Biology subjects

Makhmut, A.

Publications and source records attributed to Makhmut, A..

5 recordsLinked to original sources

bioRxiv2025

Ultrasensitive proteomics uncovers nociceptor diversity and novel pain targets

The richness of our somatosensory experience is reflected in the functional diversity of somatic sensory neurons. Single-cell sequencing (scRNA) of sensory neurons has revealed a molecular basis for such diversity1-3. However, sensory neuron diversity has yet to be captured at the level of the proteome. Here, we combined electrophysiology with deep visual proteomics (DVP)4 to quantify over 6,000 proteins from phenotypically-defined sensory neurons and identified novel proteomic markers of sensory neuron subtypes. Comparative analysis revealed both concordance and meaningful divergence between transcriptomes and proteomes. We further show that up to 3,000 proteins can be quantified from one-fourth of a single neuron, demonstrating subset-specific protein signatures. In culture, nociceptive neurons can be acutely sensitized to mechanical stimuli by nerve growth factor (NGF) which normally drives inflammatory pain in vivo5. Indeed, overnight exposure of peptidergic nociceptors to NGF and a protein kinase C (PKC) activator produced functional sensitization associated with proteome changes. Functional knockdown experiments identified the up-regulated B3GNT2 enzyme as a potential effector of nociceptor sensitization. In summary, we present a high-resolution proteomic resource linking molecular identity to function, enabling the discovery of novel mechanisms underlying somatic sensation and pain sensitization.

systems biology↗

bioRxiv2025

Deep spatial proteomics of ovarian cancer precursor lesions delineates early disease changes and cell-of-origin signatures

High-grade serous ovarian cancer (HGSOC) is a devastating disease that is frequently detected at an incurable stage. Advances in ultrasensitive mass spectrometry-based spatial proteomics have provided a unique opportunity to uncover early molecular events in tumorigenesis and common dysregulated pathways with high therapeutic potential. Here, we present a comprehensive proteomic analysis of serous tubal intraepithelial carcinoma (STIC), the HGSOC precursor lesion, covering more than 10,000 proteins. We found that STICs and concurrent invasive carcinomas were indistinguishable at the global proteomic level, revealing a similar level of molecular heterogeneity. Using cell-type resolved tissue proteomics, we revealed strong cell-of-origin signatures preserved in STICs and invasive tumors and identified early dysregulated pathways of therapeutic relevance, such as an onco-metabolic increase in cholesterol biosynthesis. Finally, we uncovered substantial remodeling of the co-evolving tumor microenvironment, affecting approximately one-third of the stromal proteome, and derived a common signature associated with progressive immunosuppression and extracellular matrix restructuring. In summary, our study highlights the power of spatially resolved quantitative proteomics to dissect the molecular underpinnings of early carcinogenesis and provides a rich proteomic resource for future biomarker and drug target research in ovarian cancer.

systems biology↗

bioRxiv2023

An automated and fast sample preparation workflow for laser microdissection guided ultrasensitive proteomics

Spatial tissue proteomics integrating whole-slide imaging, laser microdissection and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE(R) robotic system, which has the capacity to process 192 samples in three hours. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows on-the-fly sample clean-up, particularly pertinent for laser microdissection workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell and epithelial microregions of 4,000 {micro}m2 to a depth of [~]2,000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.

systems biology↗

bioRxiv2023

A framework for ultra-low input spatial tissue proteomics

Spatial tissue proteomics combining microscopy-based cell phenotyping with ultra-sensitive mass spectrometry (MS)-based proteomics is an emerging and powerful concept for the study of cell function and heterogeneity in health and disease. However, optimized workflows that preserve morphological information for image-based phenotype discovery and maximize proteome coverage of few or even single cells from laser microdissected archival tissue, are currently lacking. Here, we report a robust and scalable workflow for the proteomic analysis of ultra-low input formalin-fixed, paraffin-embedded (FFPE) material. Benchmarking in the murine liver resulted in up to 2,000 quantified proteins from single hepatocyte contours and nearly 5,000 proteins from 50-cell regions with high quantitative reproducibility. Applied to human tonsil, we profiled 146 microregions including spatially defined T and B lymphocyte niches and quantified cell type specific markers, cytokines, immune cell regulators and transcription factors. These rich data also highlighted proteome dynamics in spatially defined zones of activated germinal centers, illuminating sites undergoing active B-cell proliferation and somatic hypermutation. Our results demonstrate the power of spatially-resolved proteomics for tissue phenotyping by integrating high-content imaging, laser microdissection, and ultra-sensitive mass spectrometry. This approach has broad implications for a wide range of biomedical applications, including early disease profiling, drug target discovery and biomarker research.

systems biology↗

bioRxiv2022

Development of Comprehensive Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry Assays to Quantitate Cisplatin-Induced DNA-DNA Cross-Links

Cisplatin (CP) is a common anti-tumor drug used to treat many solid tumors. The activity of CP is attributed to the formation of DNA-DNA cross-links, which consist of 1,2-intra-, 1,3-intra-, and interstrand cross-links. To better understand how each intrastrand cross-link contributes to the activity of CP, we have developed comprehensive ultraperformance liquid chromatography-selective ion monitoring (UPLC-SIM) assays to quantify 1,2-GG, 1,2-AG, 1,3-GCG, and 1,3-GTG-intrastrand cross-links. The limit of quantitation for the developed assays ranged from 5 - 50 fmol, or as low as 6 cross-links per 108 nucleotides. To demonstrate the utility of the UPLC-SIM assays, we first performed in vitro cross-link formation kinetics experiments. We confirmed 1,2-GG-intrastrand cross-links were the most abundant intrastrand cross-link and formed at a faster rate compared to 1,2-AG- and 1,3-intrastrand cross-links. Furthermore, we investigated the repair kinetics of intrastrand cross-links in CP-treated wild type and nucleotide excision repair (NER)-deficient U2OS cells. We observed slow repair of both 1,2- and 1,3-intrastrand cross-links in wild type cells, and no evidence of repair in the NER-deficient cells. Taken together, we have demonstrated that our assay is capable of accurately quantifying intrastrand cross-links in CP-treated samples and can be utilized to better understand the activity of CP.

biochemistry↗