Biology subjects

Zheng, X.

Publications and source records attributed to Zheng, X..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study

Brain-computer interfaces (BCIs) have immense potential regarding the provision of therapies for disorders of development, but to date have typically been created for non-linguistic disorders such as ADHD (attention deficit hyperactivity disorder). Here we present a BCI designed to improve linguistic phonological processing during natural speech listening, aimed at participants with developmental dyslexia. Phonological "deficits" are considered a core feature of dyslexia across languages and are present from infancy in those later diagnosed with dyslexia. Here a non-invasive EEG-BCI relying on auditory inputs and visual feedback was developed to optimise brain patterns related to phonological development in infants and children. The BCI focused on neural patterns identified using Temporal Sampling theory, which has found the theta/delta ratio during natural speech listening to be a key neural associate of impaired phonology. As a first step, the BCI was tested with adults. Adults with and without dyslexia played the BCI for 16 sessions, and received pre- and post-testing regarding phonological awareness and single word and nonword reading skills. Learning was assessed both online, as in most BCI studies, and offline, enabling removal of a greater number of potential EEG artifacts. Significant associations between offline BCI scores (a measure of BCI learning) and improvements in nonword reading were found for all participants who learned the BCI, both dyslexic and control. BCI learning also showed significant associations with improvements in real word reading and amplitude rise time discrimination. The data are interpreted with respect to Temporal Sampling theory.

neuroscience↗

bioRxiv2026

CTLA-4 inhibitors drive colitis through metabolic reprogramming-mediated Treg/Th17 imbalance

Immune checkpoint inhibitors (ICIs), especially CTLA-4 inhibitors (CTLA-4), exhibit a high incidence of colitis as an immune-related adverse event (irAE) during cancer treatment, severely limiting patient benefit. Clinically, both treatment interruption and existing intervention drugs for ICI-mediated colitis may compromise antitumor efficacy. However, there is inadequate research on the pathogenesis of ICI-mediated colitis, with findings often conflicting. Here, we first established multiple clinically relevant animal models, including an immuno-humanized ICI-mediated colitis model. Through time-series transcriptomics, we discovered that CTLA-4-induced colonic toxicity exhibits characteristics ranging from early metabolic reprogramming represented by glycolysis to later immune disorders represented by Th17 responses. By targeting colonic CTLA-4+ T cells, CTLA-4 blocked CD80/CD86-CTLA-4 interaction, thereby activating the PI3K-AKT-mTOR pathway. Subsequently, mTOR mediated metabolic reprogramming in T cells, shifting them from Treg-biased oxidative phosphorylation to Th17-biased glycolysis. The colonic toxicity of CTLA-4 has also been demonstrated to depend on the PI3K-AKT-mTOR pathway, glycolysis, and Th17 responses. Notably, metformin significantly relieved ICI-mediated colitis by inhibiting mTOR without impeding antitumor efficacy. Collectively, these findings highlighted the metabolic-immune axis in the colonic toxicity of ICI and provided a clinically superior intervention strategy.

pharmacology and toxicology↗

bioRxiv2025

A Generative Foundation Model for Cryo-EM Densities

Single-particle cryo-electron microscopy (cryo-EM) enables structure determination of macromolecular complexes, yet reconstructions are often degraded by noise, anisotropic sampling and reconstruction artifacts. Correcting these effects is an ill-posed inverse problem that requires strong prior knowledge in addition to experimental data. Here we introduce cryoFM, a generative foundation model for cryo-EM densities that unifies data-driven structural priors with dataset-specific constraints within a Bayesian inference framework. CryoFM is trained in an unsupervised manner on thousands of high-quality cryo-EM maps using flow matching, learning a generalizable prior over macromolecular density distributions. Combined with explicit likelihood models describing experimental degradations, cryoFM enables flow posterior sampling, an inference-only procedure that performs denoising and restoration and refinement while remaining explicitly constrained by dataset-derived statistics. We show that this framework improves density reconstruction and refinement across diverse experimental settings, including preferred-orientation datasets and cases with strong spatial heterogeneity in signal-to-noise ratio, without introducing hallucinated features. In addition, cryoFM can be fine-tuned into conditional generative models for density post-processing, yielding maps with improved interpretability and fewer artifacts compared to existing supervised approaches. Together, cryoFM establishes generative foundation models as a principled and controllable framework for cryo-EM density reconstruction and modification.

biophysics↗

bioRxiv2025

Cross-sectional association study from NHANES between some dietary supplements and anti-HAV antibodies

Background/Objectivesdietary supplements intake is known for its importance in preserving immune system and immune response but we need to estimate if there were direct cross-sectional association between some dietary supplements use 24-hours and anti-HAV antibodies or not. Methodsdata merged from three NHANES three cycles along (2013-2018) were analyzed, representing 29.400 participants across all ages. The data collected were subjected to a logistic regression analysis to assess the relationship between the reported frequency of infections and dietary nutrients consumed including minerals and some vitamins. Resultsthe results in overall verified no significant association between investigated dietary supplements use 24-hours and anti-HAV antibodies. However, vitamin D (p = 0.004) showed a significant positive association. Conclusionsthere were true direct association revealed of vitamin D on anti-HAV antibodies.

immunology↗

bioRxiv2025

Genetic diversity of Collaborative Cross mice enables the establishment of a novel Chlamydia muridarum female genital tract infection model

Chlamydial infection in women displays wide variation in bacterial burden, persistence, and risk of upper genital tract pathology, yet the host genetic factors underlying this heterogeneity remain poorly defined. We evaluated genital tract infection with Chlamydia muridarum across 20 Collaborative Cross (CC) strains, a recombinant inbred mouse panel that captures broad genetic diversity with high within-strain reproducibility. CC strains exhibited striking differences in early bacterial burden, time to clearance, and oviduct pathology, including prolonged low-inflammatory infections and burden-pathology discordance that mirror key features of human disease. Heritability analyses demonstrated that host genetics accounted for most of the variation observed in Day 7 bacterial burden and pathological outcomes. Genome-wide scans identified suggestive quantitative trait loci associated with both traits. Genes within the burden-associated locus converged on host pathways implicated in chlamydial intracellular growth, including membrane dynamics and lipid metabolism, ubiquitin signaling, host cell survival mechanisms, and immune regulatory signaling. In contrast, genes within the pathology-associated locus were enriched for pathways regulating inflammatory cell recruitment, inflammasome activation, and tissue remodeling, processes central to genital tract damage following infection. Cervical transcriptional profiling further revealed strain-dependent innate and adaptive immune programs associated with bacterial burden and disease phenotype. Together, these findings establish the CC as a powerful platform for dissecting the genetic architecture of chlamydial immunopathogenesis, and for improving preclinical evaluation of vaccines and therapeutics.

immunology↗

bioRxiv2025

HypoxamicroRNA-210 protects against hepatic steatosis by inhibiting CIDEC expression

Background and AimsMetabolic dysfunction-associated steatotic liver disease (MASLD) is a major global health burden. Although hypoxia is known to contribute to MASLD pathogenesis, the role of hypoxia signaling remains poorly defined. We investigated whether HypoxamicroRNA-210 (miR-210), a key hypoxia-inducible microRNA, regulates hepatic lipid metabolism and MASLD development. MethodsSerum miR-210 levels were quantified in MASLD patients and matched controls. Human hepatic spheroids and HepG2 cells were exposed to fatty acids to assess miR-210 induction and lipid accumulation. miR-210 knockout mice were fed a Western diet to evaluate hepatic steatosis and transcriptomic changes using RNA sequencing. RNA pull-down and 3UTR-driven luciferase reporter assays were employed to identify miR-210 targets. Functional effects of miR-210 mimic were examined in knockout mice, db/db mice, and in vitro human hepatic spheroid models. ResultsSerum miR-210 levels were significantly reduced in MASLD patients compared with matched controls. Consistently, human hepatic spheroids did not appropriately increase miR-210 expression in response to fatty acid-induced intracellular hypoxia. This blunted miR-210 response contributed to hepatic lipid accumulation, as loss of miR-210 in a mouse model of MASLD led to increased hepatic lipid deposition and activation of lipid metabolic pathways. We identified CIDEC as a direct miR-210 target mediating its inhibitory effects on hepatic lipid accumulation, and restoring miR-210 expression suppressed CIDEC and reduced hepatic lipid content in knockout mice on a Western diet. Moreover, miR-210 attenuated lipid accumulation in both in vitro human hepatic spheroids and in vivo db/db mice models of MASLD. ConclusionsmiR-210 protects against hepatic steatosis by inhibiting CIDEC expression, suggesting miR-210-CIDEC axis as a promising therapeutic target for reducing hepatic lipid accumulation and preventing MASLD progression. Impact and ImplicationsThis study addresses a critical gap in understanding how hypoxia signaling shapes MASLD and uncovers a novel pathogenic mechanism of hepatic steatosis arising from fatty acids-induced dysregulation of miR-210. Impaired hypoxia responses, via blunted miR-210 induction, contribute to hepatic lipid accumulation through upregulation of CIDEC, a newly identified target of miR-210. These findings establish miR-210 as a novel regulator of hepatic lipid homeostasis and underscore its therapeutic potential. Interventions aimed at restoring miR-210 function in the liver may offer a promising strategy to ameliorate hepatic steatosis and prevent MASLD progression.

molecular biology↗

bioRxiv2025

TUPAD: A Tn5-Mediated, Pre-amplification/Adapter-Dimer-Free Platform for Ultra-Uniform, One-Step PGT Profiling with High Stability and Broad Compatibility

High-throughput sequencing stands as a cornerstone of clinical molecular diagnostics, particularly in preimplantation genetic testing (PGT)--a key application where the selection of chromosomally normal embryos is critical to enhancing in vitro fertilization (IVF) success rates. A fundamental challenge inherent to PGT, however, lies in the ultra-low gDNA input (typically <100 pg) from embryo biopsies. To mitigate this limitation, traditional workflows rely on whole genome amplification (WGA) technologies, such as MDA, PicoPlex, and MALBAC. Yet these WGA-based protocols inherently entail pre-amplification of gDNA prior to standard library construction---a step that introduces significant coverage bias and compromised uniformity. These are intrinsic flaws irreparable by downstream library preparation or bioinformatics analysis, ultimately leading to clinical uncertainty in the interpretation of copy number variations (CNVs). In this study, we developed TUPAD (Tn5-Mediated, Uniform Pre-amplification-free and Adapter-Dimer-Free Library preparation), a transformative technology that bypasses the limitations of traditional WGA. By engineering a novel adapter-dimer-free transposon system, TUPAD enables high-efficiency library construction from as little as 1 picogram (pg) of gDNA. This breakthrough allows for a pre-amplification-free workflow, effectively eliminating the primary source of amplification bias. Compared to existing WGA standards, these advantages are fully retained in embryo biopsy and positive sample testing, TUPAD consistently generates highly uniform library data, significantly enhancing the detection limit and accuracy of CNVs and other genomic variants. Beyond these performance advantages, TUPAD also cuts wet-lab processing time by 50%. Practical validation confirms TUPAD results are stable, reliable, with proven practical utility in PGT testing.

molecular biology↗

bioRxiv2025

Comparative evaluation of reference genomes and cell-type annotation frameworks for single-nucleus transcriptomic analysis in apple

Single-nucleus RNA sequencing (snRNA-seq) provides a powerful tool to profile cell-type-specific transcriptional programs in woody fruit trees. Yet its application in Malus domestica has been limited by heterogeneous reference genomes and the lack of validated marker genes. Here, we first established a comprehensive set of marker genes corresponding to 29 plant cell types and identified their orthologs in apple. Using these resources, we systematically evaluated six publicly available apple genome assemblies as references for snRNA-seq analysis. Our results demonstrate that reference genome selection has a major impact on mapping performance and downstream cell type annotation, with the GDDH13 assembly consistently producing the highest transcript counts per nucleus and the greatest number of identifiable transcriptional clusters (15 clusters representing 11 distinct cell types across 35,557 high-quality nuclei). To achieve robust cell type annotation, we integrated classical marker gene-based annotation with two cross-species computational frameworks -- Orthologous Marker Gene Groups (OMGs) and XSpeciesSpanner. These three approaches enabled confident identification of 11 major cell types in apple seedlings and provided cross-validation for ambiguous or previously unannotated clusters. Pseudotime analysis reconstructed the developmental trajectories of both procambial and stomatal lineages, revealing their progressive transcriptional transitions and enabling the delineation of key molecular programs underlying vascular differentiation and early guard-cell formation. Together, this work provides a reference-quality single-nucleus transcriptomic atlas for apple and underlined the critical impact of genome choice and multi-method cell-type annotation on single-cell studies in non-model crops.

bioinformatics↗

bioRxiv2025

Developmental deviations of structural connectivity in youths with ADHD predict symptom and treatment outcomes

Attention-deficit/hyperactivity disorder (ADHD) lacks validated biomarkers to track symptom development or guide treatment selection in youth. We quantified individual deviations from normative age-related trajectories of white-matter structural connectivity (SC) across two independent cohorts: 6,687 typically developing and 1,114 ADHD scans from the ABCD study, and 292 typically developing and 482 ADHD participants from a Chinese cohort. Youth with ADHD showed pronounced SC deviations, especially in higher-order association pathways. A subset of connections showed ADHD-specific developmental reductions in deviations beyond typical developmental patterns, and these changes mediated the age-related decline in ADHD symptoms. Longitudinal within-individual analyses demonstrated that decreases in deviation over two years tracked symptom improvement. Baseline deviations also predicted 12-week treatment response to atomoxetine, but not methylphenidate, and follow-up imaging revealed treatment-related reductions in deviation. Together, these findings identify SC deviation as a robust developmental biomarker with prognostic and theragnostic relevance for ADHD, supporting precision care through risk stratification, individualized pharmacotherapy selection, and objective monitoring of treatment effects.

neuroscience↗

bioRxiv2025

DCBK: A Fragment-Based Hybrid Simulation and Machine Learning Framework for Predicting Ligand Dissociation Kinetics

Predicting small-molecule dissociation kinetics remains challenging due to the high computational cost of simulating rare unbinding events and the limited scalability of existing approaches. Here, we introduce DCBK (Divide-and-Compute Binding Kinetics), a physics-informed, fragment-resolved framework for predicting ligand dissociation across diverse protein-ligand systems. DCBK integrates steered molecular dynamics and umbrella sampling to reconstruct unbinding pathways and free energy profiles, followed by BRICS-based ligand fragmentation. Fragment-level energetic and structural features are combined with machine learning trained on experimental kinetics data, enabling efficient prediction of dissociation rate constant (koff) values. Validation across five protein families demonstrates strong agreement with experiments, with ablation and unseen-target analyses highlighting the contribution of fragment-level features and the frameworks transferability. Importantly, DCBK allows dissociation kinetics to be interpreted in terms of fragment-level contributions, offering mechanistic insight and guiding ligand modification to optimize residence time. This interpretable and extensible framework links molecular structure, energetics, and kinetics, providing actionable insights for lead optimization and rational drug design.

molecular biology↗

bioRxiv2025

Symmetric brain-liver circuits mediate lateralized regulation of hepatic glucose output

Neural lateralization is well recognized in the control of contralateral somatic movement, yet its relevance to visceral organ regulation remains poorly understood. This study aimed to determine whether the central nervous system exerts lateralized control over hepatic glucose metabolism and to localize the site of peripheral sympathetic crossover to the liver. Pseudorabies virus (PRV) tracing revealed bilateral projections from the lateral paragigantocellular nucleus (LPGi) with preferential innervation of the contralateral hepatic lobes. Unilateral LPGi activation elevated systemic glucose by enhancing glycogenolysis and gluconeogenesis specifically in contralateral lobes, whereas bilateral activation produced additive effects. Following unilateral hepatic denervation, contralateral LPGi activation induced metabolic compensation in the remaining innervated lobes, characterized by increased norepinephrine release, glucose production, and glycogen depletion. Whole-mount tissue clearing and dual viral tracing localized the sympathetic crossover to the porta hepatis. Developmental analysis showed that lobar-specific innervation along the vasculature emerges by postnatal week 2. These findings demonstrate that the brainstem can exert lobe-specific, lateralized control of hepatic glucose metabolism via bilaterally projecting brain - liver sympathetic pathways. This contralateral regulation arises from a peripheral decussation at the porta hepatis, and the compensatory activation observed after denervation reveals an intrinsic neuroadaptive mechanism that helps safeguard systemic glucose homeostasis. HighlightsO_LIBrain-liver sympathetic projections exhibit predominant contralateral innervation C_LIO_LIUnilateral LPGi activation drives glucose production in contralateral hepatic lobes C_LIO_LIUnilateral denervation augments contralateral LPGi-mediated metabolic compensation C_LIO_LISympathetic crossover to the liver localizes at the porta hepatis C_LI

neuroscience↗

bioRxiv2025

A multicenter spatial transcriptomics atlas of human tuberculosis and non-tuberculous mycobacterial disease

Granulomas are the hallmark of mycobacterial (MB) infections, forming structured immune environments that contain bacteria but also drive disease persistence. However, their spatial and functional organization remains unclear. Using spatial RNA sequencing on 38 patient samples, we identified five distinct granuloma niches: a necrotic core, an immune-activated inner niche, an inflammatory and an extracellular matrix (ECM)-remodeling middle niche, an outer structural niche, and a tertiary lymphoid structure niche supporting antigen presentation. Immune activity peaks in the inner niche, transitioning to fibrosis at the periphery. Lymph node granulomas display reduced fibroblast involvement but stronger JAK-STAT activation. Mycobacterium tuberculosis (MTB) granulomas exhibit heightened JAK-STAT and IFN-{gamma} signaling, while non-tuberculous mycobacteria (NTM) granulomas show increased hypoxia signatures. Compared to sarcoidosis, MB granulomas feature a structured adaptive immune response, marked by the clustering of plasma cells. Our findings, accessible via https://lab-li.ciim-hannover.de/mb-granuloma/, define key disease signatures, guiding biomarker discovery and therapeutic targeting in granuloma-related diseases.

bioinformatics↗

bioRxiv2025

A spatially-resolved human brain proteome atlas for understanding function and disease

While the brain performs specialized functions across distinct regions, the spatial organization of the human brain proteome remains largely uncharted. Here we present a comprehensive spatially-resolved proteome atlas of the human brain, analyzing over two thousand MRI- guided locations across four individuals. Proteome analysis integrated with transcriptomics reveals extensive post-transcriptional regulation, with cortical regions showing markedly higher protein diversity than transcript. Unsupervised molecular clustering defines distinct brain territories that transcend anatomical boundaries, instead reflecting metabolic demands and functional specialization patterns. Application to epilepsy brain tissue uncovered disrupted astrocyte metabolism, protein homeostasis and therapeutic targets including the seizure-associated purinergic receptor P2RX7. This resource bridges molecular and systems neuroscience to accelerate neurological drug discovery.

neuroscience↗

bioRxiv2025

Joint analysis of expression and variation at single cell resolution by scVar

Tumor heterogeneity represents a critical determinant affecting both cancer diagnosis and therapeutic efficacy. Traditional bulk sequencing approaches are limited in their ability to resolve genomic alterations at the resolution of individual cells. In this study, we present scVar, an integrated analytical framework designed for mutation profiling using single-cell transcriptomic data. scVar enables sensitive and robust detection of single-nucleotide variants, particularly facilitating the identification of low-frequency variants. The framework incorporates customizable filtering parameters including variant allele frequency, and provides comprehensive functional and clinical annotations for identified mutations. Furthermore, scVar includes downstream analytical modules that facilitate the joint investigation of transcriptomic and mutational profiles within single cells. Benchmarking on simulated datasets and matched tumor samples demonstrates that scVar consistently outperforms existing methods, especially in detecting variants of low abundance, and shows strong concordance with whole-exome sequencing data. Application of scVar to non-small cell lung cancer samples effectively characterized ITH across spatially distinct tumor regions and diverse cellular populations. Collectively, scVar offers an integrated platform for concurrent analysis of somatic mutations and transcriptomic data derived from single-cell RNA sequencing, providing a powerful tool for elucidating tumor evolution and the complex interplay between genomic heterogeneity and the tumor microenvironment.

bioinformatics↗

bioRxiv2025

Interruption of rat absence seizures by auditory stimulation

Absence seizures are episodes of impaired consciousness and responsiveness that impact an individuals ability to interact with the world around them. Childhood absence epilepsy, a condition defined by these seizures, can have profound effects on childrens social, educational, and psychological development. Absence seizures are accompanied by a distinctive electrographic signature called a spike-wave discharge. The impairment of consciousness associated with a spike-wave discharge can be variable: some people maintain responsiveness during some absence seizures, and some rodent oscillations resembling spike-wave discharges may not have any behavioral impact. We previously observed that spike-wave discharges in the Genetic Absence Epilepsy Rat from Strasbourg model sometimes terminated shortly after presentation of a conditioned auditory stimulus. In this study we found that these terminations were caused by the stimuli and that they occurred after approximately 50% of stimuli. We also found that the probability of a spike-wave discharge being interrupted depended on stimulus timing, degree of conditioning, and electrographic signal power. These data provide insight into the factors that determine the mechanisms of absence seizure termination, with possible implications for therapy.

neuroscience↗

bioRxiv2025

Castl: Robust Identification of Spatially Variable Genes in Spatial Transcriptomics via an Ensemble-based Framework

Spatially variable genes (SVGs) are essential for elucidating tissue organization within spatially resolved transcriptomics. While a number of computational methods have been developed for SVG identification, their reliance on algorithm-specific assumptions, such as predefined kernel functions or spatial neighborhood graphs, often results in substantial variability in sensitivity and inflated false discovery rates (FDRs) across heterogeneous datasets. To address this challenge, we here develop Castl, an ensemble-based framework for SVG identification that integrates multiple detection methods through statistically designed aggregation modules. Comprehensive evaluations on both simulated and real-world data demonstrate that Castl consistently identifies biologically meaningful spatial expression patterns, mitigates method-specific biases and effectively controls FDRs across various biological contexts, resolutions, and spatial technologies. This flexible, assumption-free framework offers a robust and standardized foundation for spatially informed feature discovery in complex biological systems.

bioinformatics↗

bioRxiv2025

GlialCAM Cytoplasmic Signaling in Oligodendrocytes and Astrocytes is Essential for White Matter Homeostasis in the Brain

Glial cell adhesion molecule (GlialCAM) is an astrocyte- and oligodendrocyte-expressed transmembrane protein with two extracellular IgG-like domains and a cytoplasmic tail with putative signaling functions. While numerous studies have explored functions for the GlialCAM IgG-like domains in brain development and physiology, functions for its cytoplasmic signaling tail remain largely unknown. Therefore, we developed a mutant mouse model that expresses a truncated GlialCAM construct (GlialCAM {Delta}CT) that contains intact extracellular and transmembrane domains but lacks the cytoplasmic tail. Deletion of the GlialCAM cytoplasmic domain in glial cells of the brain results in vacuolization within white matter regions without disrupting neurovascular barrier integrity. Consequently, mutant mice exhibited selective deficits in motor coordination, muscular strength, and memory. Single cell transcriptome sequencing identifies GlialCAM-dependent defects in ECM remodeling pathways in white matter tracts. In situ spatial profiling revealed robust activation of astrocytes and microglia in the mutant brain. Proteomic analysis identified GlialCAM cytoplasmic tail interactors with links to MAPK signaling and cytoskeletal regulatory networks. These data reveal important functions for the GlialCAM cytoplasmic tail in homeostasis of white matter tracts in the adult murine brain. The GlialCAM {Delta}CT model may also be useful for studying the pathogenesis and possible treatment of neurological diseases linked to white matter degeneration.

neuroscience↗

bioRxiv2025

Single-cell proteomics: a powerful new tool to study kidney cell heterogeneity

BackgroundTechnological advancements in protein mass spectrometry have significantly enhanced analytical sensitivity and throughput, enabling single-cell proteomics by mass spectrometry (SCP-MS) to become reality. SCP-MS allows high-resolution analysis of cellular heterogeneity and function, bypassing bulk analysis limitations. Here, we used SCP-MS to document at the protein level the cellular diversity of mouse kidney cells. We further focused SCP-MS on low abundance distal convoluted tubule (DCT) cells that are essential for body electrolyte homeostasis and blood pressure control. MethodsMouse kidney cells were isolated via enzymic digestion and single-cells isolated using fluorescence- activated cell sorting (FACS). DCT cells were isolated from mice with GFP expression specifically in the DCT (parvalbumin-GFP) using a similar workflow. SCP-MS analyses was performed using an Orbitrap Ascend Mass Spectrometer with a FAIMS Pro Duo interface coupled with Wide ISolation window High-resolution MS1 Data Independent Acquisition (WISH-DIA). Spectronaut was used for protein identification and quantification, and cell-type annotation and clustering were performed in Python by scanpy implementation. ResultsWorkflow benchmarking using Hela cells confirmed a successful SCP-MS setup. From 768 single mouse kidney cells, SCP-MS identified 2626 unique proteins. Computational approaches resolved various nephron segments, including distinct DCT populations. From enriched DCT cells, 1912 proteins were identified, enabling classification of three populations - DCT1, DCT2, and a proliferative subset (ProLIF) that represented a transient state between DCT1 and DCT2. ProLIF cells had elevated abundance of the sodium-chloride cotransporter NCC and represented approximately 33% of DCT cells, substantially exceeding previous transcriptomic estimates of ProLIF cell frequency (~0.1%). High proliferation (~39%) of DCT cells was confirmed using immunohistochemistry. ConclusionsThis SCP-MS analysis of mouse kidney uncovered significant cellular heterogeneity not captured effectively using transcriptomics. Despite imitations in proteome depth and throughput, SCP-MS provides a powerful approach for investigating kidney cellular dynamics at the protein level. Key pointsO_LIWe developed a single-cell proteomics by mass spectrometry (SCP-MS) workflow identifying up to ~2,000 proteins in a single mouse kidney cell C_LIO_LISCP-MS identified a substantial proliferative subset of cells in the DCT underestimated by transcriptomics C_LIO_LISCP-MS could inform on clinical strategies for kidney disease monitoring, offering robust indicators of tubular injury or regeneration. C_LI

biochemistry↗