MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets

MPP is a Java application, encompassing both new and established algorithms, for the analysis of gene and marker content datasets arising from high-throughput microarray techniques. MPP analyses flat file output from microarray experiments to determine the probability of the presence or absence of genes or markers within a genome. MPP can construct gene or marker content datasets for a number of genomes and can use the data to estimate an evolutionary tree or network. Results from gene content analyses may be validated by comparing them to known gene contents. MPP was initially developed to analyse data derived from comparative genome hybridization (CGH) microarray experiments in fungi and bacteria. It has recently been adapted to analyse retrotransposon-based insertion polymorphism (RBIP) marker scores derived from tagged microarray marker (TAM) experiments in pea. New analytical procedures may be added easily to MPP as plugins in order to increase the scope of the software. AVAILABILITY: MPP source code, executables and online help are available at http://cbr.jic.ac.uk/dicks/software/     

MADGene: retrieval and processing of gene identifier lists for the analysis of heterogeneous microarray datasets

MADGene is a software environment comprising a web-based database and a java application. This platform aims at unifying gene identifiers (ids) and performing gene set analysis. MADGene allows the user to perform inter-conversion of clone and gene ids over a large range of nomenclatures relative to 17 species. We propose a set of 23 functions to facilitate the analysis of gene sets and we give two microarray applications to show how MADGene can be used to conduct meta-analyses. AVAILABILITY: The MADGene resources are freely available online from http://www.madtools.org, a website dedicated to the analysis and annotation of DNA microarray data.     

A novel gene and pathway-level subtyping analysis scheme to understand biological mechanisms in complex disease: a case study in rheumatoid arthritis

Complex diseases have heterogeneous underlying molecular mechanisms. In order to improve the diagnosis and treatment of disease, it is vital to stratify patients into homogeneous subgroups that share a similar disease etiology. In this study, we performed gene-level subtyping analysis on two independent Rheumatoid Arthritis gene expression cohorts from different ethnic groups to discover the possible disease mechanisms associated with each subtype. Also, a novel pathway-level analysis is proposed to increase the subtyping robustness and facilitate biological interpretation. This approach could stratify RA patients into two robust and homogeneous groups with differing activation of central signal transduction pathways and pro-inflammatory cytokines in the pathogenesis of RA. Such a methodology can help understand disease mechanisms at play in different patient sub-populations and also potentially explain why some patients don't respond to anti-TNF treatment.     

ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples

Analysis of 16S ribosomal RNA (rRNA) gene amplification data for microbial barcoding can be inaccurate across complex environmental samples. A method, ANCHOR, is presented and designed for improved species-level microbial identification using paired-end sequences directly, multiple high-complexity samples and multiple reference databases. A standard operating procedure (SOP) is reported alongside benchmarking against artificial, single sample and replicated mock data sets. The method is then directly tested using a real-world data set from surface swabs of the International Space Station (ISS). Simple mock community analysis identified 100% of the expected species and 99% of expected gene copy variants (100% identical). A replicated mock community revealed similar or better numbers of expected species than MetaAmp, DADA2, Mothur and QIIME1. Analysis of the ISS microbiome identified 714 putative unique species/strains and differential abundance analysis distinguished significant differences between the Destiny module (U.S. laboratory) and Harmony module (sleeping quarters). Harmony was remarkably dominated by human gastrointestinal tract bacteria, similar to enclosed environments on earth; however, Destiny module bacteria also derived from nonhuman microbiome carriers present on the ISS, the laboratory's research animals. ANCHOR can help substantially improve sequence resolution of 16S rRNA gene amplification data within biologically replicated environmental experiments and integrated multidatabase annotation enhances interpretation of complex, nonreference microbiomes.     

A unique reaction in a common pathway: mechanism and function of chorismate synthase in the shikimate pathway

Chorismate synthase, the seventh enzyme in the shikimate pathway, catalyzes the transformation of 5-enolpyruvylshikimate 3-phosphate to chorismate which is the last common precursor in the biosynthesis of numerous aromatic compounds in bacteria, fungi and plants. The enzyme has an absolute requirement for reduced FMN as a cofactor, although the 1,4-anti elimination of phosphate and the C(6proR)-hydrogen does not involve a net redox change. The role of the reduced FMN in catalysis has long been elusive. However, recent detailed kinetic and bioorganic approaches have fundamentally advanced our understanding of the mechanism of action, suggesting an initial electron transfer from tightly bound reduced flavin to the substrate, a process which results in C—O bond cleavage. Studies on chorismate synthases from bacteria, fungi and plants revealed that in these organisms the reduced FMN cofactor is made available in different ways to chorismate synthase: chorismate synthases in fungi – in contrast to those in bacteria and plants – carry a second enzymatic activity which enables them to reduce FMN at the expense of NADPH. Yet, as shown by the analysis of the corresponding genes, all chorismate synthases are derived from a common ancestor. However, several issues revolving around the origin of reduced FMN, as well as the possible regulation of the enzyme activity by means of the availability of reduced FMN, remain poorly understood. This review summarizes recent developments in the biochemical and genetic arena and identifies future aims in this field. Received: 22 June 1998 / Accepted: 7 August 1998     

Identification of common biological pathways and drug targets across multiple respiratory viruses based on human host gene expression analysis

Background

Pandemic and seasonal respiratory viruses are a major global health concern. Given the genetic diversity of respiratory viruses and the emergence of drug resistant strains, the targeted disruption of human host-virus interactions is a potential therapeutic strategy for treating multi-viral infections. The availability of large-scale genomic datasets focused on host-pathogen interactions can be used to discover novel drug targets as well as potential opportunities for drug repositioning.

Methods/Results

In this study, we performed a large-scale analysis of microarray datasets involving host response to infections by influenza A virus, respiratory syncytial virus, rhinovirus, SARS-coronavirus, metapneumonia virus, coxsackievirus and cytomegalovirus. Common genes and pathways were found through a rigorous, iterative analysis pipeline where relevant host mRNA expression datasets were identified, analyzed for quality and gene differential expression, then mapped to pathways for enrichment analysis. Possible repurposed drugs targets were found through database and literature searches. A total of 67 common biological pathways were identified among the seven different respiratory viruses analyzed, representing fifteen laboratories, nine different cell types, and seven different array platforms. A large overlap in the general immune response was observed among the top twenty of these 67 pathways, adding validation to our analysis strategy. Of the top five pathways, we found 53 differentially expressed genes affected by at least five of the seven viruses. We suggest five new therapeutic indications for existing small molecules or biological agents targeting proteins encoded by the genes F3, IL1B, TNF, CASP1 and MMP9. Pathway enrichment analysis also identified a potential novel host response, the Parkin-Ubiquitin Proteasomal System (Parkin-UPS) pathway, which is known to be involved in the progression of neurodegenerative Parkinson''s disease.

Conclusions

Our study suggests that multiple and diverse respiratory viruses invoke several common host response pathways. Further analysis of these pathways suggests potential opportunities for therapeutic intervention.     

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems.     

A comparative analysis of global, national, and state red lists for threatened amphibians in Brazil

The knowledge about the conservation status of species is an important data for conservation biology. Therefore, threatened species lists are a powerful tool for conservation planning and prioritization. Our objective is to compare the global, the national and state red lists of amphibians in Brazil. Threatened species were categorized according to their listing in one or several of these lists. We analyzed for true inconsistencies across lists in order to evaluate practical consequences of such incongruences on amphibian conservation in Brazil. We recorded a total of 61 threatened amphibian species in Brazil (across all red lists). Only one species, Phrynomedusa fimbriata, was listed as Extinct (both in IUCN, Brazil and S?o Paulo lists). A total of eleven endemic species are listed as threatened by the global red list, but do not appear in Brazil’s national red list, which represent an inconsistence among these lists. Besides that, the threat category of Thoropa lutzi and Thoropa petropolitana, two endemic species, differ among both lists, which also represents a problem between both lists. These mismatches may be due to several reasons such as different interpretation of the criteria; different methodologies used; different data availability on species; differences in the dates of assessments processes; the assessors’ attitudes to uncertainty; outdated red lists. Harmonization among red lists permits a better picture of threatened amphibian diversity across scales and to develop global, national and state plans to complement conservation actions in order to maximize the chance of success of these initiatives.     

ComPath: comparative enzyme analysis and annotation in pathway/subsystem contexts

Background  

Once a new genome is sequenced, one of the important questions is to determine the presence and absence of biological pathways. Analysis of biological pathways in a genome is a complicated task since a number of biological entities are involved in pathways and biological pathways in different organisms are not identical. Computational pathway identification and analysis thus involves a number of computational tools and databases and typically done in comparison with pathways in other organisms. This computational requirement is much beyond the capability of biologists, so information systems for reconstructing, annotating, and analyzing biological pathways are much needed. We introduce a new comparative pathway analysis workbench, ComPath, which integrates various resources and computational tools using an interactive spreadsheet-style web interface for reliable pathway analyses.     

A murine model for human immune thrombocytopenic purpura and comparative analysis of multiple gene expression in bone marrow and spleen

Homeostasis of platelet number in human and other mammals is well maintained for prevention of minor bleeding and for other immunological functions,but the exact molecular mechanism responsible for immune thrombocytopenic purpura(ITP) has not been fully understood.In an effort to identify genetic factors involved in initiation of platelet production in response to bleeding injury or platelet destruction,we have successfully generated an animal model of human ITP via intraperitoneal injection of anti-platele...     

RNA-mediated silencing in Algae: biological roles and tools for analysis of gene function

Algae are a large group of aquatic, typically photosynthetic, eukaryotes that include species from very diverse phylogenetic lineages, from those similar to land plants to those related to protist parasites. The recent sequencing of several algal genomes has provided insights into the great complexity of these organisms. Genomic information has also emphasized our lack of knowledge of the functions of many predicted genes, as well as the gene regulatory mechanisms in algae. Core components of the machinery for RNA-mediated silencing show widespread distribution among algal lineages, but they also seem to have been lost entirely from several species with relatively small nuclear genomes. Complex sets of endogenous small RNAs, including candidate microRNAs and small interfering RNAs, have now been identified by high-throughput sequencing in green, red, and brown algae. However, the natural roles of RNA-mediated silencing in algal biology remain poorly understood. Limited evidence suggests that small RNAs may function, in different algae, in defense mechanisms against transposon mobilization, in responses to nutrient deprivation and, possibly, in the regulation of recently evolved developmental processes. From a practical perspective, RNA interference (RNAi) is becoming a promising tool for assessing gene function by sequence-specific knockdown. Transient gene silencing, triggered with exogenously synthesized nucleic acids, and/or stable gene repression, involving genome-integrated transgenes, have been achieved in green algae, diatoms, yellow-green algae, and euglenoids. The development of RNAi technology in conjunction with system level "omics" approaches may provide the tools needed to advance our understanding of algal physiological and metabolic processes.     

High-throughput liquid chromatography for drug analysis in biological fluids: investigation of extraction column life

A novel method was developed and assessed to extend the lifetime of extraction columns of high-throughput liquid chromatography (HTLC) for bioanalysis of human plasma samples. In this method, a 15% acetic acid solution and 90% THF were respectively used as mobile phases to clean up the proteins in human plasma samples and residual lipids from the extraction and analytical columns. The 15% acetic acid solution weakens the interactions between proteins and the stationary phase of the extraction column and increases the protein solubility in the mobile phase. The 90% THF mobile phase prevents the accumulation of lipids and thus reduces the potential damage on the columns. Using this novel method, the extraction column lifetime has been extended to about 2000 direct plasma injections, and this is the first time that high concentration acetic acid and THF are used in HTLC for on-line cleanup and extraction column lifetime extension.     

Identification of multiple cell adhesion receptors for collagen and fibronectin in human fibrosarcoma cells possessing unique alpha and common beta subunits

Using monoclonal antibody technology and affinity chromatography we have identified four distinct classes of cell surface receptors for native collagen on a cultured human fibrosarcoma cell line, HT-1080. Two classes of monoclonal antibodies prepared against HT-1080 cells inhibited adhesion to extracellular matrix components. Class I antibodies inhibited cell adhesion to collagen, fibronectin, and laminin. These antibodies immunoprecipitated two noncovalently linked proteins (subunits) with molecular masses of 147 and 125 kD, termed alpha and beta, respectively. Class II antibodies inhibited cell adhesion to native collagen only and not fibronectin or laminin. Class II antibodies immunoprecipitated a single cell surface protein containing two noncovalently linked subunits with molecular masses of 145 and 125 kD, termed alpha and beta, respectively. The two classes of antibodies did not cross-react with the same cell surface protein and recognized epitopes present on the alpha subunits. Pulse-chase labeling studies with [35S]methionine indicated that neither class I nor II antigen was a metabolic precursor of the other. Comparison of the alpha and beta subunits of the class I and II antigens by peptide mapping indicated that the beta subunits were identical while the alpha subunits were distinct. In affinity chromatography experiments HT-1080 cells were extracted with Triton X-100 or octylglucoside detergents and chromatographed on insoluble fibronectin or native type I or VI collagens. A single membrane protein with the biochemical characteristics of the class I antigen was isolated on fibronectin-Sepharose and could be immunoprecipitated with the class I monoclonal antibody. The class I antigen also specifically bound to type I and VI collagens, consistent with the observation that the class I antibodies inhibit cell adhesion to types VI and I collagen and fibronectin. The class II antigen, however, did not bind to collagen (or fibronectin) even though class II monoclonal antibodies completely inhibited adhesion of HT-1080 cells to types I and III-VI collagen. The class I beta and II beta subunits were structurally related to the beta subunit of the fibronectin receptor described by others. However, none of these receptors shared the same alpha subunits. Additional membrane glycoprotein(s) with molecular mass ranges of 80-90 and 35-45 kD, termed the class III and IV receptors, respectively, bound to types I and VI collagen but not to fibronectin. Monoclonal antibodies prepared against the class III receptor had no consistent effect on cell attachment or spreading, suggesting that it is not directly involved in adhesion to collagen-coated substrates.(ABSTRACT TRUNCATED AT 400 WORDS)     

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Background

Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult.

Results

S TAR N ET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. S TAR N ET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new H EAT S EEKER module.

Conclusion

S TAR N ET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a S TAR N ET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at http://vanburenlab.medicine.tamhsc.edu/starnet2.html, and does not require user registration.     

Development and application of microwave-assisted extraction technique in biological sample preparation for small molecule analysis

Microwave-assisted extraction (MAE) has emerged as an efficient extraction technique for various kinds of biological samples due to its low usage of extraction solvents and shorter extraction time. This review will focus on the recent developments and advantages of incorporating MAE in sample preparation protocols for the analysis of small molecules in plant, food and clinical samples in recent years. The operating principles of this technique and the key parameters influencing its extraction efficiency, including the nature of solvent, temperature, power and extraction time and their limitations are first mentioned. This is followed by a discussion on the advantages of applying MAE to extract organic contaminants in food for routine food safety analysis and active ingredients recovery. The successful application of MAE technique to recover bioactive compounds from plants in drug discovery studies and quality control purposes is then described. Additionally, the feasibility of using green solvents such as water, micelle and ionic liquids with MAE for plant metabolite profiling studies is evaluated and the associated challenges discussed. Finally, the application of MAE in clinical samples is highlighted. The use of MAE in this field is currently limited to the targeted detection of small molecules in human samples, due to a lack of knowledge of its effects on thermally labile metabolites. Consequently, the need for additional studies on how MAE impacts the recoveries of different metabolite classes in mammalian samples is discussed. The outcome of these studies can potentially broaden MAE applications in the clinical field.     

PlasmoGF: an integrated system for comparative genomics and phylogenetic analysis of Plasmodium gene families

Summary: Malaria, one of the world's most common diseases, iscaused by the intracellular protozoan parasite known as Plasmodium.Recently, with the arrival of several malaria parasite genomes,we established an integrated system named PlasmoGF for comparativegenomics and phylogenetic analysis of Plasmodium gene families.Gene families were clustered using the Markov Cluster algorithmimplemented in TribeMCL program and could be searched usingkeywords, gene-family information, domain composition, GeneOntology and BLAST. Moreover, a number of useful bioinformaticstools were implemented to facilitate the analysis of these putativePlasmodium gene families, including gene retrieval, annotation,sequence alignment, phylogeny construction and visualization.In the current version, PlasmoGF contained 8980 sets of genefamilies derived from six malaria parasite genomes: Plasmodium.falciparum, P. berghei, P. knowlesi, P. chabaudi, P. vivax andP. yoelii. The availability of such a highly integrated systemwould be of great interest for the community of researchersworking on malaria parasite phylogenomics. Availability: PlasmoGF is freely available at http://bioinformatics.zj.cn/pgf/ Contact: xiaokunli{at}163.net; baoqy{at}genomics.org.cn; fuz3{at}psu.edu Associate Editor: Jonathan Wren The authors wish it to be known that, in their opinion, thefirst two authors should be regarded as joint First Authors.