Biology subjects

Kent, J.

Publications and source records attributed to Kent, J..

8 recordsLinked to original sources

bioRxiv2026

Dynamic TET1 repression coordinates activation of macroH2A.2-poised bivalent genes during neuroectoderm differentiation

Cell state transitions involve changes in gene expression programs in conjunction with epigenetic regulation occurring in chromatin. Bivalent chromatin, marked by overlapping active H3K4me3 and repressive H3K27me3, poises key developmental genes during pluripotency for cell type-specific activation during differentiation. However, the molecular mechanisms that activate bivalent genes during lineage commitment remain poorly understood. Here, we elucidate how the cytosine dioxygenase TET1 promotes neuroectoderm differentiation through dynamic chromatin binding and a non-catalytic repressor function. Through a hypothesis-free screen for TET1 chromatin complex partners, we find that TET1 physically interacts with macroH2A.2 and H2A.X on chromatin. Integrated multi-omic analyses reveal that the non-catalytic repressor function of TET1 and a novel activating function of the H2A variant macroH2A.2 together promote a poised transcriptional state within bivalent chromatin during pluripotency. Upon pluripotency exit, TET1 disengages from macroH2A.2-marked early neuroectoderm genes to permit their activation, while remaining bound as a repressor at mesoendoderm and late neural genes to prevent alternative cell state transitions. Furthermore, TET1 retention at accessible primed enhancers supports neural program activation. Together, our findings reveal a noncanonical functional interplay within bivalent chromatin between TET1 and macroH2A.2 that maintains a poised state during pluripotency and predicts selective gene activation during neuroectoderm specification.

developmental biology↗

bioRxiv2026

In vivo Proximity & Spatial Proteomics with CRISPR Screening Identify STXBP1 as a Protective Modifier of a-synuclein Toxicity in Dopamine Neurons.

Parkinsons disease (PD) is a disease of adults involving the loss of dopaminergic neurons after a long, asymptomatic, prodromal period. -synuclein, LRRK2, and VPS35 are linked to familial PD, however, how these mutations predispose dopamine neurons to death during the early prodromal phases remains unclear. Here, we used in vivo native proximity proteomics (iBioID) and dopaminergic neuron-specific subcellular proteomics across multiple PD models to uncover early alterations preceding neuronal loss. Our analyses identified convergent disruptions in synaptic protein abundance, indicating that presynaptic trafficking defects are early events in PD pathogenesis. Using a targeted CRISPR-based genetic screen in dopamine neurons, we demonstrated that mimicking this misregulation of STXBP1 amplifies vulnerability to -synuclein, implicating it as a previously underappreciated toxicity buffering factor. These findings highlight convergent mechanisms that sensitize dopamine neuronal degeneration and that presynaptic vesicle SNARE-complex proteins could serve as key targets for disease-modifying therapies in PD and related neurodegenerative disorders. HighlightsO_LIIn vivo native-BioID mapping of multiple Parkinsons disease (PD) protein interactomes revealed a convergent presynaptic network. C_LIO_LIiBioID analysis on mutant PD proteins (-synuclein A30P, LRRK2 G2019S, VPS35 D620N) uncovered mutation-specific shifts in local proximity networks, notably in endocytic and vesicle recycling pathways. C_LIO_LISpatial proteomics (iBioCoFrac) of dopamine neurons in vivo identified functional modules with reduced levels of key synaptic proteins in PD models. C_LIO_LIComparative proteomics using iBioCoFrac revealed synaptic vesicle regulation as a primary site of molecular convergence and early molecular signatures in dopamine neurons across multiple PD mouse models. C_LIO_LIAn in vivo CRISPR screen pinpointed the presynaptic protein Stxbp1/Munc18-1 as an -synuclein toxicity modifier in dopaminergic neurons. C_LI

neuroscience↗

bioRxiv2025

Clonal interference and changing selective pressures shape the escape of SARS-CoV-2 from hundreds of antibodies

SARS-CoV-2 rapidly evolves to evade human immunity. While the viruss overall resistance to human polyclonal antibody responses has steadily increased over time, the dynamics by which it escaped individual monoclonal antibodies within these responses have not been thoroughly explored. Recently, a series of studies by Cao et al. [1, 2, 3] used deep mutational scanning (DMS) to identify which mutations allow the Wuhan-Hu-1 receptor-binding domain to escape binding by individual antibodies, doing so for thousands of antibodies. Here, we sought to use these data to retrospectively examine the evolutionary dynamics of escape from a set of 1,603 antibodies. For each antibody, we used the DMS data to predict an antibody-escape score for each of thousands of globally circulating viral sequences from the first 3.5 years of the pandemic, and then computed an escape trajectory that quantifies how the populations average escape score changed over time. We use pseudovirus neutralization data from Cao et al. and Wang et al. [4] to validate common patterns in escape trajectories. While some trajectories increase monotonically over time, others show large fluctuations as a result of clade-displacement events that reduce the frequency of antibody-escape mutations in the viral population. Fitness effects of mutations estimated from natural sequences suggest that the mutations are displaced due to clonal interference. Further, these estimates suggest that the order in which escape mutations arose is shaped by changing selective pressures. Overall, this work helps describe how SARS-CoV-2 evaded the individual components of a polyclonal immune response in nature, and suggests that evasion occurred via complex evolutionary dynamics.

microbiology↗

bioRxiv2025

Meta all the way down: An overview of neuroimaging meta-analyses

Meta-analyses are invaluable tools for navigating the rapidly expanding scientific literature. Given their high value, ensuring the quality of meta-analyses is paramount. We conducted a multifaceted overview, examining each step in a manual neuroimaging meta-analysis on a large scale. We used four novel datasets comprising over 14,000 papers, including fMRI meta-analyses, fMRI studies, studies included in meta-analyses, and studies associated with image data on NeuroVault. Regarding successes, two-thirds of meta-analyses stated that they followed PRISMA guidelines, and 65% included a flowchart describing their inclusion process. We point out several areas for improvement. Pre-registration was fairly rare (20%), and only half listed their exact search strategy. There could be a location bias in which papers are included, and many did not include enough studies to be robust against publication bias (68% of meta analyses have less than 30 studies included). We also offer ideas for future directions. As image based meta-analysis is the gold standard, we have indicated which topics have the most image data available. The potential redundancy of topics can be visualized in our paper, and we recommend future meta-analyses be in conversation with past ones by citing and discussing previous similar work. By addressing these findings, the neuroimaging community can collectively improve the field of neuroimaging meta-analyses.

neuroscience↗

bioRxiv2024

Inducible, but not constitutive, pancreatic REG/Reg isoforms are regulated by intestinal microbiota and pancreatic diseases

The REG/Reg gene locus encodes for a conserved family of potent antimicrobial but also pancreatitis-associated proteins. Here we investigated whether REG/Reg family members differ in their baseline expression levels and abilities to be regulated in the pancreas and gut upon perturbations. We found, in human and mouse, pancreas and gut differed in REG/Reg isoform levels and preferences, with duodenum most resembling the pancreas. Pancreatic acinar cells and intestinal enterocytes were the dominant REG producers. Intestinal symbiotic microbes regulated the expression of the same, select Reg members in gut and pancreas. These Reg members had the most STAT3-binding sites close to the transcription start sites and were partially IL-22 dependent. We thus categorized them as "inducible" and others as "constitutive". Indeed, also in models of pancreatic-ductal adenocarcinoma and pancreatitis, only inducible Reg members were upregulated in pancreas. While intestinal Reg expression remained unchanged upon pancreatic perturbation, pancreatitis altered the microbial composition of the duodenum and feces shortly after disease onset. Our study reveals differential usage and regulation of REG/Reg isoforms as a mechanism for tissue-specific innate immunity, highlights the intimate connection of pancreas and duodenum, and implies a gut-to-pancreas communication axis resulting in a coordinated Reg response.

immunology↗

bioRxiv2024

EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancers response to endocrine therapies and explore resistance mechanisms.

cancer biology↗

bioRxiv2022

FOXA2 controls the antioxidant response in FH-deficient cells independent of NRF2

Hereditary Leiomyomatosis and renal cell cancer (HLRCC) is a cancer syndrome caused by inactivating germline mutations in fumarate hydratase (FH) and subsequent accumulation of fumarate. Fumarate accumulation leads to the activation of an anti-oxidant response via nuclear translocation of the transcription factor NRF2. The activation of the anti-oxidant response is key for cellular survival in FH-deficient cells, yet the extent to which chromatin remodelling shapes the anti-oxidant response is currently unknown. Here, we explored the global effects of FH loss on the chromatin landscape to identify transcription factor networks involved in the highly remodelled chromatin landscape of FH-deficient cells. We identify FOXA2 as a key transcription factor which directly regulates anti-oxidant response genes and subsequent metabolic rewiring. Moreover, we also find that FOXA2 regulates anti-oxidant genes independent of the canonical anti-oxidant regulator NRF2. The identification of FOXA2 as an anti-oxidant regulator provides new insights into the molecular mechanisms behind cell responses to fumarate accumulation, and potentially provides new avenues for therapeutic intervention for HLRCC.

cancer biology↗

bioRxiv2018

FMRIPrep: a robust preprocessing pipeline for functional MRI

Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available for each step. The complexity of these workflows has snowballed with rapid advances in MR data acquisition and image processing techniques. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for task-based and resting fMRI data. FMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing with no manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software-testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection comprising participants from 54 different studies in the OpenfMRI repository. We review the distinctive features of fMRIPrep in a qualitative comparison to other preprocessing workflows. We demonstrate that fMRIPrep achieves higher spatial accuracy as it introduces less uncontrolled spatial smoothness than commonly used preprocessing tools. FMRIPrep has the potential to transform fMRI research by equipping neuroscientists with a high-quality, robust, easy-to-use and transparent preprocessing workflow which can help ensure the validity of inference and the interpretability of their results.

bioinformatics↗