Biology subjects

Kelly, M. C.

Publications and source records attributed to Kelly, M. C..

10 recordsLinked to original sources

bioRxiv2025

Long-read sequencing of single cell-derived melanoma subclones reveals divergent and parallel genomic and epigenomic evolutionary trajectories

Tumor evolution is driven by various mutational processes, ranging from single-nucleotide vari- ants (SNVs) to large structural variants (SVs) to dynamic shifts in DNA methylation. Current short-read sequencing methods struggle to accurately capture the full spectrum of these genomic and epigenomic alter- ations due to inherent technical limitations. To overcome that, here we introduce an approach for long-read sequencing of single-cell derived subclones, and use it to profile 23 subclones of a mouse melanoma cell line, characterized with distinct growth phenotypes and treatment responses. We develop a computational frame- work for harmonization and joint analysis of different variant types in the evolutionary context. Uniquely, our framework enables detection of recurrent amplifications of putative driver genes, generated by indepen- dent SVs across different lineages, suggesting parallel evolution. In addition, our approach revealed gradual and lineage-specific methylation changes associated with aggressive clonal phenotypes. We also show our set of phylogeny-constrained variant calls along with openly released sequencing data can be a valuable resource for the development of new computational methods.

genomics↗

bioRxiv2025

Inhibition of MAPK signaling suppresses cytomegalovirus reactivation in CD34+ Kasumi-3 cells

Reactivation of latent human cytomegalovirus (CMV) can lead to severe complications in individuals with dysregulated immune systems. While antiviral therapies for CMV are approved, these compounds are limited by their toxicity and inability to specifically target the latent reservoir or prevent reactivation. Herein we show that CMV reactivation in Kasumi-3 cells, a CD34+ hematopoietic cell line, requires mitogen-activated protein kinase (MAPK) activation. Importantly, pharmacological inhibition of the MAPK signaling pathway, including MEK and ERK, restricts viral reactivation in Kasumi-3 cells. In sum, our findings show MAPK signaling is critical for CMV reactivation, revealing a potential avenue for therapeutic intervention to prevent viral reactivation and downstream pathogenesis that is often detrimental for immunosuppressed and immunocompromised patients.

microbiology↗

bioRxiv2025

Spatial profiling identifies regionally distinct microenvironments and targetable immunosuppressive mechanisms in pediatric osteosarcoma pulmonary metastases.

Osteosarcoma is the most common malignant bone tumor in young patients and remains a significant clinical challenge, particularly in the context of metastatic disease. Despite extensive documentation of genomic alterations in osteosarcoma, studies detailing the immunosuppressive mechanisms within the metastatic osteosarcoma microenvironment are lacking. Our objective was to characterize the spatial transcriptional landscape of metastatic osteosarcoma to reveal these immunosuppressive mechanisms and identify promising therapeutic targets. Here, we performed spatial transcriptional profiling on a cohort of osteosarcoma pulmonary metastases from pediatric patients. We reveal a conserved spatial gene expression pattern resembling a foreign body granuloma, characterized by peripheral inflammatory signaling, fibrocollagenous encapsulation, lymphocyte exclusion, and peritumoral macrophage accumulation. We also show that the intratumoral microenvironment of these lesions lack inflammatory signaling. Additionally, we identified CXCR4 as an actionable immunomodulatory target that bridges both the intratumoral and extratumoral microenvironments and highlights the spatial heterogeneity and complexity of this pathway. Collectively, this study reveals that metastatic osteosarcoma specimens are comprised of multiple regionally distinct immunosuppressive microenvironments.

cancer biology↗

bioRxiv2024

Estimating and correcting index hopping misassignments in single-cell RNA-seq data

BackgroundIndex hopping causes read assignment errors in data from multiplexed sequencing libraries. This issue has become more prevalent with the widespread use of high-capacity sequencers and highly multiplexed single-cell RNA sequencing (scRNA- seq). ResultsWe conducted deep, plate-based scRNA-seq on a mixed population of mouse skin cells. Analysis of transcriptomes from 1152 cells identified four distinct cell types. To estimate the error rate in sample assignment due to index hopping, we employed differential expression analysis to identify signature genes that were highly and specifically expressed in each cell type. We quantified the proportion of misassigned reads by examining the detection rates of signature genes in other cell types. Remarkably, regardless of gene expression levels, we estimated that 0.65% of reads per gene were assigned to incorrect cell across our data. To computationally compensate for index hopping, we developed a simple correction method wherein, for each gene, 0.65% of the librarys average expression level was subtracted from the expression in each cell. This correction had notable effects on transcriptome analyses, including increased cell-cell clustering distance and alterations in intermediate state assignments of cell differentiation. ConclusionsIndex hopping misassignments are measurable and can impact the experimental interpretation of sequencing results. We devised a straightforward method to estimate and correct for the index hopping rate by quantifying misassigned genes in distinct cell types within an scRNA-seq library. This approach can be applied to any barcoded, multiplexed scRNA-seq library containing cells with distinct expression profiles, allowing for correction of the expression matrix before conducting biological analysis.

genomics↗

bioRxiv2024

A conserved cell-type gradient across the human mediodorsal and paraventricular thalamus

The mediodorsal thalamus (MD) and adjacent midline nuclei are important for cognition and mental illness, but their cellular composition is not well defined. Using single-nucleus and spatial transcriptomics, we identified a conserved excitatory neuron gradient, with distinct spatial mapping of individual clusters. One end of the gradient was expanded in human MD compared to mice, which may be related to the expansion of granular prefrontal cortex in hominids. Moreover, neurons preferentially mapping onto the parvocellular division MD were associated with genetic risk for schizophrenia and bipolar disorder. Midbrain-derived inhibitory interneurons were enriched in human MD and implicated in genetic risk for major depressive disorder.

neuroscience↗

bioRxiv2023

Developmental conversion of thymocyte-attracting cells into self-antigen-displaying cells in embryonic thymus medulla epithelium

Thymus medulla epithelium establishes immune self-tolerance and comprises diverse cellular subsets. Functionally relevant medullary thymic epithelial cells (mTECs) include a self-antigen-displaying subset that exhibits genome-wide promiscuous gene expression promoted by the nuclear protein Aire and that resembles a mosaic of extrathymic cells including mucosal tuft cells. An additional mTEC subset produces the chemokine CCL21, thereby attracting positively selected thymocytes from the cortex to the medulla. Both self-antigen-displaying and thymocyte-attracting mTEC subsets are essential for self-tolerance. Here we identify a developmental pathway by which mTECs gain their diversity in functionally distinct subsets. We show that CCL21-expressing mTECs arise early during thymus ontogeny. Fate-mapping analysis reveals that self-antigen-displaying mTECs, including Aire-expressing mTECs and thymic tuft cells, are derived from CCL21-expressing cells. The differentiation capability of CCL21-expressing embryonic mTECs is verified in reaggregate thymus experiments. These results indicate that CCL21-expressing embryonic mTECs carry a developmental potential to give rise to self-antigen-displaying mTECs, revealing that the sequential conversion of thymocyte-attracting subset into self-antigen-displaying subset serves to assemble functional diversity in the thymus medulla epithelium.

immunology↗

bioRxiv2022

A Multi-scale, Multiomic Atlas of Human Normal and Follicular Lymphoma Lymph Nodes

Reference atlases, molecular and spatial maps of mammalian tissues, are critical resources for discovery efforts and translational research. Their utility is dependent on operationalizing the resulting data by identifying cell types, histological patterns, and predictive biomarkers underlying health and disease. The human lymph node (LN) offers a compelling use case because of its importance in immunity, structural and cellular diversity, and neoplastic involvement. One hematological malignancy, follicular lymphoma (FL), evolves from developmentally blocked germinal center B cells residing in and trafficking through these tissues. To promote survival and immune escape, tumor B cells undergo significant genetic changes and extensively remodel the lymphoid microenvironment. Here, we present an integrated portrait of healthy and FL LNs using multiple genomic and advanced imaging technologies. By leveraging the strengths of each platform, we identified several tumor-specific features and microenvironmental patterns enriched in individuals who experience early relapse, the most high-risk of FL patients.

cancer biology↗

bioRxiv2021

A single-cell reference atlas delineates CD4+ T cell subtype-specific adaptation during acute and chronic viral infections

CD4+ T cells are critical orchestrators of immune responses against a large variety of pathogens, including viruses. The multifaceted roles of CD4+ T cells, including their help to innate cells, CD8+ T and B cells and their support for long-lived immunity rely on a profound functional heterogeneity. While multiple CD4+ T cell subtypes and their key transcriptional regulators have been identified, there is a lack of consistent definition for CD4+ T cell transcriptional states. In addition, the progressive changes affecting CD4+ T cell subtypes during and after immune responses remain poorly defined. Taking advantage of single-cell transcriptomics, efficient computational methods, and robust animal models, we characterize the transcriptional landscape of CD4+ T cells responding to self-resolving and chronic viral infections. We build a comprehensive atlas of virus-specific CD4+ T cells and their evolution over time, and identify six major distinct cell states that are consistently observed in acute and chronic infections. During the course of acute infection, T cell composition progressively changes from effector to memory states, with subtype-specific gene modules and kinetics. Conversely, T cells in persistent infections fail to transition from effector to memory states, and acquire distinct, chronicity-associated transcriptional programs. By single-cell T cell receptor (TCR) sequencing analysis, we characterize the clonal structure of virus-specific CD4+ T cells across individuals and T cell subtypes. We find that virus-specific CD4+ T cell responses are mainly private across individuals and that most T cells differentiate into all subtypes independently of their TCR, in both acute and chronic infections. Finally, we show that our CD4+ T cell atlas can be used as a reference to accurately interpret cell states in external single-cell datasets. Overall, this study describes a previously unappreciated level of adaptation of the transcriptional states of CD4+ T cells responding to viruses and provides a new computational resource for CD4+ T cell analysis, available online at https://spica.unil.ch.

immunology↗

bioRxiv2021

Profiles of expressed mutations in single cells reveal patterns of tumor evolution and therapeutic impact of intratumor heterogeneity

Advances in single-cell RNA sequencing (scRNAseq) technologies uncovered an unexpected complexity in tumors, underlining the relevance of intratumor heterogeneity to cancer progression and therapeutic resistance. Heterogeneity in the mutational composition of cancer cells is a result of distinct (sub)clonal expansions, each with a distinct metastatic potential and resistance to specific treatments. Unfortunately, due to their low read coverage per cell, scRNAseq datasets are too sparse and noisy to be used for detecting expressed mutations in single cells. Additionally, the large number of cells and mutations present in typical scRNAseq datasets are too large for available computational tools to, e.g., infer distinct subclones, lineages or trajectories in a tumor. Finally, there are no principled methods to assess distinct subclones inferred through single-cell sequencing data and the genomic alterations that seed and potentially cause them. Here we present Trisicell, a computational toolkit for scalable mutational intratumor heterogeneity inference and assessment from scRNAseq as well as single-cell genome or exome sequencing data. Trisicell allows reliable identification of distinct clonal lineages of a tumor, offering the ability to focus on the most important subclones and the genomic alterations that are associated with tumor proliferation. We comprehensively assessed Trisicell on a melanoma model by comparing distinct lineages and subclones it identifies on scRNAseq data, to those inferred using matching bulk whole exome (bWES) and transcriptome (bWTS) sequencing data from clonal sublines derived from single cells. Our results demonstrate that distinct lineages and subclones of a tumor can be reliably inferred and evaluated based on mutation calls from scRNAseq data through the use of Trisicell. Additionally, they reveal a strong correlation between aggressiveness and mutational composition, both across the inferred subclones, and among human melanomas. We also applied Trisicell to infer and evaluate distinct subclonal expansion patterns of the same mouse melanoma model after treatment with immune checkpoint blockade (ICB). After integratively analyzing our cell-specific mutation calls with their expression profiles, we observed that each subclone with a distinct set of novel somatic mutations is strongly associated with a specific developmental status. Moreover, each subclone had developed a unique ICB-resistance mechanism. These results demonstrate that Trisicell can robustly utilize scRNAseq data to delineate intratumor heterogeneity and help understand biological mechanisms underlying tumor progression and resistance to therapy.

bioinformatics↗

bioRxiv2020

Urine single cell RNA-sequencing in focal segmental glomerulosclerosis reveals inflammatory signatures in immune cells and podocytes

The diagnosis of focal segmental glomerulosclerosis (FSGS) requires a renal biopsy, which is invasive and can be problematic in children and in some adults. We used single cell RNA-sequencing to explore disease-related cellular signatures in 23 urine samples from 12 FSGS subjects. We identified immune cells, predominantly monocytes, and renal epithelial cells, including podocytes. Analysis revealed M1 and M2 monocyte subsets, and podocytes showing high expression of genes for epithelial-to-mesenchymal transition (EMT). We confirmed M1 and M2 gene signatures using published monocyte/macrophage data from lupus nephritis and cancer. Using renal transcriptomic data from the Nephrotic Syndrome Study Network (NEPTUNE), we found that urine cell immune and EMT signature genes showed higher expression in FSGS biopsies compared to minimal change disease biopsies. These results suggest that urine cell profiling may serve as a diagnostic and prognostic tool in nephrotic syndrome and aid in identifying novel biomarkers and developing personalized therapeutic strategies.

immunology↗