Biology subjects

Baker, S. M.

Publications and source records attributed to Baker, S. M..

13 recordsLinked to original sources

bioRxiv2026

Spartan: Spatial Activation Aware Transcriptomic Analysis Network

Spatial transcriptomics is rapidly advancing toward single-cell-level resolution, revealing complex tissue architectures organized across continuous anatomical gradients. However, accurate identification of spatial domains remains a central computational challenge, as many existing clustering approaches blur anatomical boundaries, merge transitional zones, or fail to resolve localized microstructures. Here we introduce Spartan, an activation-aware multiplex graph framework for high-resolution domain discovery. Spartan integrates spatial topology and Local Spatial Activation (LSA), a neighborhood deviation signal that captures localized transcriptional heterogeneity often attenuated by similarity-based clustering. By jointly modeling cohesion within domains and localized activation structure, Spartan recovers anatomically aligned partitions across spatially resolved transcriptomics technologies including Visium HD, MERFISH, Stereo-seq, and STARmap. We further demonstrate its utility in a high-resolution Visium HD section of developing human esophagus and stomach, where activation-aware graph integration enables precise delineation of complex transitional regions such as the gastroesophageal junction and supports stable multi-scale domain recovery without fragile hyperparameter tuning. Beyond domain identification, Spartan leverages activation-aware structure to detect spatially variable genes associated with localized tissue remodeling. Spartan scales near-linearly with dataset size, providing a robust and interpretable framework for spatial systems-level analysis.

bioinformatics↗

bioRxiv2025

Decoding the Spatial and Epigenetic Logic of Early Skin Development

The embryonic epidermis originates from a simple single-layered ectoderm that undergoes precise transcriptional and morphological transitions to generate a self-replenishing, multi-layered epidermis. A key early milestone is the emergence of the periderm; a transient, protective layer whose disruption underlies a series of devastating human congenital disorders. Despite its importance, the gene regulatory networks that drive periderm formation remain poorly defined. Here, we integrate single-cell multiome profiling with high-resolution spatial transcriptomics analysis in wild-type and transcription factor p63 mutant (Trp63-/-) embryos to dissect the transcriptional and epigenetic programs driving epidermal lineage diversification. We resolve the cellular repertoire of early embryonic skin, define epithelial subpopulations and reconstruct the transcriptional dynamics underlying the periderm emergence. We show that p63 sits at the core of a multilayered enhancer-gene regulatory network, demonstrate how this network is perturbed in vivo, and functionally validate key targets using comparative cellular models. Together, these findings delineate the gene regulatory architecture of early skin development and establish a framework for understanding epithelial-associated congenital disorders.

developmental biology↗

bioRxiv2025

DeepPathway: Predicting Pathway Expression from Histopathology Images

Spatial transcriptomics (ST) technologies provide spatially resolved gene expression along with image data, allowing the integrative analysis of complex tissue microenvironments. Despite their potential, the widespread adoption of ST remains limited due to high costs, and methodological challenges in data acquisition. Thus, there have been recent efforts to develop deep learning methods capable of inferring spatial gene expression from the much cheaper and easily available haematoxylin and eosin (H&E) images. These methods demonstrate promising results in reconstructing transcriptomic landscapes within tissue sections. While existing approaches predominantly focus on gene-level predictions, biological processes are often regulated at the pathway level through coordinated activity among functionally related genes. We present DeepPathway, a contrastive learning-based approach trained on ST data to predict pathway expression from H&E-stained sections. We compute input pathway expression by summarizing the expression of constituent genes using established pathway definitions. We evaluate the performance of our method on two prostate cancer datasets and validate our approach on the H&E images acquired from The Cancer Genome Atlas (TCGA) clearly differentiating between normal and tumour tissues. Finally, we apply our method to predict hypoxia signatures using H&Es of brain tumour samples where hypoxia staining with pimonidazole was available as ground truth. Implementation code for DeepPathway is available at https://github.com/aahsan045/DeepPathway.

bioinformatics↗

bioRxiv2024

Single-Cell Atlas of AML Reveals Age-Related Gene Regulatory Networks in t(8;21) AML

BackgroundAcute myeloid leukemia (AML) is characterized by cellular and genetic heterogeneity, which correlates with clinical course. Although single-cell RNA sequencing (scRNA-seq) reflects this diversity to some extent, the low sample numbers in individual studies limit the analytic potential when comparing specific patient groups. ResultsWe performed large scale integration of published scRNA-seq datasets to create a unique single-cell transcriptomic atlas for AML (AML scAtlas), totaling 748,679 cells, from 159 AML patients and 44 healthy donors from 20 different studies. This is the largest single-cell data resource for AML to our knowledge, publicly available at https://cellxgene.bmh.manchester.ac.uk/AML/. This AML scAtlas allowed investigations into 20 patients with t(8;21) AML, where we explored the clinical importance of age, given the in-utero origin of pediatric disease. We uncovered age-associated gene regulatory network (GRN) signatures, which we validated using bulk RNA sequencing data to delineate distinct groups with divergent biological characteristics. Furthermore, using an additional multiomic dataset (scRNA-seq and scATAC-seq), we validated our initial findings and created a de-noised enhancer-driven GRN reflecting the previously defined age-related signatures. ConclusionsApplying integrated data analysis of the AML scAtlas, we reveal age-dependent gene regulation in t(8;21) AML, potentially reflecting immature/fetal HSC origin in prenatal origin disease vs postnatal origin. Our analysis revealed that BCLAF1, which is particularly enriched in pediatric AML with t(8;21) of inferred in-utero origin, is a promising prognostic indicator. The AML scAtlas provides a powerful resource to investigate molecular mechanisms underlying different AML subtypes.

cancer biology↗

bioRxiv2024

MIIST305 mitigates gastrointestinal acute radiation syndrome injury and ameliorates radiation-induced gut microbiome dysbiosis

High-dose radiation exposure results in gastrointestinal (GI) acute radiation syndrome identified by the destruction of mucosal layer, intestinal epithelial barrier dysfunction, and aberrant inflammatory responses. In addition, radiation causes gut microbiome dysbiosis characterized by diminished microbial diversity, reduction in the abundance of beneficial commensal bacteria, and the spread of bacterial pathogens that trigger the recruitment of immune cells and the production of pro-inflammatory factors that lead to further GI tissue damage. Currently, there are no FDA- approved countermeasures that can treat radiation-induced GI injury. To meet this critical need, Synedgen Inc., has developed a glycopolymer radiomitigator (MIIST305) that is specifically targeted to the GI tract which acts by intercalating into the mucus layer and the glycocalyx of intestinal epithelial cells that could potentially ameliorate the deleterious effects of radiation. Male C57BL/6J adult mice were exposed to 13 Gy total body X-irradiation with 5% bone marrow shielding and MIIST305 was administered on days 1, 3, and 5 post-irradiation. Approximately 85% of the animals survived the irradiation exposure and were apparently healthy until the end of the 30-day study period. In contrast, no control, vehicle-treated animals survived past day 10 at this radiation dose. We show that MIIST305 improved intestinal epithelial barrier function and suppressed systemic inflammatory response mediated by radiation-induced pro-inflammatory cytokines. Taxonomic profiling and community structure of the fecal and colonic mucosa microbiota demonstrated that MIIST305 treatment increased microbial diversity and restored abundance of beneficial commensal bacteria, including Lactobacillus and Bifidobacterium genera, while suppressing potentially pathogenic bacteria compared with vehicle-treated animals. In summary, MIIST305 is a novel GI-targeted therapeutic that greatly enhances survival in mice exposed to lethal radiation and protects the GI tract from injury by restoring a balanced gut microbiota and effectively reducing proinflammatory responses. Further development of this drug as an FDA-approved medical countermeasure will be of critical importance in the event of a radiation public health emergency.

microbiology↗

bioRxiv2023

CellPie: a fast spatial transcriptomics topic discovery method via joint factorization of gene expression and imaging data

Spatially resolved transcriptomics has enabled the study of expression of genes within tissues while retaining their spatial identity. Most spatial transcriptomics technologies generate a matched histopathological image as part of the standard pipeline, providing morphological information that can complement the transcriptomics data. Here we present CellPie, a fast, unsupervised factor discovery method, based on joint non-negative matrix factorisation of spatial RNA transcripts and histological image features.CellPie employs the accelerated hierarchical least squares method to significantly reduce the computational time, enabling efficient application to high-dimensional spatial transcriptomics datasets. We assessed CellPie on two different human cancer types and spatial resolutions, showing an improved performance against published factorisation methods. Additionally, we applied CellPie to a highly resolved Visium HD dataset, demonstrating its high computational efficiency compared to standard non-negative matrix factorisation and other existing methods. Availabilityhttps://github.com/ManchesterBioinference/CellPie

bioinformatics↗

bioRxiv2023

Rapid establishment of a tumor-retained state curtails the contribution of conventional NK cells to anti-tumor immunity in solid cancers

Immune cell dysfunction within the tumor microenvironment undermines the control of cancer progression. NK cells play critical roles in limiting early tumor growth and metastatic disease, however, established cancers contain a phenotypically distinct, tumor-specific NK cell compartment. The temporal dynamics, mechanistic underpinning and functional significance of this tumor NK pool remains incompletely understood. To address this, we exploited photo-labeling, combined with longitudinal transcriptomic and cellular analyses, to interrogate the fate of NK cells after tumor entry. In multiple murine cancer models we reveal that conventional NK cells are continuously recruited into tumors, but rapidly adopt a distinct phenotypic state with features associated with tissue-residency and complete loss of effector functions (including chemokine and cytokine production and cytotoxicity), within 48-72 hrs of entering the tumor. Depletion of NK cells from established tumors did not alter tumor growth, indicating that intratumoral NK cells cease to actively contribute to anti- tumor responses. Furthermore, comparable NK populations were identified in human colorectal cancers, confirming translational relevance and raising the possibility that interventions to reactivate NK cells within tissues may boost anti-tumor immunity in established cancers. Indeed, administration of IL-15:IL-15Ra complexes prevented the loss of NK cell function and improved tumor control, generating intratumoral NK cells with both enhanced tissue-residency characteristics and effector function. Collectively, our data reveals the fate of cNK cells after recruitment into tumors and provides insight into how intratumoral NK cell functions may be revived. SummaryConventional NK cells recruited from the circulation rapidly establish a tissue-resident phenotype defined by impaired cytotoxicity and chemokine production after tumor entry; administration of IL- 15:IL-15R complexes further promotes this tissue-residency programme but maintains core NK cell effector functions within the tumor.

immunology↗

bioRxiv2023

A spatial map of human liver cirrhosis reveals the patho-architecture and gene signatures associated with cell state transitions during liver disease

Liver fibrosis is a major cause of death worldwide. As a progressive step in chronic liver disease, fibrosis is almost always diagnosed too late with limited treatment options. Here, we uncover the spatial transcriptional landscape driving human liver fibrosis using single nuclei RNA and Assay for Transposase-Accessible Chromatin (ATAC) sequencing to deconvolute multi-cell spatial transcriptomic profiling in human liver cirrhosis. Through multi-modal data integration, we define molecular signatures driving cell state transitions in liver disease and define an impaired cellular response and directional trajectory from hepatocytes to cholangiocytes associated with disease remodelling. We identify pro-fibrogenic signatures in non-parenchymal cell subpopulations co-localised within the fibrotic niche and localise transitional cell states at the scar interface. This combined approach provides a spatial atlas of gene regulation and defines molecular signatures associated liver disease for targeted therapeutics or as early diagnostic markers of progressive liver disease.

genomics↗

bioRxiv2022

Pro- and anti-tumour activities of CD146/MCAM in breast cancer result from its heterogeneous expression and association with epithelial to mesenchymal transition

CD146, also known as melanoma cell adhesion molecule (MCAM), is expressed in numerous cancers and has been implicated in the regulation of metastasis. We show that CD146 negatively regulates transendothelial migration (TEM) in breast cancer. This tumour suppressor-like activity is supported by a reduction in MCAM gene expression and increased promoter methylation in tumour tissue compared to normal breast tissue. However, increased CD146/MCAM expression is associated with poor prognosis in breast cancer, a characteristic that is difficult to reconcile with inhibition of TEM by CD146 and its epigenetic silencing. Single cell transcriptome data revealed MCAM expression in multiple cell types, including the tumour vasculature and malignant epithelial cells. MCAM expressing tumour cells were in the minority and expression was associated with epithelial to mesenchymal transition (EMT). Furthermore, gene expression signatures defining invasiveness and a stem cell-like phenotype were most strongly associated with mesenchymal-like tumour cells with low levels of MCAM mRNA, likely to represent an intermediate or hybrid E/M state. Our results show that high levels of MCAM gene expression are associated with poor prognosis in breast cancer because they reflect tumour vascularisation and EMT. However, the inhibitory effects of CD146 on TEM are likely to be weakest in an intermediate state between the epithelial and mesenchymal phenotypes, consistent with highly tumourigenic nature of this population.

cancer biology↗

bioRxiv2021

Genotype and Th2 cells control monocyte to tissue resident macrophage differentiation during nematode infection of the pleural cavity

The recent revolution in tissue-resident macrophage biology has resulted largely from murine studies performed in the C57BL/6 strain. Here, we provide a comprehensive analysis of immune cells in the pleural cavity using both C57BL/6 and BALB/c mice. Unlike C57BL/6 mice, naive tissue-resident Large Cavity Macrophages (LCM) of BALB/c mice failed to fully implement the tissue residency program. Following infection with a pleural-dwelling nematode these pre-existing differences were accentuated with LCM expansion occurring in C57BL/6 but not BALB/c mice. While infection drove monocyte recruitment in both strains, only in C57BL/6 mice were monocytes able to efficiently integrate into the resident pool. Monocyte to macrophage conversion required both T cells and IL-4R signalling. Host genetics are therefore a key influence on tissue resident macrophage biology, and during nematode infection Th2 cells control the differentiation pathway of tissue resident macrophages. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/472661v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@bba5e1org.highwire.dtl.DTLVardef@1876aa4org.highwire.dtl.DTLVardef@16a6b1corg.highwire.dtl.DTLVardef@19e18b6_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

Complexities in the role of acetylation dynamics in modifying inducible gene activation parameters

High levels of histone acetylation are associated with the regulatory elements of active genes, suggesting a link between acetylation and gene activation. However, several studies have shown that histone acetylation dynamics rather than hyperacetylation per se are important determinants in gene activation, particularly at inducible genes. We revisited this model, in the context of EGF-inducible gene expression and found that rather than a simple unifying model, there are two broad classes of genes; one in which high lysine acetylation activity is required for efficient gene activation, and a second group where the opposite occurs and high acetylation activity is inhibitory. We examined the latter class in more detail using EGR2 as a model gene and found that lysine acetylation levels are critical for several activation parameters, including the timing of expression onset, and overall amplitudes of the transcriptional response. In contrast, DUSP1 responds in the canonical manner and its transcriptional activity is promoted by acetylation. Single cell approaches demonstrate heterogenous DUSP1 activation kinetics and that acetylation levels influence allele activation frequencies. Our data therefore point to a complex interplay between acetylation dynamics and target gene induction, which cannot simply be explained by a unified response to acetylation activity. Instead, acetylation level thresholds are an important determinant of transcriptional induction dynamics that are sensed in a gene-specific manner.

molecular biology↗

bioRxiv2020

Foxm1 regulates neuronal progenitor fate during spinal cord regeneration

Mammals have limited tissue regeneration capabilities, particularly in the case of the central nervous system. Spinal cord injuries are often irreversible and lead to the loss of motor and sensory function below the site of the damage [1]. In contrast, amphibians such as Xenopus tadpoles can regenerate a fully functional tail, including their spinal cord, following amputation [2,3]. A hallmark of spinal cord regeneration is the re-activation of Sox2/3+ progenitor cells to promote regrowth of the spinal cord and the generation of new neurons [4,5]. In axolotls, this increase in proliferation is tightly regulated as progenitors switch from a neurogenic to a proliferative division via the planar polarity pathway (PCP) [6-8]. How the balance between self-renewal and differentiation is controlled during regeneration is not well understood. Here, we took an unbiased approach to identify regulators of the cell cycle expressed specifically in X.tropicalis spinal cord after tail amputation by RNAseq. This led to the identification of Foxm1 as a potential key transcription factor for spinal cord regeneration. Foxm1-/- X.tropicalis tadpoles develop normally but cannot regenerate their spinal cords. Using single cell RNAseq and immunolabelling, we show that foxm1+ cells in the regenerating spinal cord undergo a transient but dramatic change in the relative length of the different phases of the cell cycle, suggesting a change in their ability to differentiate. Indeed, we show that Foxm1 does not regulate the rate of progenitor proliferation but is required for neuronal differentiation leading to successful spinal cord regeneration.

developmental biology↗

bioRxiv2017

Classifying cells with Scasat - a tool to analyse single-cell ATAC-seq

MotivationThe assay for transposase-accessible chromatin using sequencing (ATAC-seq) reveals the landscape and principles of DNA regulatory mechanisms by identifying the accessible genome of mammalian cells. When done at single-cell resolution, it provides an insight into the cell-to-cell variability that emerges from identical DNA sequences by identifying the variability in the genomic location of open chromatin sites in each of the cells. Processing of single-cell ATAC-seq requires a number of steps and a simple pipeline to processes and analyse single-cell ATAC-seq is not yet available.\n\nResultsThis paper presents ScAsAT (single-cell ATAC-seq analysis tool), a complete pipeline to process scATAC-seq data with simple steps. The pipeline is developed in a Jupyter notebook environment that holds the executable code along with the necessary description and results. For the initial sequence processing steps, the pipeline uses a number of well-known tools which it executes from a python environment for each of the fastq files. While functions for the data analysis part are mostly written in R, it is robust, flexible, interactive and easy to extend. The pipeline was applied to a single-cell ATAC-seq dataset in order to identify different cell-types from a complex cell mixture. The results from Scasat showed that open chromatin location corresponding to potential regulatory elements can account for cellular heterogeneity and can identify regulatory regions that separates cells from a complex population.\n\nAvailabilityThe jupyter notebook with the complete pipeline applied to the dataset published with this paper are publicly available on the Github (https://github.com/ManchesterBioinference/Scasat). An additional notebook is also provided for analysis of a publicly available dataset. The fastq files are submitted at ArrayExpress database at EMBL-EBI (www.ebi.ac.uk/arrayexpress) under accession number E-MTAB-6116.\n\nContactsyed.murtuzabaker@manchester.ac.uk and magnus.rattray@manchester.ac.uk\n\nSupplementary informationSupplementary data are available at bioRxiv online.

bioinformatics↗