Search PubMedSearch

PubMed · 42674810

Crotonylome profiling identifies MLKL crotonylation in lupus nephritis associated with RAB1A-mTOR signalling and autophagy changes in tubular epithelial cells.

Abstract

OBJECTIVE: To investigate whether MLKL crotonylation is associated with tubular autophagy-lysosome pathway homeostasis in lupus nephritis (LN) and to explore its relationship with RAB1A-mechanistic target of rapamycin (mTOR) signalling. METHODS: Crotonylome proteomics was performed in peripheral blood mononuclear cells from patients with LN, patients with systemic lupus erythematosus without nephritis and healthy controls. Renal biopsy tissues were evaluated for tubulointerstitial fibrosis and autophagy-lysosome pathway-related markers. Mechanistic studies were conducted in lipopolysaccharide-stimulated HK-2 cells. Autophagic flux was assessed using bafilomycin A1. The dependency of mTOR/autophagy changes on RAB1A was tested by siRNA-mediated knockdown. RESULTS: MLKL was identified as a differentially crotonylated protein in LN, with increased crotonylation at K95 and K219. Kidney tissues from patients with LN showed increased fibronectin and collagen III deposition compared with controls, whereas no significant difference was observed between class IV and class V LN. LC3 signal did not differ significantly between groups, whereas LAMP1 expression and LC3-LAMP1 co-localisation were reduced in LN. In HK-2 cells, crotonylation-deficient MLKL mutants were associated with increased LC3-II and reduced p62, whereas K219Q showed the opposite pattern. Autophagic flux assays using bafilomycin A1 showed that K219R-expressing cells had higher LC3-II levels than WT cells both before and after lysosomal inhibition, with comparable BafA1-induced LC3-II accumulation, consistent with increased autophagosome formation rather than impaired lysosomal degradation. HDAC1 knockdown increased MLKL crotonylation and was accompanied by mTOR activation. MLKL crotonylation enhanced RAB1A guanriphosphat osphate (GTP) binding without altering total RAB1A abundance. RAB1A knockdown in MLKL WT-expressing cells attenuated mTOR phosphorylation and partly reversed the autophagy-suppressive marker profile. Sodium crotonate induced an autophagy-suppressive marker profile that was partly reversed by rapamycin. CONCLUSION: MLKL crotonylation is associated with activation of the RAB1A-mTOR axis and altered tubular autophagy-lysosome pathway homeostasis in LN. These findings suggest that tubular injury-related changes in LN may not be fully reflected by glomerulus-based classification alone.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rui-Ling Lu, Shu-Hui Meng, Quan-Zhou Peng, Yanran Chen, Xufa Yang, Hong Yang Liu, Feng-Ping Zheng, Dongzhou Liu, Xiaoping Hong. 2026-08-31. Crotonylome profiling identifies MLKL crotonylation in lupus nephritis associated with RAB1A-mTOR signalling and autophagy changes in tubular epithelial cells.. https://doi.org/10.1136/lupus-2026-002116

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans