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Michael Gribskov

Publications and source records attributed to Michael Gribskov.

At least 19 recordsLinked to original sources

Wiggle-predicting functionally flexible regions from primary sequence.

The Wiggle series are support vector machine-based predictors that identify regions of functional flexibility using only protein sequence information. Functionally flexible regions are defined as regions that can adopt different conformational states and are assumed to be necessary for bioactivity. Many advances have been made in understanding the relationship between protein sequence and structure. This work contributes to those efforts by making strides to understand the relationship between protein sequence and flexibility. A coarse-grained protein dynamic modeling approach was used to generate the dataset required for support vector machine training. We define our regions of interest based on the participation of residues in correlated large-scale fluctuations. Even with this structure-based approach to computationally define regions of functional flexibility, predictors successfully extract sequence-flexibility relationships that have been experimentally confirmed to be functionally important. Thus, a sequence-based tool to identify flexible regions important for protein function has been created. The ability to identify functional flexibility using a sequence based approach complements structure-based definitions and will be especially useful for the large majority of proteins with unknown structures. The methodology offers promise to identify structural genomics targets amenable to crystallization and the possibility to engineer more flexible or rigid regions within proteins to modify their bioactivity.

Algorithms↗

Protein kinase resource: an integrated environment for phosphorylation research.

The protein kinase superfamily is an important group of enzymes controlling cellular signaling cascades. The increasing amount of available experimental data provides a foundation for deeper understanding of details of signaling systems and the underlying cellular processes. Here, we describe the Protein Kinase Resource, an integrated online service that provides access to information relevant to cell signaling and enables kinase researchers to visualize and analyze the data directly in an online environment. The data set is synchronized with Uniprot and Protein Data Bank (PDB) databases and is regularly updated and verified. Additional annotation includes interactive display of domain composition, cross-references between orthologs and functional mapping to OMIM records. The Protein Kinase Resource provides an integrated view of the protein kinase superfamily by linking data with their visual representation. Thus, human kinases can be mapped onto the human kinome tree via an interactive display. Sequence and structure data can be easily displayed using applications developed for the PKR and integrated with the website and the underlying database. Advanced search mechanisms, such as multiparameter lookup, sequence pattern, and blast search, enable fast access to the desired information, while statistics tools provide the ability to analyze the relationships among the kinases under study. The integration of data presentation and visualization implemented in the Protein Kinase Resource can be adapted by other online providers of scientific data and should become an effective way to access available experimental information.

Amino Acid Sequence↗

Protein-protein interactions of tandem affinity purification-tagged protein kinases in rice.

Forty-one rice cDNAs encoding protein kinases were fused to the tandem affinity purification (TAP) tag and expressed in transgenic rice plants. The TAP-tagged kinases and interacting proteins were purified from the T1 progeny of the transgenic rice plants and identified by mass spectrometry. Ninety-five percent of the TAP-tagged kinases were recovered. Fifty-six percent of the TAP-tagged kinases were found to interact with other rice proteins. A number of these interactions were consistent with known protein complexes found in other species, validating the TAP-tag method in rice plants. Phosphorylation sites were identified on four of the kinases that interacted with either 14-3-3 proteins or cyclins.

14-3-3 Proteins↗

MAASE: an alternative splicing database designed for supporting splicing microarray applications.

Alternative splicing is a prominent feature of higher eukaryotes. Understanding of the function of mRNA isoforms and the regulation of alternative splicing is a major challenge in the post-genomic era. The development of mRNA isoform sensitive microarrays, which requires precise splice-junction sequence information, is a promising approach. Despite the availability of a large number of mRNAs and ESTs in various databases and the efforts made to align transcript sequences to genomic sequences, existing alternative splicing databases do not offer adequate information in an appropriate format to aid in splicing array design. Here we describe our effort in constructing the Manually Annotated Alternatively Spliced Events (MAASE) database system, which is specifically designed to support splicing microarray applications. MAASE comprises two components: (1) a manual/computational annotation tool for the efficient extraction of critical sequence and functional information for alternative splicing events and (2) a user-friendly database of annotated events that allows convenient export of information to aid in microarray design and data analysis. We provide a detailed introduction and a step-by-step user guide to the MAASE database system to facilitate future large-scale annotation efforts, integration with other alternative splicing databases, and splicing array fabrication.

Alternative Splicing↗

Characteristics and regulatory elements defining constitutive splicing and different modes of alternative splicing in human and mouse.

Alternative splicing is a major contributor to genomic complexity, disease, and development. Previous studies have captured some of the characteristics that distinguish alternative splicing from constitutive splicing. However, most published work only focuses on skipped exons and/or a single species. Here we take advantage of the highly curated data in the MAASE database (see related paper in this issue) to analyze features that characterize different modes of splicing. Our analysis confirms previous observations about alternative splicing, including weaker splicing signals at alternative splice sites, higher sequence conservation surrounding orthologous alternative exons, shorter exon length, and more frequent reading frame maintenance in skipped exons. In addition, our study reveals potentially novel regulatory principles underlying distinct modes of alternative splicing and a role of a specific class of repeat elements (transposons) in the origin/evolution of alternative exons. These features suggest diverse regulatory mechanisms and evolutionary paths for different modes of alternative splicing.

Alternative Splicing↗

Characterization of the yeast ionome: a genome-wide analysis of nutrient mineral and trace element homeostasis in Saccharomyces cerevisiae.

BACKGROUND: Nutrient minerals are essential yet potentially toxic, and homeostatic mechanisms are required to regulate their intracellular levels. We describe here a genome-wide screen for genes involved in the homeostasis of minerals in Saccharomyces cerevisiae. Using inductively coupled plasma-atomic emission spectroscopy (ICP-AES), we assayed 4,385 mutant strains for the accumulation of 13 elements (calcium, cobalt, copper, iron, potassium, magnesium, manganese, nickel, phosphorus, selenium, sodium, sulfur, and zinc). We refer to the resulting accumulation profile as the yeast 'ionome'. RESULTS: We identified 212 strains that showed altered ionome profiles when grown on a rich growth medium. Surprisingly few of these mutants (four strains) were affected for only one element. Rather, levels of multiple elements were altered in most mutants. It was also remarkable that only six genes previously shown to be involved in the uptake and utilization of minerals were identified here, indicating that homeostasis is robust under these replete conditions. Many mutants identified affected either mitochondrial or vacuolar function and these groups showed similar effects on the accumulation of many different elements. In addition, intriguing positive and negative correlations among different elements were observed. Finally, ionome profile data allowed us to correctly predict a function for a previously uncharacterized gene, YDR065W. We show that this gene is required for vacuolar acidification. CONCLUSION: Our results indicate the power of ionomics to identify new aspects of mineral homeostasis and how these data can be used to develop hypotheses regarding the functions of previously uncharacterized genes.

Elements↗

Examining the architecture of cellular computing through a comparative study with a computer.

The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software-hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's "hardware" equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the "bandwidth" of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed.

Cell Physiological Phenomena↗

Predicting N-terminal myristoylation sites in plant proteins.

BACKGROUND: N-terminal myristoylation plays a vital role in membrane targeting and signal transduction in plant responses to environmental stress. Although N-myristoyltransferase enzymatic function is conserved across plant, animal, and fungal kingdoms, exact substrate specificities vary, making it difficult to predict protein myristoylation accurately within specific taxonomic groups. RESULTS: A new method for predicting N-terminal myristoylation sites specifically in plants has been developed and statistically tested for sensitivity, specificity, and robustness. Compared to previously available methods, the new model is both more sensitive in detecting known positives, and more selective in avoiding false positives. Scores of myristoylated and non-myristoylated proteins are more widely separated than with other methods, greatly reducing ambiguity and the number of sequences giving intermediate, uninformative results. The prediction model is available at http://plantsp.sdsc.edu/myrist.html. CONCLUSION: Superior performance of the new model is due to the selection of a plant-specific training set, covering 266 unique sequence examples from 40 different species, the use of a probability-based hidden Markov model to obtain predictive scores, and a threshold cutoff value chosen to provide maximum positive-negative discrimination. The new model has been used to predict 589 plant proteins likely to contain N-terminal myristoylation signals, and to analyze the functional families in which these proteins occur.

Acyltransferases↗

2HAPI: a microarray data analysis system.

SUMMARY: 2HAPI (version 2 of High density Array Pattern Interpreter) is a web-based, publicly-available analytical tool designed to aid researchers in microarray data analysis. 2HAPI includes tools for searching, manipulating, visualizing, and clustering the large sets of data generated by microarray experiments. Other features include association of genes with NCBI information and linkage to external data resources. Unique to 2HAPI is the ability to retrieve upstream sequences of co-regulated genes for promoter analysis using MEME (Multiple Expectation-maximization for Motif Elicitation) AVAILABILITY: 2HAPI is freely available at http://array.sdsc.edu. Users can try 2HAPI anonymously with pre-loaded data or they can register as a 2HAPI user and upload their data.

Algorithms↗

The PlantsP and PlantsT Functional Genomics Databases.

PlantsP and PlantsT allow users to quickly gain a global understanding of plant phosphoproteins and plant membrane transporters, respectively, from evolutionary relationships to biochemical function as well as a deep understanding of the molecular biology of individual genes and their products. As one database with two functionally different web interfaces, PlantsP and PlantsT are curated plant-specific databases that combine sequence-derived information with experimental functional-genomics data. PlantsP focuses on proteins involved in the phosphorylation process (i.e., kinases and phosphatases), whereas PlantsT focuses on membrane transport proteins. Experimentally, PlantsP provides a resource for information on a collection of T-DNA insertion mutants (knockouts) in each kinase and phosphatase, primarily in Arabidopsis thaliana, and PlantsT uniquely combines experimental data regarding mineral composition (derived from inductively coupled plasma atomic emission spectroscopy) of mutant and wild-type strains. Both databases provide extensive information on motifs and domains, detailed information contributed by individual experts in their respective fields, and descriptive information drawn directly from the literature. The databases incorporate a unique user annotation and review feature aimed at acquiring expert annotation directly from the plant biology community. PlantsP is available at http://plantsp.sdsc.edu and PlantsT is available at http://plantst.sdsc.edu.

Arabidopsis↗

Rival penalized competitive learning (RPCL): a topology-determining algorithm for analyzing gene expression data.

DNA arrays have become the immediate choice in the analysis of large-scale expression measurements. Understanding the expression pattern of genes provide functional information on newly identified genes by computational approaches. Gene expression pattern is an indicator of the state of the cell, and abnormal cellular states can be inferred by comparing expression profiles. Since co-regulated genes, and genes involved in a particular pathway, tend to show similar expression patterns, clustering expression patterns has become the natural method of choice to differentiate groups. However, most methods based on cluster analysis suffer from the usual problems (i) dead units, and (ii) the problem of determining the correct number of clusters (k) needed to classify the data. Selecting the k has been an open problem of pattern recognition and statistics for decades. Since clustering reveals similar patterns present in the data, fixing this number strongly influences the quality of the result. While there is no theoretical solution to this problem, the number of clusters can be decided by a heuristic clustering algorithm called rival penalized competitive learning (RPCL). We present a novel implementation of RPCL that transforms the correct number of clusters problem to the tractable problem of clustering based on the degree of similarity. This is biologically significant since our implementation clusters functionally co-regulated genes and genes that present similar patterns of expression. This new approach reveals potential genes that are co-involved in a biological process. This implementation of the RPCL algorithm is useful in differentiating groups involved in concerted functional regulation and helps to progressively home into patterns, which are closely similar.

Algorithms↗

MODULEWRITER: a program for automatic generation of database interfaces.

MODULEWRITER is a PERL object relational mapping (ORM) tool that automatically generates database specific application programming interfaces (APIs) for SQL databases. The APIs consist of a package of modules providing access to each table row and column. Methods for retrieving, updating and saving entries are provided, as well as other generally useful methods (such as retrieval of the highest numbered entry in a table). MODULEWRITER provides for the inclusion of user-written code, which can be preserved across multiple runs of the MODULEWRITER program.

Computational Biology↗

Challenges in data management for functional genomics.

Biological databases face challenges in four main areas: (1). integration, interoperation and federation; (2). ontologies and definitions of semantics; (3). community annotation; and (4). integration of data analysis tools with databases. Each of these areas provides interesting targets for research and development.

Computational Biology↗

The Arabidopsis CDPK-SnRK superfamily of protein kinases.

The CDPK-SnRK superfamily consists of seven types of serine-threonine protein kinases: calcium-dependent protein kinase (CDPKs), CDPK-related kinases (CRKs), phosphoenolpyruvate carboxylase kinases (PPCKs), PEP carboxylase kinase-related kinases (PEPRKs), calmodulin-dependent protein kinases (CaMKs), calcium and calmodulin-dependent protein kinases (CCaMKs), and SnRKs. Within this superfamily, individual isoforms and subfamilies contain distinct regulatory domains, subcellular targeting information, and substrate specificities. Our analysis of the Arabidopsis genome identified 34 CDPKs, eight CRKs, two PPCKs, two PEPRKs, and 38 SnRKs. No definitive examples were found for a CCaMK similar to those previously identified in lily (Lilium longiflorum) and tobacco (Nicotiana tabacum) or for a CaMK similar to those in animals or yeast. CDPKs are present in plants and a specific subgroup of protists, but CRKs, PPCKs, PEPRKs, and two of the SnRK subgroups have been found only in plants. CDPKs and at least one SnRK have been implicated in decoding calcium signals in Arabidopsis. Analysis of intron placements supports the hypothesis that CDPKs, CRKs, PPCKs and PEPRKs have a common evolutionary origin; however there are no conserved intron positions between these kinases and the SnRK subgroup. CDPKs and SnRKs are found on all five Arabidopsis chromosomes. The presence of closely related kinases in regions of the genome known to have arisen by genome duplication indicates that these kinases probably arose by divergence from common ancestors. The PlantsP database provides a resource of continuously updated information on protein kinases from Arabidopsis and other plants.

Arabidopsis↗

Arabidopsis proteins containing similarity to the universal stress protein domain of bacteria.

We have collected a set of 44 Arabidopsis proteins with similarity to the USPA (universal stress protein A of Escherichia coli) domain of bacteria. The USPA domain is found either in small proteins, or it makes up the N-terminal portion of a larger protein, usually a protein kinase. Phylogenetic tree analysis based upon a multiple sequence alignment of the USPA domains shows that these domains of protein kinases 1.3.1 and 1.3.2 form distinct groups, as do the protein kinases 1.4.1. This indicates that their USPA domain structures have diverged appreciably and suggests that they may subserve distinct cellular functions. Two USPA fold classes have been proposed: one based on Methanococcus jannaschii MJ0577 (1MJH) that binds ATP, and the other based on the Haemophilus influenzae universal stress protein (1JMV), highly similar to E. coli UspA, which does not bind ATP. A set of common residues involved in ATP binding in 1MJH and conserved in similar bacterial sequences is also found in a distinct cluster of Arabidopsis sequences. Threading analysis, which examines aspects of secondary and tertiary structure, confirms this Arabidopsis sequence cluster as highly similar to 1MJH. This structural approach can distinguish between the characteristic fold differences of 1MJH-like and 1JMV-like bacterial proteins and was used to assign the complete set of candidate Arabidopsis proteins to one of these fold classes. It is clear that all the plant sequences have arisen from a 1MJH-like ancestor.

Adenosine Triphosphate↗

Systematic trans-genomic comparison of protein kinases between Arabidopsis and Saccharomyces cerevisiae.

The genome of the budding yeast (Saccharomyces cerevisiae) provides an important paradigm for transgenomic comparisons with other eukaryotic species. Here, we report a systematic comparison of the protein kinases of yeast (119 kinases) and a reference plant Arabidopsis (1,019 kinases). Using a whole-protein-based, hierarchical clustering approach, the complete set of protein kinases from both species were clustered. We validated our clustering by three observations: (a) clustering pattern of functional orthologs proven in genetic complementation experiments, (b) consistency with reported classifications of yeast kinases, and (c) consistency with the biochemical properties of those Arabidopsis kinases already experimentally characterized. The clustering pattern identified no overlap between yeast kinases and the receptor-like kinases (RLKs) of Arabidopsis. Ten more kinase families were found to be specific for one of the two species. Among them, the calcium-dependent protein kinase and phosphoenolpyruvate carboxylase kinase families are specific for plants, whereas the Ca(2+)/calmodulin-dependent protein kinase and provirus insertion in mouse-like kinase families were found only in yeast and animals. Three yeast kinase families, nitrogen permease reactivator/halotolerance-5), polyamine transport kinase, and negative regulator of sexual conjugation and meiosis, are absent in both plants and animals. The majority of yeast kinase families (21 of 26) display Arabidopsis counterparts, and all are mapped into Arabidopsis families of intracellular kinases that are not related to RLKs. Representatives from 11 of the common families (54 kinases from Arabidopsis and 17 from yeast) share an extremely high degree of similarity (blast E value < 10(-80)), suggesting the likelihood of orthologous functions. Selective expansion of yeast kinase families was observed in Arabidopsis. This is most evident for yeast genes CBK1, HRR25, and SNF1 and the kinase family S6K. Reduction of kinase families was also observed, as in the case of the NEK-like family. The distinguishing features between the two sets of kinases are the selective expansion of yeast families and the generation of a limited number of new kinase families for new functionality in Arabidopsis, most notably, the Arabidopsis RLKs that constitute important components of plant intercellular communication apparatus.

Arabidopsis↗

Genomic comparison of P-type ATPase ion pumps in Arabidopsis and rice.

Members of the P-type ATPase ion pump superfamily are found in all three branches of life. Forty-six P-type ATPase genes were identified in Arabidopsis, the largest number yet identified in any organism. The recent completion of two draft sequences of the rice (Oryza sativa) genome allows for comparison of the full complement of P-type ATPases in two different plant species. Here, we identify a similar number (43) in rice, despite the rice genome being more than three times the size of Arabidopsis. The similarly large families suggest that both dicots and monocots have evolved with a large preexisting repertoire of P-type ATPases. Both Arabidopsis and rice have representative members in all five major subfamilies of P-type ATPases: heavy-metal ATPases (P1B), Ca2+-ATPases (endoplasmic reticulum-type Ca2+-ATPase and autoinhibited Ca2+-ATPase, P2A and P2B), H+-ATPases (autoinhibited H+-ATPase, P3A), putative aminophospholipid ATPases (ALA, P4), and a branch with unknown specificity (P5). The close pairing of similar isoforms in rice and Arabidopsis suggests potential orthologous relationships for all 43 rice P-type ATPases. A phylogenetic comparison of protein sequences and intron positions indicates that the common angiosperm ancestor had at least 23 P-type ATPases. Although little is known about unique and common features of related pumps, clear differences between some members of the calcium pumps indicate that evolutionarily conserved clusters may distinguish pumps with either different subcellular locations or biochemical functions.

Adenosine Triphosphatases↗