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Results for “Bioinformatics analysis”

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PubMed2005

Species-specific bacteria identification using differential mobility spectrometry and bioinformatics pattern recognition.

As bacteria grow and proliferate, they release a variety of volatile compounds that can be profiled and used for speciation, providing an approach amenable to disease diagnosis through quick analysis of clinical cultures as well as patient breath analysis. As a practical alternative to mass spectrometry detection and whole cell pyrolysis approaches, we have developed methodology that involves detection via a sensitive, micromachined differential mobility spectrometer (microDMx), for sampling headspace gases produced by bacteria growing in liquid culture. We have applied pattern discovery/recognition algorithms (ProteomeQuest) to analyze headspace gas spectra generated by microDMx to reliably discern multiple species of bacteria in vitro: Escherichia coli, Bacillus subtilis, Bacillus thuringiensis, and Mycobacterium smegmatis. The overall accuracy for identifying volatile profiles of a species within the 95% confidence interval for the two highest accuracy models evolved was between 70.4 and 89.3% based upon the coordinated expression of between 5 and 11 features. These encouraging in vitro results suggest that the microDMx technology, coupled with bioinformatics data analysis, has potential for diagnosis of bacterial infections.

Bacillus↗

PubMed2006

Current bioinformatics tools in genomic biomedical research (Review).

On the advent of a completely assembled human genome, modern biology and molecular medicine stepped into an era of increasingly rich sequence database information and high-throughput genomic analysis. However, as sequence entries in the major genomic databases currently rise exponentially, the gap between available, deposited sequence data and analysis by means of conventional molecular biology is rapidly widening, making new approaches of high-throughput genomic analysis necessary. At present, the only effective way to keep abreast of the dramatic increase in sequence and related information is to apply biocomputational approaches. Thus, over recent years, the field of bioinformatics has rapidly developed into an essential aid for genomic data analysis and powerful bioinformatics tools have been developed, many of them publicly available through the World Wide Web. In this review, we summarize and describe the basic bioinformatics tools for genomic research such as: genomic databases, genome browsers, tools for sequence alignment, single nucleotide polymorphism (SNP) databases, tools for ab initio gene prediction, expression databases, and algorithms for promoter prediction.

Computational Biology↗

PubMed2006

Candidate genes affecting Drosophila life span identified by integrating microarray gene expression analysis and QTL mapping.

The current increase in life expectancy observed in industrialized societies underscores the need to achieve a better understanding of the aging process that could help the development of effective strategies to achieve healthy aging. This will require not only identifying genes involved in the aging process, but also understanding how their effects are modulated by environmental factors, such as dietary intake and life style. Although the human genome has been sequenced, it may be impractical to study humans or other long-lived organisms to gain a mechanistic understanding about the aging process. Thus, short-lived animal models are essential to identifying the mechanisms and genes that affect the rate and quality of aging as a first step towards identifying genetic variants in humans. In this study, we investigated gene expression changes between two strains of Drosophila (Oregon and 2b) for which quantitative trait loci (QTLs) affecting life span were identified previously. We collected males and females from both strains at young and old ages, and assessed whole genome variation in transcript abundance using Affymetrix GeneChips. We observed 8217 probe sets with detectable transcripts. A total of 2371 probe sets, representing 2220 genes, exhibited significant changes in transcript abundance with age; and 839 probe sets were differentially expressed between Oregon and 2b. We focused on the 359 probe sets (representing 354 genes) that exhibited significant changes in gene expression both with age and between strains. We used these genes to integrate the analysis of microarray gene expression data, bioinformatics, and the results of genetic mapping studies reported previously, to identify 49 candidate genes and four pathways that could potentially be responsible for regulating life span and involved in the process of aging in Drosophila and humans.

Aging↗

PubMed2026

Protocol for haplotype-resolved structural variant detection via long-read sequencing using cuteHap.

Long-read sequencing technologies have revolutionized human genome exploration at an unparalleled resolution, particularly facilitating the analysis of structural variation (SV) at haplotype resolution. Here, we present a protocol for using cuteHap, a robust framework for haplotype-aware SV detection through phased alignment reads generated by diverse long-read sequencing platforms. We describe procedures for single-nucleotide variant (SNV) calling, read phasing, SV calling, and genotyping. We also establish a benchmarking pipeline to evaluate the detected SV callsets. For complete details on the use and execution of this protocol, please refer to Cao et al.1.

Bioinformatics↗

PubMed2004

Microarray transfection analysis of transcriptional regulation by cAMP-dependent protein kinase.

A wide variety of bioinformatic tools have been described to characterize potential transcriptional regulatory mechanisms based on genomic sequence analysis and microarray hybridization studies. However, these regulatory mechanisms are still experimentally verified using transient transfection methods. Current transfection methods are limited both by their large scale and by the low level of efficiency for certain cell types. Our goals were to develop a microarray-based transfection method that could be optimized for different cell types and that would be useful in reporter assays of transcriptional regulation. Here we describe a novel transfection method, termed STEP (surface transfection and expression protocol), which employs microarray-based DNA transfection of adherent cells in the functional analysis of transcriptional regulation. In STEP, recombinant proteins with biological activities designed to enhance transfection are complexed with expression vector DNAs prior to spotting on microscope slides. The recombinant proteins used in STEP complexes can be varied to increase the efficiency for different cell types. We demonstrate that STEP efficiently transfects both supercoiled plasmids and PCR-generated linear expression cassettes. A co-transfection assay using effector expression vectors encoding the cAMP-dependent protein kinase (PKA), as well as reporter vectors containing PKA-regulated promoters, showed that STEP transfection allows detection and quantitation of transcriptional regulation by this protein kinase. Because bioinformatic studies often result in the identification of many putative regulatory elements and signaling pathways, this approach should be of utility in high-throughput functional genomic studies of transcriptional regulation.

Animals↗

PubMed2003

Mining the biomedical literature in the genomic era: an overview.

The past decade has seen a tremendous growth in the amount of experimental and computational biomedical data, specifically in the areas of genomics and proteomics. This growth is accompanied by an accelerated increase in the number of biomedical publications discussing the findings. In the last few years, there has been a lot of interest within the scientific community in literature-mining tools to help sort through this abundance of literature and find the nuggets of information most relevant and useful for specific analysis tasks. This paper provides a road map to the various literature-mining methods, both in general and within bioinformatics. It surveys the disciplines involved in unstructured-text analysis, categorizes current work in biomedical literature mining with respect to these disciplines, and provides examples of text analysis methods applied towards meeting some of the current challenges in bioinformatics.

Biomedical Research↗

PubMed2005

New bioinformatics tools for viral genome analyses at Viral Bioinformatics--Canada.

Viruses are much smaller than prokaryotes and eukaryotes, and it is now practical to sequence closely related members of virus families, strains, or even different isolates recovered during the course of an outbreak. However, comparative analysis of viral genomes requires the development of novel bioinformatics tools that allow us to align, edit, compare and interact with these genomes at all levels, from whole genome, to gene family, to single nucleotide polymorphisms. Comparative viral genomics can lead to the identification of the core characteristics that define a virus family, as well as the unique properties of viral species or isolates that contribute to variations in pathogenesis. This paper describes a number of tools, mainly developed for Viral Bioinformatics--Canada, that can be used for annotation and comparative genomic analysis of poxviruses. Nonetheless, these tools are also broadly applicable to other virus families.

Base Sequence↗

PubMed2026

Novel genetic variants identification and immune profiling in ataxia telangiectasia patients.

BACKGROUND: Ataxia telangiectasia (AT) is an autosomal recessive neurodegenerative disease. While heterozygous relatives of AT patients are known to be clinically healthy, a predisposition to various pathologies has been reported. Our aim was firstly, to further characterize the clinical features and broaden the spectrum of genetic pathogenic variants in AT patients. Secondly, we aimed to study the immune profiles of AT patients and their relatives to identify similarities or common biomarkers. METHODS: A Target Gene Sequencing for six patients suspected with AT was performed. Computational analysis was conducted to assess the pathogenicity of novel variants. The distribution of immune cells was assessed by flow cytometry in patients with AT, AT-like disorder, Friedreich ataxia, and in AT relatives. The expression pattern of candidate genes was evaluated by RT-qPCR. RESULTS: We identified and predicted the pathogenicity of novel variants in the ATM gene. Computational analysis suggested that the novel identified missense mutation could affect ATP binding pattern and ATM protein flexibility, while Alu element insertion could probably induces a premature stop codon. Furthermore, our results confirm the pathogenic effect of identified splicing mutations on the ATM transcript. Moreover, we noticed a high percentage of LTCD4 + and LTCD8 + senescent subsets in AT patients and a relative increase of the of intermediate and non-classical monocytes accompanied with a decrease of classical monocytes specifically in AT patients with truncated biallelic mutations which was intriguingly similar to the immune profile of AT parents. In addition, a difference of immune pattern was observed between AT patients with biallelic truncated mutations compared to those with at least one non-truncated mutation, with a variability intragroup. Gene expression analysis identified FOXO3, IL33 and METTL3 as putative genes that may yield clues into AT pathogenesis. CONCLUSION: Taken together, our study expands the mutational spectrum of AT disease worldwide and further characterize the immune profile of AT patients uncovering a possible difference in some immune cellular subsets related to ATM mutation type and delineate putative immune abnormalities related to ATM heterozygosity among AT parents. Furthermore, dysregulation in FOXO3, IL33 and METTL3 expression could be related to disease severity.

Humans↗

PubMed2004

Bioinformatics strategies for proteomic profiling.

Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling.

Computational Biology↗

PubMed2005

Representations of molecular pathways: an evaluation of SBML, PSI MI and BioPAX.

MOTIVATION: Analysis and simulation of pathway data is of high importance in bioinformatics. Standards for representation of information about pathways are necessary for integration and analysis of data from various sources. Recently, a number of representation formats for pathway data, SBML, PSI MI and BioPAX, have been proposed. RESULTS: In this paper we compare these formats and evaluate them with respect to their underlying models, information content and possibilities for easy creation of tools. The evaluation shows that the main structure of the formats is similar. However, SBML is tuned towards simulation models of molecular pathways while PSI MI is more suitable for representing details about particular interactions and experiments. BioPAX is the most general and expressive of the formats. These differences are apparent in allowed information and the structure for representation of interactions. We discuss the impact of these differences both with respect to information content in existing databases and computational properties for import and analysis of data.

Computational Biology↗

PubMed2001

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarrays. 22-24 January 2001, Zurich, Switzerland.

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarray technology covered the latest advances in this technology and applications in life sciences. Highlights of the meetings are reported briefly with emphasis on applications in genomics, drug discovery and molecular diagnostics. There was an emphasis on microfluidics because of the wide applications in laboratory and drug discovery. The lab-on-a-chip provides the facilities of a complete laboratory in a hand-held miniature device. Several microarray systems have been used for hybridisation and detection techniques. Oligonucleotide scanning arrays provide a versatile tool for the analysis of nucleic acid interactions and provide a platform for improving the array-based methods for investigation of antisense therapeutics. A method for analysing combinatorial DNA arrays using oligonucleotide-modified gold nanoparticle probes and a conventional scanner has considerable potential in molecular diagnostics. Various applications of microarray technology for high-throughput screening in drug discovery and single nucleotide polymorphisms (SNP) analysis were discussed. Protein chips have important applications in proteomics. With the considerable amount of data generated by the different technologies using microarrays, it is obvious that the reading of the information and its interpretation and management through the use of bioinformatics is essential. Various techniques for data analysis were presented. Biochip and microarray technology has an essential role to play in the evolving trends in healthcare, which integrate diagnosis with prevention/treatment and emphasise personalised medicines.

Computational Biology↗

PubMed2001

Characterization of differently processed forms of enolase 2 from Saccharomyces cerevisiae by two-dimensional gel electrophoresis and mass spectrometry.

Two-dimensional gel electrophoresis, bioinformatics, and mass spectrometry are key analysis tools in proteome analysis. The further characterization of post-translational modifications in gel-separated proteins relies fully on data obtained by mass spectrometric analysis. In this study, stress-induced changes in protein expression in Saccharomyces serevisiae were investigated. A total of eleven spots on a silver-stained two-dimensional (2-D) gel were identified by matrix-assisted laser desorption/ionization (MALDI) peptide mass mapping to represent C and/or N-terminal processed forms of enolase 2. The processing sites were determined by MALDI peptide mass mapping using a variety of proteolytic enzymes, by optimizing the sample preparation procedure and by specific labeling of all C-termini derived from in-gel digestion using a buffer containing 16O:18O (1:1). Out of eleven processed forms of enolase 2, six were fully characterized and the approximate processing sites identified for the remaining five.

Amino Acid Sequence↗

PubMed2004

Isolation of ESTs from cacao (Theobroma cacao L.) leaves treated with inducers of the defense response.

Pathogenic diseases represent a major constraint to the growth and yield of cacao (Theobroma cacao L.). Ongoing research on model plant systems has revealed that defense responses are activated via signaling pathways mediated by endogenous signaling molecules such as salicylic acid, jasmonic acid and ethylene. Activation of plant defenses is associated with changes in the expression of large numbers of genes. To gain a better understanding of defense responses in cacao, we have employed suppressive subtractive hybridization (SSH) cDNA libraries, macroarray hybridization analysis, high throughput DNA sequencing and bioinformatics to identify cacao genes induced by these signaling molecules. Additionally, we investigated gene activation by a phytotoxic elicitor-like protein, Nep1. We have identified a unigene set of 1,256 members, including 330 members representing genes induced during the defense response.

Cacao↗

PubMed2005

SAGE reveals expression of Wnt signalling pathway members during mouse prostate development.

To identify genes and pathways not previously implicated in the mesenchymal-epithelial (M/E) interactions that are critical for normal mouse prostate development, we constructed six serial analysis of gene expression (SAGE) libraries. Bioinformatic analyses revealed expression of various members of numerous signalling pathways and the differential expression of several members of the wingless-related MMTV integration site (Wnt) signalling pathway. This pathway has not been previously implicated in prostate development thus expression of selected Wnt pathway members in the developing prostate was confirmed by RT-qPCR. Of particular interest, an antagonist of the Wnt pathway, secreted frizzled related protein 2 (Sfrp2), was highly expressed in the early prostate libraries and down regulated at later developmental stages. The expression levels of four Wnt ligands reported to interact with Sfrp2 were, therefore, examined by RT-qPCR. We found that only Wnt4 transcripts were detectable in the developing prostate. Expression of Sfrp2 was validated using RT-qPCR and localization of Sfrp2 transcripts and protein was carried out using in situ hybridization and immunofluorescence, respectively. These studies provide the first evidence that Wnt pathway members are expressed in the developing prostate. Functional analyses are now required to establish the biological significance of this observation.

Animals↗

PubMed2004

Comparative analysis of the catalytic domain of hemorrhagic and non-hemorrhagic snake venom metallopeptidases using bioinformatic tools.

Snake venom metalloproteases (SVMPs) are a set of interesting enzymes that are one of the major components of venom affecting hemostasis. A great challenge since their discovery has been to find molecular features responsible for their hemorrhagic potency and many attempts have been made without any consistent result. Here we describe a series of comparisons between the catalytic domains of hemorrhagic and non-hemorrhagic SVMPs made with the help of bioinformatics. These involved sequence and structure-based multiple alignments, phylogenetic reconstruction, predicted physical and chemical properties, motif scanning and structural analyses. Although hemorrhagic activity seems to be complex, involving multiple factors, we found some molecular characteristics that may influence the toxic effects. Among these findings, it was possible to use a molecular surface feature to subdivide the P-I class in hemorrhagic and non-hemorrhagic SVMPs. It was also possible to suggest a role for the conserved Asp148 and Ser176 residues in the stabilization of the active site.

Animals↗

PubMed2026

Genomic and proteogenomic insights into Spontaneous Coronary Artery Dissection (SCAD): A systematic review of emerging multi-omic evidence.

BACKGROUND: Spontaneous coronary artery dissection (SCAD) is a major cause of myocardial infarction in young women without traditional cardiovascular risk factors (Hayes et al., 2018; Adlam et al., 2018 [1, 2]). Despite growing awareness, its biological underpinnings remain incompletely understood, and clinical management is largely based on observational evidence rather than mechanistic insight (Saw et al., 2014; Lettieri et al., 2015; Steg et al., 2024 [3-5]). OBJECTIVES: To systematically integrate genomic, epitranscriptomic, proteomic, and metabolomic data in order to characterize the multi-omic architecture of SCAD and identify potential biomarkers and therapeutic targets. METHODS: A systematic review was conducted in accordance with the PRISMA 2020 statement (Arbelo et al., 2023 [6]). PubMed/MEDLINE was searched for original studies investigating genomic and multi-omic features of SCAD. Data were extracted on study design, patient characteristics, identified variants, circulating biomarkers, and implicated biological pathways. Functional enrichment analysis was performed using the DAVID bioinformatics resource (Page et al., 2021 [7]). RESULTS: A total of 16 studies were included. Genome-wide association studies consistently identified susceptibility loci related to arterial structure and extracellular matrix integrity, including ADAMTSL4, PHACTR1/EDN1, LRP1, and FBN1 (Huang et al., 2009; Saw et al., 2020; Turley et al., 2020 [8-10]). Rare variant analyses further supported the role of genes involved in extracellular matrix remodeling and vascular smooth muscle cell function, including COL3A1, COL4A1/2, SMAD3, and TLN1 (Adlam et al., 2023; Turley et al., 2021, 2019; Carss et al., 2020; Zekavat et al., 2022; Wang et al., 2022 [11-16]), while ancestry-specific signals such as TSR1 variants were observed in distinct populations (Turley et al., 2023 [17]). Proteogenomic approaches linked genetic susceptibility loci to circulating proteins involved in matrix remodeling and inflammation, including cathepsin B and ECM1 (Maioli et al., 2010 [18]). Epitranscriptomic analyses identified differential microRNA expression profiles associated with vascular injury and repair pathways (Sun et al., 2019 [19]). CONCLUSIONS: SCAD is characterized by a complex, multi-layered biological architecture involving genetic susceptibility, extracellular matrix dysregulation, and vascular signaling pathways. Integration of multi-omic data provides novel insights into disease mechanisms and highlights potential biomarkers and targets for precision medicine approaches in SCAD.

Animals↗

PubMed2026

ProteoParc: A Reference Protein Database Builder for Ancient and Nonmodel Organisms.

Over the past few years, the increasing interest in analyzing the proteome of extinct and nonmodel organisms has generated a new field of research expanding the scope of proteomics. The lack of curated databases and/or molecular data from these organisms forces researchers to manually search in different public repositories for related protein sequences, either for MS/MS peptide identification or ZooMS marker annotation. This can lead to format incongruences and hinder reproducibility between studies. To address this issue, we introduce ProteoParc, a user-friendly software that builds reference databases by systematically downloading and processing protein sequences from the most widely used public repositories. The pipeline's output is a nonredundant protein database, formatted in a way to be interpreted by typical peptide identification software. Moreover, the user can adjust the database dimension and composition by applying different criteria to include only a certain number of genes or species. Thus, ProteoParc is an easy and fast, custom-made bioinformatic tool useful for future paleoproteomics analysis in ancient samples related to understudied organisms.

Databases, Protein↗

PubMed2006

Bioinformatics for study of autoimmunity.

Recent years have witnessed an explosive growth in available biological data pertaining to autoimmunity research. This includes a tremendous quantity of sequence data (biological structures, genetic and physical maps, pathways, etc.) generated by genome and proteome projects plus extensive clinical and epidemiological data. Autoimmunity research stands to greatly benefit from this data so long as appropriate strategies are available to enable full access to and utilization of this data. The quantity and complexity of this biological data necessitates use of advanced bioinformatics strategies for its efficient retrieval, analysis and interpretation. Major progress has been made in development of specialized tools for storage, analysis and modeling of immunological data, and this has led to development of a whole new field know as immunoinformatics. With advances in novel high-throughput immunology technologies immunoinformatics is transforming understanding of how the immune system functions. This paper reviews advances in the field of immunoinformatics pertinent to autoimmunity research including databases, tools in genomics and proteomics, tools for study of B- and T-cell epitopes, integrative approaches, and web servers.

Allergy and Immunology↗