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Making mechanistic connections between cell signaling pathways and pathological endpoints.

Cell signaling is a term used to describe a complex interactive system of signals that act to regulate or mediate a cellular response. Therapies that target cell signaling pathways have the potential to effectively reverse molecular deregulation underlying disease. The inherent complexity of cell signaling presents a major challenge to designing such therapies however, because perturbation of pathways has the potential to produce dramatic adverse effects. Pathologists are in the primary position of detecting adverse responses in drug development and are essential members of teams whose goal is to determine the mechanisms underlying tissue responses. The pathologist therefore will be expected to integrate morphologic interpretation with data obtained from several laboratory-based methods and data derived from novel technologies. Approaches being used include several in silico tools that provide access to public databases and signal pathway visualization that can serve to focus on key mechanistic hypotheses. The main objective of this article is to discuss a basic mechanistic approach and methods that can be used to associate modulation of cell signaling pathways with pathologic endpoints. The approach suggested begins with diagnostic pathology and uses global gene expression analysis in conjunction with transcription factor profiling and confirmatory protein technologies, to elucidate pathways relevant to the biological mechanism. Another important objective is to highlight the use of in silico technologies to prioritize laboratory efforts and focus these efforts on key hypotheses.

Animals↗

Quadrupole ion trap mass spectrometry.

A number of other features of ITMS systems that will enhance their ability to analyze biological macromolecules are worth mentioning. As has already been demonstrated for ESI/quadrupole, ESI/magnetic sector, and ESI/FTICR systems, the capability of inducing fragmentation of the ESI-generated multiply charged ions of biological macromolecules in the capillary/skimmer region of the ESI source and subsequently selectively analyzing fragments can also be carried out with the QITMS, as we have demonstrated using bovine serum albumin (data not shown). The ability to carry out chemical reactions on biological macromolecules inside the QITMS has been demonstrated by McCluckey et al. by showing that the introduction of a pulse of volatile base, such as diethylamine, can result in proton removal from multiply charged protein ions, resulting in species with lower charge states. The application of the technique of deuterium exchange of active hydrogens on peptides to simplify the interpretation of MS/MS sequencing experiments can be implemented for ESI/QITMS. Carrying out such exchange inside the ITMS may also be possible, with resulting analytical advantages. Reports of a hybrid QITMS-TOF system, which was operated with either ESI or MALDI methodology, and which demonstrated low femtomolar sensitivity with higher resolution of the TOF analyzer because of ion injection of essentially monoenergetic ions from the QITMS into the TOF, illustrate additional uses of the QITMS. The reverse combination (e.g., ESI/TOF/QITMS or MALDI/TOF/QITMS) could afford preselection of ions for even higher performance in the QITMS, because space charging (loss of performance such as resolution because of too much charge in close proximity in the ion trap) would be minimized. Opportunities for the application of QITMS technology for the analysis of biological macromolecules abound, including ultrahigh-sensitivity protein sequencing using specifically derivatized amino acids released by Edman chemistry; rapid sequencing of MHC-associated antigenic peptides of variable length (approximately nonamers for the MHC I complexes to > dodecamers for the MHC II complexes), which are available in only very low amounts (femtomole/attomole) and in very complex mixtures (5000-10,000 species) of closely related peptide structures; ultrahigh-sensitivity analysis of peptides and proteins directly in vivo using microelectrospray; direct analysis of metal ion binding to peptides and proteins and analysis of noncovalent interactions, including conformation; and possible analysis of plasmid DNA, as has been suggested by ESI ionization of a 2-MDa DNA species. In summary, the ability of the QITMS to interface to key separations systems such as HPLC and HPCE through the critical ionization techniques of ESI and MALDI, coupled with the high mass range, high mass resolution, high sensitivity, high-efficiency CID, and MS capabilities of this device, will provide an astonishing array of cost-effective capabilities for the qualitative and quantitative analysis of biological macromolecules.

Amino Acid Sequence↗

Web-based information retrieval system for the prediction of metabolic pathways.

Analysis of metabolic pathways is a central topic in understanding the relationship between genotype and phenotype. The rapid accumulation of biological data provides the possibility of studying metabolic pathways both at the genomic and metabolic levels. Our motivation is to develop a conceptual framework and computational system that will allow retrieval of metabolic information and prediction of metabolic pathways. In this paper, we introduce a metabolic pathway prediction framework that extracts metabolic information from biological databases via the Internet, and builds metabolic pathways with data sources of genes, sequences, enzymes, metabolites, etc. It provides an easy-to-use interface to retrieve, display, and manipulate metabolic information. The system has been implemented into PathAligner, available at http://bibiserv.techfak.uni-bielefeld. de/pathaligner/.

Computer Simulation↗

Comparative genomics and understanding of microbial biology.

The sequences of close to 30 microbial genomes have been completed during the past 5 years, and the sequences of more than 100 genomes should be completed in the next 2 to 4 years. Soon, completed microbial genome sequences will represent a collection of >200,000 predicted coding sequences. While analysis of a single genome provides tremendous biological insights on any given organism, comparative analysis of multiple genomes provides substantially more information on the physiology and evolution of microbial species and expands our ability to better assign putative function to predicted coding sequences.

Bacteria↗

Human endometrial receptivity: a genomic approach.

The endometrium is a specialized tissue, hormonally-regulated, that is non-adhesive for embryos throughout most of the menstrual cycle in humans and other primates. Thus, endometrial receptivity is a self-limited period in which the endometrial epithelium (EE) acquires a functional and transient ovarian steroid-dependent status. The luminal EE acquires the ability to adhere (receptivity) the developing human blastocyst during this period due mainly to the presence of progesterone after appropriate 17beta-oestradiol priming. This status is a key element for embryonic implantation and appears to be closely associated with morphological and biochemical changes of EE cells. This specific time window is thought to be open after 4-5 days and closes after 9-10 days of progesterone production or administration, creating a physiological window of receptivity limited to days 19-24 of the menstrual cycle in humans. The scientific knowledge of the endometrial receptivity process is fundamental for the understanding of the human reproduction, but, so far, none of the proposed biochemical markers for endometrial receptivity have been proved clinically useful. In this work new strategies are presented based on molecular biology technologies that aim to clarify the fragmented information in this field using differential display, quantitative PCR and cDNA microarray analysis of endometrial epithelial-derived cell lines and endometrial samples to investigate the hierarchy at the mRNA level of molecules implicated in the process of endometrial receptivity.

Blastocyst↗

Application of sequence-based methods in human microbial ecology.

Ecologists studying microbial life in the environment have recognized the enormous complexity of microbial diversity for many years, and the development of a variety of culture-independent methods, many of them coupled with high-throughput DNA sequencing, has allowed this diversity to be explored in ever-greater detail. Despite the widespread application of these new techniques to the characterization of uncultivated microbes and microbial communities in the environment, their application to human health and disease has lagged. Because DNA-based techniques for defining uncultured microbes allow not only cataloging of microbial diversity but also insight into microbial functions, investigators are beginning to apply these tools to the microbial communities that abound on and within us, in what has aptly been called "the second Human Genome Project." In this review we discuss the sequence-based methods for microbial analysis that are currently available and their application to identify novel human pathogens, improve diagnosis of known infectious diseases, and advance understanding of our relationship with microbial communities that normally reside in and on the human body.

Animals↗

Molecular features of adult mouse small intestinal epithelial progenitors.

The adult mouse small intestinal epithelium undergoes perpetual regeneration, fueled by a population of multipotential stem cells and oligopotential daughters located at the base of crypts of Lieberkühn. Although the morphologic features of small intestinal epithelial progenitors (SiEPs) are known, their molecular features are poorly defined. Previous impediments to purification and molecular characterization of SiEPs include lack of ex vivo clonigenic assays and the difficulty of physically retrieving them from their niche where they are interspersed between their numerous differentiated Paneth cell daughters. To overcome these obstacles, we used germ-free transgenic mice lacking Paneth cells to obtain a consolidated population of SiEPs with normal proliferative activity. These cells were harvested by laser capture microdissection. Functional genomics analysis identified 163 transcripts enriched in SiEPs compared with Paneth cell-dominated normal crypt base epithelium. The dataset was validated by (i) correlation with the organellar composition of SiEPs versus Paneth cells, (ii) similarities to databases generated from recent mouse hematopoietic and neural stem cell genome anatomy projects, and (iii) laser capture microdissectionreal-time quantitative RT-PCR studies of progenitor cell-containing populations retrieved from the small intestines, colons, and stomachs of conventionally raised mice. The SiEP profile has prominent representation of genes involved in c-myc signaling and in the processing, localization, and translation of mRNAs. This dataset, together with our recent analysis of gene expression in the gastric stem cell niche, discloses a set of molecular features shared by adult mouse gut epithelial progenitors.

Animals↗

Gene expression profiles of proliferating vs. G1/G0 arrested human leukemia cells suggest a mechanism for glucocorticoid-induced apoptosis.

Glucocorticoids (GC) have pronounced effects on metabolism, differentiation, proliferation, and cell survival (1). In certain lymphocytes and lymphocyte-related malignancies, GC inhibit proliferation and induce apoptotic cell death, which has led to their extensive use in the therapy of malignant lymphoproliferative disorders (2). Most of these effects result from regulation of gene expression via the GC receptor (GR), a ligand-activated transcription factor (3). Although hundreds of genes are regulated by GC (1), how certain biological GC effects relate to individual gene regulation remains enigmatic. To address this question with respect to GC-induced cell cycle arrest and apoptosis, we applied DNA chip technology (4, 5) to determine gene expression profiles in proliferating and G1/G0-arrested (by conditional expression of the CDK inhibitor p16/INK4a) acute lymphoblastic T cells undergoing GC-induced apoptosis. Of 7074 genes tested, 163 were found to be regulated by dexamethasone in the first 8 h in proliferating cells and 66 genes in G1/G0-arrested cells. An almost nonoverlapping set of genes (i.e., only eight genes) was coordinately regulated in proliferating and arrested cells. Analysis of the regulated genes supports the concept that GC-induced apoptosis results from positive GR autoregulation entailing persistent down-regulation of metabolic pathways critical for survival

Apoptosis↗

Microarray databases: standards and ontologies.

A single microarray can provide information on the expression of tens of thousands of genes. The amount of information generated by a microarray-based experiment is sufficiently large that no single study can be expected to mine each nugget of scientific information. As a consequence, the scale and complexity of microarray experiments require that computer software programs do much of the data processing, storage, visualization, analysis and transfer. The adoption of common standards and ontologies for the management and sharing of microarray data is essential and will provide immediate benefit to the research community.

Database Management Systems↗

String analysis and energy minimization in the partition of DNA sequences.

Two approaches to the understanding of biological sequences are confronted. While the recognition of particular signals in sequences relies on complex physical interactions, the problem is often analysed in terms of the presence or absence of literal motifs (strings) in the sequence. We present here a test-case for evaluating the potential of this approach. We classify DNA sequences as positive or negative depending on whether they contain a single melted domain in the middle of the sequence, which is a global physical property. Two sets of positive "biological" sequences were generated by a computer simulation of evolutionary divergence along the branches of a phylogenetic tree, under the constraint that each intermediate sequence be positive. These two sets and a set of random positive sequences were subjected to pattern analysis. The observed local patterns were used to construct expert systems to discriminate positive from negative sequences. The experts achieved 79% to 90% success on random positive sequences and up to 99% on the biological sets, while making less than 2% errors on negative sequences. Thus, the global constraints imposed on sequences by a physical process may generate local patterns that are sufficient to predict, with a reasonable probability, the behaviour of the sequences. However, rather large sets of biological sequences are required to generate patterns free of illegitimate constraints. Furthermore, depending upon the initial sequence, the sets of sequences generated on a phylogenetic tree may be amenable or refractory to string analysis, while obeying identical physical constraints. Our study clarifies the relationship between experts' errors on positive and negative sequences, and the contributions of legitimate and illegitimate patterns to these errors. The test-case appears suitable both for further investigations of problems in the theory of sequence evolution and for further testing of pattern analysis techniques.

Base Sequence↗

BiologicalNetworks: visualization and analysis tool for systems biology.

Systems level investigation of genomic scale information requires the development of truly integrated databases dealing with heterogeneous data, which can be queried for simple properties of genes or other database objects as well as for complex network level properties, for the analysis and modelling of complex biological processes. Towards that goal, we recently constructed PathSys, a data integration platform for systems biology, which provides dynamic integration over a diverse set of databases [Baitaluk et al. (2006) BMC Bioinformatics 7, 55]. Here we describe a server, BiologicalNetworks, which provides visualization, analysis services and an information management framework over PathSys. The server allows easy retrieval, construction and visualization of complex biological networks, including genome-scale integrated networks of protein-protein, protein-DNA and genetic interactions. Most importantly, BiologicalNetworks addresses the need for systematic presentation and analysis of high-throughput expression data by mapping and analysis of expression profiles of genes or proteins simultaneously on to regulatory, metabolic and cellular networks. BiologicalNetworks Server is available at http://brak.sdsc.edu/pub/BiologicalNetworks.

Computer Graphics↗

Molecular evolution of minisatellites in hemiascomycetous yeasts.

Minisatellites are DNA tandem repeats exhibiting size polymorphism among individuals of a population. This polymorphism is generated by two different mechanisms, both in human and yeast cells, "replication slippage" during S-phase DNA synthesis and "repair slippage" associated to meiotic gene conversion. The Saccharomyces cerevisiae genome contains numerous natural minisatellites. They are located on all chromosomes without any obvious distribution bias. Minisatellites found in protein-coding genes have longer repeat units and on the average more repeat units than minisatellites in noncoding regions. They show an excess of cytosines on the coding strand, as compared to guanines (negative GC skew). They are always multiples of three, encode serine- and threonine-rich amino acid repeats, and are found preferably within genes encoding cell wall proteins, suggesting that they are positively selected in this particular class of genes. Genome-wide, there is no statistically significant association between minisatellites and meiotic recombination hot spots. In addition, minisatellites that are located in the vicinity of a meiotic hot spot are not more polymorphic than minisatellites located far from any hot spot. This suggests that minisatellites, in S. cerevisiae, evolve probably by strand slippage during replication or mitotic recombination. Finally, evolution of minisatellites among hemiascomycetous yeasts shows that even though many minisatellite-containing genes are conserved, most of the time the minisatellite itself is not conserved. The diversity of minisatellite sequences found in orthologous genes of different species suggests that minisatellites are differentially acquired and lost during evolution of hemiascomycetous yeasts at a pace faster than the genes containing them.

Amino Acid Motifs↗

GenePro: a Cytoscape plug-in for advanced visualization and analysis of interaction networks.

MOTIVATION: Analyzing the networks of interactions between genes and proteins has become a central theme in systems biology. Versatile software tools for interactively displaying and analyzing these networks are therefore very much in demand. The public-domain open software environment Cytoscape has been developed with the goal of facilitating the design and development of such software tools by the scientific community. RESULTS: We present GenePro, a plugin to Cytoscape featuring a set of versatile tools that greatly facilitates the visualization and analysis of protein networks derived from high-throughput interactions data and the validation of various methods for parsing these networks into meaningful functional modules. AVAILABILITY: The GenePro plugin is available at the website http://genepro.ccb.sickkids.ca.

Algorithms↗

The Caenorhabditis briggsae genome contains active CbmaT1 and Tcb1 transposons.

The maT clade of transposons is a group of transposable elements intermediate in sequence and predicted protein structure to mariner and Tc transposons, with a distribution thus far limited to a few invertebrate species. We present evidence, based on searches of publicly available databases, that the nematode Caenorhabditis briggsae has several maT-like transposons, which we have designated as CbmaT elements, dispersed throughout its genome. We also describe two additional transposon sequences that probably share their evolutionary history with the CbmaT transposons. One resembles a fold back variant of a CbmaT element, with long (380-bp) inverted terminal repeats (ITRs) that show a high degree (71%) of identity to CbmaT1. The other, which shares only the 26-bp ITR sequences with one of the CbmaT variants, is present in eight nearly identical copies, but does not have a transposase gene and may therefore be cross mobilised by a CbmaT transposase. Using PCR-based mobility assays, we show that CbmaT1 transposons are capable of excising from the C. briggsae genome. CbmaT1 excised approximately 500 times less frequently than Tcb1 in the reference strain AF16, but both CbmaT1 and Tcb1 excised at extremely high frequencies in the HK105 strain. The HK105 strain also exhibited a high frequency of spontaneous induction of unc-22 mutants, suggesting that it may be a mutator strain of C. briggsae.

Amino Acid Sequence↗

Genome-scale analysis of the uses of the Escherichia coli genome: model-driven analysis of heterogeneous data sets.

The recent availability of heterogeneous high-throughput data types has increased the need for scalable in silico methods with which to integrate data related to the processes of regulation, protein synthesis, and metabolism. A sequence-based framework for modeling transcription and translation in prokaryotes has been established and has been extended to study the expression state of the entire Escherichia coli genome. The resulting in silico analysis of the expression state highlighted three facets of gene expression in E. coli: (i) the metabolic resources required for genome expression and protein synthesis were found to be relatively invariant under the conditions tested; (ii) effective promoter strengths were estimated at the genome scale by using global mRNA abundance and half-life data, revealing genes subject to regulation under the experimental conditions tested; and (iii) large-scale genome location-dependent expression patterns with approximately 600-kb periodicity were detected in the E. coli genome based on the 49 expression data sets analyzed. These results support the notion that a structured model-driven analysis of expression data yields additional information that can be subjected to commonly used statistical analyses. The integration of heterogeneous genome-scale data (i.e., sequence, expression data, and mRNA half-life data) is readily achieved in the context of an in silico model.

Bacterial Proteins↗

Predictive screening for regulators of conserved functional gene modules (gene batteries) in mammals.

BACKGROUND: The expression of gene batteries, genomic units of functionally linked genes which are activated by similar sets of cis- and trans-acting regulators, has been proposed as a major determinant of cell specialization in metazoans. We developed a predictive procedure to screen the mouse and human genomes and transcriptomes for cases of gene-battery-like regulation. RESULTS: In a screen that covered approximately 40 percent of all annotated protein-coding genes, we identified 21 co-expressed gene clusters with statistically supported sharing of cis-regulatory sequence elements. 66 predicted cases of over-represented transcription factor binding motifs were validated against the literature and fell into three categories: (i) previously described cases of gene battery-like regulation, (ii) previously unreported cases of gene battery-like regulation with some support in a limited number of genes, and (iii) predicted cases that currently lack experimental support. The novel predictions include for example Sox 17 and RFX transcription factor binding sites that were detected in approximately 10% of all testis specific genes, and HNF-1 and 4 binding sites that were detected in approximately 30% of all kidney specific genes respectively. The results are publicly available at http://www.wlab.gu.se/lindahl/genebatteries. CONCLUSION: 21 co-expressed gene clusters were enriched for a total of 66 shared cis-regulatory sequence elements. A majority of these predictions represent novel cases of potential co-regulation of functionally coupled proteins. Critical technical parameters were evaluated, and the results and the methods provide a valuable resource for future experimental design.

Amino Acid Motifs↗

Molecular community analysis of microbial diversity.

New technologies that avoid the need for either gene amplification (e.g. microarrays) or nucleic acid extraction (e.g. in situ PCR) have recently been implemented in microbial ecology. Together with new approaches for culturing microorganisms and an increased understanding of the biases of molecular methods, these techniques form the most exciting advances in this field during the past year.

Ecosystem↗