Dysregulation of protein homeostasis by mutant UBA1 in VEXAS syndrome [RNA-seq]

VEXAS is a hematopoietic disorder characterized by hyperinflammation,high mortality, and mutations at methionine 41 (M41) in the E1 ubiquitin enzyme, UBA1. Here, we developed ahuman model of VEXAS by engineering the male THP1 cell line to express the UBA1-M41V mutation. We found that UBA1-M41V cells exhibit aberrant UBA1 isoform expression, increased vacuolization, and upregulation of the unfolded protein response, recapitulating features of VEXAS.Proteomic analyses revealed dysregulated ubiquitination and proteotoxic stress in UBA1-M41V cells, with alterations in inflammatory and stress-response pathways. UBA1-M41V cells were sensitive to genetic or pharmacological inhibition of E1 enzymes. Treatment with theE1 inhibitor TAK-243 preferentially suppressed colony formation of UBA1-M41V cells. Moreover,UBA1-M41V cells exhibited greater sensitivity to TAK-243 in competition assays and showed increased apoptosis. Interestingly, TAK-243 preferentially inhibited UBA6 activity over UBA1 ,suggesting that UBA6 may compensate for UBA1 dysfunction. Targeting UBA6 using shRNA orthe UBA6-specific inhibitor phytic acid further revealed an acquired dependency on UBA6 inUBA1-M41V cells. Phytic acid impaired UBA1-M41V cells while sparing WT cells. Together, these findings establish a novel human model of VEXAS, identify key roles for UBA1 and UBA6, and demonstrate that UBA6 inhibition represents a therapeutic strategy for selectively targeting UBA1 mutant clones. THP1 WT, M41V, Scramble non-targetting, UBA1 knockdown, and UBA6 knockdown cells were collected in triplicate, and RNA was extracted using ZYMO RESEARCH Quick-RNA Miniprep kit (cat #R1055). After the confirmation of the RNA quality using Agilent 2100 Bioanalyzer, the libraries were prepared with polyA selection using the Truseq RNA Library Prep Kit, and the libraries were sequenced at an average depth of 30M paired-end 100bp nucleotide reads. After the quality of reads was examined using FastQC (v0.11.7, https://www.bioinformatics.babraham.ac.uk/projects/fastqc), paired-end reads were aligned against human GRCh38 genome (iGenome,https://support.illumina.com/sequencing/sequencing_software/igenome.html) using HISAT2 (v2.0.5,http://daehwankimlab.github.io/hisat2). The raw gene counts were calculated using ​featureCounts (v1.5.2, http://subread.sourceforge.net/) and normalized using edgeR (v3.16.5, https://bioconductor.org/packages/release/bioc/html/edgeR.html) in iGEAK (https://pubmed.ncbi.nlm.nih.gov/30841853/). Differentially expressed genes were predicted using limma/voom (v3.30.6, https://bioconductor.org/packages/release/bioc/html/limma.html).