Biology subjects

Bennett, E.

Publications and source records attributed to Bennett, E..

8 recordsLinked to original sources

bioRxiv2026

A scalable in vitro cell competition model identifies preleukemic super competitor clones

Preleukemic and leukemic conditions are frequently characterized by the acquisition of recurrent genetic mutations in hematopoietic stem cells (HSCs). One of the most frequently mutated genes in both clonal hematopoiesis and myeloid malignancies is the ten-eleven translocation 2 (TET2) gene, which encodes an epigenetic enzyme with a critical role in the regulation of gene transcription. While substantial work has shown that TET2 loss-of-function mutations lead to a clonal advantage, the underpinning cellular mechanism remains unclear, especially with respect to the early interactions with other cells. To study these early cell interactions of mutant and non-mutant cells, we developed an in vitro clonal competition platform where single-cell derived cultures are split into subclonal fractions which can be simultaneously cross-competed against multiple different clones of an opposing genotype. We identify a novel preleukemic cell phenotype that parallels the developmental biology phenomenon of super-competition, whereby ~10% of TET2-mutant clones actively and selectively suppress wild type (WT) cell expansion and, in some cases, completely eliminate WT clones. Molecular profiling and functional assays point to RAC1-GEF signalling inhibition as a specific WT cell vulnerability that is promoted, and tolerated, by neighbouring TET2-mutated clones. In addition to pinpointing selective drivers of non-mutant cell suppression, this clonal competition platform offers a broadly applicable new approach to study cell competition dynamics at an unprecedented scale.

cancer biology↗

bioRxiv2025

Resolution of collided ribosomes by ZNF598 is required for adipocyte energy dissipation

Cellular adaptation to stress evoked by high energy demand requires tight coordination between transcriptional programs, protein synthesis, and organelle function. In many physiological contexts, metabolic remodeling depends on increased mitochondrial capacity and activity, placing high demands on the translational machinery. Beige and brown adipocytes, which undergo rapid mitochondrial expansion and activation in response to physiological cues, provide a powerful model to study how cells adapt their translational output to meet increased metabolic demand. How translational fidelity is maintained, and stress-associated conflicts in protein synthesis are resolved during such adaptive processes, remains incompletely understood. Here, we identify ZNF598 as a key factor that resolves translation stress caused by ribosome collisions during metabolic adaptation of adipocytes. We show that diverse physiological stimuli, including hormonal signaling, environmental challenges, and dietary changes, induce ZNF598 and associated enzymes in metabolically active cells. ZNF598 is required for efficient mitochondrial biogenesis and function, supporting adaptive increases in respiration and energy expenditure. Loss of ZNF598 compromises these adaptive responses and leads to metabolic dysfunction, whereas enhancement of ZNF598 activity improves cellular and organismal metabolic flexibility. Together, these findings indicate that distal steps of the translational machinery are a rate-limiting factor for adaptation to increased energy demand.

cell 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

HLAIIPred: Cross-Attention Mechanism for Modeling the Interaction of HLA Class II Molecules with Peptides

We introduce HLAIIPred, a deep learning model to predict peptides presented by class II human leukocyte antigens (HLAII) on the surface of antigen presenting cells. HLAIIPred is trained using a Transformer-based neural network and a dataset comprising of HLAII-presented peptides identified by mass spectrometry. In addition to predicting peptide presentation, the model can also provide important insights into peptide-HLAII interactions by identifying core peptide residues that form such interactions. We evaluate the performance of HLAIIPred on three different tasks, peptide presentation in monoallelic samples, immunogenicity prediction of therapeutic antibodies, and neoantigen prioritization for cancer immunotherapy. Additionally, we created a dataset of biotherapeutics HLAII peptides presented by human dendritic cells. This data is used to develop screening strategies to predict the unwanted immunogenic segments of therapeutic antibodies by HLAII presentation models. HLAIIPred demonstrates superior or equivalent performance when compared to the latest models across all evaluated benchmark datasets. We achieve a 16% increase in prediction of presented peptides compared to the second-best model on a set of unseen peptides presented by less frequent alleles. The model improves clinical immunogenicity prediction, identifies epitopes in therapeutic antibodies and prioritize neoantigens with high accuracy. HIGHLIGHTS* We developed a deep learning model to address the shortcomings of existing models for the prediction of peptides presented by HLAII molecules. * The model is end-to-end and context-free, requiring only a peptide sequence and available HLAII alleles as input. * HLAIIPred outperforms the state-of-the-art models on multiple benchmark datasets. * The model is able to predict the core residues of peptides that interact with HLAIIs. * We created experimental data and developed screening strategies to accurately predict the immunogenic hotspots in therapeutic antibodies.

bioinformatics↗

bioRxiv2023

Increased FAN1 expression by mRNA-LNP attenuates CAG repeat expansion in Huntington patients' iPSC-derived astrocytes

Expansion of repeat sequences within the human genome can lead to disease pathogenesis, such as Huntingtons Disease, primarily affecting the nervous system. Genome-wide association studies (GWAS) of age-at-onset in Huntingtons disease (HD) patients demonstrated DNA mismatch repair (MMR) genes are modifiers of somatic expansion and may be potential therapeutic targets for repeat expansion (RE) disorders. FAN1, a Fanconi anemia-associated nuclease, has been reported as an influencer of repeat expansion in the RE mouse models. Here, we show the first demonstration that FAN1 knock-out in HD patient-derived fibroblasts and results in increased CAG repeat length. We also develop a robust novel cell-based platform using stem cell technology to produce the HD patients iPSC-derived astrocytes (iAstro). This platform is a disease-relevant system and has a significantly wider assay window, making it more suitable to assess the effect of gene modulation on CAG repeats. A substantial and exponential increase in repeat instability was exhibited in this HD patients iPSC-derived astrocytes platform. Over-expression of FAN1 protein via FAN1 plasmid transfection in this platform reduced CAG repeat instability, suggesting that upregulation of FAN1 protein may have a potential protective effect in CAG repeat expansion for a therapeutic setting. We leveraged the mRNA-LNP modality to enhance FAN1 protein expression and revealed that codon-optimized FAN1 mRNA-LNP robustly prevented increased CAG repeat in HD patients iPSC-derived astrocytes platform. The data from these cell-based platforms highlight that FAN1 plays a protective role in attenuating expanded somatic HTT CAG repeats and shed light on new therapeutic directions against repeat expansion disorders.

neuroscience↗

bioRxiv2022

Backtracking: Improved methods for identifying the source of a deliberate release of Bacillus anthracis from the temporal and spatial distribution of cases

Reverse epidemiology is a mathematical modelling tool used to ascertain information about the source of a pathogen, given the spatial and temporal distribution of cases, hospitalisations and deaths. In the context of a deliberately released pathogen, such as Bacillus anthracis (the disease-causing organism of anthrax), this can allow responders to quickly identify the location and timing of the release, as well as other factors such as the strength of the release, and the realized wind speed and direction at release. These estimates can then be used to parameterise a predictive mechanistic model, allowing for estimation of the potential scale of the release, and to optimise the distribution of prophylaxis. In this paper we present two novel approaches to reverse epidemiology, and demonstrate their utility in responding to a simulated deliberate release of B. anthracis in ten locations in the UK and compare these to the standard grid-search approach. The two methods - a modified MCMC and a Recurrent Convolutional Neural Network - are able to identify the source location and timing of the release with significantly better accuracy compared to the grid-search approach. Further, the neural network method is able to do inference on new data significantly quicker than either the grid-search or novel MCMC methods, allowing for rapid deployment in time-sensitive outbreaks. Author summaryIn this paper we demonstrate three methods for estimating the source location and timing of a deliberate release of Bacillus anthracis based on the temporal and spatial distribution of cases. Two of our proposed methods, a modified MCMC approach and a neural network based approach, provide significant improvements over previous methods by directly addressing the problematic parameter-likelihood surface, and, in the case of the neural network approach, addressing the slow deployment speeds of existing methods. Our results represent a major step forward in the accuracy and speed of epidemiological back-calculation.

systems biology↗

bioRxiv2022

A Peroxiredoxin-P38 MAPK scaffold increases MAPK activity by MAP3K-independent mechanisms

Peroxiredoxins (Prdx) utilize reversibly oxidized cysteine residues to reduce peroxides but also to promote H2O2 signal transduction, including H2O2-induced activation of P38 MAPK. Prdx form H2O2-induced disulfide complexes with many proteins, including multiple kinases involved in P38 MAPK signaling. Here we show that a genetically-encoded fusion between Prdx and the P38 MAPK is sufficient to hyperactivate the kinase in yeast and human cells by a mechanism that does not require the H2O2-sensing cysteine of the Prdx. In yeast, we demonstrate that a P38-Prdx fusion protein compensates for the loss of a scaffold protein and upstream MAP3K kinase activity, driving entry into mitosis. Based on our findings, we propose that the H2O2-induced formation of Prdx-MAPK disulfide complexes provides a scaffold and signaling platform for MAPKK-MAPK signaling. The demonstration that formation of a complex with a Prdx can be sufficient to modify the activity of a kinase has broad implications for peroxide-based signal transduction in eukaryotes. HighlightsP38-Prdx complexes increase P38 (Sty1/MAPK14) phosphorylation in yeast and human cells The S. pombe Prdx promotes transient thioredoxin-mediated oxidation of a MAPK tyrosine phosphatase P38-Prdx complexes increase P38(Sty1) activity by phosphatase and MAP3K-independent mechanisms P38-Prdx complexes increase the stability and phosphorylation of the S. pombe P38 MAPKK (Wis1) Non-canonical, H2O2-induced autophosphorylation contributes to activation of the Wis1 MAPKK

biochemistry↗

bioRxiv2019

BTLA and PD-1 employ distinct phosphatases to differentially repress T cell signaling

T cell-mediated destruction of tumors and virus-infected cells is restricted by co-inhibitory receptors such as programmed cell death protein 1 (PD-1). Monoclonal antibodies blocking PD-1 have produced impressive clinical activity against human cancers, but durable response is limited to a minority of patients. Previous results suggest that B and T lymphocyte attenuator (BTLA), a co-inhibitory receptor structurally related to PD-1, may contribute to the resistance to PD-1 targeted therapy and co-blockade of BTLA can enhance the efficacy of anti-PD-1 immunotherapy. However, the biochemical mechanism by which BTLA represses T cell activity and to what extent the mechanism differs from that of PD-1 is unknown. Here we examine differences in the ability of BTLA and PD-1 to recruit effector molecules and regulate T cell signaling. We show that PD-1 and BTLA recruit different tyrosine phosphatases to regulate either CD28 or T cell antigen receptor (TCR)-signaling cascades. Our data reveal unexpected disparities between two structurally related immune checkpoints and two phosphatase paralogs.

cell biology↗