Tissue-Specific Protein Expression in Human Cells, Tissues and Organs

An important part of understanding human biology is the study of tissue-speci fi c expression both at the gene and protein level. In this study, the analysis of tissue speci fi c protein expression was performed based on tissue micro array data available on the public Human Protein Atlas database (www.proteinatlas.org). An analysis of human proteins, corresponding to approximately one third of the protein-encoding genes, was carried out in 65 human tissues and cell types. The spatial distribution and relative abundance of 6,678 human proteins, were analyzed in different cell populations from various organs and tissues in the human body using unsupervised methods, such as hierarchical clustering and principal component analysis, as well as with supervised methods (Breiman, 2001). Well-known markers, such as neuromodulin for the central nervous system, keratin 20 for gastrointestinal tract and CD45 for hematopoietic cells, were identi fi ed as tissue-speci fi c. Proteins expressed in a tissue-speci fi c manner were identi fi ed for cells in all of the investigated tissues, including the central nervous system, hematopoietic system, squamous epithelium, mesenchymal cells and cells from the gastrointestinal tract. Several proteins not yet associated with tissue-speci fi city were identi fi ed, providing starting points for further studies to explore tissue-speci fi c functions. This includes proteins with no known function, such as ZNF509 expressed in CNS and C1orf201 expressed in the gastro-intestinal tract. In general, the majority of the gene products are expressed in a ubiquitous manner and few proteins are detected exclusively in cells from a particular tissue class, as exempli fi ed by less than 1% of the analyzed proteins found only in the brain.

[1]  M. Uhlén Mapping the human proteome using antibodies. , 2007, Molecular & cellular proteomics : MCP.

[2]  Erez Y. Levanon,et al.  Widespread occurrence of antisense transcription in the human genome , 2003, Nature Biotechnology.

[3]  R M Levenson,et al.  Quantification of immunohistochemistry—issues concerning methods, utility and semiquantitative assessment II , 2006, Histopathology.

[4]  E. Check Genome project turns up evolutionary surprises , 2007, Nature.

[5]  J. H. Ward Hierarchical Grouping to Optimize an Objective Function , 1963 .

[6]  E. Lundberg,et al.  A global view of protein expression in human cells, tissues, and organs , 2009, Molecular systems biology.

[7]  John Quackenbush,et al.  Multiple-laboratory comparison of microarray platforms , 2005, Nature Methods.

[8]  Student,et al.  THE PROBABLE ERROR OF A MEAN , 1908 .

[9]  C. Spearman The proof and measurement of association between two things. , 2015, International journal of epidemiology.

[10]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[11]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[12]  S. Batalov,et al.  Antisense Transcription in the Mammalian Transcriptome , 2005, Science.

[13]  Dieter Stoll,et al.  Protein microarrays: Promising tools for proteomic research , 2003, Proteomics.

[14]  James A. Cuff,et al.  Distinguishing protein-coding and noncoding genes in the human genome , 2007, Proceedings of the National Academy of Sciences.

[15]  David E. Gloriam,et al.  ProteomeBinders: planning a European resource of affinity reagents for analysis of the human proteome , 2007, Nature Methods.

[16]  N. Anderson,et al.  The Human Plasma Proteome , 2002, Molecular & Cellular Proteomics.

[17]  H. Zola,et al.  Leukocyte and Stromal Cell Molecules: The CD Markers , 2007 .

[18]  J. V. Moran,et al.  Initial sequencing and analysis of the human genome. , 2001, Nature.

[19]  Steve Horvath,et al.  Tumor classification by tissue microarray profiling: random forest clustering applied to renal cell carcinoma , 2005, Modern Pathology.

[20]  D. Rimm What brown cannot do for you , 2006, Nature Biotechnology.

[21]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[22]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[23]  Timothy B. Stockwell,et al.  The Sequence of the Human Genome , 2001, Science.

[24]  J. Kononen,et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens , 1998, Nature Medicine.

[25]  E. Lundberg,et al.  A Genecentric Human Protein Atlas for Expression Profiles Based on Antibodies* , 2008, Molecular & Cellular Proteomics.

[26]  I. Jolliffe Principal Component Analysis , 2002 .