The neuropeptide landscape of human prefrontal cortex.

Human prefrontal cortex (hPFC) is a complex brain region involved in cognitive and emotional processes and several psychiatric disorders. Here, we present an overview of the distribution of the peptidergic systems in 17 subregions of hPFC and three reference cortices obtained by microdissection and based on RNA sequencing and RNAscope methods integrated with published single-cell transcriptomics data. We detected expression of 60 neuropeptides and 60 neuropeptide receptors in at least one of the hPFC subregions. The results reveal that the peptidergic landscape in PFC consists of closely located and functionally different subregions with unique peptide/transmitter-related profiles. Neuropeptide-rich PFC subregions were identified, encompassing regions from anterior cingulate cortex/orbitofrontal gyrus. Furthermore, marked differences in gene expression exist between different PFC regions (>5-fold; cocaine and amphetamine-regulated transcript peptide) as well as between PFC regions and reference regions, for example, for somatostatin and several receptors. We suggest that the present approach allows definition of, still hypothetical, microcircuits exemplified by glutamatergic neurons expressing a peptide cotransmitter either as an agonist (hypocretin/orexin) or antagonist (galanin). Specific neuropeptide receptors have been identified as possible targets for neuronal afferents and, interestingly, peripheral blood-borne peptide hormones (leptin, adiponectin, gastric inhibitory peptide, glucagon-like peptides, and peptide YY). Together with other recent publications, our results support the view that neuropeptide systems may play an important role in hPFC and underpin the concept that neuropeptide signaling helps stabilize circuit connectivity and fine-tune/modulate PFC functions executed during health and disease.

Genome-wide annotation of protein-coding genes in pig.

BACKGROUND: There is a need for functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. Here, a new annotation strategy is introduced based on dimensionality reduction and density-based clustering of whole-body co-expression patterns. This strategy has been used to explore the gene expression landscape in pig, and we present a whole-body map of all protein-coding genes in all major pig tissues and organs. RESULTS: An open-access pig expression map ( www.rnaatlas.org ) is presented based on the expression of 350 samples across 98 well-defined pig tissues divided into 44 tissue groups. A new UMAP-based classification scheme is introduced, in which all protein-coding genes are stratified into tissue expression clusters based on body-wide expression profiles. The distribution and tissue specificity of all 22,342 protein-coding pig genes are presented. CONCLUSIONS: Here, we present a new genome-wide annotation strategy based on dimensionality reduction and density-based clustering. A genome-wide resource of the transcriptome map across all major tissues and organs in pig is presented, and the data is available as an open-access resource ( www.rnaatlas.org ), including a comparison to the expression of human orthologs.

Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins.

The localization of proteins at a tissue- or cell-type-specific level is tightly linked to the protein function. To better understand each protein's role in cellular systems, spatial information constitutes an important complement to quantitative data. The standard methods for determining the spatial distribution of proteins in single cells of complex tissue samples make use of antibodies. For a stringent analysis of the human proteome, we used orthogonal methods and independent antibodies to validate 5981 antibodies that show the expression of 3775 human proteins across all major human tissues. This enhanced validation uncovered 56 proteins corresponding to the group of "missing proteins" and 171 proteins of unknown function. The presented strategy will facilitate further discussions around criteria for evidence of protein existence based on immunohistochemistry and serves as a useful guide to identify candidate proteins for integrative studies with quantitative proteomics methods.

Cell Type-Specific Expression of Testis Elevated Genes Based on Transcriptomics and Antibody-Based Proteomics.

One of the most complex organs in the human body is the testis, where spermatogenesis takes place. This physiological process involves thousands of genes and proteins that are activated and repressed, making testis the organ with the highest number of tissue-specific genes. However, the function of a large proportion of the corresponding proteins remains unknown and testis harbors many missing proteins (MPs), defined as products of protein-coding genes that lack experimental mass spectrometry evidence. Here, an integrated omics approach was used for exploring the cell type-specific protein expression of genes with an elevated expression in testis. By combining genome-wide transcriptomics analysis with immunohistochemistry, more than 500 proteins with distinct testicular protein expression patterns were identified, and these were selected for in-depth characterization of their in situ expression in eight different testicular cell types. The cell type-specific protein expression patterns allowed us to identify six distinct clusters of expression at different stages of spermatogenesis. The analysis highlighted numerous poorly characterized proteins in each of these clusters whose expression overlapped with that of known proteins involved in spermatogenesis, including 85 proteins with an unknown function and 60 proteins that previously have been classified as MPs. Furthermore, we were able to characterize the in situ distribution of several proteins that previously lacked spatial information and cell type-specific expression within the testis. The testis elevated expression levels both at the RNA and protein levels suggest that these proteins are related to testis-specific functions. In summary, the study demonstrates the power of combining genome-wide transcriptomics analysis with antibody-based protein profiling to explore the cell type-specific expression of both well-known proteins and MPs. The analyzed proteins constitute important targets for further testis-specific research in male reproductive disorders.

Integration of Transcriptomics and Antibody-Based Proteomics for Exploration of Proteins Expressed in Specialized Tissues.

A large portion of human proteins are referred to as missing proteins, defined as protein-coding genes that lack experimental data on the protein level due to factors such as temporal expression, expression in tissues that are difficult to sample, or they actually do not encode functional proteins. In the present investigation, an integrated omics approach was used for identification and exploration of missing proteins. Transcriptomics data from three different sources-the Human Protein Atlas (HPA), the GTEx consortium, and the FANTOM5 consortium-were used as a starting point to identify genes selectively expressed in specialized tissues. Complementing the analysis with profiling on more specific tissues based on immunohistochemistry allowed for further exploration of cell-type-specific expression patterns. More detailed tissue profiling was performed for >300 genes on complementing tissues. The analysis identified tissue-specific expression of nine proteins previously listed as missing proteins (POU4F1, FRMD1, ARHGEF33, GABRG1, KRTAP2-1, BHLHE22, SPRR4, AVPR1B, and DCLK3), as well as numerous proteins with evidence of existence on the protein level that previously lacked information on spatial resolution and cell-type-specific expression pattern. We here present a comprehensive strategy for identification of missing proteins by combining transcriptomics with antibody-based proteomics. The analyzed proteins provide interesting targets for organ-specific research in health and disease.

Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics.

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 ∼80% 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.

RNA- and antibody-based profiling of the human proteome with focus on chromosome 19.

An important part of the Human Proteome Project is to characterize the protein complement of the genome with antibody-based profiling. Within the framework of this effort, a new version 12 of the Human Protein Atlas ( www.proteinatlas.org ) has been launched, including transcriptomics data for 27 tissues and 44 cell lines to complement the protein expression data from antibody-based profiling. Besides the extensive addition of transcriptomics data, the Human Protein Atlas now contains antibody-based protein profiles for 82% of the 20 329 putative protein-coding genes. The comprehensive data resulting from RNA-seq analysis and antibody-based profiling performed within the Human Protein Atlas as well as information from UniProt were used to generate evidence summary scores for each of the 20 329 genes, of which 94% now have experimental evidence at least at transcript level. The evidence scores for all individual genes are displayed with regards to both RNA- and antibody-based protein profiles, including chromosome-centric visualizations. An analysis of the human chromosome 19 shows that ∼43% of the genes are expressed at the transcript level in all 27 tissues analyzed, suggesting a "house-keeping" function, while 12% of the genes show a more tissue-specific pattern with enriched expression in one of the analyzed tissues only.

Antibody-based protein profiling of the human chromosome 21.

The Human Proteome Project has been proposed to create a knowledge-based resource based on a systematical mapping of all human proteins, chromosome by chromosome, in a gene-centric manner. With this background, we here describe the systematic analysis of chromosome 21 using an antibody-based approach for protein profiling using both confocal microscopy and immunohistochemistry, complemented with transcript profiling using next generation sequencing data. We also describe a new approach for protein isoform analysis using a combination of antibody-based probing and isoelectric focusing. The analysis has identified several genes on chromosome 21 with no previous evidence on the protein level, and the isoform analysis indicates that a large fraction of human proteins have multiple isoforms. A chromosome-wide matrix is presented with status for all chromosome 21 genes regarding subcellular localization, tissue distribution, and molecular characterization of the corresponding proteins. The path to generate a chromosome-specific resource, including integrated data from complementary assay platforms, such as mass spectrometry and gene tagging analysis, is discussed.

Contribution of antibody-based protein profiling to the human Chromosome-centric Proteome Project (C-HPP).

A gene-centric Human Proteome Project has been proposed to characterize the human protein-coding genes in a chromosome-centered manner to understand human biology and disease. Here, we report on the protein evidence for all genes predicted from the genome sequence based on manual annotation from literature (UniProt), antibody-based profiling in cells, tissues and organs and analysis of the transcript profiles using next generation sequencing in human cell lines of different origins. We estimate that there is good evidence for protein existence for 69% (n = 13985) of the human protein-coding genes, while 23% have only evidence on the RNA level and 7% still lack experimental evidence. Analysis of the expression patterns shows few tissue-specific proteins and approximately half of the genes expressed in all the analyzed cells. The status for each gene with regards to protein evidence is visualized in a chromosome-centric manner as part of a new version of the Human Protein Atlas ( www.proteinatlas.org ).

A tool to facilitate clinical biomarker studies--a tissue dictionary based on the Human Protein Atlas.

The complexity of tissue and the alterations that distinguish normal from cancer remain a challenge for translating results from tumor biological studies into clinical medicine. This has generated an unmet need to exploit the findings from studies based on cell lines and model organisms to develop, validate and clinically apply novel diagnostic, prognostic and treatment predictive markers. As one step to meet this challenge, the Human Protein Atlas project has been set up to produce antibodies towards human protein targets corresponding to all human protein coding genes and to map protein expression in normal human tissues, cancer and cells. Here, we present a dictionary based on microscopy images created as an amendment to the Human Protein Atlas. The aim of the dictionary is to facilitate the interpretation and use of the image-based data available in the Human Protein Atlas, but also to serve as a tool for training and understanding tissue histology, pathology and cell biology. The dictionary contains three main parts, normal tissues, cancer tissues and cells, and is based on high-resolution images at different magnifications of full tissue sections stained with H & E. The cell atlas is centered on immunofluorescence and confocal microscopy images, using different color channels to highlight the organelle structure of a cell. Here, we explain how this dictionary can be used as a tool to aid clinicians and scientists in understanding the use of tissue histology and cancer pathology in diagnostics and biomarker studies.

Discovery of Functional Alternatively Spliced PKM Transcripts in Human Cancers.

Pyruvate kinase muscle type (PKM) is a key enzyme in glycolysis and plays an important oncological role in cancer. However, the association of PKM expression and the survival outcome of patients with different cancers is controversial. We employed systems biology methods to reveal prognostic value and potential biological functions of PKM transcripts in different human cancers. Protein products of transcripts were shown and detected by western blot and mass spectrometry analysis. We focused on different transcripts of PKM and investigated the associations between their mRNA expression and the clinical survival of the patients in 25 different cancers. We find that the transcripts encoding PKM2 and three previously unstudied transcripts, namely ENST00000389093, ENST00000568883, and ENST00000561609, exhibited opposite prognostic indications in different cancers. Moreover, we validated the prognostic effect of these transcripts in an independent kidney cancer cohort. Finally, we revealed that ENST00000389093 and ENST00000568883 possess pyruvate kinase enzymatic activity and may have functional roles in metabolism, cell invasion, and hypoxia response in cancer cells. Our study provided a potential explanation to the controversial prognostic indication of PKM, and could invoke future studies focusing on revealing the biological and oncological roles of these alternative spliced variants of PKM.

A single-cell type transcriptomics map of human tissues.

Advances in molecular profiling have opened up the possibility to map the expression of genes in cells, tissues, and organs in the human body. Here, we combined single-cell transcriptomics analysis with spatial antibody-based protein profiling to create a high-resolution single-cell type map of human tissues. An open access atlas has been launched to allow researchers to explore the expression of human protein-coding genes in 192 individual cell type clusters. An expression specificity classification was performed to determine the number of genes elevated in each cell type, allowing comparisons with bulk transcriptomics data. The analysis highlights distinct expression clusters corresponding to cell types sharing similar functions, both within the same organs and between organs.

A global view of protein expression in human cells, tissues, and organs.

Defining the protein profiles of tissues and organs is critical to understanding the unique characteristics of the various cell types in the human body. In this study, we report on an anatomically comprehensive analysis of 4842 protein profiles in 48 human tissues and 45 human cell lines. A detailed analysis of over 2 million manually annotated, high-resolution, immunohistochemistry-based images showed a high fraction (>65%) of expressed proteins in most cells and tissues, with very few proteins (<2%) detected in any single cell type. Similarly, confocal microscopy in three human cell lines detected expression of more than 70% of the analyzed proteins. Despite this ubiquitous expression, hierarchical clustering analysis, based on global protein expression patterns, shows that the analyzed cells can be still subdivided into groups according to the current concepts of histology and cellular differentiation. This study suggests that tissue specificity is achieved by precise regulation of protein levels in space and time, and that different tissues in the body acquire their unique characteristics by controlling not which proteins are expressed but how much of each is produced.

A web-based tool for in silico biomarker discovery based on tissue-specific protein profiles in normal and cancer tissues.

Here we report the development of a publicly available Web-based analysis tool for exploring proteins expressed in a tissue- or cancer-specific manner. The search queries are based on the human tissue profiles in normal and cancer cells in the Human Protein Atlas portal and rely on the individual annotation performed by pathologists of images representing immunohistochemically stained tissue sections. Approximately 1.8 million images representing more than 3000 antibodies directed toward human proteins were used in the study. The search tool allows for the systematic exploration of the protein atlas to discover potential protein biomarkers. Such biomarkers include tissue-specific markers, cell type-specific markers, tumor type-specific markers, markers of malignancy, and prognostic or predictive markers of cancers. Here we show examples of database queries to generate sets of candidate biomarker proteins for several of these different categories. Expression profiles of candidate proteins can then subsequently be validated by examination of the underlying high resolution images. The present study shows examples of search strategies revealing several potential protein biomarkers, including proteins specifically expressed in normal cells and in cancer cells from specified tumor types. The lists of candidate proteins can be used as a starting point for further validation in larger patient cohorts using both immunological approaches and technologies utilizing more classical proteomics tools.

Toward a confocal subcellular atlas of the human proteome.

Information on protein localization on the subcellular level is important to map and characterize the proteome and to better understand cellular functions of proteins. Here we report on a pilot study of 466 proteins in three human cell lines aimed to allow large scale confocal microscopy analysis using protein-specific antibodies. Approximately 3000 high resolution images were generated, and more than 80% of the analyzed proteins could be classified in one or multiple subcellular compartment(s). The localizations of the proteins showed, in many cases, good agreement with the Gene Ontology localization prediction model. This is the first large scale antibody-based study to localize proteins into subcellular compartments using antibodies and confocal microscopy. The results suggest that this approach might be a valuable tool in conjunction with predictive models for protein localization.

A genecentric Human Protein Atlas for expression profiles based on antibodies.

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 approximately 25% 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, immunofluorescence-based 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.

An atlas of the protein-coding genes in the human, pig, and mouse brain.

The brain, with its diverse physiology and intricate cellular organization, is the most complex organ of the mammalian body. To expand our basic understanding of the neurobiology of the brain and its diseases, we performed a comprehensive molecular dissection of 10 major brain regions and multiple subregions using a variety of transcriptomics methods and antibody-based mapping. This analysis was carried out in the human, pig, and mouse brain to allow the identification of regional expression profiles, as well as to study similarities and differences in expression levels between the three species. The resulting data have been made available in an open-access Brain Atlas resource, part of the Human Protein Atlas, to allow exploration and comparison of the expression of individual protein-coding genes in various parts of the mammalian brain.

A genome-wide transcriptomic analysis of protein-coding genes in human blood cells.

Blood is the predominant source for molecular analyses in humans, both in clinical and research settings. It is the target for many therapeutic strategies, emphasizing the need for comprehensive molecular maps of the cells constituting human blood. In this study, we performed a genome-wide transcriptomic analysis of protein-coding genes in sorted blood immune cell populations to characterize the expression levels of each individual gene across the blood cell types. All data are presented in an interactive, open-access Blood Atlas as part of the Human Protein Atlas and are integrated with expression profiles across all major tissues to provide spatial classification of all protein-coding genes. This allows for a genome-wide exploration of the expression profiles across human immune cell populations and all major human tissues and organs.

The human secretome.

The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immunoassays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood.

Enhanced validation of antibodies for research applications.

There is a need for standardized validation methods for antibody specificity and selectivity. Recently, five alternative validation pillars were proposed to explore the specificity of research antibodies using methods with no need for prior knowledge about the protein target. Here, we show that these principles can be used in a streamlined manner for enhanced validation of research antibodies in Western blot applications. More than 6,000 antibodies were validated with at least one of these strategies involving orthogonal methods, genetic knockdown, recombinant expression, independent antibodies, and capture mass spectrometry analysis. The results show a path forward for efforts to validate antibodies in an application-specific manner suitable for both providers and users.