Project description:Post-transcriptional modifications to messenger RNAs (mRNAs) have the potential to alter the biological function of this important class of biomolecules. The study of mRNA modifications is a rapidly emerging field, and the full complement of chemical modifications in mRNAs is not yet established. We sought to identify and quantify the modifications present in yeast mRNAs using an ultra-high performance liquid chromatography tandem mass spectrometry method to detect 40 nucleoside variations in parallel. We observe six modified nucleosides with high confidence in highly purified mRNA samples (N7-methylguanosine, N6-methyladenosine, 2’-O-methylguanosine, 2’-O-methylcytidine, N4-acetylcytidine and 5-formylcytidine), and identify the yeast protein responsible for N4-acetylcytidine incorporation in mRNAs, Rra1. Additionally, we find that mRNA modification levels change in response to heat shock, glucose starvation and/or oxidative stress. This work expands the repertoire of potential chemical modifications in mRNAs, and highlights the value of integrating mass spectrometry tools in the mRNA modification discovery and characterization pipeline.
Project description:Human cells produce thousands of lipids that impact biological processes in ways we are only starting to characterize. The cellular composition in lipids changes during differentiation and also varies across individual cells of the same type. Yet, whether and how cell-to-cell differences in lipid composition affect cell phenotypes remain unknown. Here we have measured the lipidomes and transcriptomes of individual human dermal fibroblasts by coupling high-resolution mass spectrometry imaging to single-cell transcriptomics. We find that the cell-to-cell variation of specific lipid metabolic pathways contributes to the establishment of cell states involved in the organization of skin architecture. In fact, sphingolipid composition defines fibroblast subpopulations and its metabolic rewiring drives cell state transitions. These data uncover a role for cell-to-cell lipid heterogeneity in the determination of cell states and reveal a new regulatory component to the self-organization of multicellular systems.
Project description:Integrin alpha3beta1, a major epidermal adhesion receptor is critical for organization of the basement membrane during development and wound healing. Integrin alpha3 deficiency leads to interstitial lung disease, nephrotic syndrome and epidermolysis bullosa (ILNEB), an autosomal recessive multiorgan disease characterized by basement membrane abnormalities in skin, lung and kidney. The pathogenetic chains from ITGA3 mutation to tissue abnormalities are still unclear. Although integrin 3 was reported to regulate multiple extracellular proteins, the composition of the extracellular compartment of integrin alpha3-negative keratinocytes has not been resolved so far. In a comprehensive approach, quantitative proteomics of deposited extracellular matrix, conditioned cultured media as well as of the intracellular compartment of keratinocytes isolated from an ILNEB patient and from normal skin were performed. By mass spectrometry-based proteomics, 167 proteins corresponding to the GO terms “extracellular” and “cell adhesion”, or included in the “human matrisome” were identified in the deposited extracellular matrix, and 217 in the conditioned media of normal human keratinocytes. In the absence of integrin alpha3, 33% and 26% respectively were dysregulated. Dysregulated proteins were functionally related to integrin alpha3 or were known interaction partners. The results show that in the absence of integrin alpha3 ILNEB keratinocytes produce a fibronectin-rich microenvironment and make use of fibronectin-binding integrin subunits alphav and alpha5.
Project description:Human embryonic stem cells (hESCs) provide a powerful in vitro model to study lineage specification and the regulatory programs underlying early human development. Here, we present a high-resolution, temporal multi-omics dataset tracking mRNA, translation, and protein expression dynamics during hESC differentiation into definitive endoderm and subsequent polyhormonal (PH) cells, a key pancreatic lineage. RNA-seq, ribosome profiling, and quantitative mass spectrometry-based proteomics were performed on matched samples collected at ten time points in biological duplicates, allowing detailed characterization of transcriptional, translational, and protein abundance changes over the differentiation timeline. The dataset exhibits high technical quality, with strong reproducibility between replicates and rigorous quality control metrics across all omics platforms. This extensive dataset provides critical insights into the complex regulatory mechanisms driving polyhormonal cell differentiation and serves as a valuable resource for the research community, enabling deeper exploration of mammalian development, endodermal lineage specification, and gene regulation.
Project description:Human embryonic stem cells (hESCs) provide a powerful in vitro model to study lineage specification and the regulatory programs underlying early human development. Here, we present a high-resolution, temporal multi-omics dataset tracking mRNA, translation, and protein expression dynamics during hESC differentiation into definitive endoderm and subsequent polyhormonal (PH) cells, a key pancreatic lineage. RNA-seq, ribosome profiling, and quantitative mass spectrometry-based proteomics were performed on matched samples collected at ten time points in biological duplicates, allowing detailed characterization of transcriptional, translational, and protein abundance changes over the differentiation timeline. The dataset exhibits high technical quality, with strong reproducibility between replicates and rigorous quality control metrics across all omics platforms. This extensive dataset provides critical insights into the complex regulatory mechanisms driving polyhormonal cell differentiation and serves as a valuable resource for the research community, enabling deeper exploration of mammalian development, endodermal lineage specification, and gene regulation.
Project description:Bulk and single-cell RNA sequencing do not provide full characterization of tissue spatial diversity in cancer samples, and currently available in situ techniques (multiplex immunohistochemistry, imaging mass cytometry) allow for only limited analysis of a small number of targets. The current study represents the first comprehensive approach to spatial transcriptomics of high-grade serous ovarian carcinoma using intact tumor tissue. We selected a small cohort of patients with highly annotated high-grade serous ovarian carcinoma, categorized them by response to neoadjuvant chemotherapy (poor or excellent), and analyzed pre-treatment tumor tissue specimens. Our study uncovered extensive differences in tumor composition between the poor responders and excellent responders to chemotherapy, related to cell cluster organization and localization. This in-depth characterization of high-grade serous ovarian carcinoma tumor tissue from poor and excellent responders showed that spatial interactions between cell clusters may influence chemo-responsiveness more than cluster composition alone.
Project description:RNA sequencing of A431 cell line samples before and after gefitinib treatment, at 0, 2, 6 and 24 hours, was performed in order to characterize the cell line's early and late response to this drug, and to compare against proteomics (mass spectrometry) characterization of the cell line using the same setup. These data were used in Branca et al., HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics., Nat Methods. 2014 Jan;11(1):59-62 (doi: 10.1038/nmeth.2732).