A computerized database-scan to identify c-MYC targets

Spinocerebellar ataxia type 7 (SCA7) is a neurodegenerative disease caused by the expansion of a polyglutamine tract in the protein ataxin-7, a protein of unknown function. In order to analyze the expression pattern of wild type ataxin-7 in detail, the murine SCA7 gene homolog was cloned and the expression pattern in mice analyzed. The SCA7 mouse and human gene exhibit a high degree of identity at both DNA (88.2%) and protein (88.7%) level. The CAG repeat region, known to be polymorphic in man, is conserved in mouse but contained only five repeats in all mouse strains analyzed. The arrestin homology domain and the nuclear localization signal found in human ataxin-7 is also conserved in the murine homolog. Expression of ataxin-7 was detected during mouse embryonic development and in all adult mouse tissues examined by northern and western blots. In brain, immunohistological staining revealed an ataxin-7 expression pattern similar to that in human, with ataxin-7 expression in cerebellum, several brainstem nuclei, cerebral cortex and hippocampus. Our data show high conservation of ataxin-7 both structurally and at the level of expression, suggesting a conserved role for the protein in mice and humans.     

A global approach to identify novel broad-spectrum antibacterial targets among proteins of unknown function

Attempted allelic replacement of 144 Streptococcus pneumoniae open reading frames of previously uncharacterized function led to the identification of 36 genes essential for growth under laboratory conditions. Of these, 14 genes (obg, spoIIIJ2, trmU, yacA, yacM, ydiC, ydiE, yjbN, yneS, yphC, ysxC, ytaG, yloI and yxeH4) were also essential in Staphylococcus aureus and Haemophilus influenzae or Escherichia coli, 2 genes (yrrK and ydiB) were only essential in H. influenzae as well as S. pneumoniae and 8 genes were necessary for growth of S.pneumoniae and S. aureus and did not have a homolog in H. influenzae(murD2, ykqC, ylqF, yqeH, ytgP, yybQ) or were not essential in that organism (yqeL, yhcT). The proteins encoded by these genes could represent good targets for novel antibiotics covering different therapeutic profiles. The putative functions of some of these essential proteins, inferred by bioinformatic analysis, are presented. Four mutants, with deletions of loci not essential for in vitro growth, were found to be severely attenuated in a murine respiratory tract infection model, suggesting that not all targets for antibacterial therapeutics are revealed by simple in vitro essentiality testing. The results of our experiments together with those collated from previously reported studies including Bacillus subtilis, E. coli and Mycoplasma sp. demonstrate that gene conservation amongst bacteria does not necessarily indicate that essentiality in one organism can be extrapolated to others. Moreover, this study demonstrates that different experimental procedures can produce apparently contradictory results.     

A novel data mining method to identify assay-specific signatures in functional genomic studies

Background:  

The highly dimensional data produced by functional genomic (FG) studies makes it difficult to visualize relationships between gene products and experimental conditions (i.e., assays). Although dimensionality reduction methods such as principal component analysis (PCA) have been very useful, their application to identify assay-specific signatures has been limited by the lack of appropriate methodologies. This article proposes a new and powerful PCA-based method for the identification of assay-specific gene signatures in FG studies.     

Towards an efficient computational mining approach to identify EST-SSR markers

Microsatellites are the markers of choice due to their high abundance reproducibility, degree of polymorphism and co-dominant nature. These are mainly used for studying the genetic variability in different species and Marker assisted selection. Expressed Sequence Tags (ESTs) serve as the main resource for Simple Sequence Repeats (SSRs). The computational approach for detecting SSRs and developing SSR markers from EST-SSRs is preferred over the conventional methods as it reduces time and cost to a great extent. The available EST sequence databases, various web interfaces and standalone tools provide the platform for an easy analysis of the EST sequences leading to the development of potential EST-SSR Markers. This paper is an overview of in silico approach to develop SSR Markers from the EST sequence using some of the most efficient tools that are available freely for academic purpose.     

A novel in silico approach to identify potential therapeutic targets in human bacterial pathogens

In recent years, genome-sequencing projects of pathogens and humans have revolutionized microbial drug target identification. Of the several known genomic strategies, subtractive genomics has been successfully utilized for identifying microbial drug targets. The present work demonstrates a novel genomics approach in which codon adaptation index (CAI), a measure used to predict the translational efficiency of a gene based on synonymous codon usage, is coupled with subtractive genomics approach for mining potential drug targets. The strategy adopted is demonstrated using respiratory pathogens, namely, Streptococcus pneumoniae and Haemophilus influenzae as examples. Our approach identified 8 potent target genes (Streptococcus pneumoniae?C2, H. influenzae?C6), which are functionally significant and also play key role in host-pathogen interactions. This approach facilitates swift identification of potential drug targets, thereby enabling the search for new inhibitors. These results underscore the utility of CAI for enhanced in silico drug target identification.     

TargetScreen: An unbiased approach to identify functionally important microRNA targets

We recently identified miR-19 as the critical activity for leukemogenesis within the oncogenic 17~92 cluster of microRNAs.¹ This finding prompted us to test an unbiased method for pinpointing those miR-19 targets may be key to its oncogenic action. Specifically, we used a large-scale short hairpin RNA screen to identify those miR-19 target genes, whose knockdown could reproduce miR-19's effects on lymphocyte transformation. In this way, we found that miR-19 produces a coordinate clampdown on multiple negative regulators of PI3K-related survival signals. These findings have implications for the therapy of miR-19 expressing tumors. They also validate a new strategy for the unbiased identification of functionally important microRNA target genes. Using the example of miR-19 in leukemia, we will discuss some possibilities and limitations of this new approach.     

Phospho-proteomic approach to identify new targets of leucine deprivation in muscle cells

The aim of this study was to optimize a protocol that allows identifying changes at the phosphorylation level of specific proteins in response to cell stimulation by leucine starvation. To make possible the identification of differentially phosphorylated proteins by the combination of two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), we prepared fraction enriched in phosphoproteins. For that purpose, we adapted the immobilized metal affinity chromatography (IMAC) technique to make it compatible with 2D-PAGE. On the whole, this procedure allowed identifying regulated targets of leucine deprivation: molecular chaperones glucose-regulated protein 58 kDa (GRP58) and BiP (GRP78), RNA helicase DEAD box polypeptide 3, and eukaryotic translation initiation factor 4B (eIF4B).     

A composite genome approach to identify phylogenetically informative data from next-generation sequencing

Background

Improvements in sequencing technology now allow easy acquisition of large datasets; however, analyzing these data for phylogenetics can be challenging. We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, multiple genome alignment, and annotation.

Results

For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered eight phylogenies that resolved the basal relationships among mammals using datasets with different levels of missing data. The three alternate resolutions of the basal relationships are consistent with the major hypotheses for the relationships among mammals, all of which have been supported previously by different molecular datasets.

Conclusions

SISRS has the potential to transform phylogenetic research. This method eliminates the need for expensive marker development in many studies by using whole genome shotgun sequence data directly. SISRS is open source and freely available at https://github.com/rachelss/SISRS/releases.

     

Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures

Background  

DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting information on this genomic scale, and a first step towards the rapid and comprehensive interpretation of this data is gene clustering with respect to the expression patterns. Classifying genes into clusters can lead to interesting biological insights. In this study, we describe an iterative clustering approach to uncover biologically coherent structures from DNA microarray data based on a novel clustering algorithm EP_GOS_Clust.     

Visualizing information across multidimensional post-genomic structured and textual databases

MOTIVATION: Visualizing relationships among biological information to facilitate understanding is crucial to biological research during the post-genomic era. Although different systems have been developed to view gene-phenotype relationships for specific databases, very few have been designed specifically as a general flexible tool for visualizing multidimensional genotypic and phenotypic information together. Our goal is to develop a method for visualizing multidimensional genotypic and phenotypic information and a model that unifies different biological databases in order to present the integrated knowledge using a uniform interface. RESULTS: We developed a novel, flexible and generalizable visualization tool, called PhenoGenesviewer (PGviewer), which in this paper was used to display gene-phenotype relationships from a human-curated database (OMIM) and from an automatic method using a Natural Language Processing tool called BioMedLEE. Data obtained from multiple databases were first integrated into a uniform structure and then organized by PGviewer. PGviewer provides a flexible query interface that allows dynamic selection and ordering of any desired dimension in the databases. Based on users' queries, results can be visualized using hierarchical expandable trees that present views specified by users according to their research interests. We believe that this method, which allows users to dynamically organize and visualize multiple dimensions, is a potentially powerful and promising tool that should substantially facilitate biological research. AVAILABILITY: PhenogenesViewer as well as its support and tutorial are available at http://www.dbmi.columbia.edu/pgviewer/ CONTACT: Lussier@dbmi.columbia.edu.     

A structured approach to design and operation of biotransformation processes

A structured approach to design and operation of biotransformation (bioconversion) processes, based on previous case studies, has been developed. This requires knowledge of the key characteristics of a biotransformation which determine the constraints on process selection. The approach is illustrated for five biotransformations, two enzymic and three microbial. Some generic problems such as low water solubility and volatility of reactants, reactant and product toxicity have been identified. The microblal oxidations of toluene and fluorobenzene to toluenecis-glycol and fluorocatechol respectively byPseudomonas putida have been used to illustrate how these constraints may be overcome by addition of tetradecane as a second liquid phase, use of a membrane oxygenator and introduction ofin situ product removal.     

A genomic approach to identify hybrid incompatibility genes

Uncovering the genetic and molecular basis of barriers to gene flow between populations is key to understanding how new species are born. Intrinsic postzygotic reproductive barriers such as hybrid sterility and hybrid inviability are caused by deleterious genetic interactions known as hybrid incompatibilities. The difficulty in identifying these hybrid incompatibility genes remains a rate-limiting step in our understanding of the molecular basis of speciation. We recently described how whole genome sequencing can be applied to identify hybrid incompatibility genes, even from genetically terminal hybrids. Using this approach, we discovered a new hybrid incompatibility gene, gfzf, between Drosophila melanogaster and Drosophila simulans, and found that it plays an essential role in cell cycle regulation. Here, we discuss the history of the hunt for incompatibility genes between these species, discuss the molecular roles of gfzf in cell cycle regulation, and explore how intragenomic conflict drives the evolution of fundamental cellular mechanisms that lead to the developmental arrest of hybrids.     

A multidimensional proteomic approach to identify hypertrophy-associated proteins

Left ventricular hypertrophy (LVH) is a leading cause of congestive heart failure. The exact mechanisms that control cardiac growth and regulate the transition to failure are not fully understood, in part due to the lack of a complete inventory of proteins associated with LVH. We investigated the proteomic basis of LVH using the transverse aortic constriction model of pressure overload in mice coupled with a multidimensional approach to identify known and novel proteins that may be relevant to the development and maintenance of LVH. We identified 123 proteins that were differentially expressed during LVH, including LIM proteins, thioredoxin, myoglobin, fatty acid binding protein 3, the abnormal spindle-like microcephaly protein (ASPM), and cytoskeletal proteins such as actin and myosin. In addition, proteins with unknown functions were identified, providing new directions for future research in this area. We also discuss common pitfalls and strategies to overcome the limitations of current proteomic technologies. Together, the multidimensional approach provides insight into the proteomic changes that occur in the LV during hypertrophy.