- [Show abstract] [Hide abstract] ABSTRACT: Lipidomic analyses of the frontal cortex of Rhesus macaques across three selected age groups (young, sexually-mature, old) revealed that docosahexaenoic acids (DHAs) displayed notable and unique accretions in sexually-mature macaques for all phospholipid classes examined, which were not observable in all remaining polyunsaturated fatty acids (PUFAs) investigated. On the other hand, arachidonic acid (ARA) exhibited sharp attritions in the membrane lipidomes of sexually-mature macaques, a decline which was attenuated only for cardiolipins (CLs). DHA enrichment in phospholipids was lost in old macaques, with accompanying augmentations in very-long-chain sphingomyelins (VLC-SMs). Age-dependent alterations in membrane lipidomes point to a possibly complex temporal interplay between DHA-enriched membrane microdomains and SM-/cholesterol-rich rafts in neural membranes during normative aging. Lipid co-regulation data revealed an increasingly intense degree of co-regulation between membrane lipid classes with age, and suggest that reduction in CLs during normative brain aging may prompt alternative membrane lipid synthetic pathways driven by a compromised energy availability in the aging brain.
- [Show abstract] [Hide abstract] ABSTRACT: Mycolic acids are attractive diagnostic markers for tuberculosis (TB) infection because they are bacteria-derived, contain information about bacterial species, modulate host-pathogen interactions and are chemically inert. Here, we present a novel approach based on mass spectrometry. Quantification of specific precursor → fragment transitions of approximately 2000 individual mycolic acids (MAs) resulted in high analytical sensitivity and specificity. We next used this tool in a retrospective case-control study of patients with pulmonary TB with varying disease burdens from South Korea, Vietnam, Uganda and South Africa. MAs were extracted from small volume sputum (200 µl) and analysed without the requirement for derivatization. Infected patients (70, 19 of whom were HIV+) could be separated from controls (40, 20 of whom were HIV+) with a sensitivity and specificity of 94 and 93%, respectively. Furthermore, we quantified MA species in lung tissue of TB-infected mice and demonstrated effective clearance of MA levels following curative rifampicin treatment. Thus, our results demonstrate for the first time the feasibility and clinical relevance of direct detection of mycobacterial lipids as biomarkers of TB infection.
Data: Supplementary Material
- [Show abstract] [Hide abstract] ABSTRACT: Recent rapid growth of lipidomics is mainly attributed to technological advances in mass spectrometry. Development of soft ionization techniques, in combination with computational tools, has spurred subsequent development of various methods for lipid analysis. However, none of these existing approaches can cover major cellular lipids in a single run. Here we demonstrate that a single method of liquid chromatography coupled with mass spectrometry (LCMS) can be used for simultaneous profiling of major cellular lipids including glycerophospholipids (PLs), sphingolipids (SPLs), waxes, sterols (ST) and mono-, di- as well as triacylglycerides (MAG, DAG, TAG). We applied this approach to analyze these lipids in various organisms including Saccharomyces cerevisiae and Schizosaccharomyces pombe. While phospholipids and triacylglycerides of S. pombe mainly contain 18 : 1 fatty acyls, those of S. cerevisiae contain 16 : 1, 16 : 0 and 18 : 1 fatty acyls. S. cerevisiae and S. pombe contain distinct sphingolipid profiles. S. cerevisiae has abundant inositol phytoceramides (IPC), while S. pombe contains high levels of free phytoceramides as well as short chain phytoceramides (t18:1/20 : 0-B) and IPC (t18:1/20 : 0-B). In S. cerevisiae, our results demonstrated accumulation of ergosterol esters in tgl1Delta cells and accumulation of various TAG species in tgl3Delta cells, which are consistent with the function of the respective enzymes. Furthermore, we, for the first time, systematically characterized lipids in S. pombe and measured their dynamic changes in Deltaplh1Deltadga1 cells at different growth phases. We further discussed dynamic changes of phospholipids, sphingolipids and neutral lipids in the progress of programmed cell death in Deltaplh1Deltadga1 cells of S. pombe.
- [Show abstract] [Hide abstract] ABSTRACT: Cyclin dependent kinases (CDK) associate with cyclins to regulate cell cycle progression and gene transcription by phosphorylating key proteins. The different cyclin-CDK complexes display differences in substrate specificities with substrates binding across a shallow, hydrophobic, substrate-binding pocket known as the cyclin groove. However the mechanism underlying this differential substrate recognition remains largely unknown and cannot be explained merely on the basis of sequence variability. A subset of cyclins, cyclins A2, E1 and B1 despite being structurally and functionally similar, show marked differences in their interactions with recruitment peptides derived from their substrate or inhibitor proteins p27, p21, p57, E2F1, p53, pRb and p107. While these peptides (characterized by a cyclin binding motif of four residues ZRXL where Z and X are cationic residues) inhibit the activity of cyclins A2 and E1, no such inhibition is observed for cyclin B1. Electrostatic potentials of cyclins A2, E1 and B1 show that anionic regions of cyclins A2 and E1 enable them to bind peptides while cationic regions at homologous locations in cyclin B1 abrogate binding. These arise from charged residues that are conserved. Mutations that switch these characters are suggested. Computed energetics of binding confirms this. Deregulation of the enzymatic activity of this class of enzymes is a ubiquitous feature of human neoplasia, but attempts to exploit this therapeutically have been confounded by a lack of understanding of the precise specificity of the different cyclin complexes. Here we begin to clarify this issue by explaining the mechanism by which cyclin B1 escapes regulation by the p21 family of CDKIs.
- [Show abstract] [Hide abstract] ABSTRACT: P53 is probably the most important tumor suppressor known. Over the years, information about this gene has increased dramatically. We have built a comprehensive knowledgebase of p53, which aims to facilitate wet-lab biologists to formulate their experiments and new-comers to learn whatever they need about the gene and bioinformaticians to make new discoveries through data analysis. Using the information curated, including mutation information, transcription factors, transcriptional targets, and single nucleotide polymorphisms, we have performed extensive bioinformatics analysis, and made several new discoveries about p53. We have identified point missense mutations that are over-represented in cancers, but lack of functional studies. By assessing the capability of six p53 transcriptional targets' tag SNPs selected from HapMap to capture SNPs obtained from National Institute of Environmental Health Sciences (NIEHS) Environmental Genome project and vice versa, we conclude that NIEHS data is a better source for tagSNP selections of these genes in future association studies. Analysis of microRNA regulation in the transcriptional network of the p53 gene reveals potentially important regulatory relationships between oncogenic microRNAs and transcription factors of p53. By mapping transcription factors of p53 to pathways involved in cell cycle and apoptosis, we have identified distinctive transcriptional controls of p53 in these two physiological states.
- [Show abstract] [Hide abstract] ABSTRACT: Some research has suggested that patches of six constitute an important amino acid window length in proteins for conveying information. We present database evidence that supports this conjecture, as well as additional recurrence-based data that characterization and quantification of these words affect the folding/aggregation features of proteins. Other indirect evidence is presented and discussed. (c) 2006 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
- [Show abstract] [Hide abstract] ABSTRACT: A variety of protein physicochemical as well as topological properties, demonstrate a scaling behavior relative to chain length. Many of the scalings can be modeled as a power law which is qualitatively similar across the examples. In this article, we suggest a rational explanation to these observations on the basis of both protein connectivity and hydrophobic constraints of residues compactness relative to surface volume. Unexpectedly, in an examination of these relationships, a singularity was shown to exist near 255-270 residues length, and may be associated with an upper limit for domain size. Evaluation of related G-factor data points to a wide range of conformational plasticity near this point. In addition to its theoretical importance, we show by an application of CASP experimental and predicted structures, that the scaling is a practical filter for protein structure prediction.
Data: Additional File 1[Show abstract] [Hide abstract] ABSTRACT: This file lists the top five amino acid indices found by parameter search for each of the binary classifiers.
- [Show abstract] [Hide abstract] ABSTRACT: Protein subcellular localization is an important determinant of protein function and hence, reliable methods for prediction of localization are needed. A number of prediction algorithms have been developed based on amino acid compositions or on the N-terminal characteristics (signal peptides) of proteins. However, such approaches lead to a loss of contextual information. Moreover, where information about the physicochemical properties of amino acids has been used, the methods employed to exploit that information are less than optimal and could use the information more effectively. In this paper, we propose a new algorithm called pSLIP which uses Support Vector Machines (SVMs) in conjunction with multiple physicochemical properties of amino acids to predict protein subcellular localization in eukaryotes across six different locations, namely, chloroplast, cytoplasmic, extracellular, mitochondrial, nuclear and plasma membrane. The algorithm was applied to the dataset provided by Park and Kanehisa and we obtained prediction accuracies for the different classes ranging from 87.7%-97.0% with an overall accuracy of 93.1%. This study presents a physicochemical property based protein localization prediction algorithm. Unlike other algorithms, contextual information is preserved by dividing the protein sequences into clusters. The prediction accuracy shows an improvement over other algorithms based on various types of amino acid composition (single, pair and gapped pair). We have also implemented a web server to predict protein localization across the six classes (available at http://pslip.bii.a-star.edu.sg/).