Biology subjects

Rose, C. M.

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

17 recordsLinked to original sources

bioRxiv2026

Integrated morphological, multi-omics, and functional profiling reveals microglial plasticity driven by AD risk genes

Microglia, the resident macrophages of the central nervous system, are highly dynamic cells essential for brain homeostasis. While genome-wide association studies (GWAS) strongly implicate microglial dysfunction in Alzheimer's disease (AD), the mechanistic links coordinating their diverse transcriptional, morphological, and functional states remain poorly understood. Using human induced pluripotent stem cell-derived microglia (iMicroglia) and single-cell RNA sequencing, we identified six distinct transcriptional profiles and mapped them to specific morphological phenotypes via targeted immunofluorescence, establishing a link between microglial morphology and molecular identity. Transcriptomic and morphological profiling further demonstrated profound microglial plasticity, revealing distinct, stimulus-specific responses to AD-relevant pathologies, including Tau PFF, amyloid-beta, and apoptotic neurons. To assess how AD risk variants perturb these states, we performed high-efficiency CRISPR-Cas9 ribonucleoprotein (RNP) knockouts of specific AD GWAS genes. Bulk RNA-seq profiling revealed extensive transcriptional remodeling following genetic perturbation. Crucially, we show that depletion of these AD risk genes disrupts baseline morpho-transcriptomic coupling and fundamentally alters microglial phagocytic capacity. Together, this study reveals how AD GWAS genes may drive microglia into dysfunctional states characterized by altered morphology, distinct multi-omic signatures, and impaired functions.

neuroscience↗

bioRxiv2026

Real-time artificial intelligence prediction of peptide characteristics and MSFragger search improves multiplexed quantification of non-canonical HLA presented peptides in clear cell renal cell carcinoma.

Non-canonical HLA-presented peptides are promising therapeutic targets, but their low abundance makes them difficult to reproducibly identify and quantify, particularly in multiplexed immunopeptidomics workflows. Here we present MIRA-MS (Model-Informed Real-time Acquisition for Mass Spectrometry), a real-time acquisition strategy that combines fragment ion-indexed database searching with artificial intelligence-based prediction of peptide fragmentation and retention time to guide quantitative scan acquisition. In a clear cell renal cell carcinoma model, MIRA-MS increased the number of quantified non-canonical immunopeptides by 97-107% relative to standard acquisition methods while also improving recovery of canonical peptides by 45-89%. These results establish real-time AI-guided acquisition as a powerful approach for deeper and more reproducible immunopeptidome profiling.

cancer biology↗

bioRxiv2026

Direct RNA Sequencing reveals epitranscriptomic regulation of brain cells and Alzheimer's Disease pathology

Alternative mRNA splicing and post-transcriptional RNA modification are key mechanisms that regulate transcript function; however, their role in neuronal activity and neurodegenerative disease remains poorly defined. In this study, we evaluated two nanopore-based long-read sequencing (LR-seq) formats: cDNA-PCR sequencing (CPS) and direct RNA sequencing (DRS). We then applied DRS to profile both full-length isoforms and RNA modifications in major brain cell types derived from induced pluripotent stem cells (iPSCs) and post-mortem Alzheimers disease (AD) brains. Relative to CPS, DRS achieved higher accuracy and sensitivity for transcript quantification, de novo transcript model construction, and open reading frame (ORF) annotation across neuropathological gene sets. Focusing on iPSC-derived neurons, we built a multi-omic atlas to connect transcriptional output with translational engagement and protein abundance, by integrating DRS-based mRNA abundance, N6-methyladenosine (m6A) status and poly(A) tail length with ribosome profiling (Ribo-seq) and mass spectrometry (MS). The combination of DRS and Ribo-seq data demonstrated synergism in predicting protein abundance. This analysis also uncovered a significant inverse relationship between m6A modification and mRNA abundance, which was dependent on the engagement of the ribosomal A-site. Lastly, we applied DRS to the epitranscriptomic analysis of AD brain samples, demonstrating that m6A profiles can be used to distinguish early-versus late-stage disease.

neuroscience↗

bioRxiv2026

Phosphorylated ubiquitin is a secondary messenger and an epigenetic mark mediating mitochondria to nucleus signaling

AbstractParkinsons disease (PD) is commonly associated with dysfunctional mitochondrial homeostasis. PINK1, a S/T kinase mutated in early-onset PD, generates phosphoserine 65 ubiquitin (pS65Ub) on damaged mitochondria facilitating their removal. Here, we show that pS65Ub translocates into the nucleus after generation at damaged mitochondria and is directly attached to substrates by resident E3 ligases. Histone H2A is a major substrate and is modified at lysine 119 (H2AK119) by the polycomb silencer, E3 ligase RING1B. At nucleosomes, pS65Ub simultaneously suppresses RING1B and potentiates H2A deubiquitinases USP16 and USP21. Epigenetic profiling and RNA sequencing reveal that pS65Ub is enriched at the promoters of poorly expressed yet dynamically regulated genes and is associated with H2AK119ub depletion. Functionally, we show that pS65Ub enrichment drives polycomb target gene expression, which accelerates the maturation of dopaminergic neurons. Importantly, post-mortem PD brains exhibit elevated nuclear pS65Ub, potentially linking nuclear pS65Ub accumulation with disease pathogenesis. Together, these data indicate that pS65Ub generated at damaged mitochondria regulates fundamental cellular processes at distant sites.

cell biology↗

bioRxiv2025

Architecture and Function of Holocentric CENP-A-Independent Kinetochores

Kinetochores are essential macromolecular complexes that anchor chromosomes to the mitotic spindle to ensure faithful cell division1. Despite their critical role, the structural organization of kinetochores assembled on centromeres with vastly distinct architectures across diverse species remains poorly understood2,3. To address this question, we determined the cryo-EM structures of the inner kinetochore (CCAN) from the silkmoth Bombyx mori, an insect that lacks the canonical centromere-specifying histone variant CENP-A and exhibits chromosome-wide centromeric activity (holocentric). Our analysis reveals that B. mori CCAN assembles via atypical histone-fold protein dimerization into a self-contained, head-to-head dimer that topologically entraps and loops DNA, creating a point-centromere-like architecture. This structure also incorporates four previously uncharacterized Centromeric Subunit proteins that are evolutionarily repurposed from the outer kinetochore Dam1/DASH complex. Our work establishes this self-contained CCAN dimer as a key structural unit that forms the basis of a holocentric organization and suggests that large-scale centromere architectures can emerge from the modular arrangement of such discrete kinetochore units.

cell biology↗

bioRxiv2025

Epithelial tumor cells utilize mast cell-derived histamine to regulate perineural invasion

Cancer dissemination by perineural invasion (PNI) is associated with poor outcomes in epithelial malignancies, yet the cellular interactions critical to this process are not fully defined. Single-cell transcriptomic analysis of cutaneous squamous cell carcinoma (cSCC) with PNI highlighted KITLG-KIT signaling activation between keratinocytes and mast cells. Additionally, we observed increased expression of HRH1 on tumor cells, which encodes the H1 histamine receptor. We confirmed these changes in other cancers, including PNI-positive hepatobiliary and oral mucosal tumors. Histamine enhanced tumor invasion into nerve in organoids that recapitulate key features of PNI, an effect rescued by H1-antihistamines. Mechanistically, broad upregulation of matrix metalloproteinases (MMPs) through P38 activation underscored histamine-mediated PNI by enabling collagen degradation in the nerve sheath. Examination of multiple cancer types with PNI showed co-expression of HRH1 and MMP2 on tumor cells as well as type IV collagen loss in involved nerves. Retrospective analysis of >15,000 patient health records in two independent databases demonstrated that H1-antihistamine use improved overall survival and immunotherapy response in cancers that spread by PNI. Together, these data reveal a critical role for mast cells in PNI and present a new therapeutic strategy for targeting this process in epithelial cancers.

cancer biology↗

bioRxiv2025

A microbiota-derived bile acid modulates biofilm formation by the probiotic strain Escherichia coli Nissle 1917

Bacteria that colonize the human gut must withstand a variety of stressors, including detergent-like compounds known as bile acids. Here, we investigated how bile acids found in the human cecum and colon impact the behavior of the probiotic strain Escherichia coli Nissle 1917 (EcN). We found that lithocholic acid (LCA), which is a microbiota-derived secondary bile acid, promotes the formation of a distinctive surface-coating biofilm by EcN, including on an organoid-derived model of the human colonic epithelium. Mechanistic investigations revealed that LCA upregulates the production of several components of flagella, which are essential for LCA-induced biofilm formation and form part of the biofilm matrix. Furthermore, LCA-induced biofilm formation helps EcN compete against certain pathogenic strains. Taken together, our findings shed light on how an abundant colonic metabolite influences the behavior of a clinically-proven probiotic strain, triggering the formation of biofilms that may contribute to pathogen suppression.

microbiology↗

bioRxiv2025

Nova: A library for rapid development of mass spectrometry software applications

Nova is a software library for the reading, writing, and management of mass spectrometry data natively in the C# language. It complements similar software libraries ubiquitously used in application development for C++, Python, and Java. Few software libraries and resources for mass spectrometry data analysis have been developed for C# relative to other languages. C#, however, remains the dominant language of choice for development of real time mass spectrometry (RTMS) analysis and instrument control applications, illustrating the need for native C# libraries when developing RTMS software. Nova provides fast, easy-to-use structures and classes built upon interfaces that support open community standards, and are easily extensible for current or future mass spectrometry software development needs.

biochemistry↗

bioRxiv2025

Cell-Type-Specific Surfaceome Profiling of 100-500 Isolated Cells using a Droplet-Based Magnetic Affinity Purification System

Cell surface proteins (CSPs) represent an important source of biomarkers and therapeutic targets. However, due to the inherent sensitivity limitations of existing technologies, tissue and cell-type-specific surfaceomes remain poorly characterized, especially in the context of human diseases. Herein, we develop nanoMAPS (nanoscale Magnetic Affinity Purification System), a miniaturized proteomic sample preparation method for surfaceome profiling of as few as 100-500 cells (1000x to 100,000x lower than existing technologies). We demonstrate that the miniaturization of magnetic bead-based affinity purification inside a single droplet can efficiently improve the recovery of surface proteins and reduce non-specific absorption of intracellular proteins. By applying nanoMAPS to human immune cells isolated from PBMCs, we demonstrate robust identification of both well-known cell-type-specific surface markers and candidate proteins. We establish nanoMAPS as a promising platform to expand surface proteomics from cultured cells to primary cells isolated from patients or mouse models.

systems biology↗

bioRxiv2024

Offset mass carrier proteome improves quantification of multiplexed single cell proteomics

Multiplexed single cell proteomics by mass spectrometry (scpMS) approaches currently offer the highest throughput as measured by cells analyzed per day. These methods employ isobaric labels and typically a carrier proteome - a sample added at 20-500x the single cell level that improves peptide sampling and identification. Peptides from the carrier and single cell proteomes exist within the same precursor isotopic cluster and are co-isolated for identification and quantification. This represents a challenge as high levels of carrier proteome limit the sampling of peptide ions from single cell samples and can potentially lead to decreased accuracy of quantitative measurements. Here, we address this limitation by introducing a triggered by offset mass acquisition method for scpMS (toma-scpMS) that utilizes a carrier proteome labeled with non-isobaric tags that have the same chemical composition but different mass as the labels used for quantitative multiplexing. Within toma-scpMS the carrier proteome and single cell proteome are separated at the precursor level, enabling separate isolation, fragmentation, and quantitation of the single cell samples. To enable this workflow we implemented a custom data acquisition scheme within inSeqAPI, an instrument application programming interface program, that performed real-time identification of carrier proteome peptides and subsequent triggering of offset single cell quantification scans. We demonstrate that toma-scpMS is more robust to high-levels of carrier proteome and offers superior quantitative accuracy as compared to traditional multiplexed scpMS approaches when similar carrier proteome levels are employed.

systems biology↗

bioRxiv2024

diaPASEF analysis for HLA-I peptides enables quantification of common cancer neoantigens

Human leukocyte antigen class I (HLA-I) molecules present short peptide sequences from endogenous or foreign proteins to cytotoxic T cells. The low abundance of HLA-I peptides poses significant technical challenges for their identification and accurate quantification. While mass spectrometry (MS) is currently a method of choice for direct system-wide identification of cellular immunopeptidome, there is still a need for enhanced sensitivity in detecting and quantifying tumor specific epitopes. As gas phase separation in data-dependent MS data acquisition (DDA) increased HLA-I peptide detection by up to 50%, here, we aimed to evaluate the performance of data-independent acquisition (DIA) in combination with ion mobility (diaPASEF) for high-sensitivity identification of HLA presented peptides. Our streamlined diaPASEF workflow enabled identification of 11,412 unique peptides from 12.5 million A375 cells and 3,426 8-11mers from as low as 500,000 cells with high reproducibility. By taking advantage of HLA binder-specific in-silico predicted spectral libraries, we were able to further increase the number of identified HLA-I peptides. We applied SILAC-DIA to a mixture of labeled HLA-I peptides, calculated heavy-to-light ratios for 7,742 peptides across 5 conditions and demonstrated that diaPASEF achieves high quantitative accuracy up to 4-fold dilution. Finally, we identified and quantified shared neoantigens in a monoallelic C1R cell line model. By spiking in heavy synthetic peptides, we verified the identification of the peptide sequences and calculated relative abundances for 13 neoantigens. Taken together, diaPASEF analysis workflows for HLA-I peptides can increase the peptidome coverage for lower sample amounts. The sensitivity and quantitative precision provided by DIA can enable the detection and quantification of less abundant peptide species such as neoantigens across samples from the same background.

cancer biology↗

bioRxiv2023

Targeting the Hippo pathway in cancers via ubiquitination dependent TEAD degradation

The Hippo pathway is among the most frequently altered key signaling pathways in cancer. TEAD1-4 are essential transcription factors and key downstream effectors in the Hippo pathway in human cells. Here, we identified RNF146 as a ubiquitin ligase (E3) of TEADs, which negatively regulates their stability in cells through proteasome-mediated degradation. We show that RNF146-mediated TEAD ubiquitination is dependent on the TEAD PARylation state. We further validated the genetic interaction between RNF146 and the Hippo pathway in cancer cell lines and the model organism Drosophila melanogaster. Despite the RNF146 and proteasome-mediated degradation mechanisms, TEADs are stable proteins with a long half-life in cells. We demonstrate that degradation of TEADs can be greatly enhanced pharmacologically with heterobifunctional chemical inducers of protein degradation (CIDEs). These TEAD-CIDEs can effectively suppress activation of YAP/TAZ target genes in a dose-dependent manner and exhibit significant anti-proliferative effects in YAP/TAZ-dependent tumor cells, thus phenocopying the effect of genetic ablation of TEAD protein. Collectively, this study demonstrates that the ubiquitin-proteasome system plays an important role in regulating TEAD functions and provides a proof-of-concept demonstration that pharmacologically induced TEAD ubiquitination could be leveraged to target YAP/TAZ-driven cancers.

cancer biology↗

bioRxiv2023

Increasing the Throughput and Reproducibility of Activity-Based Proteome Profiling Studies with Hyperplexing and Intelligent Data Acquisition

Intelligent data acquisition (IDA) strategies, such as real-time database search (RTS), have improved the depth of proteome coverage for experiments that utilize isobaric labels and gas phase purification techniques (i.e., SPS-MS3). While most applications of IDA have been focused on the analysis of protein abundance, these approaches have recently been applied to activity-based proteome profiling (ABPP) studies aimed at characterization of protein site engagement by small molecules. In this work, we extend IDA capabilities offered by vendor software through a program called InSeqAPI. First, we demonstrate robust performance of InSeqAPI in the analysis of biotinylated cysteine peptides from ABPP experiments. Then, we describe PairQuant, a method within InSeqAPI designed for the hyperplexing approach that utilizes protein-level isotopic labeling and peptide-level TMT labeling. PairQuant allows for TMT analysis of 36 conditions in a single sample and achieves [~]98% coverage of both peptide pair partners in a hyperplexed experiment as well as a 40% improvement in the number of quantified cysteine sites compared to non-RTS acquisition. We applied this method in ABPP study of ligandable cysteine sites in the nucleus leading to an identification of additional druggable sites on protein-and DNA-interaction domains of transcription regulators and on nuclear ubiquitin ligases.

biochemistry↗

bioRxiv2023

An RNA Damage Response Network Mediates the Lethality of 5-FU in Clinically Relevant Tumor Types

5-fluorouracil (5-FU) is a successful and broadly used anti-cancer therapeutic. A major mechanism of action of 5-FU is thought to be through thymidylate synthase (TYMS) inhibition resulting in dTTP depletion and activation of the DNA damage response. This suggests that 5-FU should synergize with other DNA damaging agents. However, we found that combinations of 5-FU and oxaliplatin or irinotecan failed to display any evidence of synergy in clinical trials, and resulted in sub-additive killing in a panel of colorectal cancer (CRC) cell lines. In seeking to understand this antagonism, we unexpectedly found that an RNA damage response during ribosome biogenesis dominates the drugs efficacy in tumor types for which 5-FU shows clinical benefit. 5-FU has an inherent bias for RNA incorporation, and blocking this greatly reduced drug-induced lethality, indicating that accumulation of damaged RNA is more deleterious than the lack of new RNA synthesis. Using 5-FU metabolites that specifically incorporate into either RNA or DNA revealed that CRC cell lines and patient-derived colorectal cancer organoids are inherently more sensitive to RNA damage. This difference held true in cell lines from other tissues in which 5-FU has shown clinical utility, whereas cell lines from tumor tissues that lack clinical 5-FU responsiveness typically showed greater sensitivity to the drugs DNA damage effects. Analysis of changes in the phosphoproteome and ubiquitinome shows RNA damage triggers the selective ubiquitination of multiple ribosomal proteins leading to autophagy-dependent rRNA catabolism and proteasome-dependent degradation of ubiquitinated ribosome proteins. Further, RNA damage response to 5-FU is selectively enhanced by compounds that promote ribosome biogenesis, such as KDM2A inhibitors. These results demonstrate the presence of a strong RNA damage response linked to apoptotic cell death, with clear utility of combinatorially targeting this response in cancer therapy.

cancer biology↗

bioRxiv2022

HLApollo: A superior transformer model for pan-allelic peptide-MHC-I presentation prediction, with diverse negative coverage, deconvolution and protein language features.

Antigen presentation on MHC class I (MHC-I) is key to the adaptive immune response to cancerous cells. Computational prediction of peptide presentation by MHC-I has enabled individualized cancer immunotherapies. Here, we introduce HLApollo, a transformer-based approach with end-to-end modeling of MHC-I sequence, deconvolution, and flanking sequences. To achieve this, we develop a novel training strategy, negative set switching, which greatly reduces overfitting to falsely presumed negatives that are necessarily found in presentation datasets. HLApollo shows a meaningful improvement compared to recent MHC-I models on peptide presentation (20.19% average precision (AP)) and immunogenicity (4.1% AP). As expected, adding gene expression boosts the performance of HLApollo. More interestingly, we show that introduction of features from a protein language model, ESM 1b, remarkably recoups much of the benefits of gene expression in absence of true expression measurements. Finally, we demonstrate excellent pan-allelic generalization, and introduce a framework for estimating the expected accuracy of HLApollo for untrained alleles. This guides the use of HLApollo in a clinical setting, where rare alleles may be observed in some subjects, particularly for underrepresented minorities.

immunology↗

bioRxiv2022

Discovery of prevalent, clinically actionable tumor neoepitopes via integrated biochemical and cell-based platforms

Strategies for maximizing the potency and specificity of cancer immunotherapies have sparked efforts to identify recurrent epitopes presented in the context of defined tumor-associated neoantigens. Discovering these "neoepitopes" can be difficult owing to the limited number of peptides that arise from a single point mutation, a low number of copies presented on the cell surface, and variable binding specificity of the human leukocyte antigen (HLA) class I complex. Due to these limitations, many discovery efforts focus on identifying neoepitopes from a small number of cancer neoantigens in the context of few HLA alleles. Here we describe a systematic workflow to characterize binding and presentation of neoepitopes derived from 47 shared cancer neoantigens in the context of 15 HLA alleles. Through the development of a high-throughput neoepitope-HLA binding assay, we surveyed 24,149 candidate neoepitope-HLA combinations resulting in 587 stable complexes. These data were supplemented by computational prediction that identified an additional 257 neoepitope-HLA pairs, resulting in a total of 844 unique combinations. We used these results to build sensitive targeted mass spectrometry assays to validate neoepitope presentation on a panel of HLA-I monoallelic cell lines engineered to express neoantigens of interest as a single polypeptide. Altogether, our analyses detected 84 unique neoepitope-HLA pairs derived from 37 shared cancer neoantigens and presented across 12 HLA alleles. We subsequently identified multiple TCRs which specifically recognized two of these neoantigen-HLA combinations. Finally, these novel TCRs were utilized to elicit a T cell response suggesting that these neoepitopes are likely to be immunogenic. Together these data represent a validated, extensive resource of therapeutically relevant neoepitopes and the HLA context in which they can be targeted.

cancer biology↗

bioRxiv2020

Sensitive and quantitative detection of MHC-I displayed neoepitopes using a semi-automated workflow and TOMAHAQ mass spectrometry

Advances in several key technologies, including MHC peptidomics, has helped fuel our understanding of basic immune regulatory mechanisms and identify T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. This multi-step analytical process remains challenging, and throughput and reproducibility are paramount for rapidly characterizing multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines, can be enriched in a semi-automated fashion on reusable, dry-storage, customized antibody cartridges. TOMAHAQ, a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation.

cancer biology↗