A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis

Formalin fixation and paraffin-embedding (FFPE) is the most common method to preserve human tissue for clinical diagnosis, and FFPE archives represent an invaluable resource for biomedical research. Proteins in FFPE material are stable over decades but their efficient extraction and streamlined analysis by mass spectrometry (MS)-based proteomics has so far proven challenging. Herein we describe a MS-based proteomic workflow for quantitative profiling of large FFPE tissue cohorts directly from histopathology glass slides. We demonstrate broad applicability of the workflow to clinical pathology specimens and variable sample amounts, including low-input cancer tissue isolated by laser microdissection. Using state-of-the-art data dependent acquisition (DDA) and data independent acquisition (DIA) MS workflows, we consistently quantify a large part of the proteome in 100 min single-run analyses. In an adenoma cohort comprising more than 100 samples, total workup took less than a day. We observed a moderate trend towards lower protein identification in long-term stored samples (>15 years), but clustering into distinct proteomic subtypes was independent of archival time. Our results underscore the great promise of FFPE tissues for patient phenotyping using unbiased proteomics and they prove the feasibility of analyzing large tissue cohorts in a robust, timely, and streamlined manner

Spatially and cell-type resolved quantitative proteomic atlas of healthy human skin

Human skin provides both physical integrity and immunological protection from the external environment using functionally distinct layers, cell types and extracellular matrix. Despite its central role in human health and disease, the constituent proteins of skin have not been systematically characterized. Here, we combine advanced tissue dissection methods, flow cytometry and state-of-the-art proteomics to describe a spatially-resolved quantitative proteomic atlas of human skin. We quantify 10,701 proteins as a function of their spatial location and cellular origin. The resulting protein atlas and our initial data analyses demonstrate the value of proteomics for understanding cell-type diversity within the skin. We describe the quantitative distribution of structural proteins, known and previously undescribed proteins specific to cellular subsets and those with specialized immunological functions such as cytokines and chemokines. We anticipate that this proteomic atlas of human skin will become an essential community resource for basic and translational research (https://skin.science/)

Deep Visual Proteomics defines single-cell identity and heterogeneity

Peer reviewe

Deep Visual Proteomics defines single-cell identity and heterogeneity

Deep Visual Proteomics combines machine learning, automated image analysis and single-cell proteomics. Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples

Efficient mitotic checkpoint signaling depends on integrated activities of Bub1 and the RZZ complex

Kinetochore localized Mad1 is essential for generating a "wait anaphase" signal during mitosis, hereby ensuring accurate chromosome segregation. Inconsistent models for the function and quantitative contribution of the two mammalian Mad1 kinetochore receptors: Bub1 and the Rod-Zw10-Zwilch (RZZ) complex exist. By combining genome editing and RNAi, we achieve penetrant removal of Bub1 and Rod in human cells, which reveals that efficient checkpoint signaling depends on the integrated activities of these proteins. Rod removal reduces the proximity of Bub1 and Mad1, and we can bypass the requirement for Rod by tethering Mad1 to kinetochores or increasing the strength of the Bub1-Mad1 interaction. We find that Bub1 has checkpoint functions independent of Mad1 localization that are supported by low levels of Bub1 suggesting a catalytic function. In conclusion, our results support an integrated model for the Mad1 receptors in which the primary role of RZZ is to localize Mad1 at kinetochores to generate the Mad1-Bub1 complex

FAM111 protease activity undermines cellular fitness and is amplified by gain‐of‐function mutations in human disease

Dominant missense mutations in the human serine protease FAM111A underlie perinatally lethal gracile bone dysplasia and Kenny-Caffey syndrome, yet how FAM111A mutations lead to disease is not known. We show that FAM111A proteolytic activity suppresses DNA replication and transcription by displacing key effectors of these processes from chromatin, triggering rapid programmed cell death by Caspase-dependent apoptosis to potently undermine cell viability. Patient-associated point mutations in FAM111A exacerbate these phenotypes by hyperactivating its intrinsic protease activity. Moreover, FAM111A forms a complex with the uncharacterized homologous serine protease FAM111B, point mutations in which cause a hereditary fibrosing poikiloderma syndrome, and we demonstrate that disease-associated FAM111B mutants display amplified proteolytic activity and phenocopy the cellular impact of deregulated FAM111A catalytic activity. Thus, patient-associated FAM111A and FAM111B mutations may drive multisystem disorders via a common gain-of-function mechanism that relieves inhibitory constraints on their protease activities to powerfully undermine cellular fitness

Spatially and cell-type resolved quantitative proteomic atlas of healthy human skin

Human skin provides both physical integrity and immunological protection from the external environment using functionally distinct layers, cell types and extracellular matrix. Despite its central role in human health and disease, the constituent proteins of skin have not been systematically characterized. Here, we combine advanced tissue dissection methods, flow cytometry and state-of-the-art proteomics to describe a spatially-resolved quantitative proteomic atlas of human skin. We quantify 10,701 proteins as a function of their spatial location and cellular origin. The resulting protein atlas and our initial data analyses demonstrate the value of proteomics for understanding cell-type diversity within the skin. We describe the quantitative distribution of structural proteins, known and previously undescribed proteins specific to cellular subsets and those with specialized immunological functions such as cytokines and chemokines. We anticipate that this proteomic atlas of human skin will become an essential community resource for basic and translational research (https://skin.science/)