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PubMed2006

Protein Circular Dichroism Data Bank (PCDDB): data bank and website design.

The Protein Circular Dichroism Data Bank (PCDDB) is a new deposition data bank for validated circular dichroism spectra of biomacromolecules. Its aim is to be a resource for the structural biology and bioinformatics communities, providing open access and archiving facilities for circular dichroism and synchrotron radiation circular dichroism spectra. It is named in parallel with the Protein Data Bank (PDB), a long-existing valuable reference data bank for protein crystal and NMR structures. In this article, we discuss the design of the data bank structure and the deposition website located at http://pcddb.cryst.bbk.ac.uk. Our aim is to produce a flexible and comprehensive archive, which enables user-friendly spectral deposition and searching. In the case of a protein whose crystal structure and sequence are known, the PCDDB entry will be linked to the appropriate PDB and sequence data bank files, respectively. It is anticipated that the PCDDB will provide a readily accessible biophysical catalogue of information on folded proteins that may be of value in structural genomics programs, for quality control and archiving in industrial and academic labs, as a resource for programs developing spectroscopic structural analysis methods, and in bioinformatics studies.

Circular Dichroism↗

PubMed2025

PROLONG: penalized regression for outcome guided longitudinal omics analysis with network and group constraints.

MOTIVATION: There is a growing interest in longitudinal omics data paired with some longitudinal clinical outcome. Given a large set of continuous omics variables and some continuous clinical outcome, each measured for a few subjects at only a few time points, we seek to identify those variables that co-vary over time with the outcome. To motivate this problem we study a dataset with hundreds of urinary metabolites along with Tuberculosis mycobacterial load as our clinical outcome, with the objective of identifying potential biomarkers for disease progression. For such data clinicians usually apply simple linear mixed effects models which often lack power given the low number of replicates and time points. We propose a penalized regression approach on the first differences of the data that extends the lasso + Laplacian method [Li and Li (Network-constrained regularization and variable selection for analysis of genomic data. Bioinformatics 2008;24:1175-82.)] to a longitudinal group lasso + Laplacian approach. Our method, PROLONG, leverages the first differences of the data to increase power by pairing the consecutive time points. The Laplacian penalty incorporates the dependence structure of the variables, and the group lasso penalty induces sparsity while grouping together all contemporaneous and lag terms for each omic variable in the model. RESULTS: With an automated selection of model hyper-parameters, PROLONG correctly selects target metabolites with high specificity and sensitivity across a wide range of scenarios. PROLONG selects a set of metabolites from the real data that includes interesting targets identified during EDA. AVAILABILITY AND IMPLEMENTATION: An R package implementing described methods called "prolong" is available at https://github.com/stevebroll/prolong. Code snapshot available at 10.5281/zenodo.14804245.

Humans↗

PubMed2026

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

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↗

PubMed2004

A case study of high-throughput biological data processing on parallel platforms.

MOTIVATION: Analysis of large biological data sets using a variety of parallel processor computer architectures is a common task in bioinformatics. The efficiency of the analysis can be significantly improved by properly handling redundancy present in these data combined with taking advantage of the unique features of these compute architectures. RESULTS: We describe a generalized approach to this analysis, but present specific results using the program CEPAR, an efficient implementation of the Combinatorial Extension algorithm in a massively parallel (PAR) mode for finding pairwise protein structure similarities and aligning protein structures from the Protein Data Bank. CEPAR design and implementation are described and results provided for the efficiency of the algorithm when run on a large number of processors. AVAILABILITY: Source code is available by contacting one of the authors.

Algorithms↗

PubMed2003

Whole-proteome interaction mining.

MOTIVATION: A major post-genomic scientific and technological pursuit is to describe the functions performed by the proteins encoded by the genome. One strategy is to first identify the protein-protein interactions in a proteome, then determine pathways and overall structure relating these interactions, and finally to statistically infer functional roles of individual proteins. Although huge amounts of genomic data are at hand, current experimental protein interaction assays must overcome technical problems to scale-up for high-throughput analysis. In the meantime, bioinformatics approaches may help bridge the information gap required for inference of protein function. In this paper, a previously described data mining approach to prediction of protein-protein interactions (Bock and Gough, 2001, Bioinformatics, 17, 455-460) is extended to interaction mining on a proteome-wide scale. An algorithm (the phylogenetic bootstrap) is introduced, which suggests traversal of a phenogram, interleaving rounds of computation and experiment, to develop a knowledge base of protein interactions in genetically-similar organisms. RESULTS: The interaction mining approach was demonstrated by building a learning system based on 1,039 experimentally validated protein-protein interactions in the human gastric bacterium Helicobacter pylori. An estimate of the generalization performance of the classifier was derived from 10-fold cross-validation, which indicated expected upper bounds on precision of 80% and sensitivity of 69% when applied to related organisms. One such organism is the enteric pathogen Campylobacter jejuni, in which comprehensive machine learning prediction of all possible pairwise protein-protein interactions was performed. The resulting network of interactions shares an average protein connectivity characteristic in common with previous investigations reported in the literature, offering strong evidence supporting the biological feasibility of the hypothesized map. For inferences about complete proteomes in which the number of pairwise non-interactions is expected to be much larger than the number of actual interactions, we anticipate that the sensitivity will remain the same but precision may decrease. We present specific biological examples of two subnetworks of protein-protein interactions in C. jejuni resulting from the application of this approach, including elements of a two-component signal transduction systems for thermoregulation, and a ferritin uptake network.

Algorithms↗

PubMed2005

Increased power of microarray analysis by use of an algorithm based on a multivariate procedure.

MOTIVATION: The power of microarray analyses to detect differential gene expression strongly depends on the statistical and bioinformatical approaches used for data analysis. Moreover, the simultaneous testing of tens of thousands of genes for differential expression raises the 'multiple testing problem', increasing the probability of obtaining false positive test results. To achieve more reliable results, it is, therefore, necessary to apply adjustment procedures to restrict the family-wise type I error rate (FWE) or the false discovery rate. However, for the biologist the statistical power of such procedures often remains abstract, unless validated by an alternative experimental approach. RESULTS: In the present study, we discuss a multiplicity adjustment procedure applied to classical univariate as well as to recently proposed multivariate gene-expression scores. All procedures strictly control the FWE. We demonstrate that the use of multivariate scores leads to a more efficient identification of differentially expressed genes than the widely used MAS5 approach provided by the Affymetrix software tools (Affymetrix Microarray Suite 5 or GeneChip Operating Software). The practical importance of this finding is successfully validated using real time quantitative PCR and data from spike-in experiments. AVAILABILITY: The R-code of the statistical routines can be obtained from the corresponding author. CONTACT: Schuster@imise.uni-leipzig.de

Algorithms↗

PubMed1998

A highly conserved intraspecies homolog of the Saccharomyces cerevisiae elongation factor-3 encoded by the HEF3 gene.

A paralog (intraspecies homolog) of the Saccharomyces cerevisiae YEF3 gene, encoding elongation factor-3, has been sequenced in the course of the yeast genome project, and identified by database searching; this gene has been designated HEF3. Bioinformatic and Northern blot analysis indicate that the HEF3 gene is not expressed during vegetative growth. Deletion of the HEF3 gene reveals no growth defects, nor any defects in mating or sporulation. A high copy 2 mu clone of HEF3 was constructed, and was shown to be unable to complement a null allele of yef3. Finally, an in vitro assay for ribosome-stimulated ATPase activity was performed with isogenic HEF3 and delta hef3 strains; no difference in biochemical activity could be detected in these strains. From these results, we conclude that the HEF3 gene does not encode a functional homolog of YEF3.

Adenosine Triphosphatases↗

PubMed2000

IUBMB updates Ph.D. standards.

The Education Committee of the International Union of Biochemistry (IUB, but IUBMB since 1991) published its report on "Standards for the Ph.D. Degree in Biochemistry and Molecular Biology" in 1989. Developments since then have led to the disappearance of the traditional demarcations between many of the biological disciplines, while information technology and bioinformatics have revolutionized the analysis, storage, and communication of scientific data. To meet these challenges, that report has now been revised through a broad interdisciplinary and international consultation. This has led to the recent publication, on behalf of the same Committee, of "Standards for the PhD Degree in the Molecular Biosciences". Like its predecessor this revised report not only defines in behavioural terms the qualities and skills expected of doctoral graduates by the international community of molecular bioscientists but also offers useful suggestions and advice as to how those skills can be developed and maximized. In addition, it discusses various topics related to doctoral education.

Biochemistry↗

PubMed2005

Correlation-associated peptide networks of human cerebrospinal fluid.

Profiling of peptides and small proteins from either human body fluids or tissues by chromatography and subsequent mass spectrometry reveals several thousand individual peptide signals per sample. Any peptide is an intermediate in the course of biosynthesis, post-translational modification (PTM), proteolytic processing and degradation. Changes in the concentration of one peptide often affects the concentration of the other, hence a challenge consists in the development of suitable tools to turn this large amount of data into biologically relevant information. Comprehensive statistical analysis of the peptide profiling data allows associating peptides, which are closely related in terms of peptide biochemistry. Here, the bioinformatic concept of peptide networks, correlation-associated peptide networks (CANs), is introduced. Peptides with statistical similarity of their concentrations are grouped in form of networks, and these networks are interpreted in terms of peptide biochemistry. The spectrum of functional relationships found in cerebrospinal fluid CAN covers PTM and proteolytic degradation of peptides, clearance processing in the complement cascade, common secretion of peptides by neuroendocrine cells as well as ubiquitin-mediated degradation. Our results indicate that CAN is a powerful bioinformatic tool for the systematic analysis and interpretation of large peptidomics and proteomics data and helps to discover novel bioactive and diagnostic peptides.

Chemical Fractionation↗

PubMed2025

Automated Machine Learning Tools to Build Regression Models for Schizosaccharomyces pombe Omics Data.

Machine learning is a powerful tool for analyzing biological data and making useful predictions. The surge of biological data from high-throughput omics technologies has raised the need for modeling approaches capable of tackling such amounts of data, which is pivotal to understanding the nature of complex molecular systems. Here, we show how to construct a simple model using automated machine learning (AutoML) to predict protein abundance in Schizosaccharomyces pombe, using data obtained from codon usage bias and quantitative proteomics.

Machine Learning↗

PubMed2002

Genomic characterization of the human prion protein (PrP) gene locus.

Prion protein (PrP) is intimately linked with a class of neurodegenerative diseases known as transmissible spongiform encephalopathies (TSEs). Employing bioinformatics and direct molecular analysis, we demonstrated that the human PrP gene (PRNP) locus, which is situated at Chromosome (Chr) position 20p12-ter, contains three genes within a 55-kb interval: PRNP; DOPPEL or PRND, located 20 kb 3' of PRNP; and a novel gene, designated PRNT, that maps 3 kb 3' to PRND and is transcribed to generate at least three alternatively spliced mRNAs. All three genes of this locus demonstrate low sequence homology, implying that, although they may be evolutionarily related, they are functionally distinct. Analysis of both adult and fetal human tissues confirmed the ubiquitous but variable expression profile of PRNP, with the highest levels observed in the CNS and testis. Contrastingly, although PRND shows a wide tissue expression pattern in fetal tissues, it is expressed exclusively in adult testis, whereas all three PRNT isoforms were detected only in adult testis, implying that PRND is developmentally regulated. An investigation of the regulatory mechanisms underlying this complex gene expression pattern from the PRNP locus should provide insight into the function of these genes and the possible involvement of the non-PrP proteins in the development of TSEs.

Adult↗

PubMed2001

Identification of a novel, multifunctional beta-defensin (human beta-defensin 3) with specific antimicrobial activity. Its interaction with plasma membranes of Xenopus oocytes and the induction of macrophage chemoattraction.

Previous studies have shown the implication of beta-defensins in host defense of the human body. The human beta-defensins 1 and 2 (hBD-1, hBD-2) have been isolated by biochemical methods. Here we report the identification of a third human beta-defensin, called human beta-defensin 3 (hBD-3; cDNA sequence, Genbank accession no. AF295370), based on bioinformatics and functional genomic analysis. Expression of hBD-3 is detected throughout epithelia of many organs and in non-epithelial tissues. In contrast to hBD-2, which is upregulated by microorganisms or tumor necrosis factor-alpha (TNF-alpha), hBD-3 expression is increased particularly after stimulation by interferon-gamma. Synthetic hBD-3 exhibits a strong antimicrobial activity against gram-negative and gram-positive bacteria and fungi, including Burkholderia cepacia. In addition, hBD-3 activates monocytes and elicits ion channel activity in biomembranes, specifically in oocytes of Xenopus laevis. This paper also shows that screening of genomic sequences is a valuable tool with which to identify novel regulatory peptides. Human beta-defensins represent a family of antimicrobial peptides differentially expressed in most tissues, regulated by specific mechanisms, and exerting physiological functions not only related to direct host defense.

Amino Acid Sequence↗

PubMed2026

Investigation of Fatty Acid Metabolism-Associated Molecular CPOX and the Underlying Mechanism in Follicular Lymphoma.

Dysregulated lipid metabolism is a key driver of follicular lymphoma (FL). This study aimed to explore the lipid metabolism-related genes (LMRGs) and clarify the underlying roles and mechanisms in FL. Bioinformatics methods, including differential analysis, WGCNA, machine learning, and Mendelian randomization, were utilized to select the LMRGs in FL. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the function of the key LMRG. Receiver operator characteristic (ROC) was used to evaluate the diagnostic value of the key gene CPOX. A pan-cancer analysis investigated CPOX's expression level and immune correlations. In vitro experiments using FL cell lines (WSU-FSCCL, DOHH2) validated CPOX expression, and CPOX knockdown in DOHH2 cells was used to assess its impact on viability, migration, invasion, and fatty acid metabolism. CPOX was confirmed to be a risk factor, significantly overexpressed in FL, and exhibited effective diagnostic ability in FL (AUC = 0.731). Functional analysis linked CPOX to mitochondrial function, oxidative phosphorylation, and heme metabolic process. Pan-cancer indicated the dysregulated CPOX across multiple cancers and closely correlation with immune characteristics. Experimentally, CPOX was higher in the more invasive DOHH2 cells; and CPOX knockdown suppressed FL progression and reduced lipid droplet formation, triglyceride, total cholesterol, and free fatty acid levels. In conclusion, this study fills the gap in understanding the significance of lipid metabolism-related molecules in FL, and innovatively proposes that CPOX is a risk factor for FL. Knockdown of CPOX inhibits the FL progression, which is regulated by fatty acid metabolism.

Lymphoma, Follicular↗

PubMed2004

The characterisation and functional analysis of the human glyoxalase-1 gene using methods of bioinformatics.

Methylglyoxal (MG), which forms MG-derived AGE, is elevated in diabetic subjects with vascular disease. Detoxification of MG occurs through the glyoxalase system incorporating glyoxalase-1 (GLO1) and glyoxalase-2. Perturbations of the glyoxalase-1 gene (GLO1) may result in vulnerability to vascular complications through alterations in AGE interactions. We used bioinformatics to predict the structure, function and genetic variation of GLO1. We identified a previously unreported exon. Seventy single nucleotide polymorphisms (SNPs) were identified bioinformatically. The amino acid substitution Ala 111 Glu was confirmed and predicted to be tolerant. Though no alternative splice variants were identified, novel multiple alternative transcription start sites and alternative 3' UTRs were demonstrated. Ubiquitous expression of GLO1 was confirmed. Conserved regulatory regions were predicted 5' to the transcription start site and in the distal promoter, and several predicted conserved transcription regulatory elements were suggested in the 5' UTR. This study of GLO1 demonstrates multiple sequence variants at DNA and mRNA levels, areas of sequence conservation and SNPs that are predicted to affect function. A differential ability of glyoxalase-1 to reduce the formation and subsequent interaction of AGEs may have a role in the structural and functional manifestations of diabetic vascular disease.

Amino Acid Sequence↗

PubMed2005

Single nucleotide polymorphism in transcriptional regulatory regions and expression of environmentally responsive genes.

Single nucleotide polymorphisms (SNPs) in the human genome are DNA sequence variations that can alter an individual's response to environmental exposure. SNPs in gene coding regions can lead to changes in the biological properties of the encoded protein. In contrast, SNPs in non-coding gene regulatory regions may affect gene expression levels in an allele-specific manner, and these functional polymorphisms represent an important but relatively unexplored class of genetic variation. The main challenge in analyzing these SNPs is a lack of robust computational and experimental methods. Here, we first outline mechanisms by which genetic variation can impact gene regulation, and review recent findings in this area; then, we describe a methodology for bioinformatic discovery and functional analysis of regulatory SNPs in cis-regulatory regions using the assembled human genome sequence and databases on sequence polymorphism and gene expression. Our method integrates SNP and gene databases and uses a set of computer programs that allow us to: (1) select SNPs, from among the >9 million human SNPs in the NCBI dbSNP database, that are similar to cis-regulatory element (RE) consensus sequences; (2) map the selected dbSNP entries to the human genome assembly in order to identify polymorphic REs near gene start sites; (3) prioritize the candidate polymorphic RE containing genes by searching the existing genotype and gene expression data sets. The applicability of this system has been demonstrated through studies on p53 responsive elements and is being extended to additional pathways and environmentally responsive genes.

Databases, Genetic↗

PubMed2006

The human desmin locus: gene organization and LCR-mediated transcriptional control.

Locus control regions (LCRs) are defined by their ability to confer reproducible physiological levels of transgene expression in mice and therefore thought to possess the ability to generate dominantly a transcriptionally active chromatin structure. We report the first characterization of a muscle-cell-specific LCR, which is linked to the human desmin gene (DES). The DES LCR consists of five regions of muscle-specific DNase I hypersensitivity (HS) localized between -9 and -18 kb 5' of DES and reproducibly drives full physiological levels of expression in all muscle cell types. The DES LCR DNase I HS regions are highly conserved between humans and other mammals and can potentially bind a broad range of muscle-specific and ubiquitous transcription factors. Bioinformatics and direct molecular analysis show that the DES locus consists of three muscle-specific (DES) or muscle preferentially expressed genes (APEG1 and SPEG, the human orthologue of murine striated-muscle-specific serine/threonine protein kinase, Speg). The DES LCR may therefore regulate expression of SPEG and APEG1 as well as DES.

Amino Acid Sequence↗

PubMed2002

Assessment of soil contamination--a functional perspective.

In many industrialized countries the use of land is impeded by soil pollution from a variety of sources. Decisions on clean-up, management or set-aside of contaminated land are based on various considerations, including human health risks, but ecological arguments do not have a strong position in such assessments. This paper analyses why this should be so, and what ecotoxicology and theoretical ecology can improve on the situation. It seems that soil assessment suffers from a fundamental weakness, which relates to the absence of a commonly accepted framework that may act as a reference. Soil contamination can be assessed both from a functional perspective and a structural perspective. The relationship between structure and function in ecosystems is a fundamental question of ecology which receives a lot of attention in recent literature, however, a general concept that may guide ecotoxicological assessments has not yet arisen. On the experimental side, a good deal of progress has been made in the development and standardized use of terrestrial model ecosystems (TME). In such systems, usually consisting of intact soil columns incubated in the laboratory under conditions allowing plant growth and drainage of water, a compromise is sought between field relevance and experimental manageability. A great variety of measurements can be made on such systems, including microbiological processes and activities, but also activities of the decomposer soil fauna. I propose that these TMEs can be useful instruments in ecological soil quality assessments. In addition a "bioinformatics approach" to the analysis of data obtained in TME experiments is proposed. Soil function should be considered as a multidimensional concept and the various measurements can be considered as indicators, whose combined values define the "normal operating range" of the system. Deviations from the normal operating range indicate that the system is in a condition of stress. It is hoped that more work along this line will improve the prospects for ecological arguments in soil quality assessment.

Computational Biology↗