Myoinformatics report: myosin regulatory light chain paralogs in the human genome

On-line bioinformatics tools were used to identify and characterize all paralogs (intragenomic homologs) of muscle myosin regulatory light chains in the human genome. The initial search yielded 22 possible paralogs, but careful examination of supporting data eliminated most of these. Five paralogs were clearly identified with the tissue types (skeletal and cardiac muscles, smooth muscle, non-muscle cytoplasm) in which they are expressed. Sequence comparisons and phylogenetic analysis showed early divergence of a common ancestor of smooth muscle and non-muscle paralogs from a common ancestor of skeletal and cardiac muscle paralogs. An unusual sixth human paralog was very similar to the regulatory light chain of “superfast” myosin, which to date has been found only in cat. Finally, a unique and questionable “precursor lymphocyte” paralog was tentatively identified. Three-dimensional structural models of all seven human paralogs were constructed using the known structure of chicken fast skeletal muscle regulatory light chain as a template.     

Linking information systems in the health service

Various information systems have existed in the hygiene service for a number of years and the outputs of these systems are partially used. By interconnection (comprehensive evaluation) of these systems objective information on the relationship of various factors could be obtained. For the epidemic season 1985/86 (September-April) the outputs of information systems "Reports on acute respiratory diseases" (ARD), "Contamination of the atmosphere in the CSR", "Meteofond" were analyzed in a comprehensive way. The incidence of acute respiratory diseases, the sulphur dioxide concentration, the concentration of dust and nitrogen oxides in the air, the temperature and the moisture of the atmosphere were evaluated. The incidence of acute respiratory diseases, which markedly depends on the season, is recorded most accurately in the age group of 0-5 years. The most marked excesses of the incidence are associated as a rule with the circulation of the influenza virus in the population. The sulphur dioxide concentration is also dependent on the season, similarly as the concentration of dust and the temperature and moisture of the air assessed at 2 p.m. There are some identical features between the level of the incidence of acute respiratory diseases, the atmospheric concentration of the mentioned substances and values of the mentioned climatic factors in the course of the epidemic season of acute respiratory diseases. Causal relationships between the incidence of acute respiratory diseases and all mentioned factors must be, however, evaluated with great care.     

Multiple clonally-restricted immunoglobulins in human sera: disease associations

Diseases associated with multiple clonally-restricted serum immunoglobulin (Ig) abnormalities present at levels which, in most cases, preclude detection by conventional immunoelectrophoresis, were studied using methods for detection and characterization of homogeneous Ig that are approximately equal to 40 times more sensitive than either cellulose acetate zone electrophoresis or immunoelectrophoresis. Patients with these Ig abnormalities had a high incidence of infectious disease (29% of total cases), malignancy (19%), connective tissue disease (14%) and liver disease (10%). The concentration of individual clonal products was found to wax and wane, but it could not be determined whether these clonally-restricted Ig species represent, wholly or in part, the products of dominant antibody-producing plasma cell clones involved in the patients' response to their disease. We conclude that multiple homogeneous serum Ig abnormalities occur in clinical situations where heightened antigenic stimulation and/or immune reactivity are thought to occur (e.g., infections, malignancies and autoimmunity). Laboratory evaluation of these Ig abnormalities could be useful for diagnostic and/or therapeutic monitoring purposes in situations where the specificity of the clonally-restricted Ig species can be established.     

The actin-myosin regulatory MRCK kinases: regulation,biological functions and associations with human cancer

The contractile actin-myosin cytoskeleton provides much of the force required for numerous cellular activities such as motility, adhesion, cytokinesis and changes in morphology. Key elements that respond to various signal pathways are the myosin II regulatory light chains (MLC), which participate in actin-myosin contraction by modulating the ATPase activity and consequent contractile force generation mediated by myosin heavy chain heads. Considerable effort has focussed on the role of MLC kinases, and yet the contributions of the myotonic dystrophy-related Cdc42-binding kinases (MRCK) proteins in MLC phosphorylation and cytoskeleton regulation have not been well characterized. In contrast to the closely related ROCK1 and ROCK2 kinases that are regulated by the RhoA and RhoC GTPases, there is relatively little information about the CDC42-regulated MRCKα, MRCKβ and MRCKγ members of the AGC (PKA, PKG and PKC) kinase family. As well as differences in upstream activation pathways, MRCK and ROCK kinases apparently differ in the way that they spatially regulate MLC phosphorylation, which ultimately affects their influence on the organization and dynamics of the actin-myosin cytoskeleton. In this review, we will summarize the MRCK protein structures, expression patterns, small molecule inhibitors, biological functions and associations with human diseases such as cancer.     

Sequence variation and disease in the wake of the draft human genome.

The sequencing phase of the human genome project will soon be over. In its wake, repertoires of sequence polymorphisms among the human population are being sampled and a battery of functional genomics projects, from gene and protein expression studies to whole proteome interaction experiments, are generating vast quantities of data. Now that the data, or the means to generate data, are available it is the application of this information in enhancing our understanding of biology that represents the next formidable challenge. Two prominent issues should be considered. First, existing data must be analysed using the best methods available. The prediction of enzymatic activity for bestrophin, whose gene is mutated in Best macular dystrophy, is described in this review. This is an example of the experimentally testable hypotheses that can result from such detailed and exhaustive analyses. Secondly, the torrents of data from high-throughput studies will need to be made more accessible to all using web-based resources that integrate and digest complementary data types. The internet sites that showcase the human genome sequence are blazing a new trail. Ultimately, the success of genome sequencing and functional genomics will be measured not by the quantity and accuracy of raw data generated, but how rapidly they can be harnessed to span the divide between genotype and phenotype.     

Exploring the human genome with functional maps

Human genomic data of many types are readily available, but the complexity and scale of human molecular biology make it difficult to integrate this body of data, understand it from a systems level, and apply it to the study of specific pathways or genetic disorders. An investigator could best explore a particular protein, pathway, or disease if given a functional map summarizing the data and interactions most relevant to his or her area of interest. Using a regularized Bayesian integration system, we provide maps of functional activity and interaction networks in over 200 areas of human cellular biology, each including information from ∼30,000 genome-scale experiments pertaining to ∼25,000 human genes. Key to these analyses is the ability to efficiently summarize this large data collection from a variety of biologically informative perspectives: prediction of protein function and functional modules, cross-talk among biological processes, and association of novel genes and pathways with known genetic disorders. In addition to providing maps of each of these areas, we also identify biological processes active in each data set. Experimental investigation of five specific genes, AP3B1, ATP6AP1, BLOC1S1, LAMP2, and RAB11A, has confirmed novel roles for these proteins in the proper initiation of macroautophagy in amino acid-starved human fibroblasts. Our functional maps can be explored using HEFalMp (Human Experimental/Functional Mapper), a web interface allowing interactive visualization and investigation of this large body of information.The completion of the Human Genome Project and the subsequent flood of genomic data and analyses have provided a wealth of information regarding the entire catalog of human genes. Comprehensive assays of gene expression, protein binding, genetic interactions, and regulatory relationships all provide snapshots of molecular activity in specific cell types and environments, but turning these biomolecular parts lists into an understanding of pathways, processes, and systems biology has proven to be a challenging task. This abundance of data can sometimes obscure biological truths: The size of the human genome, the complexity of human tissue types and regulatory mechanisms, and the sheer amount of available data all contribute to the analytical complexity of understanding human functional genomics.In order to take advantage of large collections of genomic data, they must be integrated, summarized, and presented in a biologically informative manner. We provide a means of mining tens of thousands of whole-genome experiments by way of functional maps. Each map represents a body of data, probabilistically weighted and integrated, focused on a particular biological question. These questions can include, for example, the function of a gene, the relationship between two pathways, or the processes disrupted in a genetic disorder. Functional integrations investigating individual genes'' relationships have been successful with smaller data collections in less complex organisms (Lee et al. 2004; Date and Stoeckert Jr. 2006; Myers and Troyanskaya 2007), although (as discussed below) it is particularly challenging to scale these techniques up to the size and complexity of the human genome. Each functional map, based on an underlying predicted interaction network, summarizes an entire collection of genomic experimental results in a biologically meaningful way.While functional maps can readily predict functions for uncharacterized genes (Murali et al. 2006), it is important to take advantage of the scale of available data to understand entire pathways and processes. Cross-talk and coregulation among pathways, processes, and genetic disorders can be mapped by analyzing the structure of underlying functional relationship networks. This includes the association of disease genes with (potentially causative) pathways; for example, many known breast cancer genes are involved in aspects of the cell cycle and DNA repair, and novel associations of this type can be mined from high-throughput data. Similarly, associations between distinct but interacting biological processes (e.g., mitosis and DNA replication) can be quantified by examining functional relationships between groups of genes, allowing the identification of proteins key to interprocess regulation.The functional maps we provide for the human genome include information on protein function, associations between diseases, genes, and pathways, and cross-talk between biological processes. These are all based on probabilistic data integration using regularized naïve Bayesian classifiers. Naïve Bayesian systems have been used successfully to analyze protein–protein interaction (PPI) data (Rhodes et al. 2005; von Mering et al. 2007), whereas our focus is on functional relationships and the biological roles of gene products. Prior work performing functional integration in simpler organisms with smaller data collections (Date and Stoeckert Jr. 2006; Myers and Troyanskaya 2007) has been similarly successful; see Supplemental Text 1 for a complete discussion. Such integrations have not previously been scaled biologically (i.e., to complex metazoans) or computationally (over very large genomic data collections) to provide a functional view of the human genome driven purely by experimental results. In addition to challenges of computational efficiency in the presence of hundreds of genome-scale data sets, naïve classifiers assume that all input data sets are independent; this becomes increasingly untrue and problematic as more data sets are analyzed, resulting in a paradox of decreasing performance with increasing training data. To address this, we use Bayesian regularization (Steck and Jaakkola 2002), a process by which an observed distribution of data can be combined with a prior belief in a principled manner. Intuitively, this results in groups of data sets containing similar information making a more modest contribution to the integration process, up-weights unique data sets, and prevents overconfident predictions. Our regularization of the naïve classifier parameters using a score based on mutual information up- and down-weighted appropriate subsets of data, maintaining both efficiency and accuracy.We applied our functional maps to a specific biological question in the area of autophagy, the process by which a cell can recycle its own biomass under conditions of starvation or stress (Klionsky 2007). Among many proteins predicted to participate in this biological process by our maps, we chose to investigate AP3B1, ATP6AP1, BLOC1S1, LAMP2, and RAB11A in the laboratory. We demonstrated through multiple lines of experimental evidence that these proteins are indeed involved in macroautophagy in amino acid-starved human fibroblasts, a specific type of autophagy in which bulk cytoplasm is lysosomally degraded. The results of our integration are available through a web-based interface, HEFalMp (Human Experimental/Functional Mapper), at http://function.princeton.edu/hefalmp. This tool allows a user to interactively explore functional maps integrating evidence from thousands of genomic experiments, focusing as desired on specific genes, processes, or diseases of interest.     

An update of the HLA genomic region, locus information and disease associations: 2004

The human major histocompatibility (MHC) genomic region at chromosomal position 6p21 encodes the six classical transplantation HLA genes and many other genes that have important roles in the regulation of the immune system as well as in some fundamental cellular processes. This small segment of the human genome has been associated with more than 100 diseases, including common diseases--such as diabetes, rheumatoid arthritis, psoriasis, asthma and various autoimmune disorders. The MHC 3.6 Mb genomic sequence was first reported in 1999 with the annotation of 224 gene loci. The locus and allelic information of the MHC continue to be updated by identifying newly mapped expressed genes and pseudogenes based on comparative genomics, SNP analysis and cDNA projects. Since 1999, new innovations in bioinformatics and gene-specific functional databases and studies on the MHC genes have resulted in numerous changes to gene names and better ways to update and link the MHC gene symbols, names and sequences together with function, variation and disease associations. In this study, we present a brief overview of the MHC genomic structure and the recent information that we have gathered on the MHC gene loci via LocusLink at the National Centre for Biological Information (http://www.ncbi.nih.gov/.) and the MHC genes' association with various diseases taken from publications and records in public databases, such as the Online Mendelian Inheritance in Man and the Genetic Association Database.     

DNA inoculation as a novel vaccination method against human retroviruses with rheumatic disease associations

There are a number of rheumatologic manifestations of human retroviral infections associated with human immunodeficiency virus type I (HIV-I) and the human T-cell leukemia virus type I (HTLV-I) including arthritis, Sjøgren's syndrome-like symptoms as well as other varied autoimmune phenomena. Infection with HTLV-1 may be directly involved in the etiology and/or pathogenesis of an arthritic condition similar to rheumatoid arthritis. We have been characterizing a new vaccination strategy against human retroviral infections, designated DNA inoculation. This procedure involves the intramuscular injection of DNA plasmids which express specific human retroviral antigens. This technique results in the development of humoral and cellular immune responses against these proteins. Specifically, this method has been successfully used to develop immune responses against HIV-I and HTLV-I. The availability of rat and rabbit infection models for HTLV-I, coupled with the successful development of immune responses in these animals after DNA inoculation with an HTLV-I envelope expressing plasmid, will allow the efficacy of this vaccination technique to be evaluated with protection against in vivo viral challenge as an endpoint.