Biology subjects

Manda, V.

Publications and source records attributed to Manda, V..

4 recordsLinked to original sources

bioRxiv2025

Deuterium labeling enables proteome wide turnover kinetics analysis in cell culture

The half-life of proteins is tightly regulated and underlies many cellular processes. It remains unclear the extent to which proteins are dynamically synthesized and degraded in different cell types and cell states. We introduce an improved D2O labeling workflow and apply it to examine the landscape of protein turnover in pluripotent and differentiating human induced pluripotent stem cells (hiPSC). The majority of hiPSC proteins show minimal turnover beyond cell doubling rates, but we also identify over 100 new fast-turnover proteins not previously described as short-lived. These include proteins that function in cell division and cell cycle checkpoints, that are enriched in APC/C and SPOP degrons, and that are depleted upon pluripotency exit. Differentiation rapidly shifts the set of fast-turnover proteins toward including RNA binding and splicing proteins. The ability to identify fast-turnover proteins in different cell cultures also facilitates secretome analysis, as exemplified by studies of hiPSC-derived cardiac myocytes and primary human cardiac fibroblasts. The presented workflow is broadly applicable to protein turnover studies in diverse primary, pluripotent, and transformed cells.

biochemistry↗

bioRxiv2024

Ablation of hematopoietic stem cell derived adipocytes reduces tumor burden in syngeneic mouse models of high-grade serous carcinoma

Hematopoietic stem cell-derived adipocytes (HSCDAs) are an adipose subtype derived from myeloid precursors that are distinct from conventional mesenchymal adipocytes (CMAs). We hypothesized that HSCDAs promote high grade serous carcinoma (HGSC), the most common form of ovarian cancer. Despite similar rates of differentiation, primary human HSCDAs from female donors showed marked transcriptional differences from CMAs, including downregulation of cell cycle and upregulation of lipid metabolic pathways. HSCDAs secreted greater amounts of inflammatory cytokines than CMAs. We also conducted two independent tumor studies using ID8 and SO syngeneic HGSC murine models in immunocompetent mice that were either HSCDA Proficient (HSCDA-Pro; can make both adipocyte subtypes) or Deficient (HSCDA-Def; can only make CMAs). Tumor burden trended lower in HSCDA-Def mice in both models. Relative to HSCDA-Pro mice, omental ID8 tumors from HSCDA-Def mice downregulated transcription of multiple metabolic pathways that were enriched in human HSCDA cells in vitro, suggesting that ablation of HSCDAs altered the tumor metabolic environment. Compared to HSCDA-Pro mice, tumors from HSCDA-Def mice had lower densities of dendritic cells (DC) and natural killer (NK) cells, as well as fewer DCs, NKs, and B-cells in proximity to tumor cells. Our data suggest that HSCDAs alter the peritoneal immune and metabolic environment to support HGSC progression. ONE SENTENCE SUMMARYHematopoietic stem cell derived adipocytes may alter the peritoneal metabolic and immune environment to establish a metastatic niche and support ovarian cancer progression.

cancer biology↗

bioRxiv2024

Improved determination of protein turnover rate with heavy water labeling by mass isotopomer ratio selection

The synthesis and degradation rates of proteins form an essential component of gene expression control. Heavy water labeling has been used in conjunction with mass spectrometry to measure protein turnover rates, but the optimal analytical approaches to derive turnover rates from the isotopomer patterns of deuterium labeled peptides continue to be a subject of research. Here we describe a method, which comprises a reverse lookup of numerically approximated peptide isotope envelopes, coupled to the selection of optimal isotopomer pairs based on peptide sequence, to calculate the molar fraction of new peptide synthesis in heavy water labeling mass spectrometry experiments. We validated this approach using an experimental calibration curve comprising mixtures of fully unlabeled and fully labeled proteomes. We then re-analyzed 17 proteome-wide turnover experiments from four mouse organs, and showed that the method increases the coverage of well-fitted peptides in protein turnover experiments by 25-82%. The method is implemented in the Riana software tool for protein turnover analysis, and may avail ongoing efforts to study the synthesis and degradation kinetics of proteins in animals on a proteome-wide scale. Whats newWe describe a reverse lookup method to calculate the molar fraction of new synthesis from numerically approximated peptide isotopomer profiles in heavy water labeling mass spectrometry experiments. Using an experimental calibration curve comprising mixtures of fully unlabeled and fully labeled proteomes at various proportions, we show that this method provides a straightforward way to calculate the proportion of new proteins in a protein pool from arbitrarily chosen isotopomer ratios. We next analyzed which of the isotopomer pairs within the peptide isotope envelope yielded isotopomer time courses that fit most closely to kinetic models, and found that the identity of the isotopomer pair depends partially on the number of deuterium accessible labeling sites of the peptide. We next derived a strategy to automatically select the isotopomer pairs to calculate turnover rates based on peptide sequence, and showed that this increases the coverage of existing proteome-wide turnover experiments in multiple data sets of the mouse heart, liver, kidney, and skeletal muscle by up to 25-82%.

biochemistry↗

bioRxiv2023

Simultaneous proteome localization and turnover analysis reveals spatiotemporal dynamics of unfolded protein responses

The functions of proteins depend on their spatial and temporal distributions, which are not directly measured by static protein abundance. Under endoplasmic reticulum (ER) stress, the unfolded protein response (UPR) pathway remediates proteostasis in part by altering the turnover kinetics and spatial distribution of proteins. A global view of these spatiotemporal changes has yet to emerge and it is unknown how they affect different cellular compartments and pathways. Here we describe a mass spectrometry-based proteomics strategy and data analysis pipeline, termed Simultaneous Proteome Localization and Turnover (SPLAT), to measure concurrently the changes in protein turnover and subcellular distribution in the same experiment. Investigating two common UPR models of thapsigargin and tunicamycin challenge in human AC16 cells, we find that the changes in protein turnover kinetics during UPR varies across subcellular localizations, with overall slowdown but an acceleration in endoplasmic reticulum and Golgi proteins involved in stress response. In parallel, the spatial proteomics component of the experiment revealed an externalization of amino acid transporters and ion channels under UPR, as well as the migration of RNA-binding proteins toward an endosome co-sedimenting compartment. The SPLAT experimental design classifies heavy and light SILAC labeled proteins separately, allowing the observation of differential localization of new and old protein pools and capturing a partition of newly synthesized EGFR and ITGAV to the ER under stress that suggests protein trafficking disruptions. Finally, application of SPLAT toward human induced pluripotent stem cell derived cardiomyocytes (iPSC-CM) exposed to the cancer drug carfilzomib, identified a selective disruption of proteostasis in sarcomeric proteins as a potential mechanism of carfilzomib-mediated cardiotoxicity. Taken together, this study provides a global view into the spatiotemporal dynamics of human cardiac cells and demonstrates a method for inferring the coordinations between spatial and temporal proteome regulations in stress and drug response.

cell biology↗