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Multi-sampling allows intra-tumoral heterogeneity querying and vulnerability profiling in glioblastoma.

BACKGROUND: Glioblastoma (GBM) remains a devastating cancer with limited treatment options, largely due to its heterogeneity. While supramaximal resection has recently provided survival benefits, therapeutic profiling of different tumor compartments, particularly its infiltrative edge remains largely unexplored. METHODS: Here, we leveraged magnetic resonance imaging (MRI)-guided multi-sampling, collecting 2 cores and 2 margins per case, to query GBM heterogeneity. Whole-exome and RNA-seq with drug testing in two patient-derived 3D models were used to reveal similarities and differences in genomic and transcriptomic makeups, cellular compositions, and drug responses across cores and margins. Bioinformatics interrogations further identified response biomarkers. RESULTS: Mutation analysis showed that oncogenes exhibited a higher degree of spatial heterogeneity than tumor suppressor genes, regardless of MRI status. While the mesenchymal transcriptional subtype with extracellular matrix remodeling, stress response, and immune programs were preferentially enriched in enhancing cores, proneural tumors with neurological processes favored non-enhancing margins. Using a 15-drug GBM-targeted panel, ERK (ulixertinib) and PI3K pathway (paxalisib, CC-115) inhibitors showed preferential efficacy in enhancing cores and non-enhancing margins, respectively. The anti-apoptosis, pan-Bcl2 agent navitoclax and the epigenetic drug trotabresib represented the most effective, tumor-wide monotherapies. Importantly, drug combinations generally outperformed single agents across all regions. CONCLUSIONS: This work demonstrates the regional heterogeneity of therapeutic vulnerabilities in GBM ex vivo, showing various drugs with tumor-wide or MRI-enhancement informed activity. These findings offer preclinical bases of numerous monotherapies and drug combinations for future clinical trial design.

Humans↗

Molecular genetics and structural genomics of the human protein kinase C gene module.

BACKGROUND: Protein kinase C (PKC) has become a major focus among cell biologists interested in second-messenger signal transduction and much has been learned about differences in the cellular localization and function of its different isotypes. In this study we systematically address the genomic locations and gene structures of the human PKC gene module. RESULTS: We first carried out fine chromosomal mapping of all nine PKC genes by fluorescence in situ hybridization (FISH), using cosmid and BAC probes. The PKC genes are found to be dispersed throughout the genome, and in some positions distinct from those previously reported: PKCalpha is at 17q24, PKCbeta at 16p12, PKCgamma at 19q13.4, PKCdelta at 3p21.2, PKCepsilon at 2p21, PKCzeta at 1p36.3, PKCeta at 14q22-23, PKCtheta; at 10p15 and PKCiota at 3q26. For PKCiota, an additional FISH signal mapped on Xq21.3 revealed a pseudogene (derived by retrotransposition). PKCgamma, zeta, and theta; are found to map to the most distal positions on the chromosomes, potentially implicating telomere position effects in their expression. Using the complete human genome draft sequence and bioinformatics tools, we then carried out a systematic analysis of PKC gene structure, including determination of the occurrence of single-nucleotide polymorphisms corresponding to the PKC loci. CONCLUSION: This resource of genomic information now facilitates investigation of the PKC gene module in structural chromosomal abnormalities and human disease locus mapping studies.

Alternative Splicing↗

[Identification and analysis of a mouse gene homologous to human hepatitis B virus pre-S1 protein-binding protein using the bioinformatics method].

OBJECTIVE: To clone and identify the mouse gene homologous to human hepatitis B virus (HBV) pre-S1 protein-binding protein (PS1BP). METHODS: The human PS1BP cDNA sequence was used as the reference sequence to search homologous mouse cDNA sequence from GenBank established by National Center for Biotechnology (NCBI), National Institute of Health (NIH), for its homologous cDNA sequences of mouse by BLASTn tool. The characteristics of mouse PS1BP protein primary structure were predicted by online software. Finally the genomic DNA structure of mouse PS1BP was deduced and compared. RESULTS: The mouse PS1BP was identified and consisted of 1455 nt, coding a protein of 484 aa. The identity of human and mouse PS1BP protein is 84.92% (411/484). The genomic DNA of mouse PS1BP consisted of 3 exons and 2 introns. CONCLUSION: The identification and characterization of mouse PS1BP cDNA and genomic DNA pave a way for further study of their structures and functions.

Amino Acid Sequence↗

Combining bioinformatics resources for the structural modelling of eukaryotic metabolic networks.

The architecture of the cellular metabolic network is almost completely available from several databases. This has paved the way for computational analyses. Whereas kinetic modelling is still restrained to small metabolic sub-systems for which enzyme-kinetic details are known, so-called structural modelling techniques can be applied to complete metabolic networks even if the kinetics and regulation of the underlying enzymes is still unknown. Structural modelling requires detailed information on the presence of metabolic enzymes in a specific cell type of interest and the thermodynamics of the reactions, determining their direction under cellular conditions. If compartments are distinguished the sub-cellular compartmentation of reactions and enzymes and the membrane transporters exchanging metabolites between cellular compartments must be included. All this information cannot be taken from a single data base but has to be compiled from various Bioinformatics resources. Here we present an approach towards the organization of Bioinformatics data that enables the flux-balance analysis of comprehensive compartmentalized metabolic networks of eukaryotic cells with special focus on human hepatocytes.

Aspartate Aminotransferases↗

Identification of a novel, putative cataract-causing allele in CRYAA (G98R) in an Indian family.

PURPOSE: The aim of the present study was to investigate the molecular basis underlying a nonsyndromic presenile autosomal dominant cataract in a three-generation pedigree. The phenotype was progressive from a peripheral ring-like opacity to a total cataract with advancing age from teenage to adulthood. The visual impairment started as problem in distant vision at the age of 16 years, to diminishing vision by the age of 24. METHODS: Clinical interventions included complete ophthalmological examination, a collection of case history, and pedigree details. Blood samples were collected from available family members irrespective of their clinical status. A functional candidate gene approach was employed for PCR screening and sequencing of the exons and their flanking regions of CRYGC, CRYGD, and CRYAA genes. For structural consequences of the mutated alphaA-crystallin we used the bioinformatics tool of the ExPASy server. RESULTS: Sequence analysis of CRYGC and CRYGD genes excluded possible causative mutations but identified known polymorphisms. Sequencing of the exons of the CRYAA gene identified a sequence variation in exon 2 (292 G->A) with a substitution of Gly to Arg at position 98. All three affected members revealed this change but it was not observed in the unaffected father or sister. The putative mutation obliterated a restriction site for the enzyme BstDSI. The same was checked in controls representing the general population of the same ethnicity (n=30) and of randomly selected DNA samples from ophthalmologically normal individuals from the population-based KORA S4 study (n=96). Moreover, the Gly at position 98 is highly conserved throughout the animal kingdom. For the mutant protein, the isoelectric point was raised from pH 5.77 to 5.96. Moreover, an extended alpha-helical structure is predicted in this region. CONCLUSIONS: The G98R mutation segregates only in affected family members and is not seen in representative controls. It represents very likely the fourth dominant cataract-causing allele in CRYAA. In all reported alleles the basic amino acid Arg is involved, suggesting the major importance of the net charge of the alphaA-crystallin for functional integrity in the lens.

Adult↗

BRIGEP--the BRIDGE-based genome-transcriptome-proteome browser.

The growing amount of information resulting from the increasing number of publicly available genomes and experimental results thereof necessitates the development of comprehensive systems for data processing and analysis. In this paper, we describe the current state and latest developments of our BRIGEP bioinformatics software system consisting of three web-based applications: GenDB, EMMA and ProDB. These applications facilitate the processing and analysis of bacterial genome, transcriptome and proteome data and are actively used by numerous international groups. We are currently in the process of extensively interconnecting these applications. BRIGEP was developed in the Bioinformatics Resource Facility of the Center for Biotechnology at Bielefeld University and is freely available. A demo project with sample data and access to all three tools is available at https://www.cebitec.uni-bielefeld.de/groups/brf/software/brigep/. Code bundles for these and other tools developed in our group are accessible on our FTP server at ftp.cebitec.uni-bielefeld.de/pub/software/.

Bacterial Proteins↗

Clinical proteomics and biomarker discovery.

Early detection of disease generally provides much-improved outcomes by a definitive medical procedure or through lifestyle modification along with specific medical management strategies. For serum biomarkers, which are central to the diagnosis of many diseases, to become truly useful sentinels of pathogenesis, their sensitivity and specificity in both early detection and recurrence monitoring must be improved. Currently, the detection and monitoring of disease markers is based on solitary proteins, and this approach is not always reliable. New classes of biomarkers derived from mass spectroscopy analysis of the low molecular weight proteome have shown improved abilities in the early detection of disease and hence in patient risk stratification and outcome. The development of a modular platform technology with sufficient flexibility and design abstractions allowing for concurrent experimentation, test, and refinement will help speed the progress of mass spectroscopy-derived proteomic pattern-based diagnostics from the scientific laboratory to the medical clinic. For acceptance by scientists, physicians, and regulatory personnel, new bioinformatic tools are essential system components for data management, analysis, and intuitive display of these new and complex data. Clinically engineered mass spectroscopy systems are essential for the further development and validation of multiplexed biomarkers that have shown tremendous promise for the early detection of disease.

Biomarkers↗

Apply innovative technologies to explore cancer genome.

PURPOSE OF REVIEW: Molecular genetic alterations characterize the development of human cancer. Recent advances in molecular genetic technology and the success of the human genome project have empowered investigators with new tools in dissecting the cancer genome for discovery of new cancer-associated genes. The purpose of this review is to highlight the emerging molecular genetic methodologies and summarize their principles, applications, and potential technical challenges. The critical issue in sample preparation and a strategy that combines different molecular techniques to facilitate the identification of novel cancer-associated genes will be discussed. RECENT FINDINGS: Digital karyotyping and array-based techniques including array comparative genomic hybridization and representational oligonucleotide microarray analysis have been recently developed to study the genomic landscape in human cancer. These innovations provide tools to quantitatively measure DNA copy number changes in cancer and to map those changes directly onto the human genome. Digital karyotyping is based on counting the sequence tags that are distributed in the human genome and thus, it provides a digital readout to precisely outline the amplified and deleted chromosomal regions. Array-based technologies, on the other hand, compare the content of cancer and reference genomes followed by localizing the amplified or deleted signals in chromosomal regions using an array hybridization technique. In addition, a high-throughput mutational analysis platform has been available for a large-scale mutational analysis by using an automated capillary sequencing device and sophisticated bioinformatic tools. A number of examples have demonstrated the promise of these new molecular genetic approaches in identifying several potential new oncogenes and tumor suppressors. SUMMARY: As compared with conventional cytogenetics methods, digital karyotyping, array comparative genomic hybridization, and representational oligonucleotide microarray analysis provide an unprecedented mapping resolution that allows a precise localization of the amplified and deleted chromosomal regions. These technologies can be combined with gene expression profiling and high-throughput mutational analysis to facilitate the search for new cancer-associated genes. It is expected that applying these new technologies will lead to discovery of a host of novel oncogenes and tumor suppressors, which will have a significant impact in our understanding of tumorigenesis and in the clinical management of cancer patients.

Cytogenetics↗

NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes.

Microbiologists conducting surveys of bacterial and archaeal diversity often require comparative alignments of thousands of 16S rRNA genes collected from a sample. The computational resources and bioinformatics expertise required to construct such an alignment has inhibited high-throughput analysis. It was hypothesized that an online tool could be developed to efficiently align thousands of 16S rRNA genes via the NAST (Nearest Alignment Space Termination) algorithm for creating multiple sequence alignments (MSA). The tool was implemented with a web-interface at http://greengenes.lbl.gov/NAST. Each user-submitted sequence is compared with Greengenes' 'Core Set', comprising approximately 10,000 aligned non-chimeric sequences representative of the currently recognized diversity among bacteria and archaea. User sequences are oriented and paired with their closest match in the Core Set to serve as a template for inserting gap characters. Non-16S data (sequence from vector or surrounding genomic regions) are conveniently removed in the returned alignment. From the resulting MSA, distance matrices can be calculated for diversity estimates and organisms can be classified by taxonomy. The ability to align and categorize large sequence sets using a simple interface has enabled researchers with various experience levels to obtain bacterial and archaeal community profiles.

Algorithms↗

Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis.

Fold recognition was applied to the systematic analysis of the all sequences encoded by the genome of Mycoplasma tuberculosis H37Rv in order to identify new putative glycosyltransferases. The search was conducted against a library composed of all known crystal structures of glycosyltransferases and some related proteins. A clear relationship appeared between some sequences and some folds. It appears necessary to complete the fold recognition approach with a statistical approach in order to identify the relevant data above the background noise. Exploratory data analysis was carried out using several methods. Analytical methods confirmed the validity of the approach, while predictive methods, although very preliminary in the present case, allowed for identifying a number of sequences of interest that should be further investigated. This new approach of combining bioinformatics and chemometrics appears to be a powerful tool for analysis of newly sequenced genomes. Its application to glycobiology is of great interest.

Computational Biology↗

Complete Genome Sequencing of Occult Hepatitis B Virus in Hemodialysis Patients Reveals Subgenotype D2 and Immune Escape Mutations in Bangladesh.

Hepatitis B virus (HBV) remains a major global health concern, and occult HBV infection (OBI) presents significant diagnostic and clinical challenges, particularly among hemodialysis (HD) patients. This study is aimed at characterizing complete HBV genomes from maintenance HD patients with OBI in Bangladesh to elucidate genetic features, mutational patterns, and clinical implications. Serum samples from two HBsAg-negative HD patients were screened by ELISA and quantitative PCR. Viral DNA was amplified by PCR across four overlapping open reading frames (ORFs) and sequenced on the Illumina platform. Genome assembly, phylogenetic analysis, and mutational profiling were performed using reference datasets and bioinformatics tools. Antigenicity and hydrophilicity of HBsAg were predicted in silico. Both patients were anti-HBc and anti-HBs positive with high HBV DNA loads (2.29 × 1010 and 2.53 × 1010 copies/mL). Full-length genomes (3182 bp) were successfully sequenced and phylogenetic analysis showed both HBV genomes clustered within Genotype D, Subgenotype D2, and subtype ayw3, consistent with previously reported Bangladeshi HBV genomes. Comparative mutational analysis identified substitutions such as T1753C in the basal core promoter, C1845T in preC, and D144E within the "a" determinant of HBsAg, suggesting potential roles in vaccine escape, immune escape, and diagnostic failure. Several nonsynonymous mutations were also detected in polymerase, though none were potentially associated with antiviral resistance. Antigenicity and hydrophilicity profiles of HBsAg and its major hydrophilic region remained largely conserved. These findings demonstrate the persistence of OBI in HD patients and provide an initial indication of the need for genomic surveillance to monitor immune-escape mutations and improve HBV diagnostic strategies in endemic regions.

HBV genome sequencing↗

In silico identification of novel therapeutic targets.

The availability of the human genome sequence is a 'once in a lifetime' opportunity for scientists to uncover all possible human drug-targets. As the sequence is very large, the best way to identify new genes rapidly is by computational (in silico) methods. There are now many examples in which pharmaceutical companies have identified genes of interest initially by in silico analysis. High-throughput data-generation techniques, such as microarray analysis, are key to the generation of human genome data. Bioinformatics techniques are therefore certain to play an increasingly important role in drug discovery.

Computational Biology↗

Energy balance for analysis of complex metabolic networks.

Predicting behavior of large-scale biochemical networks represents one of the greatest challenges of bioinformatics and computational biology. Computational tools for predicting fluxes in biochemical networks are applied in the fields of integrated and systems biology, bioinformatics, and genomics, and to aid in drug discovery and identification of potential drug targets. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are promising tools for the analysis of large complex networks. Here we introduce energy balance analysis (EBA)--the theory and methodology for enforcing the laws of thermodynamics in such simulations--making the results more physically realistic and revealing greater insight into the regulatory and control mechanisms operating in complex large-scale systems. We show that EBA eliminates thermodynamically infeasible results associated with FBA.

Biophysics↗

Alternative Splicing in Mechanically Stretched Podocytes as a Model of Glomerular Hypertension.

KEY POINTS: Mechanical stretch induced over 3000 alternative splicing events in podocytes, affecting gene expression and protein abundance. Seventeen genes showed consistent splicing events across multiple analysis tools, with key isoform changes. Shroom3 and Myl6 underwent isoform switches under mechanical stretch, altering the C-terminal sequence and interaction properties of Myl6. BACKGROUND: Alterations in pre-mRNA splicing are crucial to the pathophysiology of various diseases. However, the effects of alternative splicing of mRNA on podocytes in hypertensive nephropathy are still unknown. The Sys_CARE project aimed to identify alternative splicing events involved in the development and progression of glomerular hypertension. METHODS: Murine podocytes were exposed to mechanical stretch, after which proteins and mRNA were analyzed by proteomics, RNA sequencing, and several bioinformatic alternative splicing tools. RESULTS: Using transcriptomic and proteomic analysis, we identified significant changes in gene expression and protein abundance because of mechanical stretch. RNA-Seq identified over 3000 alternative spliced genes after mechanical stretch, including all types of alternative splicing events. Among these, 17 genes exhibited an alternative splicing event across four different splicing analysis tools. From this group, we focused on Myl6, a component of the myosin protein complex, and Shroom3, an actin-binding protein essential for podocyte function. We identified two Shroom3 isoforms with significant expression changes under mechanical stretch, which was validated by quantitative RT-PCR and in situ hybridization. In addition, we observed an expression switch of two Myl6 isoforms after mechanical stretch, accompanied by an alteration in the C-terminal amino acid sequence. CONCLUSIONS: A comprehensive RNA-Seq analysis of mechanically stretched podocytes identified novel potential podocyte-specific biomarkers and highlighted significant alternative splicing events, notably in the mRNA of Shroom3 and Myl6.

podocyte↗

An interactive visualization tool to explore the biophysical properties of amino acids and their contribution to substitution matrices.

BACKGROUND: Quantitative descriptions of amino acid similarity, expressed as probabilistic models of evolutionary interchangeability, are central to many mainstream bioinformatic procedures such as sequence alignment, homology searching, and protein structural prediction. Here we present a web-based, user-friendly analysis tool that allows any researcher to quickly and easily visualize relationships between these bioinformatic metrics and to explore their relationships to underlying indices of amino acid molecular descriptors. RESULTS: We demonstrate the three fundamental types of question that our software can address by taking as a specific example the connections between 49 measures of amino acid biophysical properties (e.g., size, charge and hydrophobicity), a generalized model of amino acid substitution (as represented by the PAM74-100 matrix), and the mutational distance that separates amino acids within the standard genetic code (i.e., the number of point mutations required for interconversion during protein evolution). We show that our software allows a user to recapture the insights from several key publications on these topics in just a few minutes. CONCLUSION: Our software facilitates rapid, interactive exploration of three interconnected topics: (i) the multidimensional molecular descriptors of the twenty proteinaceous amino acids, (ii) the correlation of these biophysical measurements with observed patterns of amino acid substitution, and (iii) the causal basis for differences between any two observed patterns of amino acid substitution. This software acts as an intuitive bioinformatic exploration tool that can guide more comprehensive statistical analyses relating to a diverse array of specific research questions.

Amino Acid Sequence↗

Bioinformatics and cellular signaling.

The understanding of cellular function requires an integrated analysis of context-specific, spatiotemporal data from diverse sources. Recent advances in describing the genomic and proteomic 'parts list' of the cell and deciphering the interrelationship of these parts are described, including genome-wide location analysis, standards for microarray data analysis, and two-hybrid and mass spectrometry approaches. This information is being collected and curated in databases such as the Alliance for Cellular Signaling (AfCS) Molecule Pages, which will serve as vital tools for the reconstruction and analysis of cellular signaling networks.

Cell Physiological Phenomena↗

Squid - a simple bioinformatics grid.

BACKGROUND: BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled "Squid" that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers. RESULTS: Most distributed computing / grid solutions have complex installation procedures requiring a computer specialist, or have limitations regarding operating systems. Squid is a multi-platform, open-source program designed to "keep things simple" while offering high-end computing power for large scale applications. Squid also has an efficient fault tolerance and crash recovery system against data loss, being able to re-route jobs upon node failure and recover even if the master machine fails. Our results show that a Squid application, working with N nodes and proper network resources, can process BLAST queries almost N times faster than if working with only one computer. CONCLUSION: Squid offers high-end computing, even for the non-specialist, and is freely available at the project web site. Its open-source and binary Windows distributions contain detailed instructions and a "plug-n-play" instalation containing a pre-configured example.

Base Sequence↗

rSNP_Guide: an integrated database-tools system for studying SNPs and site-directed mutations in transcription factor binding sites.

Since the human genome was sequenced in draft, single nucleotide polymorphism (SNP) analysis has become one of the keynote fields of bioinformatics. We have developed an integrated database-tools system, rSNP_Guide (http://wwwmgs.bionet.nsc.ru/mgs/systems/rsnp/), devoted to prediction of transcription factor (TF) binding sites, alterations of which could be associated with disease phenotype. By inputting data on alterations in DNA sequence and in DNA binding pattern of an unknown TF, rSNP_Guide searches for a known TF with alterations in the recognition score calculated on the basis of TF site's sequence and consistent with the input alterations in DNA binding to the unknown TF. Our system has been tested on many relationships between known TF sites and diseases, as well as on site-directed mutagenesis data. Experimental verification of rSNP_Guide system was made on functionally important SNPs in human TDO2and mouse K-ras genes. Additional examples of analysis are reported involving variants in the human gammaA-globin (HBG1), hsp70(HSPA1A), and Factor IX (F9) gene promoters.

Animals↗