Biology subjects

Jedrychowski, M. P.

Publications and source records attributed to Jedrychowski, M. P..

5 recordsLinked to original sources

bioRxiv2026

Mitochondrial carrier SLC25A34 links clock, diet, and temperature control of interorganellar lipid cycling

Adipocyte lipid metabolism is coordinated by circadian rhythms, diet, and environmental temperature. Yet how these diverse signals are molecularly integrated remains unknown. Here we show that clock, diet, and temperature cues converge on the orphan mitochondrial transporter, SLC25A34, to orchestrate thermogenic cycling of lipid synthesis and oxidation. During sleep, the clock suppresses Slc25a34 transcription through REV-ERB. Waking, lipid-rich diets, or cold exposure abolish this repression, allowing lipolytic signals to stimulate Slc25a34 expression via PPAR. SLC25A34 then imports oxaloacetate into mitochondria to accelerate the export of substrates used for acetyl-CoA production in the cytosol. This feeds into cytosolic lipid synthesis and transcriptional induction of mitochondrial biogenesis, which collectively promote mitochondrial lipid oxidation. Thus, SLC25A34 confers circadian, dietary, and environmental control of thermogenic metabolism through interorganellar lipid cycling.

molecular biology↗

bioRxiv2021

Dynamic metabolic network modeling of a mammalian cell cycle using time-course multi-omics data

Cell cycle is a fundamental process for cell growth and proliferation, and its dysregulation leads to many diseases. How metabolic networks are regulated and rewired during the cell cycle is unknown. Here we apply a dynamic genome-scale metabolic modeling framework (DFA) to simulate a cell cycle of cytokine-activated murine pro-B cells. Phase-specific reaction activity predicted by DFA using time-course metabolomics were validated using matched time-course proteomics and phospho-proteomics data. Our model correctly predicted changes in methionine metabolism at the G1/S transition and the activation of lysine metabolism, nucleotides synthesis, fatty acid elongation and heme biosynthesis at the critical G0/G1 transition into cell growth and proliferation. Metabolic fluxes predicted from proteomics and phosphoproteomics constrained metabolic models were highly consistent with DFA fluxes and revealed that most reaction fluxes are regulated indirectly. Our model can help predict the impact of changes in nutrients, enzymes, or regulators on this critical cellular process.

systems biology↗

bioRxiv2020

Enrichment of neurodegenerative microglia signature in brain-derived extracellular vesicles isolated from Alzheimer's disease mouse model

Extracellular vesicles (EVs) are secreted by any neuronal cells in the central nervous system (CNS) for molecular clearance, cellular communications and disease spread in multiple neurodegenerative diseases, including Alzheimers disease (AD), although their exact molecular mechanism is poorly understood. We hypothesize that high-resolution proteomic profiling of EVs separated from animal models of AD would determine the composition of EV contents and their cellular origin. Here, we examined recently developed transgenic mice (CAST.APP/PS1), which express familial AD-linked mutations of amyloid precursor protein (APP) and presenilin-1 (PS1) in the CAST/EiJ mouse strain and develop hippocampal neurodegeneration. Quantitative proteomics analysis of EVs separated from CAST.APP/PS1 and age-matched control mice by tandem mass tag-mass spectrometry identified a total of 3,444 unique proteins, which are enriched in neuron, astrocyte, oligodendrocyte and microglia-specific molecules. CAST.APP/PS1-derived EVs show significant enrichment of Psen1, APP, Itgax, and reduction of Wdr61, Pmpca, Aldh1a2, Calu, Anp32b, Actn4 and Ndufv2 compared to WT-derived EVs, suggesting the involvement of A{beta}-processing complex and disease-associated / neurodegenerative microglia (DAM/MGnD) in EV secretion. In addition, Itgax and Apoe, the DAM/MGnD markers, in EV show a positive correlation with Itgax and Apoe mRNA expression from brain tissue in CAST.APP/PS1 mice. These datasets indicate the significant contribution of A{beta} plaque and neurodegeneration-induced DAM/MGnD microglia for EV secretion in CAST.APP/PS1 mice and shed light on understanding the AD pathogenesis.

neuroscience↗

bioRxiv2020

Global proteomics of Ubqln2-based murine models of ALS

Familial forms of neurodegenerative diseases commonly involve mutation of aggregation-prone proteins or components of the protein degradation machinery that act on aberrant proteins. Ubqln2 encodes a member of the UBL/UBA family of proteasome shuttle factors that is thought to facilitate proteasomal degradation of substrates, and mutation of this gene results in a familial form of ALS/FTD in humans. How Ubqln2 dysfunction leads to neurodegeneration, however, remains uncertain. We undertook a comprehensive study to identify proteomic changes upon Ubqln2 perturbation in multiple murine models of Ubqln2-mediated neurodegenerative disease. By performing quantitative multiplexed proteomics on neural tissues of affected animals, we identified a small group of proteins whose abundance is tightly linked to UBQLN2 function: the ubiquitin ligase TRIM32 and two retroelement-derived proteins, PEG10 and CXX1B. Further studies using cultured cells of human origin, including induced neurons, found similar changes in protein abundance upon Ubqln2 loss, and pulse-chase studies suggested that PEG10 and TRIM32 are direct clients of UBQLN2. In conclusion, our study provides a deep understanding of the proteomic landscape of ALS-related Ubqln2 mutants and identifies candidate client proteins that are altered in vivo in disease models and whose degradation is promoted by UBQLN2.

cell biology↗

bioRxiv2019

Defining and targeting adaptations to oncogenic KRASG12C inhibition using quantitative temporal proteomics

Covalent inhibitors of the KRASG12C oncoprotein have recently been developed and are being evaluated in clinical trials. Resistance to targeted therapies is common and likely to limit long-term efficacy of KRAS inhibitors (KRASi). To identify pathways of adaptation to KRASi and to predict drug combinations that circumvent resistance, we used a mass spectrometry-based quantitative temporal proteomics and bioinformatics workflow to profile the temporal proteomic response to KRASG12C inhibition in pancreatic and lung cancer 2D and 3D cellular models. We quantified 10,805 proteins across our datasets, representing the most comprehensive KRASi proteomics effort to date. Our data reveal common mechanisms of acute and long-term response between KRASG12C-driven tumors. To facilitate discovery in the cancer biology community, we generated an interactive KRASi proteome website (https://manciaslab.shinyapps.io/KRASi/). Based on these proteomic data, we identified potent combinations of KRASi with PI3K, HSP90, CDK4/6, and SHP2 inhibitors, in some instances converting a cytostatic response to KRASi monotherapy to a cytotoxic response to combination treatment. Overall, using our quantitative temporal proteomics-bioinformatics platform, we have comprehensively characterized the proteomic adaptations to KRASi and identified combinatorial regimens to induce cytotoxicity with potential therapeutic utility.

cancer biology↗