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PubMed2005

Transfer RNA gene-targeted integration: an adaptation of retrotransposable elements to survive in the compact Dictyostelium discoideum genome.

Almost every organism carries along a multitude of molecular parasites known as transposable elements (TEs). TEs influence their host genomes in many ways by expanding genome size and complexity, rearranging genomic DNA, mutagenizing host genes, and altering transcription levels of nearby genes. The eukaryotic microorganism Dictyostelium discoideum is attractive for the study of fundamental biological phenomena such as intercellular communication, formation of multicellularity, cell differentiation, and morphogenesis. D. discoideum has a highly compacted, haploid genome with less than 1 kb of genomic DNA separating coding regions. Nevertheless, the D. discoideum genome is loaded with 10% of TEs that managed to settle and survive in this inhospitable environment. In depth analysis of D. discoideum genome project data has provided intriguing insights into the evolutionary challenges that mobile elements face when they invade compact genomes. Two different mechanisms are used by D. discoideum TEs to avoid disruption of host genes upon retrotransposition. Several TEs have invented the specific targeting of tRNA gene-flanking regions as a means to avoid integration into coding regions. These elements have been dispersed on all chromosomes, closely following the distribution of tRNA genes. By contrast, TEs that lack bona fide integration specificities show a strong bias to nested integration, thus forming large TE clusters at certain chromosomal loci that are hardly resolved by bioinformatics approaches. We summarize our current view of D. discoideum TEs and present new data from the analysis of the complete sequences of D. discoideum chromosomes 1 and 2, which comprise more than one third of the total genome.

Animals↗

PubMed2000

PIR: a new resource for bioinformatics.

UNLABELLED: The Protein Information Resource (PIR) has greatly expanded its Web site and developed a set of interactive search and analysis tools to facilitate the analysis, annotation, and functional identification of proteins. New search engines have been implemented to combine sequence similarity search results with database annotation information. The new PIR search systems have proved very useful in providing enriched functional annotation of protein sequences, determining protein superfamily-domain relationships, and detecting annotation errors in genomic database archives. AVAILABILITY: http://pir.georgetown.edu/. CONTACT: mcgarvey@nbrf.georgetown.edu

Animals↗

PubMed2005

Analysis of the golden Syrian hamster anterior pituitary gland proteome by ion trap mass spectrometry.

We utilized mass spectrometry (MS) and bioinformatics to investigate the proteome of the anterior pituitary gland (AP). Subcellular fractions of APs from 2-month-old male Golden Syrian hamsters were prepared for protein denaturation, treatment with trypsin and analyses utilizing micro liquid chromatography MS/MS and the database search software SEQUEST. In the nuclear, non-nuclear 100,000 x g and cytosolic fractions we identified 76, 52 and 52 different proteins, respectively. A total of 145 distinct proteins were detected. We identified growth hormone, prolactin, pro-opiomelanocortin, the alpha-subunit for the glycoprotein hormones, luteinizing hormone-beta and follicle-stimulating hormone-beta. Groups of other identified proteins included hormone processing, secretion granule associated, non-hormonal endoplasmic reticulum associated, calcium binding, protein kinase C associated histone and non-histone chromosomal material, other RNA-binding, splicing factors, heterogeneous nuclear ribonucleoproteins, helicases, lamins, microfilament associated, microtubule associated, adenosine triphosphate and guanosine diphosphate associated, keratins, lysosomal, ribosomal, enzymes in glycolysis and the tricarboxylic and pentose phosphate paths, glutathione associated, transmethylation, catabolic and unknown protein products as well as blood hemoglobins. Proteins previously not reported in the AP, such as fertility protein SP22, were identified. The proteins identified in the present study form a foundation for defining the proteome in normal adult male AP.

Animals↗

PubMed2005

In search of candidate genes critically expressed in the human endometrium during the window of implantation.

BACKGROUND: In this prospective randomized blinded clinical trial, we examined gene expression profiles of the human endometrium during the early and mid-luteal phases of the natural cycle. METHODS: An endometrial biopsy was performed on day 16 (LH +3) or on day 21 (LH +8), followed by RNA extraction and microarray analysis using an Affymetrix HG-U95A microchip. Data analysis was carried out using pairwise multiple group comparison with the significance analysis of microarrays (SAM) software. RESULTS: With a false discovery rate of 0, the analysis revealed that 107 genes were significantly and differently expressed (> or =2-fold) during the early versus the mid-luteal phase of the cycle. Forty-five of these genes have not been previously linked to endometrial receptivity. Validation of the microarray data was accomplished using semiquantitative RT-PCR. We demonstrated the presence of estrogen and progesterone response elements (ERE and PRE) by analysis of the 5'-flanking regions of a subset of differentially regulated genes. CONCLUSIONS: Using a strict bioinformatics approach of microarray data, we demonstrated significant changes in candidate genes during the transition of the early to the mid-luteal phase of the human endometrium that may have functional significance for the opening and maintenance of the window of implantation.

Adult↗

PubMed2000

The role of pattern databases in sequence analysis.

In the wake of the numerous now-fruitful genome projects, we are entering an era rich in biological data. The field of bioinformatics is poised to exploit this information in increasingly powerful ways, but the abundance and growing complexity both of the data and of the tools and resources required to analyse them are threatening to overwhelm us. Databases and their search tools are now an essential part of the research environment. However, the rate of sequence generation and the haphazard proliferation of databases have made it difficult to keep pace with developments. In an age of information overload, researchers want rapid, easy-to-use, reliable tools for functional characterisation of newly determined sequences. But what are those tools? How do we access them? Which should we use? This review focuses on a particular type of database that is increasingly used in the task of routine sequence analysis--the so-called pattern database. The paper aims to provide an overview of the current status of pattern databases in common use, outlining the methods behind them and giving pointers on their diagnostic strengths and weaknesses.

Amino Acid Motifs↗

PubMed2006

The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation.

The National Microbial Pathogen Data Resource (NMPDR) (http://www.nmpdr.org) is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of approximately 50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development.

Bacteria↗

PubMed2006

FastGroupII: a web-based bioinformatics platform for analyses of large 16S rDNA libraries.

BACKGROUND: High-throughput sequencing makes it possible to rapidly obtain thousands of 16S rDNA sequences from environmental samples. Bioinformatic tools for the analyses of large 16S rDNA sequence databases are needed to comprehensively describe and compare these datasets. RESULTS: FastGroupII is a web-based bioinformatics platform to dereplicate large 16S rDNA libraries. FastGroupII provides users with the option of four different dereplication methods, performs rarefaction analysis, and automatically calculates the Shannon-Wiener Index and Chao1. FastGroupII was tested on a set of 16S rDNA sequences from coral-associated Bacteria. The different grouping algorithms produced similar, but not identical, results. This suggests that 16S rDNA datasets need to be analyzed in multiple ways when being used for community ecology studies. CONCLUSION: FastGroupII is an effective bioinformatics tool for the trimming and dereplication of 16S rDNA sequences. Several standard diversity indices are calculated, and the raw sequences are prepared for downstream analyses.

Algorithms↗

PubMed2003

Vasculin, a novel vascular protein differentially expressed in human atherogenesis.

Recent suppressive subtractive hybridization analysis on human atherosclerotic plaque-derived RNA revealed genes upregulated in plaques with a thrombus versus stable plaques. Clone SSH6, containing part of a putative open reading frame of an unknown protein, was further investigated. Full-length cDNA, coding for a 473-amino acid (aa) protein, was identified in a vascular smooth muscle cell (SMC) cDNA library. Bioinformatics suggested the presence of multiple SSH6 variants due to alternative splicing of exon 3. Multiple-tissue Northern blot analysis demonstrated a differential expression pattern of these variants, as a ubiquitously expressed SSH6 mRNA missing exon 3, was detected apart from a putative vascular SMC-specific form containing exon 3. Western blot analysis indicated a ubiquitous 35-kDa protein (SSH6-beta), in addition to a 45-kDa protein (vasculin), detected in the vascular wall and in plasma. Analysis of arteries displaying various stages of atherosclerosis indicated that the vasculin/SSH6-beta ratio increases throughout atherogenesis. Immunohistochemical analysis demonstrated cytoplasmic expression of SSH6 gene products in macrophages, endothelial cells, and SMCs. In summary, we identified a novel mRNA/protein, vasculin, in the arterial wall and plasma. The regulated expression of vasculin in plaques suggests a role in atherogenesis. Moreover, its presence in plasma opens perspectives for vasculin as a marker for atherosclerosis.

Alternative Splicing↗

PubMed2005

Proteomic analysis of proteins expressed by Helicobacter pylori under oxidative stress.

Helicobacter pylori is a spiral, slow growing gram-negative microaerophilic bacterium. It has been shown to be the etiological agent of gastroduodenal diseases, such as chronic gastritis, gastric and duodenal ulcers, and gastric cancer. To address the influence of oxidative stress and its underlying mechanisms, we have compared proliferation, urease activity and protein expression profile of H. pylori incubated under normal microaerophilic (5% O2) and aerobic stress (20% O2) conditions. Oxidative-stress cells displayed coccoid morphology and time-dependent decrease in proliferation. The urease activity was completely abrogated after 32 h. We have further compared the protein expression profiles of H. pylori under normal growing and oxidative-stress conditions by a global proteomic analysis, which includes high-resolution 2-DE followed by MALDI-TOF-MS and bioinformatic databases search/peptide-mass comparison. The results revealed that more than ten proteins were differentially expressed under oxidative stress. Most notably, the protein expression levels of urease accessory protein E (UreE, an essential metallochaperone for urease activity) and alkylhydroperoxide reductase (AhpC) with antioxidant potential are greatly decreased under stress conditions. Measurements of messenger RNA transcription level by performing RT-PCR on total mRNA also confirmed that gene expressions for these two proteins are consistently repressed under oxygen tension. These changes form a firm basis to account for the loss of urease activity and anti-oxidative ability of H. pylori after long-term exposure to reactive oxygen. Conceivably, UreE and AhpC may thus be listed as potential targets for the development of therapeutic drugs against H. pylori.

Animals↗

PubMed2005

The effect of resolution-dependent global shape modifications on rigid-body protein-protein docking.

Docking unbound molecules presents a challenge in the case where no prior biological or bioinformatic knowledge exists. This is mainly due to differences between the structures of the molecules when in a complex and in the free state. Presumably, these differences interfere with the ability of protein-protein docking algorithms, which rely on a dominant shape descriptor, to identify the correct solution and rank it higher than false solutions. In this study we verify the notion that small discords in the molecular fit can be eliminated by using appropriately designed low-resolution shape descriptors, thereby improving the docking results. We exploit the inherent gradual resolution dependency of Fourier transforms and formulate a resolution-dependent shape descriptor by truncating selected Fourier transform terms. Thus, different levels of shape modification are attained, affecting the degree of detail in the depiction of the molecular surface. We applied the modified descriptor to a selection of 23 protein-protein systems, using the unbound structures where possible. The docking results obtained with the new geometric descriptor were considerably superior to former results, improving the ranks of nearly correct solutions for 17 systems. Unification of the results of scans in which different resolutions were employed further improved the ranks of nearly correct solutions to less than 100 for 12 of the 23 systems and less than 300 for 20 systems. The new geometric descriptor can be combined with other descriptors, which typify the electrostatic or hydrophobic character of the molecular surface, and with external experimental or bioinformatic data.

Binding Sites↗

PubMed2005

Proteomics analysis of human cerebrospinal fluid.

Cerebrospinal fluid (CSF) is secreted from several different central nervous system (CNS) structures, and any changes in the CSF composition will accurately reflect pathological processes. Proteomics offers a comprehensive bird's eye view to analyze CSF proteins at a systems level. This paper reviews the variety of analytical methods that have been used for proteomics analysis of CSF, including sample preparation, two-dimensional liquid and gel electrophoresis, mass spectrometry, bioinformatics, and non-gel methods. The differentially expressed CSF proteins that have been identified by proteomics methods are discussed.

Cerebrospinal Fluid Proteins↗

PubMed2001

In silico research in drug discovery.

Target and lead discovery constitute the main components of today's early pharmaceutical research. The aim of target discovery is the identification and validation of suitable drug targets for therapeutic intervention, whereas lead discovery identifies novel chemical molecules that act on those targets. With the near completion of the human genome sequencing, bioinformatics has established itself as an essential tool in target discovery and the in silico analysis of gene expression and gene function are now an integral part of it, facilitating the selection of the most relevant targets for a disease under study. In lead discovery, advances in chemoinformatics have led to the design of compound libraries in silico that can be screened virtually. Moreover, computational methods are being developed to predict the drug-likeness of compounds. Thus, drug discovery is already on the road towards electronic R&D.

Computational Biology↗

PubMed2004

A common open representation of mass spectrometry data and its application to proteomics research.

A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.

Database Management Systems↗

PubMed2003

A life scientist's gateway to distributed data management and computing: the PathPort/ToolBus framework.

The emergent needs of the bioinformatics community challenge current information systems. The pace of biological data generation far outstrips Moore's Law. Therefore, a gap continues to widen between the capabilities to produce biological (molecular and cell) data sets and the capability to manage and analyze these data sets. As a result, Federal investments in large data set generation produces diminishing returns in terms of the community's capabilities of understanding biology and leveraging that understanding to make scientific and technological advances that improve society. We are building an open framework to address various data management issues including data and tool interoperability, nomenclature and data communication standardization, and database integration. PathPort, short for Pathogen Portal, employs a generic, web-services based framework to deal with some of the problems identified by the bioinformatics community. The motivating research goal of a scalable system to provide data management and analysis for key pathosystems, especially relating to molecular data, has resulted in a generic framework using two major components. On the server-side, we employ web-services. On the client-side, a Java application called ToolBus acts as a client-side "bus" for contacting data and tools and viewing results through a single, consistent user interface.

Biological Science Disciplines↗

PubMed2026

VisPan: real-time visualisation of multiplex amplicon-based sequencing panels for rapid syndromic surveillance and pathogen detection.

MOTIVATION: Infectious diseases persist as a major global public health challenge. Diverse factors, including climate change, globalization, deforestation, human-animal interactions, lifestyle choices, and various biological factors, can contribute to their emergence and reemergence. Rapid detection and characterization of (re)emerging pathogens are therefore critical for effective outbreak management and for enhancing our understanding of epidemics by monitoring the transmission, spread, evolution, and genomics of pathogens. In this context, next-generation sequencing technologies (NGS), particularly long-read platforms such as Oxford Nanopore Technologies (ONT), have opened new avenues for real-time pathogen monitoring. However, the bioinformatics bottleneck remains a challenge, emphasizing the need for efficient, accessible, and user-friendly analysis tools. RESULTS: Here, we present a tool adapted from the RAMPART software that enables real-time data visualisation of multiplex PCR syndromic panels combined with Oxford Nanopore sequencing. This real-time analysis enables rapid pathogen detection, from raw data acquisition to taxonomic assignment, within minutes. The interface offers dynamic visual tracking of the sequencing run and amplicon coverage, facilitating immediate insights during diagnostic workflows. Validation experiments confirmed the system's reliability, accurately identifying all pathogens present in complex clinical or environmental samples. This tool provides an integrated, user-friendly solution for genomic pathogen surveillance in field or clinical settings.

Software↗

PubMed2026

Fantastic microbes and where to find them: evaluating learning-by-doing outcomes in a crowdfunded metagenomics workshop.

Metagenomics offers a powerful framework for authentic, interdisciplinary learning, yet it remains underrepresented in undergraduate education due to technical and infrastructural barriers. We hypothesized that a research-based, learning-by-doing metagenomics workshop supported by accessible bioinformatics tools could enhance students' perceived skills, self-efficacy, and conceptual understanding of metagenomic analysis. To test this hypothesis, we designed and evaluated a hybrid hands-on workshop in which undergraduate and postgraduate students analyzed real environmental shotgun metagenomic datasets generated from soil samples collected during a citizen science initiative. Using the graphical workflow platform KBase, participants completed an end-to-end metagenomic analysis, from quality control and assembly to genome reconstruction, taxonomic classification, functional annotation, and scientific presentation of results. Educational outcomes were assessed through validated retrospective pre-post questionnaires, self-efficacy scales, and an open-ended conceptual understanding task. Participants showed significant increases in perceived metagenomic skills and confidence in performing metagenomic analyses, while gains in perceived learning showed a positive trend. Conceptual understanding improved across educational levels, particularly among participants with limited prior experience. Together, these findings demonstrate that authentic, data-driven metagenomics activities can effectively lower barriers to computational biology and foster meaningful learning through hands-on research experiences.

Metagenomics↗

PubMed2026

Longitudinal characterization of mixed-genotype SARS-CoV-2 infections in a military cohort reveals compartmentalized viral populations.

UNLABELLED: Mixed-genotype severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are a concern due to the potential generation of novel recombinants that give rise to new variants. To better understand intra-host viral dynamics, we analyzed specimens from 24 participants from the U.S. Military Health System's Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential COVID-19 cohort with suspected mixed-genotype SARS-CoV-2 infections. From an initial 24 suspected cases, we confirmed 17 as genuine coinfections and graded them by evidence: 7 were "strong"; 4 were "moderate"; 6 were "weak"; and 7 were deemed unlikely to be true mixed-genotype infections. Access to swabs from multiple body sites across the course of infection allowed us to observe compartmentalization and shifts in variant dominance that would have been missed by a single-timepoint analysis, as well as one recombinant Omicron BA.1/BA.2 genome. By using an evidence-based bioinformatic framework to assess sequencing data from well-characterized clinical cases, we distinguished genuine coinfections from bioinformatic artifacts. Our findings emphasize the importance of both extensive specimen collection and careful bioinformatic approaches in ascertaining dual genotype infections. IMPORTANCE: Novel recombinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) arise from coinfections with different lineages, but mixed infections are not screened for despite risk to public health, and most surveillance relies on single swabs. We analyzed a longitudinal data set with specimens from multiple body sites, providing an opportunity to assess intra-host dynamics. To distinguish true coinfection from bioinformatic artifacts with confidence, we applied a framework that grades evidence for mixed genotypes by incorporating lineage and clade with manually validated variant calls. This allowed investigation beyond abundance levels of mixed genotypes within a single specimen, including observations of compartmentalization and a recombinant virus. This work enables further study of evolutionary, immunological, and clinical implications of mixed SARS-CoV-2 genotypes. Detecting dual-genotype infections and discriminating between true dual-genotype infection vs potential bioinformatics-based artifacts support public health and military readiness. These efforts provide evidence to bolster decision-making in molecular epidemiological studies to track transmission and for the choice of effective countermeasures.

SARS-CoV-2↗

PubMed2005

Characterization of a highly variable eutherian microRNA gene.

Mouse microRNAs (miRNAs) miR-290-miR295 are encoded by a cluster of partially homologous pre-miRNA hairpins and are likely to be functionally important in embryonic stem (ES) cells and preimplantation embryos. We present evidence that a spliced, capped, and polyadenylated primary transcript spans this entire Early Embryonic microRNA Cluster (EEmiRC). Partial Drosha processing yields additional large nuclear RNA intermediates. A conserved promoter element containing a TATA-box directs EEmiRC transcription. Sequence analysis shows that the EEmiRC transcription unit is remarkably variable and can only be identified bioinformatically in placental (eutherian) mammals. Consistent with eutherian-specific function, EEmiRC is expressed in trophoblastic stem (TS) cells. When analyzing evolutionary and functional relationships, the organization of the entire miRNA loci should be considered in addition to the mature miRNA sequences. Application of this concept suggests that EEmiRC is a recently acquired rapidly evolving gene important for eutherian development.

Animals↗