Hanna Tegel

Tissue-based map of the human proteome

Protein expression across human tissues Sequencing the human genome gave new insights into human biology and disease. However, the ultimate goal is to understand the dynamic expression of each of the approximately 20,000 protein-coding genes and the function of each protein. Uhlén et al. now present a map of protein expression across 32 human tissues. They not only measured expression at an RNA level, but also used antibody profiling to precisely localize the corresponding proteins. An interactive website allows exploration of expression patterns across the human body. Science, this issue 10.1126/science.1260419 Transcriptomics and immunohistochemistry map protein expression across 32 human tissues. INTRODUCTION Resolving the molecular details of proteome variation in the different tissues and organs of the human body would greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on quantitative transcriptomics on a tissue and organ level combined with protein profiling using microarray-based immunohistochemistry to achieve spatial localization of proteins down to the single-cell level. We provide a global analysis of the secreted and membrane proteins, as well as an analysis of the expression profiles for all proteins targeted by pharmaceutical drugs and proteins implicated in cancer. RATIONALE We have used an integrative omics approach to study the spatial human proteome. Samples representing all major tissues and organs (n = 44) in the human body have been analyzed based on 24,028 antibodies corresponding to 16,975 protein-encoding genes, complemented with RNA-sequencing data for 32 of the tissues. The antibodies have been used to produce more than 13 million tissue-based immunohistochemistry images, each annotated by pathologists for all sampled tissues. To facilitate integration with other biological resources, all data are available for download and cross-referencing. RESULTS We report a genome-wide analysis of the tissue specificity of RNA and protein expression covering more than 90% of the putative protein-coding genes, complemented with analyses of various subproteomes, such as predicted secreted proteins (n = 3171) and membrane-bound proteins (n = 5570). The analysis shows that almost half of the genes are expressed in all analyzed tissues, which suggests that the gene products are needed in all cells to maintain “housekeeping” functions such as cell growth, energy generation, and basic metabolism. Furthermore, there is enrichment in metabolism among these genes, as 60% of all metabolic enzymes are expressed in all analyzed tissues. The largest number of tissue-enriched genes is found in the testis, followed by the brain and the liver. Analysis of the 618 proteins targeted by clinically approved drugs unexpectedly showed that 30% are expressed in all analyzed tissues. An analysis of metabolic activity based on genome-scale metabolic models (GEMS) revealed liver as the most metabolically active tissue, followed by adipose tissue and skeletal muscle. CONCLUSIONS A freely available interactive resource is presented as part of the Human Protein Atlas portal (www.proteinatlas.org), offering the possibility to explore the tissue-elevated proteomes in tissues and organs and to analyze tissue profiles for specific protein classes. Comprehensive lists of proteins expressed at elevated levels in the different tissues have been compiled to provide a spatial context with localization of the proteins in the subcompartments of each tissue and organ down to the single-cell level. The human tissue–enriched proteins. All tissue-enriched proteins are shown for 13 representative tissues or groups of tissues, stratified according to their predicted subcellular localization. Enriched proteins are mainly intracellular in testis, mainly membrane bound in brain and kidney, and mainly secreted in pancreas and liver. 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.

A Human Protein Atlas for Normal and Cancer Tissues Based on Antibody Proteomics

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, ∼400,000 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.

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.

Increased levels of recombinant human proteins with the Escherichia coli strain Rosetta(DE3).

The effect of two Escherichiacoli expression strains on the production of recombinant human protein fragments was evaluated. High-throughput protein production projects, such as the Swedish Human Protein Atlas project, are dependent on high protein yield and purity. By changing strain from E. coli BL21(DE3) to E. coli Rosetta(DE3) the overall success rate of the protein production has increased dramatically. The Rosetta(DE3) strain compensates for a number of rare codons. Here, we describe how the protein expression of human gene fragments in E. coli strains BL21(DE3) and Rosetta(DE3) was evaluated in two stages. Initially a test set of 68 recombinant proteins that previously had been expressed in BL21(DE3) was retransformed and expressed in Rosetta(DE3). The test set generated very positive results with an improved expression yield and a significantly better purity of the protein product which prompted us to implement the Rosetta(DE3) strain in the high-throughput protein production. Except for analysis of protein yield and purity the sequences were also analyzed regarding number of rare codons and rare codon clusters. The content of rare codons showed to have a significant effect on the protein purity. Based on the results of this study the atlas project permanently changed expression strain to Rosetta(DE3).

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 ).

Enhancing the protein production levels in Escherichia coli with a strong promoter

In biotechnology, the use of Escherichia coli for recombinant protein production has a long tradition, although the optimal production conditions for certain proteins are still not evident. The most favorable conditions for protein production vary with the gene product. Temperature and induction conditions represent parameters that affect total protein production, as well as the amount of soluble protein. Furthermore, the choice of promoter and bacterial strain will have large effects on the production of the target protein. In the present study, the effects of three different promoters (T7, trc and lacUV5) on E. coli production of target proteins with different characteristics are presented. The total amount of target protein as well as the amount of soluble protein were analyzed, demonstrating the benefits of using a strong promoter such as T7. To understand the underlying causes, transcription levels have been correlated with the total amount of target protein and protein solubility in vitro has been correlated with the amount of soluble protein that is produced. In addition, the effects of two different E. coli strains, BL21(DE3) and Rosetta(DE3), on the expression pattern were analyzed. It is concluded that the regulation of protein production is a combination of the transcription and translation efficiencies. Other important parameters include the nucleotide‐sequence itself and the solubility of the target protein.

High-throughput protein production – Lessons from scaling up from 10 to 288 recombinant proteins per week

The demand for high‐throughput recombinant protein production has markedly increased with the increased activity in the field of proteomics. Within the Human Protein Atlas project recombinantly produced human protein fragments are used for antibody production. Here we describe how the protein expression and purification protocol has been optimized in the project to allow for handling of nearly 300 different proteins per week. The number of manual handling steps has been significantly reduced (from 18 to 9) and the protein purification has been completely automated.

Parallel production and verification of protein products using a novel high-throughput screening method.

Protein production and analysis in a parallel fashion is today applied in laboratories worldwide and there is a great need to improve the techniques and systems used for this purpose. In order to save time and money, a fast and reliable screening method for analysis of protein production and also verification of the protein product is desired. Here, a micro-scale protocol for the parallel production and screening of 96 proteins in plate format is described. Protein capture was achieved using immobilized metal affinity chromatography and the product was verified using matrix-assisted laser desorption ionization time-of-flight MS. In order to obtain sufficiently high cell densities and product yield in the small-volume cultivations, the EnBase® cultivation technology was applied, which enables cultivation in as small volumes as 150 μL. Here, the efficiency of the method is demonstrated by producing 96 human, recombinant proteins, both in micro-scale and using a standard full-scale protocol and comparing the results in regard to both protein identity and sample purity. The results obtained are highly comparable to those acquired through employing standard full-scale purification protocols, thus validating this method as a successful initial screening step before protein production at a larger scale.

Solid-phase cloning for high-throughput assembly of single and multiple DNA parts

We describe solid-phase cloning (SPC) for high-throughput assembly of expression plasmids. Our method allows PCR products to be put directly into a liquid handler for capture and purification using paramagnetic streptavidin beads and conversion into constructs by subsequent cloning reactions. We present a robust automated protocol for restriction enzyme based SPC and its performance for the cloning of >60 000 unique human gene fragments into expression vectors. In addition, we report on SPC-based single-strand assembly for applications where exact control of the sequence between fragments is needed or where multiple inserts are to be assembled. In this approach, the solid support allows for head-to-tail assembly of DNA fragments based on hybridization and polymerase fill-in. The usefulness of head-to-tail SPC was demonstrated by assembly of >150 constructs with up to four DNA parts at an average success rate above 80%. We report on several applications for SPC and we suggest it to be particularly suitable for high-throughput efforts using laboratory workstations.

Machine learning in computational biology to accelerate high-throughput protein expression

Motivation: The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high‐throughput immunohistochemistry‐based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular‐level properties influencing expression and solubility. Results: Combining computational biology and machine learning identifies protein properties that hinder the HPA high‐throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high‐throughput experimentation. Availability and implementation: We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. Contact: ebrunk@ucsd.edu or johanr@biotech.kth.se Supplementary information: Supplementary data are available at Bioinformatics online.