting blood cell expansion and altering differentiation; however, the function of HOXA9 in other blood malignancies is still unclear. Here, we demonstrate the importance of this gene in chronic myeloproliferative neoplasms (MPN) and highlight the biological switch and prognosis marker properties of HOXA9 in AML and MPN. This binary switch function can explain the clinical stratification of these two blood disorders. First, we establish the ability of HOXA9 to stratify AML patients with distinct cellular and clinical outcomes. Then, through the use of a computational network model of MPN, we show that the self-activation of HOXA9 and its relationship to JAK2 and TET2 can explain the branching progression of JAK2/TET2 mutant MPN patients towards divergent clinical characteristics. Finally, we predict a connection between the RUNX1 and MYB genes and a suppressive role for the NOTCH pathway in MPN diseases.

cancer biology↗

bioRxiv2020

Different responses to cell crowding determine the clonal fitness of p53 and Notch inhibiting mutations in squamous epithelia

The growth and competition of cells in epithelial tissues plays an important role in both tissue homeostasis and the robustness of normal tissues to pre-cancer mutation. Whilst wild-type cells compete neutrally for dominance in the un-mutated tissue, naturally occurring mutations in individual cells may lend them a fitness advantage that can allow tissue colonisation. In mouse oesophageal epithelia, the growth of p53 mutants and a dominant negative mutant of the Notch downstream target Maml1 (DN_Maml1) have been shown to have different colonisation properties despite strong quantitative similarities in the growth of individual clones. Here we show that in order to recapitulate these behaviours whilst maintaining tissue turnover models need to take account of the response of cells to increased areal density in the tissue colonised by mutant cells. We demonstrate that p53 mutant clone growth approximates a logistic curve, but that without including limitations on mutation induced expansion the overall proliferation rate of the tissue drops due to space restrictions. In contrast, the ability of DN_Maml1 mutations to displace the wild-type population reflects a feedback that effects both mutant and wild-type cells equally. We go on to show how these distinct feedbacks are consistent with the distribution of mutations observed in human datasets.

systems biology↗

bioRxiv2020

Investigating structure function relationships in the NOTCH family through large-scale somatic DNA sequencing studies

The recent development of highly sensitive DNA sequencing techniques has detected large numbers of missense mutations of genes, including NOTCH1 and 2, in ageing normal tissues. Driver mutations persist and propagate in the tissue through a selective advantage over both wild-type cells and alternative mutations. This process of selection can be considered as a large scale, in vivo screen for mutations that increase clone fitness. It follows that the specific missense mutations that are observed in individual genes may offer us insights into the structure-function relationships. Here we show that the positively selected missense mutations in NOTCH1 and NOTCH2 in human oesophageal epithelium cause inactivation predominantly through protein misfolding. Once these mutations are excluded, we further find statistically significant evidence for selection at the ligand binding interface and calcium binding sites. In this, we observe stronger evidence of selection at the ligand interface on EGF12 over EGF11, suggesting that in this tissue EGF12 may play a more important role in ligand interaction. Finally, we show how a mutation hotspot in the NOTCH1 transmembrane helix arises through the intersection of both a high mutation rate and residue conservation. Together these insights offer a route to understanding the mechanism of protein function through in vivo mutant selection.

biophysics↗

bioRxiv2020

KCNQ gene family members act as both tumor suppressors and oncogenes in gastrointestinal cancers

Voltage sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large scale analysis of 1594 patients with GI cancers coupled with in vitro models we find KCNQ family genes are mutated in ~30% of patients, and play therapeutically targetable roles in GI cancer growth. KCNQ1 and KCNQ3 mediate the WNT pathway and MYC to increase proliferation, and its resultant effects on cadherins junctions. This also highlights novel roles for KCNQ3 in non-excitable tissues. We additionally discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors, and that inhibition of KCNQ activity reduces proliferation of GI cancer. These findings reveal a novel and exploitable role for potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GI cancers may exist through KCNQ inhibitors. SIGNIFICANCEKCNQ channels modulate the WNT pathway and MYC signalling, and drive growth of gastrointestinal cancers. Available drugs modulate these pathways and offer therapeutic potential in gastrointestinal cancer.

cancer biology↗

bioRxiv2020

Methods for analysing lineage tracing datasets

A single population of stem cells maintains many epithelial tissues. Transgenic mouse cell tracking has frequently been used to study the growth dynamics of competing clones in these tissues. A mathematical model (the single progenitor model) has been argued to reproduce the observed stem cell dynamics accurately. This requires three parameters to describe the growth dynamics observed in transgenic mouse cell tracking- a division rate, a stratification rate, and the probability of dividing symmetrically. Deriving these parameters is time intensive and complex process. We compare the alternative strategies for analysing this source of experimental data, identifying an approximate Bayesian computation-based approach as the best in terms of efficiency and appropriate error estimation. We support our findings by explicitly modelling biological variation and consider the impact of different sampling regimes. All tested solutions are made available to allow new datasets to be analysed following our workflows. Based on our findings we make recommendations for future experimental design.

systems biology↗

bioRxiv2019

The Landscape of Mutations in Fumarate Hydratase

Fumarate Hydratase (FH) is an enzyme of the citric acid (TCA) cycle that is responsible for reversibly catalysing the conversion between fumarate and malate. FH loss and subsequent buildup of the oncometabolite fumarate causes hereditary leiomyomatosis and renal cell carcinoma. We explore the mutational landscape of FH in silico, predict the functional effects of many already detected mutations, and categorise detected but un-characterised mutations in human populations. Using mutational energy predicting tools such as Rosetta and FoldX we accurately predict mutations and mutational hotspots with high disruptive capability. Furthermore, through performing molecular dynamics simulations we show that hinge regions of the protein can be stabilized or destabilized by mutations, with new mechanistic implications of the consequences on the binding affinity of the enzyme for its substrates. Finally, we categorise all potential mutations in FH into functional groups, and predict which known mutations in the human population are loss-of-function, and therefore predispose patients to papillary renal carcinoma - we validate our findings through analysis of metabolomics data of characterized cell lines.

biophysics↗