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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2022

Deep Reinforcement Learning for Stabilization of Large-scale Probabilistic Boolean Networks

AO_SCPLOWBSTRACTC_SCPLOWThe ability to direct a Probabilistic Boolean Network (PBN) to a desired state is important to applications such as targeted therapeutics in cancer biology. Reinforcement Learning (RL) has been proposed as a framework that solves a discrete-time optimal control problem cast as a Markov Decision Process. We focus on an integrative framework powered by a model-free deep RL method that can address different flavours of the control problem (e.g., with or without control inputs; attractor state or a subset of the state space as the target domain). The method is agnostic to the distribution of probabilities for the next state, hence it does not use the probability transition matrix. The time complexity is only linear on the time steps, or interactions between the agent (deep RL) and the environment (PBN), during training. Indeed, we explore the scalability of the deep RL approach to (set) stabilization of large-scale PBNs and demonstrate successful control on large networks, including a metastatic melanoma PBN with 200 nodes.

systems biology↗

bioRxiv2023

Bromodomain-containing Protein 4 Regulates Innate Inflammation in Airway Epithelial Cells via Modulation of Alternative Splicing

Bromodomain-containing Protein 4 (BRD4) is a transcriptional regulator which coordinates gene expression programs controlling cancer biology, inflammation, and fibrosis. In airway viral infection, non-toxic BRD4-specific inhibitors (BRD4i) block the release of pro-inflammatory cytokines and prevent downstream remodeling. Although the chromatin modifying functions of BRD4 in inducible gene expression have been extensively investigated, its roles in post-transcriptional regulation are not as well understood. Based on its interaction with the transcriptional elongation complex and spliceosome, we hypothesize that BRD4 is a functional regulator of mRNA processing. To address this question, we combine data-independent analysis - parallel accumulation-serial fragmentation (diaPASEF) with RNA-sequencing to achieve deep and integrated coverage of the proteomic and transcriptomic landscapes of human small airway epithelial cells exposed to viral challenge and treated with BRD4i. The transcript-level data was further interrogated for alternative splicing analysis, and the resulting data sets were correlated to identify pathways subject to post-transcriptional regulation. We discover that BRD4 regulates alternative splicing of key genes, including Interferon-related Developmental Regulator 1 (IFRD1) and X-Box Binding Protein 1 (XBP1), related to the innate immune response and the unfolded protein response, respectively. These findings extend the transcriptional elongation-facilitating actions of BRD4 in control of post-transcriptional RNA processing in innate signaling.

systems biology↗

bioRxiv2023

The evolution of binding affinities between p53 and MDM2 across the animal kingdom demonstrates high plasticity in motif-mediated interactions

The interaction between the transcription factor p53 and the ubiquitin ligase MDM2 results in degradation of p53 and is well studied in cancer biology and drug development. Available sequence data suggest that both p53 and MDM2-family proteins are present across the animal kingdom. However, the interacting regions are missing in some animal groups, and it is not clear whether MDM2 interacts with, and regulates p53 in all species. We used phylogenetic analyses and biophysical measurements to examine the evolution of affinity between the interacting protein regions: a conserved 12-residue intrinsically disordered binding motif in the p53 transactivation domain (TAD) and the folded SWIB domain of MDM2. The affinity varied significantly across the animal kingdom. The p53TAD/MDM2 interaction among jawed vertebrates displayed high affinity, in particular for chicken and human proteins (KD around 0.1 M). The affinity of the bay mussel p53TAD/MDM2 complex was lower (KD = 15 M) and those from a placozoan, an arthropod and a jawless vertebrate were very low or non-detectable (KD > 100 M). Binding experiments with reconstructed ancestral p53TAD/MDM2 variants suggested that a micromolar affinity interaction was present in the ancestral bilaterian animal and was later enhanced in tetrapods while lost in other linages. The different evolutionary trajectories of p53TAD/MDM2 affinity during speciation demonstrate high plasticity of motif-mediated interactions and the potential for rapid adaptation of p53 regulation during times of change. Neutral drift in unconstrained disordered regions may underlie the plasticity and explain the observed low sequence conservation in transactivation domains such as p53TAD. Statement for broader audienceThe protein p53 regulates central cellular processes including cell division and programmed cell death. p53 is regulated by another protein, MDM2, which binds to p53 and marks it for destruction. We measured the interaction between present-day and reconstructed ancient p53 and MDM2 proteins and found a range of binding strengths. Our findings suggest that rapid evolution of the p53/MDM2 interaction facilitates adaptation of p53 regulation during speciation.

molecular biology↗

bioRxiv2023

On growth and form of the mammary gland: Epithelial-mesenchymal interactions in embryonic mammary gland development

Mammary gland is a unique organ that undergoes dynamic alterations throughout a females reproductive life, making it an ideal model for developmental, stem cell and cancer biology research. Mammary gland development begins in utero and proceeds via a quiescent bud stage before the initial outgrowth and subsequent branching morphogenesis. How mammary epithelial cells transit from quiescence to an actively proliferating and branching tissue during embryogenesis and, importantly, how the branch pattern is determined remain largely unknown. Here we provide evidence indicating that epithelial cell proliferation, segregation into basal and luminal lineages that characterize the postnatal mammary duct, and onset of branching are independent processes, yet partially coordinated by the Eda signaling pathway. By performing heterotypic and heterochronic epithelial-mesenchymal recombination experiments between mammary and salivary gland tissues and ex vivo live imaging, we demonstrate that unlike previously concluded, the mode of branching is an intrinsic property of the mammary epithelium while the growth pace and density of the mammary ductal tree are governed by the mesenchyme. Transcriptomic profiling and ex vivo and in vivo functional studies disclose that mesenchymal Wnt/{beta}-catenin signaling, and in particular IGF-1 downstream of it critically regulate mammary gland growth. These results underscore the general need to carefully decompose the different developmental processes producing branched organs.

developmental biology↗

bioRxiv2023

Engineering of a biosensor for intracellular aspartate

Aspartate is a limiting metabolite in proliferating cells with its production closely linked to glutamine and mitochondrial metabolism. To date, measuring aspartate concentrations in live cells was deemed impossible. We present iAspSnFR, a genetically-encoded biosensor for intracellular aspartate, engineered by displaying and screening biosensor libraries in HEK293 cells. In live cells, iAspSnFR exhibits a dynamic range of 130% fluorescence change and detects reduced aspartate levels upon glutamine deprivation or glutaminase inhibition. Furthermore, iAspSnFR tracks aspartate uptake by excitatory amino acid transporters, or of asparagine after co-expression of an asparaginase. Importantly, iAspSnFR reports aspartate depletions upon electron transport chain inhibition, and therefore it can serve as a proxy for mitochondrial respiration. Consequently, iAspSnFR can dissect the major cellular pathways of aspartate production, offering immediate applications, particularly in cancer biology, such as screening small molecules targeting aspartate and glutamine metabolism.

cell biology↗

bioRxiv2023

Mitosis down-regulates nuclear volume and resets nuclear envelope folding of cancer cells under prolonged confinement

During their life, mammalian cells are subjected to numerous mechanical constraints, especially in pathological contexts such as cancer. Recent studies have highlighted the central role of the nucleus in sensing mechanical cues, but they only focus on short periods of time, and so far, whether cells can adapt to prolonged confinement remains unknown. Here, we reveal the unsuspected role of mitosis in the long-term adaptation of nuclei to prolonged uniaxial confinement. For the colorectal cancer cell line investigated, following the first confined cell division, a new homeostatic state was reached by nuclei: they were smaller, and had reset the tension of their envelope. This adaptation through mitosis relied both on the nuclear tension sensor cPLA2 and the contractility machinery. We report for the first time a mechano-adaptation during mitosis, a process that could be crucial to adapt to stresses in the tumor microenvironment. We therefore anticipate that our work could provide new insight into cancer cell plasticity and cancer relapse. Significance StatementMost cell types undergo significant deformation throughout their life cycles. Immune cells must deform to navigate through dense matrices, while cancer cells in solid tumors experience squeezing from neighboring cells. The nucleus, central for many cell function, is the stiffest and largest organelle. Understanding its long-term response to spatial constraints is hence crucial yet largely unexplored. In this study, we investigate how a colorectal cancer cell line adapts to prolonged confined environments, with a particular focus on nuclear dynamics under continuous squeezing. Our groundbreaking findings reveal for the first time a mechano-adaptation during mitosis leading to a decrease in nuclear size. This research contributes to the fundamental understanding of cellular mechanosensing, opening new avenues for cancer biology research.

biophysics↗

bioRxiv2023

Multivalent interactions of the disordered regions of XLF and XRCC4 foster robust cellular NHEJ and drive the formation of ligation-boosting condensates in vitro

In mammalian cells, DNA double-strand breaks are predominantly repaired by non-homologous end joining (NHEJ). During repair, the Ku70/80 heterodimer (Ku), XRCC4 in complex with DNA Ligase 4 (X4L4), and XLF form a flexible scaffold that holds the broken DNA ends together. Insights into the architectural organization of the NHEJ scaffold and its regulation by the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) have recently been obtained by single-particle cryo-electron microscopy analysis. However, several regions, especially the C-terminal regions (CTRs) of the XRCC4 and XLF scaffolding proteins, have largely remained unresolved in experimental structures, which hampers the understanding of their functions. Here, we used magnetic resonance techniques and biochemical assays to comprehensively characterize the interactions and dynamics of the XRCC4 and XLF CTRs at atomic resolution. We show that the CTRs of XRCC4 and XLF are intrinsically disordered and form a network of multivalent heterotypic and homotypic interactions that promotes robust cellular NHEJ activity. Importantly, we demonstrate that the multivalent interactions of these CTRs led to the formation of XLF and X4L4 condensates in vitro which can recruit relevant effectors and critically stimulate DNA end ligation. Our work highlights the role of disordered regions in the mechanism and dynamics of NHEJ and lays the groundwork for the investigation of NHEJ protein disorder and its associated condensates inside cells with implications in cancer biology, immunology and the development of genome editing strategies.

biophysics↗

bioRxiv2023

BERLIN: Basic Explorer for single-cell RNAseq analysis and cell Lineage Determination.

Single-cell RNA sequencing has revolutionized the study of immuno-oncology, cancer biology, and developmental biology by enabling the joint characterization of gene expression and cellular heterogeneity in a single platform. As of July 2023, the Gene Expression Omnibus now contains over 4000 published single-cell data sets, providing an invaluable opportunity for reanalysis to identify new cell types or cellular states as well as their defining transcriptional programs. To facilitate the reprocessing of these public datasets, we have devised a single-cell RNA sequencing analysis framework for data retrieval, quality control, expression normalization, dimension reduction, cell clustering, and data integration. Additionally, we have developed a Shiny App visualization platform that enables the exploration of gene expression, cell type annotations, and cell lineages through a user interface. We performed a re-analysis of single-cell RNAseq data generated from acute myeloid leukemia and tumor-reactive lymphocytes and found our pipeline to faithfully recapitulated the cell type assignment as well as expected lineage trajectories. Altogether, we present BERLIN, a single-cell RNAseq analysis pipeline that facilitates the integration and public dissemination of results from the reanalysis.

bioinformatics↗

bioRxiv2023

CRUX, a platform for visualising, exploring and analysing cancer genome cohort data

To better understand how tumours develop, identify prognostic biomarkers, and find new treatments, researchers have generated vast catalogues of cancer genome data. However, these datasets are complex so interpreting their important features requires specialized computational skills and analytical tools, which presents a significant technical challenge. To address this, we developed CRUX, a platform for exploring genomic data from cancer cohorts. CRUX enables researchers to perform common analyses including cohort comparisons, biomarker discovery, survival analysis, and create visualisations including oncoplots and lollipop charts. CRUX simplifies cancer genome analysis in several ways: (1) it has an easy-to-use graphical interface; (2) it enables users to create custom cohorts, as well as analyse precompiled public and private user-created datasets; (3) it allows analyses to be run locally to address data privacy concerns (though an online version is also available); and (4) it makes it easy to use additional specialized tools by exporting data in the correct formats. We showcase CRUXs capabilities with case studies employing different types of cancer genome analysis, demonstrating how it can be used flexibly to generate valuable insights into cancer biology. CRUX is freely available at https://github.com/CCICB/CRUX and https://ccicb.shinyapps.io/crux (DOI: 10.5281/zenodo.8015714).

bioinformatics↗

bioRxiv2023

Differential Modulation of Polycomb-Associated Histone Marks by cBAF, pBAF, and gBAF Complexes

Chromatin regulators are a group of proteins that can alter the physical properties of chromatin to make it more or less permissive to transcription by modulating another proteins access to a specific DNA sequence through changes in nucleosome occupancy or histone modifications at a particular locus. Mammalian SWI/SNF complexes (mSWI/SNF) are a group of ATPase-dependent chromatin remodelers that alter chromatin states. In mouse embryonic stem cells (mESCs), there are three primary forms of mSWI/SNF: canonical BAF (cBAF), polybromo-associated BAF (pBAF), and GLTSCR-associated BAF (gBAF or ncBAF). While cBAF and gBAF contain the SS18 protein subunit, pBAF lacks SS18. Previous studies used a novel dCas9-mediated inducible recruitment (FIRE-Cas9) of mSWI/SNF complexes via SS18 to the Nkx2.9 locus. Nkx2.9 is a developmentally regulated gene that requires mSWI/SNF for transcriptional activation during neural differentiation. However, in mESCs, Nkx2.9 is bivalent, meaning nucleosomes at the locus have both active and polycomb-associated repressive modifications. Upon recruitment of SS18-containing complexes, polycomb-associated histone marks are removed, followed by transcriptional activation of Nkx2.9. However, since both cBAF and gBAF share the SS18 subunit, it is unclear whether one or both complexes oppose the polycomb repressive marks. The ability of pBAF to do the same also remains unknown. In this study, we used unique subunits to recruit each of the three complexes to the Nkx2.9 locus individually. Here, we show that cBAF most effectively opposes polycomb repressive marks at Nkx2.9, leading to transcriptional activation of the gene. Recruitment of cBAF complexes leads to a significant loss of the polycomb repressive-2 H3K27me3 and polycomb repressive-1 H2AK119ub histone marks, whereas gBAF and pBAF do not. Moreover, nucleosome occupancy alone cannot explain the loss of these marks. Our results demonstrate that cBAF has a unique role in the direct opposition of polycomb-associated histone modifications that gBAF and pBAF do not share. O_LICell Cycle and Cancer Biology Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104 C_LIO_LIDepartment of Cell Biology, University of Oklahoma Health Science Center, Oklahoma City, OK, 73104 C_LI

molecular biology↗

bioRxiv2024

Flow zoometry of Drosophila

Drosophila serves as a highly valuable model organism across numerous fields including genetics, immunology, neuroscience, cancer biology, and developmental biology. Central to Drosophila-based biological research is the ability to perform comprehensive genetic or chemical screens. However, this research is often limited by its dependence on laborious manual handling and analysis, making it prone to human error and difficult to discern statistically significant or rare events amid the noise of individual variations resulting from genetic and environmental factors. In this article we present flow zoometry, a whole-animal equivalent of flow cytometry for large-scale, individual-level, high-content screening of Drosophila. Our flow zoometer automatically clears the tissues of Drosophila melanogaster, captures three-dimensional (3D) multi-color fluorescence tomograms of single flies with single-cell volumetric resolution at an unprecedented throughput of over 1,000 animals within 48 hours (24 hr for clearing; 24 hr for imaging), and performs AI-enhanced data-driven analysis - a task that would traditionally take months or years with manual techniques. To demonstrate its broad applications, we employed the flow zoometer in various laborious screening assays, including those in toxicology, genotyping, and tumor screening. Flow zoometry represents a pivotal evolution in high-throughput screening technology: previously from molecules to cells, now from cells to whole animals. This advancement serves as a foundational platform for "statistical spatial biology", to improve empirical precision and enable serendipitous discoveries across various fields of biology.

bioengineering↗

bioRxiv2024

MetaGXplore: Integrating Multi-Omics Data with Graph Convolutional Networks for Pan-cancer Patient Metastasis Identification

The spread of cancer cells from the primary tumor to distant anatomical sites, known as tumor metastasis, poses a significant challenge in clinical prognosis, impairing treatment efficacy and reducing patient survival time. Current methods for predicting and diagnosing tumor metastasis rely heavily on extensive examinations and subjective clinical judgments. Accurate and rapid prediction of tumor metastasis likelihood remains an unresolved challenge, crucial for guiding effective clinical interventions and extending patient survival. Additionally, identifying key genes highly associated with metastasis probability is a pressing issue, essential for providing valuable insights into the potential identification of tumor metastasis-specific biomarkers. We developed MetaGXplore, a pioneering Graph Convolutional Neural Network (GCN)-based framework designed to predict metastasis probability by integrating pan-cancer multi-omic datasets with a protein-protein interaction network, while also identifying key genes involved in the metastatic process. Multi-omics datasets offer a comprehensive view of cancer biology, enhancing accuracy in metastasis forecasting through superior deep learning algorithms. Our classification model results were interpreted with GNNExplainer. The efficacy of MetaGXplore was validated via model evaluations, graph structure analysis, and multi-omics data assessment. Enrichment analysis of key genes further explored their biological roles.

bioinformatics↗

bioRxiv2024

Somatic evolution of cancer genes in sex chromosomes

Cancer progression arises through the somatic evolution of oncogenes (OGs) and tumour-suppressor genes (TSGs). According to Knudsons two-hit hypothesis, both alleles of a TSG must typically be inactivated for tumorigenesis to proceed, whereas a single activating mutation can drive an OG. However, this diploid framework overlooks the distinct evolutionary dynamics of sex chromosomes. In males, the hemizygous (functionally haploid) state of the X chromosome implies that only a single mutational "hit" is needed to disable an X-linked TSG, potentially accelerating its contribution to cancer development. Here, we integrate somatic population genetics models with whole-genome mutation data to investigate how ploidy and dominance shape somatic evolution. We show that X-linked TSGs in male tumours evolve significantly faster than autosomal TSGs, particularly in highly proliferative tissues, whereas in low-proliferation tumours autosomal OGs accumulate mutations more rapidly than X-linked OGs. We further demonstrate that fixation times of advantageous mutations differ systematically between OGs and TSGs, converging only for male X-linked genes, as predicted from mathematical models. Our findings reveal that haploidy of sex chromosomes fundamentally alters the dynamics predicted by the two-hit hypothesis, providing the first systematic evidence that chromosomal context biases cancer gene evolution. Incorporating these principles into cancer biology offers a more accurate framework for understanding sex differences in tumorigenesis and highlights new avenues for therapeutic strategies targeting genomic regions with accelerated mutational dynamics.

genetics↗

bioRxiv2024

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair for somatic benchmarks

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

genomics↗

bioRxiv2024

Protein Kinases in Phagocytosis: Promising Genetic Biomarkers for Cancer

Cancer is a complex disease characterized by genetic and molecular diversity, often involving dysregulation of critical cellular pathways. Recent advances in pan-cancer research have highlighted the importance of shared oncogenic mechanisms across different cancer types, providing new avenues for therapeutic exploration. Protein kinases, particularly those involved in phagocytosis, play pivotal roles in cellular homeostasis and immune response. This study systematically examines the genetic alterations and expression profiles of protein kinases associated with phagocytosis across various cancer types, using data from The Cancer Genome Atlas (TCGA) and other publicly available resources. We analyzed single nucleotide variations (SNVs), copy number variations (CNVs), methylation patterns, and mRNA expression to identify recurring alterations and their associations with survival outcomes. Our findings reveal that MET and MERTK are the most frequently mutated genes, with missense mutations dominating across cancers. CNV analysis shows significant correlations with survival in cancers like UCEC, KIRP, and KIRC, while methylation analysis indicates cancer-specific regulatory patterns affecting gene expression. Differential expression analysis highlights distinct cancer-type-specific expression profiles, with genes like MET and BTK displaying significant variation. Crosstalk pathway analysis further reveals the involvement of these kinases in key cancer-related pathways, such as epithelial-mesenchymal transition (EMT) and apoptosis. Drug sensitivity analysis identifies potential therapeutic targets, with gene expression correlating significantly with cancer cell line responsiveness to specific compounds. These findings underscore the importance of the phagocytotic kinome in cancer biology and suggest potential therapeutic strategies targeting protein kinases to enhance immune response and improve treatment outcomes.

genetics↗

bioRxiv2024

Mammary Epithelial Migration is EMT-Independent

Epithelial tissues are traditionally considered immobile, requiring epithelial-to-mesenchymal transition (EMT) for individual or collective cell migration as mesenchymal cells. However, recent studies indicate that the mammary epithelium migrates via mechanisms distinct from mesenchymal collectives. Here, we demonstrate that mammary epithelium does not undergo EMT before migration, as evidenced by cellular and molecular characteristics, including EMT marker expression at the mRNA, protein, localization, and transcriptomic levels. Contrary to established models, cell-cell adhesion is not diminished but is required for epithelial migration. Furthermore, Snail1 does not repress cell-cell adhesion but instead plays a pivotal role in directing epithelial migration by regulating processes such as the directional movement of individual cells via Cdc42ep5. Our findings reveal the existence of both stationary and migratory states within the epithelium, providing new insights into how epithelial tissues transition between these states, with broad implications for organogenesis and cancer biology.

cell biology↗

bioRxiv2024

CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer

We present CancerFoundation, a novel single-cell RNA-seq foundation model (scFM) trained exclusively on malignant cells. Despite being trained on only one million total cells, a fraction of the data used by existing models, CancerFoundation outperforms other scFMs in key tasks such as zero-shot batch integration and drug response prediction. During training, we employ tissue and technologyaware oversampling and domain-invariant training to enhance performance on underrepresented cancer types and sequencing technologies. We propose survival prediction as a new downstream task to evaluate the generalizability of single-cell foundation models to bulk RNA data and their applicability to patient stratification. CancerFoundation demonstrates superior batch integration performance and shows significant improvements in predicting drug responses for both unseen cell lines and drugs. These results highlight the potential of focused, smaller foundation models in advancing drug discovery and our understanding of cancer biology. Our code is available here1.

bioinformatics↗

bioRxiv2024

Master regulators governing protein abundance across ten human cancer types

Protein abundance correlates only moderately with mRNA levels, and are modulated post-transcriptionally by a network of regulators including ribosomes, RNA-binding proteins (RBPs), and the proteasome. Here, we identified Master Protein abundance Regulators (MaPRs) across ten cancer types by devising a new computational pipeline that jointly analyzed transcriptomes and proteomes from 1,305 tumor samples. We identified 232 to 1,394 MaPRs per cancer type, mediating up to 79% of post- transcriptional regulatory networks. MaPRs exhibit high network connectivity, strong genetic dependency in cancer cells, and significant enrichment for RBPs. Combining tumor up-regulation, druggability, and target network analyses identified cancer-specific vulnerabilities. MaPRs predict tumor proteomic subtypes more accurately than other proteins. Finally, significant portions of RBP MaPR-target relationships were validated by experimental evidence from eCLIP binding and knockdown assays. Our findings uncover central MaPRs that govern post-transcriptional networks, highlighting diverse processes underlying human proteome regulation and identifying key regulators in cancer biology.

systems biology↗