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PubMed2025

Identification of a prognostic signature consisting of three macrophage-related genes for glioblastoma based on bulk and single-cell transcriptomes analyses.

BACKGROUND: Tumor-associated macrophages have been implicated in the progression and treatment resistance of glioblastoma (GBM). This study aimed to identify macrophage-related genes associated with prognosis and therapeutic response in GBM. MATERIALS AND METHODS: Bulk RNA-seq data from 533 patients with GBM were downloaded from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Bioinformatic tools were used to detect the co-expression gene modules associated with the infiltration of immune cells, identify a prognostic macrophage-related gene signature, and explore their association with sensitivity to chemotherapeutic drugs and immune checkpoint blockade. Single-cell RNA-seq data and multiplexed immunofluorescence were used to validate ISG20 expression (a member of the identified gene signature) in macrophages. RESULTS: We detected gene modules associated with macrophages and identified a signature consisting of three macrophage-related genes (ISG20, PARP12 and IFIT5) in the discovery set (TCGA-GBM, n = 159), and validated its prognostic value in the validation set (CGGA-GBM, n = 374). This gene signature demonstrated favorable accuracy in predicting prognosis and resistance of immuno- and chemo-therapy. The co-expression of ISG20 and PD-1 in macrophages was verified by single-cell RNA-seq data and multiplex immunofluorescence. CONCLUSIONS: This study presents a macrophage-related gene signature to predict prognosis and therapeutic response in GBM. ISG20, PARP12 and IFIT5 are interferon-stimulated genes, and further investigations may provide new insights into the interplay between macrophages and interferon signaling in GBM.

Humans↗
PubMed2004

Use of bioinformatics and PCR in the search for ABC transporter homology among various bacteria.

Bioinformatics databases and search tools are utilised to produce polymerase chain reaction (PCR) primers for the amplification of an ABC transporter gene from the clinically important anaerobe Finegoldia magna. On sequencing, a 450 base pair amplicon showed homology with the amino acid transporter of Enterococcus faecalis. Little sequence data is available for F. magna and the newly isolated DNA could be a useful tool in the identification of this organism in clinical specimens.

ATP-Binding Cassette Transporters↗
PubMed2004

Inhibition of protein crystallization by evolutionary negative design.

Why are proteins so hard to crystallize? We propose an 'evolutionary negative design' principle to explain this difficulty. Proteins have evolved to avoid crystallization because crystallization compromises the viability of the cell. Evolutionary negative design is supported by much evidence in the literature, including the effect of mutations on the crystallizability of a protein, the correlations found in the properties of crystal contacts in bioinformatics databases, and the positive use of protein crystallization by bacteria and viruses.

Biophysical Phenomena↗
PubMed2000

Wrapping and interoperating bioinformatics resources using CORBA.

Bioinformaticians seeking to provide services to working biologists are faced with the twin problems of distribution and diversity of resources. Bioinformatics databases are distributed around the world and exist in many kinds of storage forms, platforms and access paradigms. To provide adequate services to biologists, these distributed and diverse resources have to interoperate seamlessly within single applications. The Common Object Request Broker Architecture (CORBA) offers one technical solution to these problems. The key component of CORBA is its use of object orientation as an intermediate form to translate between different representations. This paper concentrates on an explanation of object orientation and how it can be used to overcome the problems of distribution and diversity by describing the interfaces between objects.

Amino Acid Sequence↗
PubMed2002

The Bioperl toolkit: Perl modules for the life sciences.

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.

Algorithms↗
PubMed2003

Subsystem identification through dimensionality reduction of large-scale gene expression data.

The availability of parallel, high-throughput biological experiments that simultaneously monitor thousands of cellular observables provides an opportunity for investigating cellular behavior in a highly quantitative manner at multiple levels of resolution. One challenge to more fully exploit new experimental advances is the need to develop algorithms to provide an analysis at each of the relevant levels of detail. Here, the data analysis method non-negative matrix factorization (NMF) has been applied to the analysis of gene array experiments. Whereas current algorithms identify relationships on the basis of large-scale similarity between expression patterns, NMF is a recently developed machine learning technique capable of recognizing similarity between subportions of the data corresponding to localized features in expression space. A large data set consisting of 300 genome-wide expression measurements of yeast was used as sample data to illustrate the performance of the new approach. Local features detected are shown to map well to functional cellular subsystems. Functional relationships predicted by the new analysis are compared with those predicted using standard approaches; validation using bioinformatic databases suggests predictions using the new approach may be up to twice as accurate as some conventional approaches.

Algorithms↗
PubMed2003

Characterization of a ComE3 homologue essential for DNA transformation in Helicobacter pylori.

To find genes involved in natural competence in Helicobacter pylori, we used a bioinformatics database search and found two transformation-related open reading frames (ORFs): a comE3 homologue (HP1361 ORF) of Bacillus subtilis and a comL homologue (HP1378 ORF) of Neisseria gonorrhoeae. We failed to obtain an HP1378 ORF knockout mutant, while an HP1361 ORF knockout mutant was obtained by transposon shuttle mutagenesis. The DNA transformation abilities of both natural transformation and electroporation were severely impaired (frequency, <10(-9)) in the HP1361(-) mutant. Complementation with a pHel2 vector carrying the HP1361 ORF restored the capabilities of natural competence (to a frequency of 4.21 x 10(-7)) and electroporation (to 3.62 x 10(-7)). The HP1361(-) mutant showed impairment in DNA binding and uptake. The results suggest that HP1361 is a comE3 homologue and is required for DNA binding and uptake during DNA transformation.

Amino Acid Sequence↗
PubMed2004

Use of an oligonucleotide array for laboratory diagnosis of bacteria responsible for acute upper respiratory infections.

We developed a diagnostic array of oligonucleotide probes targeting species-specific variable regions of the genes encoding topoisomerases GyrB and ParE of respiratory bacterial pathogens. Suitable broad-range primer sequences were designed based on alignment of gyrB/parE sequences from nine different bacterial species. These species included Corynebacterium diphtheriae, Fusobacterium necrophorum, Haemophilus influenzae, Legionella pneumophila, Moraxella catarrhalis, Mycoplasma pneumoniae, Staphylococcus aureus, Streptococcus pneumoniae, and Streptococcus pyogenes. Specific probe sequences were selected by comparative analysis against the European Bioinformatics Database, as well as gyrB/parE sequences generated for this study. To verify specificity, at least six initial oligonucleotide probe sequences per bacterial species were tested by hybridization on a solid glass support using culture collection strains as templates. Finally, three oligonucleotide probes per bacterial species were utilized to examine 65 middle ear fluid and 29 throat swab samples. The sensitivities of the developed assay compared to classic culture from middle ear fluid samples for H. influenzae, M. catarrhalis, and S. pneumoniae were 96 (93 for culture), 73 (93 for culture), and 100% (78% for culture), respectively. No cross-reactivity with bacterial species belonging to the normal oral flora was observed when the 29 throat swab samples were studied. The sensitivity of the assay to detect S. pyogenes from these samples was 93% (80% for culture). These results provide a proof of concept for the diagnostic use of microarray technology based on broad-range topoisomerase gene amplification, followed by hybridization and specific detection of bacterial species.

Bacterial Infections↗
PubMed2003

Nonsyndromic seizure disorders: epilepsy and the use of the internet to advance research.

The progress in understanding the genetics of nonsyndromic epilepsy is the direct result of dramatic advances made by the Human Genome Project. The development of thousands of precisely mapped genetic markers and the nearly complete sequencing of the entire human genome in 2001 allowed genetic researchers in epilepsy to identify many loci and genes as causal in inherited idiopathic epilepsy. This substantial increase in information has required the development of accurate and online bioinformatic databases. Only the Internet can enable such large amounts of precise DNA sequence information to be transferred to researchers. Along with the construction of these databases has been the development of efficient search algorithms for specific DNA sequences and genetic information. This article summarizes the effect that this burst of new genomic information has had on research aimed at discovering the underlying genetic factors for nonsyndromic epilepsy. Many of the web sites important to epilepsy gene discovery are listed and discussed in this article, including sites with extensive information on genetic markers, genetic analysis, gene sequence, gene expression, gene mutations, and DNA sequence variation. Continued acquisition of information on naturally occurring DNA sequence variants will greatly help research directed towards understanding the genetic susceptibility of the common, nonsyndromic epilepsies and will lead to the promise of personalized medicine.

Databases, Factual↗
PubMed2005

Proteomic identification of oxidatively modified retinal proteins in a chronic pressure-induced rat model of glaucoma.

PURPOSE: Based on the evidence of an amplified production of reactive oxygen species (ROS) during glaucomatous neurodegeneration, proteomic analysis was performed to determine oxidative modification of retinal proteins after experimental elevation of intraocular pressure (IOP). METHODS: IOP elevation was induced in rats by hypertonic saline injections into episcleral veins. Protein expression was determined by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) of retinal protein lysates obtained from eyes matched for the cumulative IOP exposure and axon loss. To determine protein oxidation levels, protein carbonyls were detected through 2D-oxyblot analysis of 2,4-dinitrophenylhydrazine (DNPH)-treated samples using an anti-DNP antibody. For identification of oxidized proteins, peptide masses were analyzed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/MS) and liquid chromatography-tandem mass spectrometry (LC/MS/MS). In addition to use of different engines in a bioinformatic database search and performance of peptide sequencing and 2D-Western blot analysis for confirmation of the identified proteins, immunohistochemistry was used for further validation of the proteomic findings. RESULTS: Comparison of 2D-oxyblots with Coomassie Blue-stained 2D-gels revealed that approximately 60 protein spots obtained with retinal protein lysates from ocular hypertensive eyes (of >400 spots) exhibited protein carbonyl immunoreactivity, which reflects oxidatively modified proteins. There was a significant increase in anti-carbonyl reactivity in individual protein spots obtained with retinal protein lysates from ocular hypertensive eyes compared with the control (P < 0.01). The identified proteins through peptide mass fingerprinting and peptide sequencing included glyceraldehyde-3-phosphate dehydrogenase, a glycolytic enzyme; HSP72, a stress protein; and glutamine synthetase, an excitotoxicity-related protein. Immunolabeling of retina sections with specific antibodies demonstrated cellular localization of these proteins as well as retinal distribution of the increased protein carbonyl immunoreactivity in ocular hypertensive eyes. CONCLUSIONS: The findings of this in vivo study provide novel evidence for oxidative modification of many retinal proteins in ocular hypertensive eyes and identify three specific targets of retinal protein oxidation in these eyes, thereby supporting the association of oxidative damage with neurodegeneration in glaucoma. By using a proteomic approach, this study also exemplifies that proteomics provide a very promising way to elucidate pathogenic mechanisms in glaucoma at the protein level.

Animals↗
PubMed2004

Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium.

BACKGROUND: Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. RESULTS: Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using tissue microarrays to demonstrate a significant association between downregulated protein expression and tumorigenesis, a process that is the reverse of what is seen in the presence of Selenium. CONCLUSIONS: Thus the outlined process demonstrates similar baseline and selenium induced gene expression profiles between rat and human prostate cancers, and provides a method for identifying testable functional pathways for the action of Selenium's chemopreventive properties in prostate cancer.

Adenocarcinoma↗
PubMed2006

Computational and experimental analysis identifies Arabidopsis genes specifically expressed during early seed development.

BACKGROUND: Plant seeds are complex organs in which maternal tissues, embryo and endosperm, follow distinct but coordinated developmental programs. Some morphogenetic and metabolic processes are exclusively associated with seed development. The goal of this study was to explore the feasibility of incorporating the available online bioinformatics databases to discover Arabidopsis genes specifically expressed in certain organs, in our case immature seeds. RESULTS: A total of 11,032 EST sequences obtained from isolated immature seeds were used as the initial dataset (178 of them newly described here). A pilot study was performed using EST virtual subtraction followed by microarray data analysis, using the Genevestigator tool. These techniques led to the identification of 49 immature seed-specific genes. The findings were validated by RT-PCR analysis and in situ hybridization. CONCLUSION: We conclude that the combined in silico data analysis is an effective data mining strategy for the identification of tissue-specific gene expression.

Arabidopsis↗
PubMed2004

Multi-line split DNA synthesis: a novel combinatorial method to make high quality peptide libraries.

BACKGROUND: We developed a method to make a various high quality random peptide libraries for evolutionary protein engineering based on a combinatorial DNA synthesis. RESULTS: A split synthesis in codon units was performed with mixtures of bases optimally designed by using a Genetic Algorithm program. It required only standard DNA synthetic reagents and standard DNA synthesizers in three lines. This multi-line split DNA synthesis (MLSDS) is simply realized by adding a mix-and-split process to normal DNA synthesis protocol. Superiority of MLSDS method over other methods was shown. We demonstrated the synthesis of oligonucleotide libraries with 1016 diversity, and the construction of a library with random sequence coding 120 amino acids containing few stop codons. CONCLUSIONS: Owing to the flexibility of the MLSDS method, it will be able to design various "rational" libraries by using bioinformatics databases.

Amino Acid Sequence↗
PubMed2006

Identification of novel brain biomarkers.

BACKGROUND: The diagnosis of diseases leading to brain injury, such as stroke, Alzheimer disease, and Parkinson disease, can often be problematic. In this study, we pursued the discovery of biomarkers that might be specific and sensitive to brain injury. METHODS: We performed gene array analyses on a mouse model to look for biomarkers that are both preferentially and abundantly produced in the brain. Via bioinformatics databases, we identified the human homologs of genes that appeared abundant in brain but not in other tissues. We then confirmed protein production of the genes via Western blot of various tissue homogenates and assayed for one of the markers, visinin-like protein 1 (VLP-1), in plasma from patients after ischemic stroke. RESULTS: Twenty-nine genes that were preferentially and abundantly expressed in the mouse brain were identified; of these 29 genes, 26 had human homologs. We focused on 17 of these genes and their protein products on the basis of their molecular characteristics, novelty, and/or availability of antibodies. Western blot showed strong signals in brain homogenates for 13 of these proteins. Tissue specificity was tested by Western blot on a human tissue array, and a sensitive and quantitative sandwich immunoassay was developed for the most abundant gene product observed in our search, VLP-1. VLP-1 was detected in plasma of patients after stroke and in cerebrospinal fluid of a rat model of stroke. CONCLUSIONS: The use of relative mRNA production appears to be a valid method of identifying possible biomarkers of tissue injury. The tissue specificity suggested by gene expression was confirmed by Western blot. One of the biomarkers identified, VLP-1, was increased in a rat model of stroke and in plasma of patients after stroke. More extensive, prospective studies of the candidate biomarkers identified appear warranted.

Animals↗
PubMed2005

A streamlined approach to high-throughput proteomics.

Proteomics has rapidly become an important tool for life science research, allowing the integrated analysis of global protein expression from a single experiment. To accommodate the complexity and dynamic nature of any proteome, researchers must use a combination of disparate protein biochemistry techniques, often a highly involved and time-consuming process. Whilst highly sophisticated, individual technologies for each step in studying a proteome are available, true high-throughput proteomics that provides a high degree of reproducibility and sensitivity has been difficult to achieve. The development of high-throughput proteomic platforms, encompassing all aspects of proteome analysis and integrated with genomics and bioinformatics technology, therefore represents a crucial step for the advancement of proteomics research. ProteomIQ (Proteome Systems) is the first fully integrated, start-to-finish proteomics platform to enter the market. Sample preparation and tracking, centralized data acquisition and instrument control, and direct interfacing with genomics and bioinformatics databases are combined into a single suite of integrated hardware and software tools, facilitating high reproducibility and rapid turnaround times. This review will highlight some features of ProteomIQ, with particular emphasis on the analysis of proteins separated by 2D polyacrylamide gel electrophoresis.

Automation↗
PubMed2026

Active components and potential mechanisms of Wuzhuyu decoction in the treatment of ethanol-induced acute gastric mucosal injury: a network pharmacology and experimental verification.

OBJECTIVE: To investigate the underlying mechanisms and active components of Wuzhuyu decoction (, WD) in alleviating ethanol-induced acute gastric mucosal injury (GMI) using an integrated approach of network pharmacology and experimental verification. METHODS: Sprague-Dawley rats were randomly divided into six groups: control (Con), model (Mod), bismuth potassium citrate (BPC), WD at low (WD-L), medium (WD-M), and high (WD-H) doses. Following seven days of continuous intragastric administration of the respective treatments, an ethanol-induced gastric mucosal injury model was established in all groups except the control group by oral gavage of anhydrous ethanol. The gastric mucosal injury index was evaluated, and pathological changes were assessed viahematoxylin and eosin (HE) staining. Levels of tumor necrosis factor-alpha (TNF-&#x3b1;), interleukin-1 beta (IL-1&#x3b2;), malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) were measured by enzyme-linked immunosorbent assay (ELISA). The chemical composition was identified by ultra-performance liquid chromatography-tandem mass spectrometry. Active compounds were screened using the Swiss-absorption, distribution, metabolism, and excretion database, and their potential targets were predicted using the Swiss Target Prediction database and bioinformatics annotation database for molecular mechanism. Simultaneously, disease targets related to GMI were retrieved from the online mendelian inheritance in man and GeneCards databases. A protein-protein interaction (PPI) network was constructed, and functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed using the Metascape database. Key predictions from the network pharmacology analysis were subsequently verified through animal experiments. Protein expression levels of B-cell lymphoma-2 (Bcl-2), Bcl-2-associated X protein (Bax), Cleaved Caspase-3, and Cleaved Caspase-9 were analyzed by Western blot. Finally, molecular docking was performed using AutoDock Vina to investigate the interactions between the active components and core targets. RESULTS: WD treatment significantly reduced the gastric mucosal injury index and the levels of TNF-&#x3b1;, IL-1&#x3b2;, MDA, while it increased the activities of SOD and GSH-Px. Histopathological examination revealed marked improvement in gastric tissue morphology. A total of 145 compounds were identified in WD. Network pharmacology analysis identified 440 overlapping targets between WD and GMI. GO and KEGG enrichment analyses highlighted the apoptosis signaling pathway as a key mechanism for WD's protective effect against ethanol-induced GMI. Experimental validation demonstrated that WD treatment reduced the apoptosis of gastric mucosal epithelial cells, promoted the expression of Bcl-2, and inhibited the expression of Bax, Cleaved Caspase-3 and Cleaved Caspase-9. Molecular docking results indicated that dehydroevodiamine, rutaecarpine, evodiamine, hexahydrocurcumin, and isorhamnetin are potential active components in WD that contribute to the inhibition of apoptosis. CONCLUSIONS: WD alleviates ethanol-induced acute GMI, at least in part, by inhibiting the apoptosis. The primary active components responsible for this effect are dehydroevodiamine, rutaecarpine, evodiamine, hexahydrocurcumin, and isorhamnetin.

Drugs, Chinese Herbal↗
PubMed2006

Bringing kinases into focus: efficient drug design through the use of chemogenomic toolkits.

The study of protein target families, as opposed to single targets, has become a very powerful tool in chemogenomics-led drug discovery. By integrating comprehensive chemoinformatics and bioinformatics databases with customised analytical tools, a 'Toolkit' approach for the target family is possible, thus allowing predictions of the ligand class, affinity, selectivity and likely off-target issues to be made for the guidance of the medicinal chemist. In this review, we highlight the development and application of the Toolkit approach to the protein kinase superfamily, drawing on examples from lead optimisation studies and the design of focused libraries for lead discovery.

Amino Acid Sequence↗