A method for Boolean analysis of protein interactions at a molecular level.

Determining the levels of protein-protein interactions is essential for the analysis of signaling within the cell, characterization of mutation effects, protein function and activation in health and disease, among others. Herein, we describe MolBoolean - a method to detect interactions between endogenous proteins in various subcellular compartments, utilizing antibody-DNA conjugates for identification and signal amplification. In contrast to proximity ligation assays, MolBoolean simultaneously indicates the relative abundances of protein A and B not interacting with each other, as well as the pool of A and B proteins that are proximal enough to be considered an AB complex. MolBoolean is applicable both in fixed cells and tissue sections. The specific and quantifiable data that the method generates provide opportunities for both diagnostic use and medical research.

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.

Elevated levels of circulating CDH5 and FABP1 in association with human drug-induced liver injury.

BACKGROUND & AIMS: The occurrence of drug-induced liver injury (DILI) is a major issue in all phases of drug development. To identify novel biomarker candidates associated with DILI, we utilised an affinity proteomics strategy, where antibody suspension bead arrays were applied to profile plasma and serum samples from human DILI cases and controls. METHODS: An initial screening was performed using 4594 randomly selected antibodies, representing 3450 human proteins. Resulting candidate proteins together with proposed DILI biomarker candidates generated a DILI array of 251 proteins for subsequent target analysis and verifications. In total, 1196 samples from 241 individuals across four independent cohorts were profiled: healthy volunteers receiving acetaminophen, patients with human immunodeficiency virus and/or tuberculosis receiving treatment, DILI cases originating from a wide spectrum of drugs, and healthy volunteers receiving heparins. RESULTS: We observed elevated levels of cadherin 5, type 2 (CDH5) and fatty acid-binding protein 1 (FABP1) in DILI cases. In the two longitudinal cohorts, CDH5 was elevated already at baseline. FABP1 was elevated after treatment initiation and seemed to respond more rapidly than alanine aminotransferase (ALT). The elevations were verified in the DILI cases treated with various drugs. In the heparin cohort, CDH5 was stable over time whereas FABP1 was elevated. CONCLUSIONS: These results suggest that CDH5 may have value as a susceptibility marker for DILI. FABP1 was identified as a biomarker candidate with superior characteristics regarding tissue distribution and kinetics compared to ALT but likely with limited predictive value for the development of severe DILI. Further studies are needed to determine the clinical utility of the proposed markers.

Transglutaminase 4 as a prostate autoantigen in male subfertility.

Autoimmune polyendocrine syndrome type 1 (APS1), a monogenic disorder caused by AIRE gene mutations, features multiple autoimmune disease components. Infertility is common in both males and females with APS1. Although female infertility can be explained by autoimmune ovarian failure, the mechanisms underlying male infertility have remained poorly understood. We performed a proteome-wide autoantibody screen in APS1 patient sera to assess the autoimmune response against the male reproductive organs. By screening human protein arrays with male and female patient sera and by selecting for gender-imbalanced autoantibody signals, we identified transglutaminase 4 (TGM4) as a male-specific autoantigen. Notably, TGM4 is a prostatic secretory molecule with critical role in male reproduction. TGM4 autoantibodies were detected in most of the adult male APS1 patients but were absent in all the young males. Consecutive serum samples further revealed that TGM4 autoantibodies first presented during pubertal age and subsequent to prostate maturation. We assessed the animal model for APS1, the Aire-deficient mouse, and found spontaneous development of TGM4 autoantibodies specifically in males. Aire-deficient mice failed to present TGM4 in the thymus, consistent with a defect in central tolerance for TGM4. In the mouse, we further link TGM4 immunity with a destructive prostatitis and compromised secretion of TGM4. Collectively, our findings in APS1 patients and Aire-deficient mice reveal prostate autoimmunity as a major manifestation of APS1 with potential role in male subfertility.

The human cardiac and skeletal muscle proteomes defined by transcriptomics and antibody-based profiling.

BACKGROUND: To understand cardiac and skeletal muscle function, it is important to define and explore their molecular constituents and also to identify similarities and differences in the gene expression in these two different striated muscle tissues. Here, we have investigated the genes and proteins with elevated expression in cardiac and skeletal muscle in relation to all other major human tissues and organs using a global transcriptomics analysis complemented with antibody-based profiling to localize the corresponding proteins on a single cell level. RESULTS: Our study identified a comprehensive list of genes expressed in cardiac and skeletal muscle. The genes with elevated expression were further stratified according to their global expression pattern across the human body as well as their precise localization in the muscle tissues. The functions of the proteins encoded by the elevated genes are well in line with the physiological functions of cardiac and skeletal muscle, such as contraction, ion transport, regulation of membrane potential and actomyosin structure organization. A large fraction of the transcripts in both cardiac and skeletal muscle correspond to mitochondrial proteins involved in energy metabolism, which demonstrates the extreme specialization of these muscle tissues to provide energy for contraction. CONCLUSIONS: Our results provide a comprehensive list of genes and proteins elevated in striated muscles. A number of proteins not previously characterized in cardiac and skeletal muscle were identified and localized to specific cellular subcompartments. These proteins represent an interesting starting point for further functional analysis of their role in muscle biology and disease.

Proteome- and transcriptome-driven reconstruction of the human myocyte metabolic network and its use for identification of markers for diabetes.

Skeletal myocytes are metabolically active and susceptible to insulin resistance and are thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes, and their elucidation at the systems level requires genome-wide data and biological networks. Genome-scale metabolic models (GEMs) provide a network context for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta-analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism, connected through the downregulated dihydrolipoamide dehydrogenase. Strikingly, the gene signature underlying this metabolic regulation successfully classifies the disease state of individual samples, suggesting that regulation of these pathways is a ubiquitous feature of myocytes in response to T2D.

Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling.

Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted 85 antimetabolites that can inhibit growth of, or even kill, any of the cell lines, while at the same time not being toxic for 83 different healthy human cell types. 60 of these antimetabolites were found to inhibit growth in all cell lines. Finally, we experimentally validated one of the predicted antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies.

Proteomics. Tissue-based map of the human proteome.

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.

Defining the human gallbladder proteome by transcriptomics and affinity proteomics.

Global protein analysis of human gallbladder tissue is vital for identification of molecular regulators and effectors of its physiological activity. Here, we employed a genome-wide deep RNA sequencing analysis in 28 human tissues to identify the genes overrepresented in the gallbladder and complemented it with antibody-based immunohistochemistry in 48 human tissues. We characterized human gallbladder proteins and identified 140 gallbladder-specific proteins with an elevated expression in the gallbladder as compared to the other analyzed tissues. Five genes were categorized as enriched, with at least fivefold higher levels in gallbladder, 60 genes were categorized as group enriched with elevated transcript levels in gallbladder shared with at least one other tissue and 75 genes were categorized as enhanced with higher expression than the average expression in other tissues. We explored the localization of the genes within the gallbladder through cell-type specific antibody-based protein profiling and the subcellular localization of the genes through immunofluorescent-based profiling. Finally, we revealed the biological processes and metabolic functions carried out by these genes through the use of GO, KEGG Pathway, and HMR2.0 that is compilation of the human metabolic reactions. We demonstrated the results of the combined analysis of the transcriptomics and affinity proteomics.

Defining the human adipose tissue proteome to reveal metabolic alterations in obesity.

White adipose tissue (WAT) has a major role in the progression of obesity. Here, we combined data from RNA-Seq and antibody-based immunohistochemistry to describe the normal physiology of human WAT obtained from three female subjects and explored WAT-specific genes by comparing WAT to 26 other major human tissues. Using the protein evidence in WAT, we validated the content of a genome-scale metabolic model for adipocytes. We employed this high-quality model for the analysis of subcutaneous adipose tissue (SAT) gene expression data obtained from subjects included in the Swedish Obese Subjects Sib Pair study to reveal molecular differences between lean and obese individuals. We integrated SAT gene expression and plasma metabolomics data, investigated the contribution of the metabolic differences in the mitochondria of SAT to the occurrence of obesity, and eventually identified cytosolic branched-chain amino acid (BCAA) transaminase 1 as a potential target that can be used for drug development. We observed decreased glutaminolysis and alterations in the BCAAs metabolism in SAT of obese subjects compared to lean subjects. We also provided mechanistic explanations for the changes in the plasma level of BCAAs, glutamate, pyruvate, and α-ketoglutarate in obese subjects. Finally, we validated a subset of our model-based predictions in 20 SAT samples obtained from 10 lean and 10 obese male and female subjects.

The lung-specific proteome defined by integration of transcriptomics and antibody-based profiling.

The combined action of multiple cell types is essential for the physiological function of the lung, and increased awareness of the molecular constituents characterizing each cell type is likely to advance the understanding of lung biology and disease. In the current study, we used genome-wide RNA sequencing of normal lung parenchyma and 26 additional tissue types, combined with antibody-based protein profiling, to localize the expression to specific cell types. Altogether, 221 genes were found to be elevated in the lung compared with their expression in other analyzed tissues. Among the gene products were several well-known markers, but also several proteins previously not described in the context of the lung. To link the lung-specific molecular repertoire to human disease, survival associations of pneumocyte-specific genes were assessed by using transcriptomics data from 7 non-small-cell lung cancer (NSCLC) cohorts. Transcript levels of 10 genes (SFTPB, SFTPC, SFTPD, SLC34A2, LAMP3, CACNA2D2, AGER, EMP2, NKX2-1, and NAPSA) were significantly associated with survival in the adenocarcinoma subgroup, thus qualifying as promising biomarker candidates. In summary, based on an integrated omics approach, we identified genes with elevated expression in lung and localized corresponding protein expression to different cell types. As biomarker candidates, these proteins may represent intriguing starting points for further exploration in health and disease.

Garbage in, garbage out: a critical evaluation of strategies used for validation of immunohistochemical biomarkers.

The use of immunohistochemistry (IHC) in clinical cohorts is of paramount importance in determining the utility of a biomarker in clinical practice. A major bottleneck in translating a biomarker from bench-to-bedside is the lack of well characterized, specific antibodies suitable for IHC. Despite the widespread use of IHC as a biomarker validation tool, no universally accepted standardization guidelines have been developed to determine the applicability of particular antibodies for IHC prior to its use. In this review, we discuss the technical challenges faced by the use of immunohistochemical biomarkers and rigorously explore classical and emerging antibody validation technologies. Based on our review of these technologies, we provide strict criteria for the pragmatic validation of antibodies for use in immunohistochemical assays.

Affinity proteomics reveals elevated muscle proteins in plasma of children with cerebral malaria.

Systemic inflammation and sequestration of parasitized erythrocytes are central processes in the pathophysiology of severe Plasmodium falciparum childhood malaria. However, it is still not understood why some children are more at risks to develop malaria complications than others. To identify human proteins in plasma related to childhood malaria syndromes, multiplex antibody suspension bead arrays were employed. Out of the 1,015 proteins analyzed in plasma from more than 700 children, 41 differed between malaria infected children and community controls, whereas 13 discriminated uncomplicated malaria from severe malaria syndromes. Markers of oxidative stress were found related to severe malaria anemia while markers of endothelial activation, platelet adhesion and muscular damage were identified in relation to children with cerebral malaria. These findings suggest the presence of generalized vascular inflammation, vascular wall modulations, activation of endothelium and unbalanced glucose metabolism in severe malaria. The increased levels of specific muscle proteins in plasma implicate potential muscle damage and microvasculature lesions during the course of cerebral malaria.

Characterization of Leukocyte Formin FMNL1 Expression in Human Tissues.

Formins are cytoskeleton regulating proteins characterized by a common FH2 structural domain. As key players in the assembly of actin filaments, formins direct dynamic cytoskeletal processes that influence cell shape, movement and adhesion. The large number of formin genes, fifteen in the human, suggests distinct tasks and expression patterns for individual family members, in addition to overlapping functions. Several formins have been associated with invasive cell properties in experimental models, linking them to cancer biology. One example is FMNL1, which is considered to be a leukocyte formin and is known to be overexpressed in lymphomas. Studies on FMNL1 and many other formins have been hampered by a lack of research tools, especially antibodies suitable for staining paraffin-embedded formalin-fixed tissues. Here we characterize, using bioinformatics tools and a validated antibody, the expression pattern of FMNL1 in human tissues and study its subcellular distribution. Our results indicate that FMNL1 expression is not restricted to hematopoietic tissues and that neoexpression of FMNL1 can be seen in epithelial cancer.

Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling.

Genome-scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype-phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six HCC patients based on the proteomics data, HMR 2.0, and a task-driven model reconstruction algorithm (tINIT). The personalized GEMs were employed to identify anticancer drugs using the concept of antimetabolites; i.e., drugs that are structural analogs to metabolites. The toxicity of each antimetabolite was predicted by assessing the in silico functionality of 83 healthy cell type-specific GEMs, which were also reconstructed with the tINIT algorithm. We predicted 101 antimetabolites that could be effective in preventing tumor growth in all HCC patients, and 46 antimetabolites which were specific to individual patients. Twenty-two of the 101 predicted antimetabolites have already been used in different cancer treatment strategies, while the remaining antimetabolites represent new potential drugs. Finally, one of the identified targets was validated experimentally, and it was confirmed to attenuate growth of the HepG2 cell line.

The human liver-specific proteome defined by transcriptomics and antibody-based profiling.

Human liver physiology and the genetic etiology of the liver diseases can potentially be elucidated through the identification of proteins with enriched expression in the liver. Here, we combined data from RNA sequencing (RNA-Seq) and antibody-based immunohistochemistry across all major human tissues to explore the human liver proteome with enriched expression, as well as the cell type-enriched expression in hepatocyte and bile duct cells. We identified in total 477 protein-coding genes with elevated expression in the liver: 179 genes have higher expression as compared to all the other analyzed tissues; 164 genes have elevated transcript levels in the liver shared with at least one other tissue type; and an additional 134 genes have a mild level of increased expression in the liver. We identified the precise localization of these proteins through antibody-based protein profiling and the subcellular localization of these proteins through immunofluorescent-based profiling. We also identified the biological processes and metabolic functions associated with these proteins, investigated their contribution in the occurrence of liver diseases, and identified potential targets for their treatment. Our study demonstrates the use of RNA-Seq and antibody-based immunohistochemistry for characterizing the human liver proteome, as well as the use of tissue-specific proteins in identification of novel drug targets and discovery of biomarkers.-Kampf, C., Mardinoglu, A., Fagerberg, L., Hallström, B. M., Edlund, K., Lundberg, E., Pontén, F., Nielsen, J., Uhlen, M. The human liver-specific proteome defined by transcriptomics and antibody-based profiling.

Antibody validation of immunohistochemistry for biomarker discovery: recommendations of a consortium of academic and pharmaceutical based histopathology researchers.

As biomarker discovery takes centre-stage, the role of immunohistochemistry within that process is increasing. At the same time, the number of antibodies being produced for "research use" continues to rise and it is important that antibodies to be used as biomarkers are validated for specificity and sensitivity before use. This guideline seeks to provide a stepwise approach for the validation of an antibody for immunohistochemical assays, reflecting the views of a consortium of academic and pharmaceutical based histopathology researchers. We propose that antibodies are placed into a tier system, level 1-3, based on evidence of their usage in immunohistochemistry, and that the degree of validation required is proportionate to their place on that tier.

Antibody performance in western blot applications is context-dependent.

An important concern for the use of antibodies in various applications, such as western blot (WB) or immunohistochemistry (IHC), is specificity. This calls for systematic validations using well-designed conditions. Here, we have analyzed 13 000 antibodies using western blot with lysates from human cell lines, tissues, and plasma. Standardized stratification showed that 45% of the antibodies yielded supportive staining, and the rest either no staining (12%) or protein bands of wrong size (43%). A comparative study of WB and IHC showed that the performance of antibodies is application-specific, although a correlation between no WB staining and weak IHC staining could be seen. To investigate the influence of protein abundance on the apparent specificity of the antibody, new WB analyses were performed for 1369 genes that gave unsupportive WBs in the initial screening using cell lysates with overexpressed full-length proteins. Then, more than 82% of the antibodies yielded a specific band corresponding to the full-length protein. Hence, the vast majority of the antibodies (90%) used in this study specifically recognize the target protein when present at sufficiently high levels. This demonstrates the context- and application-dependence of antibody validation and emphasizes that caution is needed when annotating binding reagents as specific or cross-reactive. WB is one of the most commonly used methods for validation of antibodies. Our data implicate that solely using one platform for antibody validation might give misleading information and therefore at least one additional method should be used to verify the achieved data.