Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease.Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody-based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to ϳ80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body. Molecular & Cellular Proteomics 13: 10.1074/mcp.M113.035600, 397-406, 2014.Central questions in human biology relate to how cells, tissues, and organs differ in the expression of genes and proteins and what consequences the global expression pattern has for the phenotype of various cells with different functions in the body. Therefore, the annotation of the human protein-coding genes with regards to the spatial, temporal, and functional space represents one of the greatest challenges in human biology (1). Important questions related to this are how many of the genes actually code for functional proteins, how many are expressed in a tissue-specific manner, and how many proteins have "housekeeping" functions and are therefore expressed in all cells? These questions have a major impact not only on efforts to try to understand human biology, but also for applied medical research, such as pharmaceutical drug development and biomarker discovery in the field of translational medicine.Several efforts have been initiated in the aftermath of the genome project to systematically annotate the putative protein-coding part of the human genome. Genome annotation efforts, such as Ensembl (2) and RefSeq (3), have provided an increasingly accurate map with at present ϳ20,000 proteincoding genes. Similarly, the ENCODE consortium has been launched to provide an integrated encyclopedia of DNA eleFrom the ‡Science for Life Laboratory, KTH -Royal Institute of Technology, SE-171 21 Stockholm, Sweden; §Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden; ¶Department

Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

Resolving the spatial distribution of the human proteome at a subcellular level can greatly increase our understanding of human biology and disease. Here we present a comprehensive image-based map of subcellular protein distribution, the Cell Atlas, built by integrating transcriptomics and antibody-based immunofluorescence microscopy with validation by mass spectrometry. Mapping the in situ localization of 12,003 human proteins at a single-cell level to 30 subcellular structures enabled the definition of the proteomes of 13 major organelles. Exploration of the proteomes revealed single-cell variations in abundance or spatial distribution and localization of about half of the proteins to multiple compartments. This subcellular map can be used to refine existing protein-protein interaction networks and provides an important resource to deconvolute the highly complex architecture of the human cell.

Antibody-based proteomics provides a powerful approach for the functional study of the human proteome involving the systematic generation of protein-specific affinity reagents. We used this strategy to construct a comprehensive, antibody-based protein atlas for expression and localization profiles in 48 normal human tissues and 20 different cancers. Here we report a new publicly available database containing, in the first version, ϳ400,000 high resolution images corresponding to more than 700 antibodies toward human proteins. Each image has been annotated by a certified pathologist to provide a knowledge base for functional studies and to allow queries about protein profiles in normal and disease tissues. Our results suggest it should be possible to extend this analysis to the majority of all human proteins thus providing a valuable tool for medical and biological research.

An attractive path forward in proteomics is to experimentally annotate the human protein complement of the genome in a genecentric manner. Using antibodies, it might be possible to design protein-specific probes for a representative protein from every protein-coding gene and to subsequently use the antibodies for systematical analysis of cellular distribution and subcellular localization of proteins in normal and disease tissues. A new version (4.0) of the Human Protein Atlas has been developed in a genecentric manner with the inclusion of all human genes and splice variants predicted from genome efforts together with a visualization of each protein with characteristics such as predicted membrane regions, signal peptide, and protein domains and new plots showing the uniqueness (sequence similarity) of every fraction of each protein toward all other human proteins. The new version is based on tissue profiles generated from 6120 antibodies with more than five million immunohistochemistry-based images covering 5067 human genes, corresponding to ϳ25% of the human genome. Version 4.0 includes a putative list of members in various protein classes, both functional classes, such as kinases, transcription factors, G-protein-coupled receptors, etc., and project-related classes, such as candidate genes for cancer or cardiovascular diseases. The exact antigen sequence for the internally generated antibodies has also been released together with a visualization of the application-specific validation performed for each antibody, including a protein array assay, Western blot analysis, immunohistochemistry, and, for a large fraction, immunofluorescencebased confocal microscopy. New search functionalities have been added to allow complex queries regarding protein expression profiles, protein classes, and chromosome location. The new version of the protein atlas thus is a resource for many areas of biomedical research, including protein science and biomarker discovery. Molecular

The large vascular meristem of poplar trees with its highly organized secondary xylem enables the boundaries between different developmental zones to be easily distinguished. This property of wood-forming tissues allowed us to determine a unique tissuespecific transcript profile for a well defined developmental gradient. RNA was prepared from different developmental stages of xylogenesis for DNA microarray analysis by using a hybrid aspen unigene set consisting of 2,995 expressed sequence tags. The analysis revealed that the genes encoding lignin and cellulose biosynthetic enzymes, as well as a number of transcription factors and other potential regulators of xylogenesis, are under strict developmental stage-specific transcriptional regulation.T ranscript profiling has the potential to reveal transcriptional hierarchy during development for thousands of genes, as well as providing expression data for many genes of unknown function (1, 2). This is especially true when expression patterns can be obtained for well defined tissues at specific developmental stages. However, this is technically demanding and so far there are no reports demonstrating tissue-specific analysis on cell types from a single developmental sequence. We have studied the developing secondary xylem of poplar, which is highly organized with easily recognized and distinct boundaries between the different developmental stages. Wood formation is initiated in the vascular cambium. Cambial derivatives develop into xylem cells through the processes of division, expansion, secondary wall formation, lignification, and finally, programmed cell death. The large physical size of the vascular meristem in trees offers a unique possibility to obtain samples from defined developmental stages by tangential cryo sectioning (3). To determine the steady-state mRNA levels at specific stages during the ontogeny of wood formation in Populus tremula ϫ Populus tremuloides (hybrid aspen) we sampled 30-m-thick sections through the wood development region and subsequently analyzed the samples by using a spotted cDNA-microarray (4) consisting of 2,995 unique ESTs from hybrid aspen. Our study provides a unique global examination of gene expression patterns that encompasses a developmental gradient within a multicellular organism. Materials and MethodsThe Unigene set was selected from the expressed sequence tags (ESTs) presented in ref. 5, using cluster analysis. ESTs were transformed into Escherichia coli by using TSS competent cells (6), plasmids were prepared by using 96-well Multiscreen FB plates (Millipore), inserts were PCR amplified by using vectorspecific primers, and PCR products were purified on Multiscreen PCR filter plates (Millipore) and spotted in duplicate onto CMT GAPS slides (Corning) by using the GMS 417 Arrayer (Affymetrix, Santa Clara, CA) as described (7). All PCR products were checked on ethidium bromide-stained agarose gels. Nine clones giving double PCR bands were excluded from the analysis.A subset of 2,085 of the 2,995 PCR products in the Unigene set...

SARS-CoV-2 may pose an occupational health risk to healthcare workers. Here, we report the seroprevalence of SARS-CoV-2 antibodies, self-reported symptoms and occupational exposure to SARS-CoV-2 among healthcare workers at a large acute care hospital in Sweden. The seroprevalence of IgG antibodies against SARS-CoV-2 was 19.1% among the 2149 healthcare workers recruited between April 14th and May 8th 2020, which was higher than the reported regional seroprevalence during the same time period. Symptoms associated with seroprevalence were anosmia (odds ratio (OR) 28.4, 95% CI 20.6–39.5) and ageusia (OR 19.2, 95% CI 14.3–26.1). Seroprevalence was also associated with patient contact (OR 2.9, 95% CI 1.9–4.5) and covid-19 patient contact (OR 3.3, 95% CI 2.2–5.3). These findings imply an occupational risk for SARS-CoV-2 infection among healthcare workers. Continued measures are warranted to assure healthcare workers safety and reduce transmission from healthcare workers to patients and to the community.