Showing papers in "Molecular BioSystems in 2012"

Attributes of short linear motifs.

Abstract: Traditionally, protein–protein interactions were thought to be mediated by large, structured domains. However, it has become clear that the interactome comprises a wide range of binding interfaces with varying degrees of flexibility, ranging from rigid globular domains to disordered regions that natively lack structure. Enrichment for disorder in highly connected hub proteins and its correlation with organism complexity hint at the functional importance of disordered regions. Nevertheless, they have not yet been extensively characterised. Shifting the attention from globular domains to disordered regions of the proteome might bring us closer to elucidating the dense and complex connectivity of the interactome. An important class of disordered interfaces are the compact mono-partite, short linear motifs (SLiMs, or eukaryotic linear motifs (ELMs)). They are evolutionarily plastic and interact with relatively low affinity due to the limited number of residues that make direct contact with the binding partner. These features confer to SLiMs the ability to evolve convergently and mediate transient interactions, which is imperative to network evolution and to maintain robust cell signalling, respectively. The ability to discriminate biologically relevant SLiMs by means of different attributes will improve our understanding of the complexity of the interactome and aid development of bioinformatics tools for motif discovery. In this paper, the curated instances currently available in the Eukaryotic Linear Motif (ELM) database are analysed to provide a clear overview of the defining attributes of SLiMs. These analyses suggest that functional SLiMs have higher levels of conservation than their surrounding residues, frequently evolve convergently, preferentially occur in disordered regions and often form a secondary structure when bound to their interaction partner. These results advocate searching for small groupings of residues in disordered regions with higher relative conservation and a propensity to form the secondary structure. Finally, the most interesting conclusions are examined in regard to their functional consequences.

LC-MS-based metabolomics.

Abstract: Metabolomics aims at identification and quantitation of small molecules involved in metabolic reactions. LC-MS has enjoyed a growing popularity as the platform for metabolomic studies due to its high throughput, soft ionization, and good coverage of metabolites. The success of a LC-MS-based metabolomic study often depends on multiple experimental, analytical, and computational steps. This review presents a workflow of a typical LC-MS-based metabolomic analysis for identification and quantitation of metabolites indicative of biological/environmental perturbations. Challenges and current solutions in each step of the workflow are reviewed. The review intends to help investigators understand the challenges in metabolomic studies and to determine appropriate experimental, analytical, and computational methods to address these challenges.

Drug-target interaction prediction by random walk on the heterogeneous network.

Abstract: Predicting potential drug–target interactions from heterogeneous biological data is critical not only for better understanding of the various interactions and biological processes, but also for the development of novel drugs and the improvement of human medicines. In this paper, the method of Network-based Random Walk with Restart on the Heterogeneous network (NRWRH) is developed to predict potential drug–target interactions on a large scale under the hypothesis that similar drugs often target similar target proteins and the framework of Random Walk. Compared with traditional supervised or semi-supervised methods, NRWRH makes full use of the tool of the network for data integration to predict drug–target associations. It integrates three different networks (protein–protein similarity network, drug–drug similarity network, and known drug–target interaction networks) into a heterogeneous network by known drug–target interactions and implements the random walk on this heterogeneous network. When applied to four classes of important drug–target interactions including enzymes, ion channels, GPCRs and nuclear receptors, NRWRH significantly improves previous methods in terms of cross-validation and potential drug–target interaction prediction. Excellent performance enables us to suggest a number of new potential drug–target interactions for drug development.

RWRMDA: predicting novel human microRNA–disease associations

Abstract: Recently, more and more research has shown that microRNAs (miRNAs) play critical roles in the development and progression of various diseases, but it is not easy to predict potential human miRNA–disease associations from the vast amount of biological data. Computational methods for predicting potential disease–miRNA associations have gained a lot of attention based on their feasibility, guidance and effectiveness. Differing from traditional local network similarity measures, we adopted global network similarity measures and developed Random Walk with Restart for MiRNA–Disease Association (RWRMDA) to infer potential miRNA–disease interactions by implementing random walk on the miRNA–miRNA functional similarity network. We tested RWRMDA on 1616 known miRNA–disease associations based on leave-one-out cross-validation, and achieved an area under the ROC curve of 86.17%, which significantly improves previous methods. The method was also applied to three cancers for accuracy evaluation. As a result, 98% (Breast cancer), 74% (Colon cancer), and 88% (Lung cancer) of top 50 predicted miRNAs are confirmed by published experiments. These results suggest that RWRMDA will represent an important bioinformatics resource in biomedical research of both miRNAs and diseases.

Upregulated MALAT-1 contributes to bladder cancer cell migration by inducing epithelial-to-mesenchymal transition

Abstract: Recent studies reveal that long non-coding RNAs (lncRNAs) have been shown to have important regulatory roles in cancer biology, and lncRNA MALAT-1 expression is upregulated in some tumors. However, the contributions of MALAT-1 to bladder cancer metastasis remain largely unknown. In the present study we evaluated MALAT-1 expression in bladder cancer tissues by real-time PCR, and defined its biological functions. We verified that MALAT-1 levels were upregulated in bladder cancer tissues compared with adjacent normal tissues, and MALAT-1 expression was remarkably increased in primary tumors that subsequently metastasized, when compared to those primary tumors that did not metastasize. SiRNA-mediated MALAT-1 silencing impaired in vitro bladder cancer cell migration. Downregulation of MALAT-1 resulted in a decrease of the epithelial–mesenchymal transition (EMT)-associated ZEB1, ZEB2 and Slug levels, and an increase of E-cadherin levels. We further demonstrated that MALAT-1 promoted EMT by activating Wnt signaling in vitro. These data suggest an important role for MALAT-1 in regulating metastasis of bladder cancer and the potential application of MALAT-1 in bladder cancer therapy.

iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites.

Abstract: Although numerous efforts have been made for predicting the subcellular locations of proteins based on their sequence information, it still remains as a challenging problem, particularly when query proteins may have the multiplex character, i.e., they simultaneously exist, or move between, two or more different subcellular location sites. Most of the existing methods were established on the assumption: a protein has one, and only one, subcellular location. Actually, recent evidence has indicated an increasing number of human proteins having multiple subcellular locations. This kind of multiplex proteins should not be ignored because they may bear some special biological functions worthy of our attention. Based on the accumulation-label scale, a new predictor, called iLoc-Hum, was developed for identifying the subcellular localization of human proteins with both single and multiple location sites. As a demonstration, the jackknife cross-validation was performed with iLoc-Hum on a benchmark dataset of human proteins that covers the following 14 location sites: centrosome, cytoplasm, cytoskeleton, endoplasmic reticulum, endosome, extracellular, Golgi apparatus, lysosome, microsome, mitochondrion, nucleus, peroxisome, plasma membrane, and synapse, where some proteins belong to two, three or four locations but none has 25% or higher pairwise sequence identity to any other in the same subset. For such a complicated and stringent system, the overall success rate achieved by iLoc-Hum was 76%, which is remarkably higher than that by any of the existing predictors that also have the capacity to deal with this kind of system. Further comparisons were also made via two independent datasets; all indicated that the success rates by iLoc-Hum were even more significantly higher than its counterparts. As a user-friendly web-server, iLoc-Hum is freely accessible to the public at http://icpr.jci.edu.cn/bioinfo/iLoc-Hum or http://www.jci-bioinfo.cn/iLoc-Hum. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results by choosing either a straightforward submission or a batch submission, without the need to follow the complicated mathematical equations involved.

Structural analysis of intrinsically disordered proteins by small-angle X-ray scattering

Abstract: Small-angle scattering of X-rays (SAXS) is an established method to study the overall structure and structural transitions of biological macromolecules in solution. For folded proteins, the technique provides three-dimensional low resolution structures ab initio or it can be used to drive rigid-body modeling. SAXS is also a powerful tool for the quantitative analysis of flexible systems, including intrinsically disordered proteins (IDPs), and is highly complementary to the high resolution methods of X-ray crystallography and NMR. Here we present the basic principles of SAXS and review the main approaches to the characterization of IDPs and flexible multidomain proteins using SAXS. Together with the standard approaches based on the analysis of overall parameters, a recently developed Ensemble Optimization Method (EOM) is now available. The latter method allows for the co-existence of multiple protein conformations in solution compatible with the scattering data. Analysis of the selected ensembles provides quantitative information about flexibility and also offers insights into structural features. Examples of the use of SAXS and combined approaches with NMR, X-ray crystallography, and computational methods to characterize completely or partially disordered proteins are presented.

Intrinsically disordered proteins.

Abstract: Our understanding of protein function has been predominated by the view that proteins need to adopt a defined three dimensional structure to be able to carry out their function. Indeed, crystal structures of numerous proteins have been instrumental in establishing the structure– function paradigm. For example, the structures of numerous enzymes have highlighted the need for particular chemical groups to be positioned in spatial proximity in order to catalyse specific reactions. While this concept is absolutely fundamental for a large number of proteins, research over the last decade has identified segments in proteins that do not adopt a specific three dimensional structure but are nevertheless important for function. This suggests that conformational flexibility and heterogeneity might be important for certain types of protein function. Such segments, usually referred to as intrinsically disordered regions (IDRs), may either fold upon binding to the right interaction partner, or may still remain disordered in a complex. While there was scepticism from many researchers about the existence and the functional relevance of IDRs, exciting developments over the last few years have unambiguously established the functional contribution of disordered segments. Importantly, IDRs are prominent in the proteomes of all studied organisms. Given the general excitement in this relatively young field, I believe that it is timely to dedicate a special issue of Molecular BioSystems to highlight the recent advances, experimental and computational methods, as well as emerging concepts involving IDRs. Some of the current challenges in the field are (i) to develop new experimental and computational approaches to characterise IDRs and to identify functional parts within such regions, (ii) to gain a more comprehensive understanding of the sequence features, structural properties, expression patterns, molecular networks and evolution of proteins containing disordered segments, and (iii) to understand fundamental principles involving IDRs, such as how they mediate molecular recognition, regulation, folding, allostery, mutational robustness, etc. Addressing these challenges will have a profound impact on our understanding of (a) how IDRs contribute to the functioning of organisms, (b) how mutations in such regions can cause disease, and (c) how the distinct physico-chemical properties of IDRs can be exploited for applications in various fields such as nanotechnology, material sciences and biotechnology. I am delighted that the 41 papers published in this themed issue all aim to address these challenges either directly or indirectly. The papers cover a spectrum of scientific topics from a wide range of model organisms and report specific discoveries, as well as general principles that can be applicable to a number of other systems. More importantly, the ideas and results presented in this themed issue firmly establish the fact that in addition to structured regions, disordered regions are essential for protein function. For the remaining few sceptics, I am reminded of a quote: ‘‘The difficulty lies not in the new ideas but in escaping from the old ones’’ – JohnMaynard Keynes, Cambridge, UK. I hope that the findings, reviews and approaches presented in this issue of Molecular BioSystems will serve as an inspiration for many scientists involved or interested in this area of research and that you will enjoy reading the papers.

Intrinsically disordered regions as affinity tuners in protein–DNA interactions

Abstract: Intrinsically disordered regions, terminal tails, and flexible linkers are abundant in DNA-binding proteins and play a crucial role by increasing the affinity and specificity of DNA binding. Disordered tails often undergo a disorder-to-order transition during interactions with DNA and improve both the kinetics and thermodynamics of specific DNA binding. The DNA search by proteins that interact nonspecifically with DNA can be supported by disordered tails as well. The disordered tail may increase the overall protein–DNA interface and thus increase the affinity of the protein to the DNA and its sliding propensity while slowing linear diffusion. The exact effect of the disordered tails on the sliding rate depends on the degree of positive charge clustering, as has been shown for homeodomains and p53 transcription factors. The disordered tails, which may be viewed as DNA recognizing subdomains, can facilitate intersegment transfer events that occur via a “monkey bar” mechanism in which the domains bridge two different DNA fragments simultaneously. The “monkey bar” mechanism can be facilitated by internal disordered linkers in multidomain proteins that mediate the cross-talks between the constituent domains and especially their brachiation dynamics and thus their overall capability to search DNA efficiently. The residue sequence of the disordered tails has unique characteristics that were evolutionarily selected to achieve the optimized function that is unique to each protein. Perturbation of the electrostatic characteristics of the disordered tails by post-translational modifications, such as acetylation and phosphorylation, may affect protein affinity to DNA and therefore can serve to regulate DNA recognition. Modifying the disordered protein tails or the flexibility of the inter-domain linkers of multidomain proteins may affect the cross-talk between the constituent domains so as to facilitate the search kinetics of non-specific DNA sequences and increase affinity to the specific sequences.

Human Protein Reference Database and Human Proteinpedia as resources for phosphoproteome analysis

Abstract: Human Protein Reference Database (HPRD) is a rich resource of experimentally proven features of human proteins. Protein information in HPRD includes protein–protein interactions, post-translational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization of human proteins. Although, protein–protein interaction data from HPRD has been widely used by the scientific community, its phosphoproteome data has not been exploited to its full potential. HPRD is one of the largest documentations of human phosphoproteins in the public domain. Currently, phosphorylation data in HPRD comprises of 95 016 phosphosites mapped on to 13 041 proteins. Additionally, enzyme–substrate reactions responsible for 5930 phosphorylation events were also documented. Significant improvements in technologies and high-throughput platforms in biomedical investigations led to an exponential increase of biological data and phosphoproteomic data in recent years. Human Proteinpedia, a community annotation portal developed by us, has also contributed to the significant increase in phosphoproteomic data in HPRD. A large number of phosphorylation events have been mapped on to reference sequences available in HPRD and Human Proteinpedia along with associated protein features. This will provide a platform for systems biology approaches to determine the role of protein phosphorylation in protein function, cell signaling, biological processes and their implication in human diseases. This review aims to provide a composite view of phosphoproteomic data pertaining to human proteins in HPRD and Human Proteinpedia.

Optimized TAL effector nucleases (TALENs) for use in treatment of sickle cell disease

Abstract: TAL effector nucleases (TALENs) represent a new class of artificial nucleases capable of cleaving long, specific target DNA sequences in vivo and are powerful tools for genome editing with potential therapeutic applications. Here we report a pair of custom-designed TALENs for targeted genetic correction of the sickle cell disease mutation in human cells, which represents an example of engineered TALENs capable of recognizing and cleaving a human disease-associated gene. By using a yeast reporter system, a systematic study was carried out to optimize TALEN architecture for maximal in vivo cleavage efficiency. In contrast to the previous reports, the engineered TALENs were capable of recognizing and cleaving target binding sites preceded by A, C or G. More importantly, the optimized TALENs efficiently cleaved a target sequence within the human β-globin (HBB) gene associated with sickle cell disease and increased the efficiency of targeted gene repair by >1000-fold in human cells. In addition, these TALENs showed no detectable cytotoxicity. These results demonstrate the potential of optimized TALENs as a powerful genome editing tool for therapeutic applications.

Intrinsically disordered proteins as molecular shields

Abstract: The broad family of LEA proteins are intrinsically disordered proteins (IDPs) with several potential roles in desiccation tolerance, or anhydrobiosis, one of which is to limit desiccation-induced aggregation of cellular proteins. We show here that this activity, termed molecular shield function, is distinct from that of a classical molecular chaperone, such as HSP70 – while HSP70 reduces aggregation of citrate synthase (CS) on heating, two LEA proteins, a nematode group 3 protein, AavLEA1, and a plant group 1 protein, Em, do not; conversely, the LEA proteins reduce CS aggregation on desiccation, while HSP70 lacks this ability. There are also differences in interaction with client proteins – HSP70 can be co-immunoprecipitated with a polyglutamine-containing client, consistent with tight complex formation, whereas the LEA proteins can not, although a loose interaction is observed by Forster resonance energy transfer. In a further exploration of molecular shield function, we demonstrate that synthetic polysaccharides, like LEA proteins, are able to reduce desiccation-induced aggregation of a water-soluble proteome, consistent with a steric interference model of anti-aggregation activity. If molecular shields operate by reducing intermolecular cohesion rates, they should not protect against intramolecular protein damage. This was tested using the monomeric red fluorescent protein, mCherry, which does not undergo aggregation on drying, but the absorbance and emission spectra of its intrinsic fluorophore are dramatically reduced, indicative of intramolecular conformational changes. As expected, these changes are not prevented by AavLEA1, except for a slight protection at high molar ratios, and an AavLEA1-mCherry fusion protein is damaged to the same extent as mCherry alone. A recent hypothesis proposed that proteomes from desiccation-tolerant species contain a higher degree of disorder than intolerant examples, and that this might provide greater intrinsic stability, but a bioinformatics survey does not support this, since there are no significant differences in the degree of disorder between desiccation tolerant and intolerant species. It seems clear therefore that molecular shield function is largely an intermolecular activity implemented by specialist IDPs, distinct from molecular chaperones, but with a role in proteostasis.

Fuzziness: linking regulation to protein dynamics

Abstract: Proteins are dynamic creatures. Intrinsically disordered proteins (IDPs) function as multiplicity of structures and their activities can only be described by stochastic structure–function relationships. In their complex forms, however, IDPs were thought to lose their plasticity and behave similarly to globular proteins. Although various IDPs indeed fold upon binding, this view is not valid in general. IDPs usually interact with their partners via short motifs, which require malleable environments to function. Consequently, segments of IDPs could retain their disordered state in the complex, a phenomenon termed as fuzziness. Since its recognition, the number of structurally characterized fuzzy complexes, both with protein and DNA, rapidly increases. Here I review recent advances in our understanding of fuzziness. Four basic mechanisms are described how conformationally heterogeneous regions impact specificity or binding affinity of protein complexes. A novel allostery-model is proposed, where the regulatory site modulates the conformational equilibrium of the binding interface without adopting a unique structure. Protein–protein interactions, post-translational modifications or alternative splicing of the highly flexible/disordered regions offer further opportunities for regulation and expand the functional repertoire of fuzzy complexes.

Interaction and photo-induced cleavage studies of a copper based chemotherapeutic drug with human serum albumin: spectroscopic and molecular docking study

Abstract: The interaction of new dinuclear copper(II) complex 1; [Cu2(glygly)2(ppz)(H2O)4]·2H2O, derived from dipeptide (glycyl glycine) and piperazine as a metallopeptide drug with human serum albumin (HSA) was examined by means of fluorescence spectroscopy which revealed that complex 1 has a strong ability to quench the intrinsic fluorescence of HSA through a static quenching procedure. The alterations of HSA secondary structure in the presence of complex 1 were confirmed by UV-visible, FT-IR, CD and 3D fluorescence spectroscopy. The binding constants (K), and binding site number (n), corresponding thermodynamic parameters ΔG, ΔH and ΔS at different temperatures were calculated. The molecular docking technique was utilized to ascertain the mechanism and mode of action towards the molecular target HSA indicating that complex 1 was located at the entrance of site I by electrostatic and hydrophobic forces, consistent with the corresponding experimental results. Complex 1 shows efficient photo-induced HSA cleavage activity, indicating the involvement of hydroxyl radicals as the reactive species. Furthermore, the cytotoxicity of 1 was examined on a panel of human tumor cell lines of different histological origins showing significant GI50 values specifically towards MIAPACA2, A498 and A549 tumor cell lines. These results complement previous biological studies of new specific target metallopeptides, providing additional information about possibilities of their transport and disposition in blood plasma.

Engineering ecosystems and synthetic ecologies.

Abstract: Microbial ecosystems play an important role in nature. Engineering these systems for industrial, medical, or biotechnological purposes are important pursuits for synthetic biologists and biological engineers moving forward. Here we provide a review of recent progress in engineering natural and synthetic microbial ecosystems. We highlight important forward engineering design principles, theoretical and quantitative models, new experimental and manipulation tools, and possible applications of microbial ecosystem engineering. We argue that simply engineering individual microbes will lead to fragile homogenous populations that are difficult to sustain, especially in highly heterogeneous and unpredictable environments. Instead, engineered microbial ecosystems are likely to be more robust and able to achieve complex tasks at the spatial and temporal resolution needed for truly programmable biology.

Towards a robust description of intrinsic protein disorder using nuclear magnetic resonance spectroscopy

Abstract: In order to understand the conformational behaviour of Intrinsically Disordered Proteins (IDPs), it is essential to develop a molecular representation of the partially folded state. Due to the very large number of degrees of conformational freedom available to such a disordered system, this problem is highly underdetermined. Characterisation therefore requires extensive experimental data, and novel analytical tools are required to exploit the specific conformational sensitivity of different experimental parameters. In this review we concentrate on the use of nuclear magnetic resonance (NMR) spectroscopy for the study of conformational behaviour of IDPs at atomic resolution. Each experimental NMR parameter is sensitive to different aspects of the structural and dynamic behaviour of the disordered state and requires specific consideration of the relevant averaging properties of the physical interaction. In this review we present recent advances in the description of disordered proteins and the selection of representative ensembles on the basis of experimental data using statistical coil sampling from flexible-meccano and ensemble selection using ASTEROIDS. Using these tools we aim to develop a unified molecular representation of the disordered state, combining complementary data sets to extract a meaningful description of the conformational behaviour of the protein.

Uncovering the hidden geometry behind metabolic networks.

Abstract: Metabolism is a fascinating cell machinery underlying life and disease and genome-scale reconstructions provide us with a captivating view of its complexity. However, deciphering the relationship between metabolic structure and function remains a major challenge. In particular, turning observed structural regularities into organizing principles underlying systemic functions is a crucial task that can be significantly addressed after endowing complex network representations of metabolism with the notion of geometric distance. Here, we design a cartographic map of metabolic networks by embedding them into a simple geometry that provides a natural explanation for their observed network topology and that codifies node proximity as a measure of hidden structural similarities. We assume a simple and general connectivity law that gives more probability of interaction to metabolite/reaction pairs which are closer in the hidden space. Remarkably, we find an astonishing congruency between the architecture of E. coli and human cell metabolisms and the underlying geometry. In addition, the formalism unveils a backbone-like structure of connected biochemical pathways on the basis of a quantitative cross-talk. Pathways thus acquire a new perspective which challenges their classical view as self-contained functional units.

More than just tails: intrinsic disorder in histone proteins

Abstract: Many biologically active proteins are disordered as a whole, or contain long disordered regions. These intrinsically disordered proteins/regions are very common in nature, abundantly found in all organisms, where they carry out important biological functions. The functions of these proteins complement the functional repertoire of “normal” ordered proteins, and many protein functional classes are heavily dependent on intrinsic disorder. Among these disorder-centric functions are interactions with nucleic acids and protein complex assembly. In this study, we present the results of comprehensive bioinformatics analyses of the abundance and roles of intrinsic disorder in 2007 histones from 746 species. We show that all the members of the histone family are intrinsically disordered proteins. Furthermore, intrinsic disorder is not only abundant in histones, but is absolutely necessary for various histone functions, starting from heterodimerization to formation of higher order oligomers, to interactions with DNA and other proteins, and to posttranslational modifications.

Prediction of chemical–protein interactions: multitarget-QSAR versus computational chemogenomic methods

Abstract: Elucidation of chemical–protein interactions (CPI) is the basis of target identification and drug discovery. It is time-consuming and costly to determine CPI experimentally, and computational methods will facilitate the determination of CPI. In this study, two methods, multitarget quantitative structure–activity relationship (mt-QSAR) and computational chemogenomics, were developed for CPI prediction. Two comprehensive data sets were collected from the ChEMBL database for method assessment. One data set consisted of 81 689 CPI pairs among 50 924 compounds and 136 G-protein coupled receptors (GPCRs), while the other one contained 43 965 CPI pairs among 23 376 compounds and 176 kinases. The range of the area under the receiver operating characteristic curve (AUC) for the test sets was 0.95 to 1.0 and 0.82 to 1.0 for 100 GPCR mt-QSAR models and 100 kinase mt-QSAR models, respectively. The AUC of 5-fold cross validation were about 0.92 for both 176 kinases and 136 GPCRs using the chemogenomic method. However, the performance of the chemogenomic method was worse than that of mt-QSAR for the external validation set. Further analysis revealed that there was a high false positive rate for the external validation set when using the chemogenomic method. In addition, we developed a web server named CPI-Predictor, http://www.lmmd.org/online_services/cpi_predictor/, which is available for free. The methods and tool have potential applications in network pharmacology and drug repositioning.

UPLC-MS metabolic profiling of second trimester amniotic fluid and maternal urine and comparison with NMR spectral profiling for the identification of pregnancy disorder biomarkers

Abstract: We report on the first untargeted UPLC-MS study of 2nd trimester maternal urine and amniotic fluid (AF), to investigate the possible metabolic effects of fetal malformations (FM), gestational diabetes mellitus (GDM) and preterm delivery (PTD). For fetal malformations, considerable metabolite variations were identified in AF and, to a lesser extent, in urine. Using validated PLS-DA models and statistical correlations between UPLC-MS data and previously acquired NMR data, a metabolic picture of fetal hypoxia, enhanced gluconeogenesis, TCA activity and hindered kidney development affecting FM pregnancies was reinforced. Moreover, changes in carnitine, pyroglutamate and polyols were newly noted, respectively, reflecting lipid oxidation, altered placental amino acid transfer and alterations in polyol pathways. Higher excretion of conjugated products in maternal urine was seen suggesting alterations in conjugation reactions. For the pre-diagnostic GDM group, no significant changes were observed, either considering amniotic fluid or maternal urine, whereas, for the pre-PTD group, some newly observed changes were noted, namely, the decrease of particular amino acids and the increase of an hexose (possibly glucose), suggesting alteration in placental amino acid fluxes and a possible tendency for hyperglycemia. This work shows the potential of UPLC-MS for the study of fetal and maternal biofluids, particularly when used in tandem with comparable NMR data. The important roles played by sampling characteristics (e.g. group dimensions) and the specific experimental conditions chosen for MS methods are discussed.

Targeted metabolomics identifies perturbations in amino acid metabolism that sub-classify patients with COPD

Abstract: Background: COPD, a leading cause of mortality is currently assessed by spirometry (forced expiratory volume in 1 second, FEV1). However FEV1 does not correlate with patient mortality. ECLIPSE (Evaluation of Chronic obstructive pulmonary disease to Longitudinally Identify Predictive Surrogate Endpoints) aims to identify biomarkers that correlate with clinically relevant COPD subtypes, and to assess how these may predict disease progression. New methods were developed and validated to evaluate small molecules as potential diagnostic tools in patients with COPD, COPD related cachexia and cancer related cachexia. Methods and findings: quantitative LC-MS/MS was developed to measure 34 amino acids and dipeptides for stratification of patient groups. Subsets of the ECLIPSE patients were used to assess biomarkers of lung obstruction; GOLD IV (n = 30) versus control (n = 30); emphysema (n = 38) versus airways disease (n = 21) and cachexia (n = 30) versus normal body mass index (n = 30). Serum from cachexic (n = 7) and non-cachexic (n = 5) pancreatic cancer patients were included as controls. Targeted LC-MS/MS distinguished GOLD IV patients from controls, patients with and without emphysema and patients with and without cachexia. Glutamine, aspartate and arginine were significantly increased (p < 0.05; FDR adjustment α < 0.1) in cachexia, emphysema and GOLD IV patients and aminoadipate was decreased. Several amino acid concentrations were significantly altered in patients with COPD but not patients with pancreatic cancer (serine, sarcosine, tryptophan, BCAAs and 3-methylhistdine). Increased γ-aminobutyrate (GABA, p < 0.01) levels were specific to cachexia in patients with pancreatic cancer. β-aminoisobutyrate, 1-methylhistidine and asparagine (p < 0.05) were common across the patients with cachexia from both the COPD and pancreatic cancer cohorts. Conclusion: these results demonstrate that a metabolomic fingerprint has potential to stratify patients for the treatment of COPD and may provide a means of assessing response to therapy. GOLD IV patients were distinguished from smoker control subjects, patients with emphysema were distinguished from those without emphysema and COPD patients displaying cachexia were distinguished from those not displaying cachexia. General markers of cachexia were discovered reflecting both COPD- and pancreatic cancer-related cachexia (increased glutamine, aspartate, arginine, and asparagine and decreased aminoadipate, β-aminoisobutyrate and 1-methylhistidine). Metabolomic biomarkers, particularly altered levels of GABA, could be exploited as a way of monitoring treatment efficacy and tumour recurrence for patients with pancreatic cancer experiencing cachexia.

A comprehensive overview of computational protein disorder prediction methods

Abstract: Over the past decade there has been a growing acknowledgement that a large proportion of proteins within most proteomes contain disordered regions. Disordered regions are segments of the protein chain which do not adopt a stable structure. Recognition of disordered regions in a protein is of great importance for protein structure prediction, protein structure determination and function annotation as these regions have a close relationship with protein expression and functionality. As a result, a great many protein disorder prediction methods have been developed so far. Here, we present an overview of current protein disorder prediction methods including an analysis of their advantages and shortcomings. In order to help users to select alternative tools under different circumstances, we also evaluate 23 disorder predictors on the benchmark data of the most recent round of the Critical Assessment of protein Structure Prediction (CASP) and assess their accuracy using several complementary measures.

Disease mutations in disordered regions—exception to the rule?

Abstract: Intrinsically disordered proteins (IDPs) have been implicated in a number of human diseases, including cancer, diabetes, neurodegenerative and cardiovascular disorders. Although for some of these conditions molecular mechanisms are now better understood, the big picture connecting distinct structural properties and functional repertoire of IDPs to pathogenesis and disease progression is still incomplete. Recent studies suggest that signaling and regulatory roles carried out by IDPs require them to be tightly regulated, and that altered IDP abundance may lead to disease. Here, we propose another link between IDPs and disease that takes into account disease-associated missense mutations located in the intrinsically disordered regions. We argue that such mutations are more prevalent and have larger functional impact than previously thought. In addition, we demonstrate that deleterious amino acid substitutions that cause disorder-to-order transitions are particularly enriched among disease mutations compared to neutral polymorphisms. Finally, we discuss potential differences in functional outcomes between disease mutations in ordered and disordered regions, and challenge the conventional structure-centric view of missense mutations.

Alginate modified nanostructured calcium carbonate with enhanced delivery efficiency for gene and drug delivery

Abstract: To improve the performance of nanostructured calcium carbonate in gene delivery, a hydrophilic polysaccharide, alginate, was added to calcium carbonate co-precipitation systems to form alginate/CaCO3/DNA nanoparticles. The size and ζ-potential of the nanoparticles were measured by a zetasizer. Due to the existence of alginate chains which retarded the growth of calcium carbonate based co-precipitates, the alginate/CaCO3/DNA nanoparticles exhibited a decreased size and enhanced stability in the aqueous solution. To evaluate the gene and drug co-delivery ability, doxorubicin hydrochloride (DOX), a water-soluble anticancer drug, was loaded in the nanoparticles to form alginate/CaCO3/DNA/DOX nanoparticles. The in vitrogene transfections mediated by different nanoparticles in 293 T cells and HeLa cells were carried out, using pGL3-Luc as a reporter plasmid. With an appropriate amount of alginate, the gene transfection efficiency of alginate modified nanoparticles could be significantly enhanced as compared with the nanoparticles without alginate modification for the gene delivery systems, as well as the gene and drug co-delivery systems. The study on in vitrocell inhibition effects showed that the cell viability decreased with increasing DOX amount loaded in alginate/CaCO3/DNA/DOX nanoparticles. The alginate modification is a useful strategy to improve the calcium carbonate co-precipitation technique for the preparation of gene and drug delivery systems, and the nanoparticles prepared in this study have promising applications in gene and drug delivery.

Resveratrol downregulates Akt/GSK and ERK signalling pathways in OVCAR-3 ovarian cancer cells

Abstract: Phytochemicals constitute a heterogeneous group of substances with an evident role in human health. Their properties on cancer initiation, promotion and progression are well documented. Particular attention is now devoted to better understand the molecular basis of their anticancer action. In the present work, we studied the effect of resveratrol on the ovarian cancer cell line OVCAR-3 by a proteomic approach. Our findings demonstrate that resveratrol down-regulates the protein cyclin D1 and, in a concentration dependent manner, the phosphorylation levels of protein kinase B (Akt) and glycogen synthase kinase-3β (GSK-3β). The dephosphorylation of these kinases could be responsible for the decreased cyclin D1 levels observed after treatment. We also showed that resveratrol reduces phosphorylation levels of the extracellular signal-regulated kinase (ERK) 1/2. Chemical inhibitors of phosphatidylinositol 3-kinase (PI3K) and ERK both increased the in vitro therapeutic efficacy of resveratrol. Moreover, resveratrol had an inhibitory effect on the AKT phosphorylation in cultured cells derived from the ascites of ovarian cancer patients and in a panel of human cancer cell lines. Thus, resveratrol shows antitumor activity in human ovarian cancer cell lines targeting signalling pathway involved in cell proliferation and drug-resistance.

A metabonomics approach as a means for identification of potential biomarkers for early diagnosis of endometriosis

Abstract: Our present study focuses on the identification of predictive biomarkers in serum for the early diagnosis of endometriosis in a minimally invasive manner using 1H-NMR based metabonomics. PLS-DA modeling of bins obtained from CPMG spectra of serum samples discriminated endometriosis patients from controls with sensitivity and specificity levels of about 80% and 90%, respectively. Compared with those from controls, serum samples from endometriosis patients showed increased levels of lactate, 3-hydroxybutyrate, alanine, leucine, valine, threonine, lysine, glycerophosphatidylcholine, succinic acid and 2-hydroxybutyrate as well as decreased levels of lipids, glucose, isoleucine and arginine. Our work offers valuable information for non-invasive diagnosis of endometriosis and may be of potential benefit to understand pathogenesis of the disease.

Ter-dependent stress response systems: novel pathways related to metal sensing, production of a nucleoside-like metabolite, and DNA-processing

Abstract: The mode of action of the bacterial ter cluster and TelA genes, implicated in natural resistance to tellurite and other xenobiotic toxic compounds, pore-forming colicins and several bacteriophages, has remained enigmatic for almost two decades. Using comparative genomics, sequence-profile searches and structural analysis we present evidence that the ter gene products and their functional partners constitute previously underappreciated, chemical stress response and anti-viral defense systems of bacteria. Based on contextual information from conserved gene neighborhoods and domain architectures, we show that the ter gene products and TelA lie at the center of membrane-linked metal recognition complexes with regulatory ramifications encompassing phosphorylation-dependent signal transduction, RNA-dependent regulation, biosynthesis of nucleoside-like metabolites and DNA processing. Our analysis suggests that the multiple metal-binding and non-binding TerD paralogs and TerC are likely to constitute a membrane-associated complex, which might also include TerB and TerY, and feature several, distinct metal-binding sites. Versions of the TerB domain might also bind small molecule ligands and link the TerD paralog-TerC complex to biosynthetic modules comprising phosphoribosyltransferases (PRTases), ATP grasp amidoligases, TIM-barrel carbon-carbon lyases, and HAD phosphoesterases, which are predicted to synthesize novel nucleoside-like molecules. One of the PRTases is also likely to interact with RNA by means of its Pelota/Ribosomal protein L7AE-like domain. The von Willebrand factor A domain protein, TerY, is predicted to be part of a distinct phosphorylation switch, coupling a protein kinase and a PP2C phosphatase. We show, based on the evidence from numerous conserved gene neighborhoods and domain architectures, that both the TerB and TelA domains have been linked to diverse lipid-interaction domains, such as two novel PH-like and the Coq4 domains, in different bacteria, and are likely to comprise membrane-associated sensory complexes that might additionally contain periplasmic binding-protein-II and OmpA domains. We also show that the TerD and TerB domains and the TerY-associated phosphorylation system are functionally linked to many distinct DNA-processing complexes, which feature proteins with SWI2/SNF2 and RecQ-like helicases, multiple AAA+ ATPases, McrC-N-terminal domain proteins, several restriction endonuclease fold DNases, DNA-binding domains and a type-VII/Esx-like system, which is at the center of a predicted DNA transfer apparatus. These DNA-processing modules and associated genes are predicted to be involved in restriction or suicidal action in response to phages and possibly repairing xenobiotic-induced DNA damage. In some eukaryotes, certain components of the ter system appear to be recruited to function in conjunction with the ubiquitin system and calcium-signaling pathways.

A meta-analysis of caloric restriction gene expression profiles to infer common signatures and regulatory mechanisms

Abstract: Caloric restriction, a reduction in calorie intake without malnutrition, retards age-related degeneration and extends lifespan in several organisms. CR induces multiple changes, yet its underlying mechanisms remain poorly understood. In this work, we first performed a meta-analysis of microarray CR studies in mammals and identified genes and processes robustly altered due to CR. Our results reveal a complex array of CR-induced changes and we re-identified several genes and processes previously associated with CR, such as growth hormone signalling, lipid metabolism and immune response. Moreover, our results highlight novel associations with CR, such as retinol metabolism and copper ion detoxification, as well as hint of a strong effect of CR on circadian rhythms that in turn may contribute to metabolic changes. Analyses of our signatures by integrating co-expression data, information on genetic mutants, and transcription factor binding site analysis revealed candidate regulators of transcriptional modules in CR. Our results hint at a transcriptional module involved in sterol metabolism regulated by Srebf1. A putative regulatory role of Ppara was also identified. Overall, our conserved molecular signatures of CR provide a comprehensive picture of CR-induced changes and help understand its regulatory mechanisms.

Ingenuity pathways analysis of urine metabolomics phenotypes toxicity of Chuanwu in Wistar rats by UPLC-Q-TOF-HDMS coupled with pattern recognition methods

Abstract: Chuanwu (CW), a valuable traditional Chinese medicine (TCM), is the mother root of Aconitum carmichaelii Debx. The cause of CW-induced toxicity is still under ongoing research, although this is limited by the lack of sensitive and reliable biomarkers. Ingenuity pathway analysis (IPA) was performed to analyzing global metabolomics in order to characterize the phenotypically biochemical perturbations and potential mechanisms of the CW-induced toxicity. CW was administered to Wistar rats (0.027 g/200 g and 0.108 g/200 g bw, oral) for 6 months and urine samples were collected. The urinary metabolomics was performed by UPLC-Q-TOF-HDMS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition methods (PCA, PLS-DA, and OPLS-DA), revealing a time- and dose-dependency of the biochemical perturbations induced by CW toxicity. As a result, several metabolites responsible for pentose and glucuronate interconversions, alanine, aspartate and glutamate metabolism, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, purine metabolism, tryptophan metabolism, taurine and hypotaurine metabolism, fructose and mannose metabolism, fatty acid metabolism were characterized, and it was confirmed that biochemical perturbations can be foreseen from these biomarkers. The urinary metabolomics based IPA with pattern recognition methods also revealed that CW produced serious heart and liver toxicity, consistent with clinical biochemistry and histopathology. Significant changes of 17 metabolites were identified and validated as phenotypic biomarkers of CW toxicity. Overall, our work demonstrated the metabolomics has brought enormous opportunities for improved detection of toxicity and biomarker discovery, highlighting the powerful predictive potential of the IPA to study of drug toxicity.

Roles of intrinsic disorder in protein–nucleic acid interactions

Abstract: Interactions between proteins and nucleic acids typify the role of disordered segments, linkers, tails and other entities in the function of complexes that must form with high affinity and specificity but which must be capable of dissociating when no longer needed. While much of the emphasis in the literature has been on the interactions of disordered proteins with other proteins, disorder is also frequently observed in nucleic acids (particularly RNA) and in the proteins that interact with them. The interactions of disordered proteins with DNA most often manifest as molding of the protein onto the B-form DNA structure, although some well-known instances involve remodeling of the DNA structure that seems to require that the interacting proteins be disordered to various extents in the free state. By contrast, induced fit in RNA-protein interactions has been recognized for many years – the existence and prevalence of this phenomenon provides the clearest possible evidence that RNA and its interactions with proteins must be considered as highly dynamic, and the dynamic nature of RNA and its multiplicity of folded and unfolded states is an integral part of its nature and function.