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Published online on May 31, 2005, 10.1073/pnas.0503141102
PNAS | June 7, 2005 | vol. 102 | no. 23 | 8114-8119


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APPLIED BIOLOGICAL SCIENCES
Building a human kinase gene repository: Bioinformatics, molecular cloning, and functional validation

Jaehong Park *, Yanhui Hu *, T. V. S. Murthy *, Fredrik Vannberg *, Binghua Shen *, Andreas Rolfs *, Jessica E. Hutti {dagger}, Lewis C. Cantley {dagger}, Joshua LaBaer *, Ed Harlow *, and Leonardo Brizuela *, {ddagger}

*Harvard Institute of Proteomics, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 320 Charles Street, Cambridge, MA 02141; and {dagger}Department of Systems Biology, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02115

Contributed by Ed Harlow, April 21, 2005


   Abstract
Top
 Abstract
Materials and Methods
 Results and Discussion
 References
 

Kinases catalyze the phosphorylation of proteins, lipids, sugars, nucleosides, and other important cellular metabolites and play key regulatory roles in all aspects of eukaryotic cell physiology. Here, we describe the mining of public databases to collect the sequence information of all identified human kinase genes and the cloning of the corresponding ORFs. We identified 663 genes, 511 encoding protein kinases, and 152 encoding nonprotein kinases. We describe the successful cloning and sequence verification of 270 of these genes. Subcloning of this gene set in mammalian expression vectors and their use in high-throughput cell-based screens allowed the validation of the clones at the level of expression and the identification of previously uncharacterized modulators of the survivin promoter. Moreover, expressions of the kinase genes in bacteria, followed by autophosphorylation assays, identified 21 protein kinases that showed autocatalytic activity. The work described here will facilitate the functional assaying of this important gene family in phenotypic screens and their use in biochemical and structural studies.

kinome | autophosphorylation | cell-based screens | high-throughput cloning | survivin

The term kinase refers to a large number of mechanistically, structurally, and evolutionary distinct classes of enzymes. They catalyze the transfer of the {gamma}-phosphate from nucleoside triphosphates to a large number of molecules, including proteins, sugars, nucleosides, and lipids, and affect the activity and fate of those molecules and the cell.

Phosphorylation is a common posttranslational modification of proteins and plays a key role on protein structure and function and in all aspects of cell physiology. Protein kinases contain well conserved motifs and constitute the largest family of proteins in the human genome (1–3). Mutations of protein kinases are involved in carcinogenesis and several other pathological conditions (4–6). Phosphorylations of other biomolecules also play a critical role in the physiology and pathology of cells. Lipid kinases such as the phosphoinositide-3 kinase family members are key modulators of the cellular response to growth factors, hormones, and neurotransmitters and are involved in cancer (7). Nucleotide and nucleoside kinases regulate the intracellular levels of phosphate donors and nucleic acid precursors and are involved in the cellular response to damage and ischemia (8, 9). Sugar kinases regulate the rates of sugar metabolism, energy generation, and transcription activation and are involved in the process of cellular transformation and apoptosis (10–12).

The near completion of the Human Genome Project, the ongoing annotation projects, and the availability of sequence databases has allowed the genome-scale search and identification of members of different gene families by using sequence information as well as structural or functional annotations (2, 3, 13–15). However, a systematic cloning, sequence analysis, and functional validation effort for any of these gene sets has been challenging. Indeed, a major goal for experimental biology in this postgenomic era is the creation and use of state-of-the-art clone collections that exploit the newly obtained genome sequence and gene annotation. In the most useful collections, clones would represent fully sequenced-verified ORFs, make use of recombination-based cloning techniques, and be arrayed in high-density formats where all positions are fully annotated (16, 17). All these properties will allow high-throughput (HT) subcloning of the genes in these collections, as well as facilitate experimentation (in any in vivo and in vitro system) and data collection/analysis (both positive and negative data).

In this study, we describe the construction and proof of principle use of such a collection for the human kinase genes. We describe the mining of public databases to identify all annotated human kinases (including protein and nonprotein kinases) and the generation of a sequenced verified clone collection for this gene set by using the CREATOR (BD Biosciences Clontech) cloning platform. We furthermore validated the expression of these clones, successfully screened their activity en masse in three independent cell-based assays, and confirmed enzymatic activity for some of those proteins in Escherichia coli. As we demonstrate here, this human kinase clone set will facilitate the study of this important gene class both in in vivo and in vitro settings.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results and Discussion
 References
 
Database Mining. To assemble the kinase list, LocusLink information was downloaded from the National Center for Biotechnology Information web site. Structural Query Language (SQL) was designed to query genes with proper GO/EXTANNOT annotation, CDD annotation, or proper nomenclature. See Supporting Materials and Methods, which is published as supporting information on the PNAS web site.

Molecular Cloning. PCR amplification and cloning was carried out by using a highly automated and laboratory information management system (LIMS)-supported pipeline by using CREATOR recombination-based cloning technologies (BD Biosciences Clontech) (see Supporting Materials and Methods).

Generating Expression-Ready Libraries. ORFs were subcloned from the pDNR-Dual master vector into mammalian or bacterial expression vectors. For mammalian expression, pLP-CMVneo, pLP-EGFP-C1, and pLPS-3'EGFP vectors (BD Biosciences Clontech) were chosen for native, N-, and C-terminal EGFP-tagged version for each kinase, respectively. For bacterial expression, pGEX2tk (Amersham Pharmacia Biotech) was adapted for recombinational cloning (see Supporting Materials and Methods).

Mammalian Expression and Cell-Based Screens. Cotransfections of expression clones and reporter constructs were done by using FuGene6 (Roche Molecular Biochemicals) in a 96-well format. Reporter activity was measured by using luciferase reporter assay and Great EscAPe SEAP detection kits (BD Biosciences Clontech) (see Supporting Materials and Methods).

Bacterial Expression and Autophosphorylation. For more information on bacterial expression and autophosphorylation, see Supporting Materials and Methods.


   Results and Discussion
Top
 Abstract
 Materials and Methods
 Results and Discussion
References
 
Database Mining. Annotation and curation of the human genome as well as its mining based on sequence and motif conservations have been the subject of large and continuous efforts (2, 3, 18–20). To identify and collect sequence information of all of the identified and annotated human kinase genes, we performed term-based queries of public databases. We downloaded all of the LocusLink records available for human genes and used it to perform three independent SQL queries by using functional annotation, structural annotation, and gene nomenclature, respectively. The query results were then merged and hand-curated to eliminate kinase-related genes not captured by our filters (including inhibitors, regulators, and subunits). Because most genes were represented by multiple GenBank accession numbers, representing alternative spliced forms of the genes, we selected the longest coding DNA sequences from the RefSeq and UniGene databases as the reference sequence for our cloning efforts. Because of the fact that the information at LocusLink regarding gene sequences and annotations changes rapidly, we subsequently repeated the query by using 3 LocusLink updates.

Our most recent version of the human kinase gene set, based on the June 2004 analysis, consists of 663 genes. 511 of the genes (77%) encode for protein kinases and 152 genes (23%) for nonprotein kinases (Table 1). Genes encoding protein kinases were further classified in groups according to the extended classification of protein kinases (3). Nonprotein kinases comprise 23% of all annotated human kinases and are composed of heterogeneous groups of enzymes from the point of view of substrate specificity, gene sequence, and protein fold (ref. 21; Gene Ontology Consortium, www.godatabase.org). Data Set 1, which is published as supporting information on the PNAS web site, contains all relevant information for each of the 663 identified genes.


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  		Table 1. Classification of the human kinase genes identified and cloning success rate in this study

 
Contemporaneous to our initial analysis, Kostich et al. (2) and Manning et al. (3) described the identification of 510 and 518 human genes encoding for protein kinases by using sequence alignments and pair-wise comparisons. Comparison of the data from Manning et al. with our June 2004 search results for the protein kinase subset indicates that our current list is missing eight of the genes identified by Manning et al. Seven of these genes (SK573, SK581, SK592, SK650, SK681, SK707, and SK723) were associated with LocusLink records that had been retired in the June 2004 update. Lastly, SK200 did not have a corresponding full-length GenBank record at the time. The high degree of coverage obtained with these three studies suggests a general agreement on the composition of the human protein kinase gene family, at least based on available information.



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  		Fig. 1. Expression of C-terminal EGFP-tagged kinases in HEK293T cells. Normalized fluorescence of the C-terminal EGFP-tagged kinases in HEK293T cells, determined by plate reader, and fluorescence microphotographs of representative wells are shown.

Cloning into Recombinational Plasmid Vectors. We have developed a laboratory information management system-supported highly automated cloning and validation pipeline for genome-scale cloning by using recombination-based cloning technologies (16, 17). Once we had accumulated the sequence and annotation of the human kinase genes in our relational databases, we proceeded to the HT PCR amplification and cloning of these genes. For the work described here, we initially targeted the human kinase genes whose ORF size was <4 kb (594 genes). Two strategies were used to clone the targeted genes. Kinase genes present in the Mammalian Gene Collection (MGC, March 2003 release) were used as template for amplification (152 genes). The rest of the genes (442) were amplified by using a first-strand cDNA pool produced in the laboratory from normal human placenta and brain tissues. PCR products of the expected sizes were generated for 99% of the genes amplified from MGC templates and for 46% of those amplified from the first-strand cDNA pool. Amplification of the additional genes is taking advantage of information on mRNA abundance on the different tissues, on the use of alternative cDNA libraries, recent additions to the MGC repository, and on new amplification protocols.



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  		Fig. 2. Screen for kinases that regulate the survivin promoter. (A) Activity of C-terminal EGFP-tagged kinases on the survivin promoter in HEK 293T cells. (B) Scatter plot of z values obtained from interday experiments in A. (C) Characterization of survivin promoter induction by using top activating and inhibiting kinases identified from the screen.

One of the major quality-control points in our clone production pipeline is the full sequence analysis of the amplified ORFs. This analysis allows the detection and elimination of clones with high sequencing-confidence discrepancies with respect to the reference sequence due to the introduction of mutations during the PCR amplification. We eliminated any clone with nonsense or frame-shift mutations or with more than one missense mutation (after disregarding reported nucleotide polymorphisms). We successfully cloned and accepted 73% and 55% of the PCR products obtained with the MGC template and the first-strand cDNA library, respectively. Most of the rejected clones in the MGC group were represented by clones that were significantly shorter than the targeted reference sequence, although the clone sequence matched the MGC template. The main reasons for failures in the first-strand cDNA group were the presence of deleterious mutations in the clones, such as nonsense mutations, frame-shift mutations, multiple missense mutations, and mutations in linker region introduced by the PCR primers. The findings highlight the need and importance of full-length sequence validation of the clones produced in these types of operations.

The number of accepted genes from this first pass of cloning and sequence analysis was 270, corresponding to 186 protein kinases and 84 nonprotein kinases. The coverage of protein kinase groups varied from 24% to 58% for the TK and CK1 groups. For the nonprotein kinases, we successfully cloned 55% of the targeted genes. GenBank accession numbers AY335555 [GenBank] -AY335786 have been obtained for the new clones, and the clone collection is now available from multiple distributors including RZPD, MRC, and the Dana–Farber/Harvard Cancer Center "DNA Resource Core."



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  		Fig. 3. Screen and characterization of differentially tagged kinases on the TCF/lymphoid enhancing factor responsive element. (A) Effect of the differentially tagged kinases on the expression of the SEAP reporter protein in HEK 293T cells. Characterized kinases are marked by arrowheads. (B) Specificity of the TCF modulation by comparing the activity of the kinases on wild-type c-myc promoter (TOP) (Upper) and scrambled TOP (FOP) (Lower).

There are several qualities of this kinase gene collection that make it relevant. The clones in the collection are represented by fully sequence-verified human ORFs cloned in a recombination-based cloning system, arrayed in multiwell plates, fully indexed, and annotated. All these properties facilitate the parallel creation of fully representative expression libraries, the assaying of the clone collection, and analysis of the resulting data in a comprehensive and HT fashion, as shown below.

Expression of Kinases in Mammalian Cells. To validate the expression and activity of the kinase clones in cells, we transferred the kinase genes into three mammalian expression vectors (see Materials and Methods). We then made use of the C-terminal EGFP-tagged kinase library to analyze the level of expressions of 223 clones, based on the fluorescence level of the tagged kinases. HEK 293T cells were transfected in triplicate in 96-well format with the kinase constructs, and 94% of the clones were found to be positive for GFP fluorescence, compared with those of the empty C-terminal EGFP vector with a plate reader (Fig. 1). The same positive clones identified by the plate reader also scored positive upon microscopic analysis (see Fig. 1 for representative samples). There were reproducible differences of GFP fluorescence signal (up to 86-fold) among different clones, with no significant correlation between complete DNA sequences size and GFP fluorescence. Furthermore, microscopic analysis of the transfected cells allowed us, in most cases, to identify the cellular distribution of the recombinant kinases (data not shown). For example, the recombinant forms of Src family members (CSK, LYN, and YES1) and Tec family members (ITK, BTK, and BMX) showed cytoplasmic or plasma membrane localization, as expected (22, 23). Also, recombinant PIP5K1A and B, ACVR1, and GPRK5 were mainly localized in the cell membrane (24, 25) (Fig. 5, which is published as supporting information on the PNAS web site). Recombinant PLK, CHEK1, and CHEK2 were localized in the nucleus, consistent with the temporal association of these proteins with this cellular compartment (26, 27). GFP fluorescence is only an indirect measurement of the expression of the recombinant kinases. However, analysis of the relative levels of fluorescence and immunoblot signal (by using anti-GFP antibodies), for a subset of genes identified in the screen described below, indicated a good correlation between fluorescence signal and protein levels (Fig. 6, which is published as supporting information on the PNAS web site).

Screens of Clones in Cell-Based Assays. After having validated the expression of the library in mammalian cells, the human kinase expression clone sets were screened in two independent HT cell-based reporter gene assays. In the first screen, we looked for kinase genes with capacity to modulate the survivin promoter element. Survivin (BIRC5) is involved in the inhibition of apoptosis, and its expression is up-regulated in most cancer cells (28). Although survivin levels are controlled at the transcriptional level in a cell cycle-restricted manner (29), mounting evidence indicates that several oncogenic pathways might also regulate its transcription (30). Each of the 223 C-terminal EGFP-tagged kinase clones analyzed before were then cotransfected with a luciferase reporter construct containing survivin promoter region (-1430 to -1), pLuc-1430c (29) in HEK 293T cells in triplicate. Normalized luciferase activity data from two independent experiments are shown in Fig. 2A. A scatter plot of the z values from the two independent assays indicates a good level of correlation and a high degree of reproducibility of the kinase-induced effect (r = 0.92, Fig. 2B).

We then selected the eight genes that showed the highest positive modulatory activity (ADK, ATR, MAPK1, MAP2K5, PFKM, PRKR, STK10, and STK22C), as well as four genes showing inhibitory activity (BLK, HRI, MAP3K7, and PIM1) for further analysis. All eight activating kinases significantly up-regulated the survivin promoter activity in the confirmatory experiments, showing 3- to 32-fold induction (Fig. 2C). Likewise, the four inhibitory kinases reproducibly down-regulated the basal survivin promoter activity. The magnitude of inhibition induced by these kinases was uniform and limited to 0.6-fold inhibition (Fig. 2C). Importantly, consistent with the antiapoptotic role of survivin, expressions of all of the activator kinases, except PFKM, were found to protect cells from TNF-related apoptosis-inducing ligand (TRAIL)-induced apoptosis (data not shown). Consistent with our results, both MAP2K5 and MAPK1 have been found to inhibit TRAIL-induced apoptosis (31, 32) and MAP3K7 (TAK1) has been reported to induce apoptosis through JNK (33) and p38 activation (34). Our initial screen and follow-up experiment has also allowed the identification of genes, including the unexpected results with the nucleoside kinases ADK, that clearly regulate the survivin promoter and protect cells from TRAIL-induced apoptosis and that have not been reported before.

In a second independent cell-based screen, we made use of three different forms of the kinases (native, N- and C-terminal EGFP-tagged) and tested them for their ability to up-regulate the T cell factor (TCF)/lymphoid enhancing factor-binding region of the c-myc promoter (see Materials and Methods), a well characterized responsive element involved in the WNT signaling pathway (35). As shown in Fig. 3A, significant up-regulation of the normalized c-myc promoter–secreted alkaline phosphatase reporter activity was achieved by 5 of the 699 constructs tested (233 kinases in three different expression vectors). Only one of the genes identified by the five strongest hits was represented by more than one construct (CK1-{delta}), the other two genes uncovered in the screen (CK1-{epsilon} and PRKR) were identified by only one of the three alleles generated for each one of those genes. These results clearly highlight the importance of generating and testing genes with alternative tags, thus generating different alleles for each gene, to enhance the chances of identifying the involvement of a gene in a given pathway. To further validate whether the activity of these constructs was specific to the TCF/lymphoid enhancing factor responsive element, we compared their activity and that of some negative controls against the wild type and a point-mutated scrambled TCF responsive element, FOP (35). All but the C-terminal EGFP-tagged PRKR showed specific activation of the TCF responsive element (Fig. 3B). Our findings are consistent with reports that the overexpression of CK1-{delta} or -{epsilon} are sufficient to activate the WNT signaling, but CK1-{alpha}, CK1–{gamma}, and CK2-{alpha} could not induce any significant activation of {beta}-catenin reporter (36–38).



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  		Fig. 4. Autoradiograph and Western blot of selected active kinases produced in E. coli. (A) Autoradiograph of bacterial lysates separated by SDS/PAGE after kinase assay. The active bands corresponding to the expected protein size were marked by arrowheads. (B) Western blot analysis of the bacterial lysates corresponding to those used in A by using anti-GST antibodies. Expected size bands were marked by arrowheads. Molecular size markers (Mr) were indicated on the left.

Bacterial Expression and Purification for Autophosphorylation Assay. Bacterial expression represents a simple and cost-effective system for expression and purification of proteins. However, this system is often not suitable for expression of properly folded, posttranslationally modified, and active mammalian enzymes. Nevertheless, even in the case of protein kinases, it is possible to produce properly folded as well as active enzymes in bacteria (39–41). Cumulative data from testing individual mammalian kinases in our laboratory indicates that 5–10% of those genes expressed active enzymes in bacteria. We thus took advantage of the large number of kinases present in our set, and our ability to process them in parallel, to identify previously uncharacterized kinase genes that produce active enzymes in E. coli in a quick and efficient manner. Autophosphorylation of the recombinant protein in the total bacterial extract was taken as a measure of kinase activity for any given protein. Twenty-one of 233 recombinant kinases tested (9%) showed strong kinase activity in both the original screen (data not shown) and in the retest. These corresponded to BCKDK, BMX, CKLiK, CLK4, DAPK3, FRK, HCK, HRI, LYN, OSR1, PDK3, PHKG2, PKMYT1, PLK, SNK, STK3, STK16, STK17A, STK38L, VRK1, and VRK2. Fig. 4 shows the autophosphorylation and anti-GST immunoblot results for 11 of the identified kinases. Among the 21 enzymes identified in this analysis were representatives of all of the protein kinase groups (3), indicating that, in principle, it is possible to obtain active kinases in bacteria for proteins in any of 10 protein kinase groups. Some of the enzymes identified here have also been described in ref. 41. Our results will aid in the establishment of enzymatic assays for determination of the substrate specificities for the newly identified active kinases (42) as well as helping in the definition of the specificity of kinase inhibitors. Finally, we have also identified active enzymes (such as PKMYT1) that show sufficient expression levels for structural studies.

Summary. Complete exploitation of the human genome sequence requires the building of state-of-the-art and comprehensive ORF repositories at both the gene-family and genome scales. These types of repositories will serve not only as validation tools but also as unique HT discovery tools in the form of clones (for cell-based screens) and proteins (for biochemical and immunological assays). In this study, we have concentrated on the definition of the human kinase gene set and on the initial cloning and characterization of this important clone collection. Expression of the obtained kinase set in both in vivo and in vitro assays, in a HT manner, has allowed the validation of the kinase constructs and has demonstrated the value of this gene set for cell-based and biochemical screens. Some of the hits identified in the two cell-based validation screens correlate with the published literature. Furthermore, some of the hits in the screen for regulators of the survivin promoter suggested new regulatory elements that also affect the apoptotic response of cells. Some of these genes encode sugar and nucleoside kinases and require further analysis.

Use of the clones in biochemical assays also allowed the identification of 21 kinase genes that possess autocatalytic activity when expressed in bacteria. These kinases could prove important for use in in vitro studies to define substrate specificities (by using peptide libraries) and to profile kinase inhibitors.

In addition to the wild-type kinase described here, we recognized the value of generating both a short-hairpin RNA (shRNA) library and a "dominant negative" library for the human kinase gene set. Consistently, the information generated here contributed to the construction of the shRNA library described by Paddison et al. (43) such that 80% of the human kinase genes identified here have been covered by multiple shRNA constructs in that collection. Another positive step could be to generate dominant negative (kinase-dead) alleles for those protein kinases whose wild-type alleles have been captured so far. Coordinated use of the wild-type kinase, the dominant negative, and the shRNA collections will facilitate the identification and understanding of the role of the human kinase genes in any phenotypic assay. Furthermore, construction of wild-type and alternative tagged forms of the genes results in the creation of alleles with differential activities further enhancing the chances of identifying hits in a given cell-based assay by using gene overexpression screens.

The kinase clones described here add to the growing number of recently generated human ORF and arrayed cDNA clone collections, which allow indexed experimentation at the gene family or subgenome scales (38, 44, 45). Future challenges on this area are the completion of relevant gene-family ORF collections (13–15) (to include all genes in a given gene family and all alternative spliced forms of every gene) and the production of clone isolates with full-length sequence verification (such as the clones in this study) for all predicted human ORFs.


   Acknowledgements
 
We thank Drs. Bert Vogelstein for pTOP-luc and pFOP-luc (The Johns Hopkins University, Baltimore) Dario Altieri for pLuc1430c (University of Massachusetts Medical School, Worcester, MA), Xi He for helpful comments, and Greg Hannon for generation of shRNA. This work was partially funded by the National Cancer Institute–Frederick Research Development Center Subcontract 22XS136A.


   Footnotes
 
Author contributions: J.P., Y.H., and L.B. designed research; J.P., Y.H., T.V.S.M., and J.E.H. performed research; J.P., B.S., A.R., L.C.C., J.L., E.H., and L.B. contributed new reagents/analytic tools; J.P., Y.H., T.V.S.M., F.V., and J.E.H. analyzed data; and J.P. and L.B. wrote the paper.

Abbreviations: HT, high throughput; MGC, Mammalian Gene Collection; shRNA, short-hairpin RNA; TCF, T cell factor.

Data Deposition: The gene constructs reported in this paper have been deposited in the GenBank database (accession nos. AY335555–AY335786).

{ddagger} To whom correspondence should be addressed. E-mail: lbrizuela{at}hms.harvard.edu.

© 2005 by The National Academy of Sciences of the USA


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 Abstract
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 Results and Discussion
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