Showing papers in "Molecular BioSystems in 2014"

Isothermal amplified detection of DNA and RNA

Abstract: This review highlights various methods that can be used for a sensitive detection of nucleic acids without using thermal cycling procedures, as is done in PCR or LCR. Topics included are nucleic acid sequence-based amplification (NASBA), strand displacement amplification (SDA), loop-mediated amplification (LAMP), Invader assay, rolling circle amplification (RCA), signal mediated amplification of RNA technology (SMART), helicase-dependent amplification (HDA), recombinase polymerase amplification (RPA), nicking endonuclease signal amplification (NESA) and nicking endonuclease assisted nanoparticle activation (NENNA), exonuclease-aided target recycling, Junction or Y-probes, split DNAZyme and deoxyribozyme amplification strategies, template-directed chemical reactions that lead to amplified signals, non-covalent DNA catalytic reactions, hybridization chain reactions (HCR) and detection via the self-assembly of DNA probes to give supramolecular structures. The majority of these isothermal amplification methods can detect DNA or RNA in complex biological matrices and have great potential for use at point-of-care.

KEGG-PATH: Kyoto encyclopedia of genes and genomes-based pathway analysis using a path analysis model

Abstract: The dynamic impact approach (DIA) represents an alternative to overrepresentation analysis (ORA) for functional analysis of time-course experiments or those involving multiple treatments. The DIA can be used to estimate the biological impact of the differentially expressed genes (DEGs) associated with particular biological functions, for example, as represented by the Kyoto encyclopedia of genes and genomes (KEGG) annotations. However, the DIA does not take into account the correlated dependence structure of the KEGG pathway hierarchy. We have developed herein a path analysis model (KEGG-PATH) to subdivide the total effect of each KEGG pathway into the direct effect and indirect effect by taking into account not only each KEGG pathway itself, but also the correlation with its related pathways. In addition, this work also attempts to preliminarily estimate the impact direction of each KEGG pathway by a gradient analysis method from principal component analysis (PCA). As a result, the advantage of the KEGG-PATH model is demonstrated through the functional analysis of the bovine mammary transcriptome during lactation.

Inferring novel lncRNA–disease associations based on a random walk model of a lncRNA functional similarity network

Abstract: Accumulating evidence demonstrates that long non-coding RNAs (lncRNAs) play important roles in the development and progression of complex human diseases, and predicting novel human lncRNA–disease associations is a challenging and urgently needed task, especially at a time when increasing amounts of lncRNA-related biological data are available. In this study, we proposed a global network-based computational framework, RWRlncD, to infer potential human lncRNA–disease associations by implementing the random walk with restart method on a lncRNA functional similarity network. The performance of RWRlncD was evaluated by experimentally verified lncRNA–disease associations, based on leave-one-out cross-validation. We achieved an area under the ROC curve of 0.822, demonstrating the excellent performance of RWRlncD. Significantly, the performance of RWRlncD is robust to different parameter selections. Predictively highly-ranked lncRNA–disease associations in case studies of prostate cancer and Alzheimer's disease were manually confirmed by literature mining, providing evidence of the good performance and potential value of the RWRlncD method in predicting lncRNA–disease associations.

A novel network pharmacology approach to analyse traditional herbal formulae: the Liu-Wei-Di-Huang pill as a case study.

Abstract: Understanding the mechanisms of the pharmacological effects of herbal formulae from traditional Chinese medicine (TCM) is important for their appropriate application. However, this understanding has been impeded by the complex nature of herbal formulae. A herbal formula is a mixture of hundreds of chemical ingredients with multiple potential targets. The effects produced by an entire herbal formula cannot be adequately explained by considering separately each ingredient in it. This is a recognised problem that remains in need of methods to solve it. Here we introduce a holistic analysis method to decipher the molecular mechanisms of herbal formulae. This method combines chemical and therapeutic properties with network pharmacology, using a novel approach to evaluate the importance of the targets and ingredients of herbal formulae. We used the Liu-Wei-Di-Huang (LWDH) pill, a classic herbal formula, as an example to illustrate our method and validated some results by a following experiment. We revealed the core molecular targets and bioprocess network of the pharmacological effects of LWDH and inferred its therapeutic indications. This method provides a novel strategy to understand the mechanisms of herbal formulae in a holistic way and implies new applications of classic herbal formulae.

Identification of bacteriophage virion proteins by the ANOVA feature selection and analysis

Abstract: The bacteriophage virion proteins play extremely important roles in the fate of host bacterial cells. Accurate identification of bacteriophage virion proteins is very important for understanding their functions and clarifying the lysis mechanism of bacterial cells. In this study, a new sequence-based method was developed to identify phage virion proteins. In the new method, the protein sequences were initially formulated by the g-gap dipeptide compositions. Subsequently, the analysis of variance (ANOVA) with incremental feature selection (IFS) was used to search for the optimal feature set. It was observed that, in jackknife cross-validation, the optimal feature set including 160 optimized features can produce the maximum accuracy of 85.02%. By performing feature analysis, we found that the correlation between two amino acids with one gap was more important than other correlations for phage virion protein prediction and that some of the 1-gap dipeptides were important and mainly contributed to the virion protein prediction. This analysis will provide novel insights into the function of phage virion proteins. On the basis of the proposed method, an online web-server, PVPred, was established and can be freely accessed from the website (http://lin.uestc.edu.cn/server/PVPred). We believe that the PVPred will become a powerful tool to study phage virion proteins and to guide the related experimental validations.

Evolutionary game theory: cells as players

Abstract: In two papers we review game theory applications in biology below the level of cognitive living beings. It can be seen that evolution and natural selection replace the rationality of the actors appropriately. Even in these micro worlds, competing situations and cooperative relationships can be found and modeled by evolutionary game theory. Also those units of the lowest levels of life show different strategies for different environmental situations or different partners. We give a wide overview of evolutionary game theory applications to microscopic units. In this first review situations on the cellular level are tackled. In particular metabolic problems are discussed, such as ATP-producing pathways, secretion of public goods and cross-feeding. Further topics are cyclic competition among more than two partners, intra- and inter-cellular signalling, the struggle between pathogens and the immune system, and the interactions of cancer cells. Moreover, we introduce the theoretical basics to encourage scientists to investigate problems in cell biology and molecular biology by evolutionary game theory.

Peroxisomes are juxtaposed to strategic sites on mitochondria.

Abstract: Peroxisomes are ubiquitous and dynamic organelles that house many important pathways of cellular metabolism. In recent years it has been demonstrated that mitochondria are tightly connected with peroxisomes and are defective in several peroxisomal diseases. Indeed, these two organelles share metabolic routes as well as resident proteins and, at least in mammals, are connected via a vesicular transport pathway. However the exact extent of cross-talk between peroxisomes and mitochondria remains unclear. Here we used a combination of high throughput genetic manipulations of yeast libraries alongside high content screens to systematically unravel proteins that affect the transport of peroxisomal proteins and peroxisome biogenesis. Follow up work on the effector proteins that were identified revealed that peroxisomes are not randomly distributed in cells but are rather localized to specific mitochondrial subdomains such as mitochondria–ER junctions and sites of acetyl-CoA synthesis. Our approach highlights the intricate geography of the cell and suggests an additional layer of organization as a possible way to enable efficient metabolism. Our findings pave the way for further studying the machinery aligning mitochondria and peroxisomes, the role of the juxtaposition, as well as its regulation during various metabolic conditions. More broadly, the approaches used here can be easily applied to study any organelle of choice, facilitating the discovery of new aspects in cell biology.

Extracellular matrix density promotes EMT by weakening cell–cell adhesions

Abstract: Epithelial to mesenchymal transition (EMT), the process during which epithelial cells lose adhesions with neighbouring cells and get converted to migratory and invasive cells, is closely tied to cancer progression. Cancer progression is also marked by increased deposition and cross linking of fibrillar extracellular matrix (ECM) proteins including collagen and fibronectin, which lead to increase in ECM density and increased cell–matrix adhesions. Thus, an imbalance between cell–matrix and cell–cell adhesions underlies cancer progression. Though several experimental studies have shown a crosstalk between cell–cell and cell–matrix adhesions, the extent to which changes in ECM density can trigger EMT via formation of cell–matrix adhesions and disassembly of cell–cell adhesions remains incompletely understood. In this paper, we have developed a computational framework for studying modulation of cell–cell adhesion by ECM density, integrating findings from multiple studies that connect ECM-mediated adhesion signaling and growth factor signaling with cell–cell adhesion. Here, we have specifically tracked changes in the levels of the E-cadherin–β catenin (Eβ) complex in response to alterations in ECM density. Our results illustrate a tug-of-war between ECM density and E-cadherin in determining Eβ levels both for a single cell as well as for a cell population, with increase in ligand density weakening cell–cell adhesions and increase in E-cadherin levels counterbalancing the effect of ECM density. Consistent with model predictions, lower levels of membrane to cytoplasmic ratios of E-cadherin were observed in MCF-7 human breast cancer cells plated on substrates with increasing collagen density. By performing simulations for a heterogeneous population consisting of both normal and EMT cells, we demonstrate that ligand density and the fraction of EMT cells collectively determine the scattering potential of a cell population. Taken together, our findings are in support of a model where increase in cell–matrix adhesions negatively regulates cell–cell adhesions thereby contributing to EMT and enhanced cellular invasion.

Multi-spectroscopic and molecular modeling studies on the interaction of antihypertensive drug; methyldopa with calf thymus DNA

Abstract: The interaction of methyldopa [(S)-2-amino-3-(3,4-dihydroxyphenyl)-2-methyl propanoic acid] (MDP), antihypertensive drug, with calf thymus DNA (ct-DNA) was investigated by spectroscopic and viscometric techniques. According to the results arising from the fluorescence spectra, viscosity measurements and molecular modeling studies; we concluded that MDP is a minor groove binder of ct-DNA and preferentially binds to AT rich regions. Ethidium bromide (EB) displacement studies revealed that MDP did not have any effect on EB bound DNA which is indicative of groove binding. This was substantiated by displacement studies with Hoechst 33258, a known minor groove binder. In addition, the thermodynamic and docking parameters showed that hydrophobic interaction via drug aromatic rings inside the DNA minor groove plays a major role in this binding.

Engineering reduced evolutionary potential for synthetic biology.

Abstract: The field of synthetic biology seeks to engineer reliable and predictable behaviors in organisms from collections of standardized genetic parts. However, unlike other types of machines, genetically encoded biological systems are prone to changes in their designed sequences due to mutations in their DNA sequences after these devices are constructed and deployed. Thus, biological engineering efforts can be confounded by undesired evolution that rapidly breaks the functions of parts and systems, particularly when they are costly to the host cell to maintain. Here, we explain the fundamental properties that determine the evolvability of biological systems. Then, we use this framework to review current efforts to engineer the DNA sequences that encode synthetic biology devices and the genomes of their microbial hosts to reduce their ability to evolve and therefore increase their genetic reliability so that they maintain their intended functions over longer timescales.

A red light-controlled synthetic gene expression switch for plant systems

Abstract: On command control of gene expression in time and space is required for the comprehensive analysis of key plant cellular processes. Even though some chemical inducible systems showing satisfactory induction features have been developed, they are inherently limited in terms of spatiotemporal resolution and may be associated with toxic effects. We describe here the first synthetic light-inducible system for the targeted control of gene expression in plants. For this purpose, we applied an interdisciplinary synthetic biology approach comprising mammalian and plant cell systems to customize and optimize a split transcription factor based on the plant photoreceptor phytochrome B and one of its interacting factors (PIF6). Implementation of the system in transient assays in tobacco protoplasts resulted in strong (95-fold) induction in red light (660 nm) and could be instantaneously returned to the OFF state by subsequent illumination with far-red light (740 nm). Capitalizing on this toggle switch-like characteristic, we demonstrate that the system can be kept in the OFF state in the presence of 740 nm-supplemented white light, opening up perspectives for future application of the system in whole plants. Finally we demonstrate the system's applicability in basic research, by the light-controlled tuning of auxin signalling networks in N. tabacum protoplasts, as well as its biotechnological potential for the chemical-inducer free production of therapeutic proteins in the moss P. patens.

Proteome-wide analysis of human disease mutations in short linear motifs: neglected players in cancer?

Abstract: Disease mutations are traditionally thought to impair protein functionality by disrupting the folded globular structure of proteins. However, 22% of human disease mutations occur in natively unstructured segments of proteins known as intrinsically disordered regions (IDRs). This therefore implicates defective IDR functionality in various human diseases including cancer. The functionality of IDRs is partly attributable to short linear motifs (SLiMs), but it remains an open question how much defects in SLiMs contribute to human diseases. A proteome-wide comparison of the distribution of missense mutations from disease and non-disease mutation datasets revealed that, in IDRs, disease mutations are more likely to occur within SLiMs than neutral missense mutations. Moreover, compared to neutral missense mutations, disease mutations more frequently impact functionally important residues of SLiMs, cause changes in the physicochemical properties of SLiMs, and disrupt more SLiM-mediated interactions. Analysis of these mutations resulted in a comprehensive list of experimentally validated or predicted SLiMs disrupted in disease. Furthermore, this in-depth analysis suggests that ‘prostate cancer pathway’ is particularly enriched for proteins with disease-related SLiMs. The contribution of mutations in SLiMs to disease may currently appear small when compared to mutations in globular domains. However, our analysis of mutations in predicted SLiMs suggests that this contribution might be more substantial. Therefore, when analysing the functional impact of mutations on proteins, SLiMs in proteins should not be neglected. Our results suggest that an increased focus on SLiMs in the coming decades will improve our understanding of human diseases and aid in the development of targeted treatments.

Binding of ascorbic acid and α-tocopherol to bovine serum albumin: a comparative study

Abstract: Binding of ascorbic acid (water-soluble antioxidant) and α-tocopherol (lipid-soluble antioxidant) to bovine serum albumin (BSA) has been studied using isothermal titration calorimetry (ITC), in combination with fluorescence spectroscopy, UV-vis absorption spectroscopy and Fourier transform infrared (FT-IR) spectroscopy. Thermodynamic investigations reveal that ascorbic acid/α-tocopherol binding to BSA is driven by favorable enthalpy and unfavorable entropy, and the major driving forces are hydrogen bonding and van der Waals forces. For ascorbic acid, the interaction is characterized by a high number of binding sites, which suggests that binding occurs by a surface adsorption mechanism that leads to coating of the protein surface. For α-tocopherol, one molecule of α-tocopherol combines with one molecule of BSA and no more α-tocopherol binding to BSA occurs at concentration ranges used in this study. Fluorescence experiments suggest that ascorbic acid has predominantly a “sphere of action” quenching mechanism, whereas, for α-tocopherol, the quenching mechanism is “static quenching” and due to the formation of a ground state complex. Additionally, as shown by the UV-vis absorption, synchronous fluorescence spectroscopy, and FT-IR, ascorbic acid and α-tocopherol may induce conformational and microenvironmental changes of BSA.

A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes

Abstract: In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.

A proteomic survey of widespread protein aggregation in yeast.

Abstract: Many normally cytosolic yeast proteins form insoluble intracellular bodies in response to nutrient depletion, suggesting the potential for widespread protein aggregation in stressed cells. Nearly 200 such bodies have been found in yeast by screening libraries of fluorescently tagged proteins. In order to more broadly characterize the formation of these bodies in response to stress, we employed a proteome-wide shotgun mass spectrometry assay in order to measure shifts in the intracellular solubilities of endogenous proteins following heat stress. As quantified by mass spectrometry, heat stress tended to shift the same proteins into insoluble form as did nutrient depletion; many of these proteins were also known to form foci in response to arsenic stress. Affinity purification of several foci-forming proteins showed enrichment for co-purifying chaperones, including Hsp90 chaperones. Tests of induction conditions and co-localization of metabolic enzymes participating in the same metabolic pathways suggested those foci did not correspond to multi-enzyme organizing centers. Thus, in yeast, the formation of stress bodies appears common across diverse, normally diffuse cytoplasmic proteins and is induced by multiple types of cell stress, including thermal, chemical, and nutrient stress.

Fluctuation of multiple metabolic pathways is required for Escherichia coli in response to chlortetracycline stress

Abstract: Bacterial antibiotic resistance has become a worldwide challenge with the overuse and misuse of drugs. Several mechanisms for the resistance are revealed, but information regarding the bacterial global response to antibiotics is largely absent. In this study, we characterized the differential proteome of Escherichia coli K12 BW25113 in response to chlortetracycline stress using isobaric tags for relative and absolute quantitation labeling quantitative proteomics technology. A total of 723 proteins including 10763 peptides were identified with 184 decreasing and 147 increasing in abundance by liquid chromatography matrix assisted laser desorption ionization mass spectrometry. Most interestingly, crucial metabolic pathways such as the tricarboxylic acid cycle, pyruvate metabolism and glycolysis/gluconeogenesis sharply fluctuated, while the ribosome protein complexes contributing to the translation process were generally elevated in chlortetracycline stress, which is known for a compensative tactic due to the action of chlortetracycline on the ribosome. Further antimicrobial susceptibility assays validated the role of differential proteins in metabolic pathways using genetically modified mutants of gene deletion of these differential proteins. Our study demonstrated that the down-regulation of metabolic pathways was a part of the global response and played an important role in the antibiotics resistance. These results indicate that reverting of these fluctuated pathways may become a novel strategy to combat antibiotic-resistant bacteria.

Molecular docking and molecular dynamics studies on β-lactamases and penicillin binding proteins

Abstract: Bacterial resistance to β-lactam antibiotics poses a serious threat to human health. Penicillin binding proteins (PBPs) and β-lactamases are involved in both antibacterial activity and mediation of β-lactam antibiotic resistance. The two major reasons for resistance to β-lactams include: (i) pathogenic bacteria expressing drug insensitive PBPs rendering β-lactam antibiotics ineffective and (ii) production of β-lactamases along with alteration of their specificities. Thus, there is an urgent need to develop newer β-lactams to overcome the challenge of bacterial resistance. Therefore the present study aims to identify the binding affinity of β-lactam antibiotics with different types of PBPs and β-lactamases. In this study, cephalosporins and carbapenems are docked into PBP2a of Staphylococcus aureus, PBP2b and PBP2x of Streptococcus pneumoniae and SHV-1 β-lactamase of Escherichia coli. The results reveal that Ceftobiprole can efficiently bind to PBP2a, PBP2b and PBP2x and not strongly to SHV-1 β-lactamase. Furthermore, molecular dynamics (MD) simulations are performed to refine the binding mode of the docked complex structure and to observe the differences in the stability of free PBP2x and Ceftobiprole bound PBP2x. MD simulation supports the greater stability of the Ceftobiprole–PBP2x complex compared to free PBP2x. This work demonstrates that potential β-lactam antibiotics can efficiently bind to different types of PBPs for circumventing β-lactam resistance and opens avenues for the development of newer antibiotics that can target bacterial pathogens.

Understanding and applying tyrosine biochemical diversity

Abstract: This review highlights some of the recent advances made in our understanding of the diversity of tyrosine biochemistry and shows how this has inspired novel applications in numerous areas of molecular design and synthesis, including chemical biology and bioconjugation. The pathophysiological implications of tyrosine biochemistry will be presented from a molecular perspective and the opportunities for therapeutic intervention explored.

Improved cyclopropene reporters for probing protein glycosylation

Abstract: Cyclopropenes have emerged as a new class of bioorthogonal chemical reporters. These strained rings can be metabolically introduced into target biomolecules and covalently modified via mild cycloaddition chemistries. While versatile, existing cyclopropene scaffolds are inefficient reporters of protein glycosylation, owing to their branched structures and sluggish rates of reactivity. Here we describe a set of cyclopropenes for the robust detection of glycans on cell surfaces and isolated proteins. These scaffolds comprise carbamate linkages that are compatible with cellular biosynthetic pathways and exhibit rapid cycloaddition rates. Furthermore, these probes can be used in tandem with other classic bioorthogonal motifs—including azides and alkynes—to examine multiple biomolecules in tandem.

The intrinsic disorder status of the human hepatitis C virus proteome

Abstract: Many viral proteins or their biologically important regions are disordered as a whole, or contain long disordered regions. These intrinsically disordered proteins/regions do not possess unique structures and possess functions that complement the functional repertoire of "normal" ordered proteins and domains, with many protein functional classes being heavily dependent on the intrinsic disorder. Viruses commonly use these highly flexible regions to invade the host organisms and to hijack various host systems. These disordered regions also help viruses in adapting to their hostile habitats and to manage their economic usage of genetic material. In this article, we focus on the structural peculiarities of proteins from human hepatitis C virus (HCV) and use a wide spectrum of bioinformatics techniques to evaluate the abundance of intrinsic disorder in the completed proteomes of several human HCV genotypes, to analyze the peculiarities of disorder distribution within the individual HCV proteins, and to establish potential roles of the structural disorder in functions of ten HCV proteins. We show that the intrinsic disorder or increased flexibility is not only abundant in these proteins, but is also absolutely necessary for their functions, playing a crucial role in the proteolytic processing of the HCV polyprotein, the maturation of the individual HCV proteins, and being related to the posttranslational modifications of these proteins and their interactions with DNA, RNA, and various host proteins.

An increased ratio of serum miR-21 to miR-181a levels is associated with the early pathogenic process of chronic obstructive pulmonary disease in asymptomatic heavy smokers.

Abstract: Heavy smoking is associated with the development of chronic obstructive pulmonary disease (COPD). However, there is no valuable biomarker for evaluating COPD development in heavy smokers because they are usually asymptomatic. This study is aimed at evaluating whether the levels of serum miRNAs can serve as biomarkers for predicting the occurrence of COPD. A rat model of emphysema was induced by enforced smoking, and the dynamic miRNAs expression profile at different stages of emphysema with varying periods of smoking were analyzed by microarray and quantitative real-time polymerase chain reaction (qRT-PCR). The differentially expressing miRNAs were analyzed using Gene Ontology and the KEGG PATHWAY database. The levels of three serum candidate miRNAs were measured by qRT-PCR in 41 healthy controls (HC), 40 asymptomatic heavy smokers, and 49 COPD patients. Following smoking for varying periods, different severities of lung emphysema were observed in different groups of rats, accompanied by altered levels of some serum miRNAs associated with regulating some pathways. Furthermore, the levels of miR-21 were significantly higher in the COPD patients and asymptomatic heavy smokers than in the HC (P < 0.001), while the levels of miR-181a were significantly lower in the COPD patients and asymptomatic heavy smokers than in the HC (P < 0.001). Accordingly, the levels of serum miR-21 and miR-181a as well as their ratios had a high sensitivity (0.854) and specificity (0.850) for evaluating the development of COPD. Our data suggest that the levels of serum miR-21 and miR-181a may be valuable for evaluating the development of COPD in heavy smokers.

TGF-β upregulates miR-182 expression to promote gallbladder cancer metastasis by targeting CADM1

Abstract: Transforming growth factor β (TGF-β) plays important roles in tumor metastasis by regulating miRNAs expression. miR-182 is an important molecule in the regulation of cancer progression. The aim of the study is to assess the role of miR-182 in TGF-β-induced cancer metastasis. In the present study, we found that miR-182 levels are significantly upregulated in GBC tissues compared with normal controls, and miR-182 expression is remarkably increased in primary tumors that subsequently metastasized, when compared to those primary tumors that did not metastasize. TGF-β induces miR-182 expression in GBC cells, and overexpression of miR-182 promotes GBC cell migration and invasion, whereas miR-182 inhibition suppresses TGF-β-induced cancer cell migration and invasion. The blockage of miR-182 by a specific inhibitor effectively inhibits pulmonary metastases in vivo. We further identified that the cell adhesion molecule1 (CADM1) is a new target gene of miR-182. miR-182 negatively regulates CADM1 expression in vitro and in vivo. Importantly, re-expression of CADM1 in GBC cells partially abrogates miR-182-induced cell invasion. Conclusions: miR-182 is an important mediator of GBC metastasis, thus offering a new target for the development of therapeutic agents against GBC.

Prioritizing candidate disease miRNAs by integrating phenotype associations of multiple diseases with matched miRNA and mRNA expression profiles

Abstract: MicroRNAs (miRNAs) have been validated to show widespread disruption of function in many cancers. However, despite concerted efforts to develop prioritization approaches based on a priori knowledge of disease-associated miRNAs, uncovering oncogene or tumor-suppressor miRNAs remains a challenge. Here, based on the assumption that diverse diseases with phenotype associations show similar molecular mechanisms, we present an approach for the systematic prioritization of disease-specific miRNAs by using known disease genes and context-dependent miRNA-target interactions derived from matched miRNA and mRNA expression data, independent of known disease miRNAs. After collecting matched miRNA and mRNA expression data for 11 cancer types, we applied this approach to systematically prioritize miRNAs involved in these cancers. Our approach yielded an average area under the ROC curve (AUC) of 75.84% according to known disease miRNAs from the miR2Disease database, with the highest AUC (80.93%) for pancreatic cancer. Moreover, we assessed the sensitivity and specificity as well as the integrative importance of this approach. Comparative analyses also showed that our method is comparable to previous methods. In summary, we provide a novel method for prioritization of disease-related miRNAs that can help researchers better understand the important roles of miRNAs in human disease.

Effects of Tet-induced oxidation products of 5-methylcytosine on Dnmt1- and DNMT3a-mediated cytosine methylation.

Abstract: We investigated systematically the effects of Tet-induced oxidation products of 5-methylcytosine on Dnmt1- and DNMT3a-mediated cytosine methylation in synthetic duplex DNA. We found that the replacement of 5-methylcytosine at a CpG site with a 5-hydroxymethylcytosine, 5-formylcytosine, 5-carboxylcytosine or 5-hydroxymethyluracil resulted in altered methylation of cytosine at both the opposite and the neighboring CpG sites. Our results provided important new knowledge about the implications of the 5-methylcytosine oxidation products in maintenance cytosine methylation.

Relationship between the lipidome, inflammatory markers and insulin resistance.

Abstract: The objectives of the present study were to (1) examine the effects of the phenotypic factors age, gender and BMI on the lipidomic profile and (2) investigate the relationship between the lipidome, inflammatory markers and insulin resistance. Specific ceramide, phosphatidylcholine and phosphatidylethanolamine lipids were increased in females relative to males and specific lysophosphatidylcholine, lysophosphatidylethanolamine, phosphatidylcholine and phosphatidylethanolamine lipids decreased as BMI increased. However, age had a minimal effect on the lipid profile with significant differences found in only two lipid species. Network analysis revealed strong negative correlations between the inflammatory markers CRP, TNF-α, resistin and MCP-1 and lipids in the LPC, PC and PE classes, whereas IL-8 formed positive correlations with lipids from the CER and SM classes. Further analysis revealed that LPC a C18:1 and PE ae C40:6 were highly associated with insulin resistance as indicated by HOMA-IR score. The present study identified lipids that are affected by BMI and gender and identified a series of lipids which had significant relationships with inflammatory markers. LPC a C18:1 and PE ae C40:6 were found to be highly associated with insulin resistance pointing to the possibility that the alterations in these specific lipids may play a role in the development of insulin resistance.

GC-MS based metabolomics identification of possible novel biomarkers for schizophrenia in peripheral blood mononuclear cells.

Abstract: Schizophrenia is a debilitating mental disorder. Currently, the lack of disease biomarkers to support objective laboratory tests constitutes a bottleneck in the clinical diagnosis of schizophrenia. Here, a gas chromatography-mass spectrometry (GC-MS) based metabolomic approach was applied to characterize the metabolic profile of schizophrenia subjects (n = 69) and healthy controls (n = 85) in peripheral blood mononuclear cells (PBMCs) to identify and validate biomarkers for schizophrenia. Multivariate statistical analysis was used to visualize group discrimination and to identify differentially expressed metabolites in schizophrenia subjects relative to healthy controls. The multivariate statistical analysis demonstrated that the schizophrenia group was significantly distinguishable from the control group. In total, 18 metabolites responsible for the discrimination between the two groups were identified. These differential metabolites were mainly involved in energy metabolism, oxidative stress and neurotransmitter metabolism. A simplified panel of PBMC metabolites consisting of pyroglutamic acid, sorbitol and tocopherol-α was identified as an effective diagnostic tool, yielding an area under the receiver operating characteristic curve (AUC) of 0.82 in the training samples (45 schizophrenia subjects and 50 healthy controls) and 0.71 in the test samples (24 schizophrenic patients and 35 healthy controls). Taken together, these findings help to develop diagnostic tools for schizophrenia.

An integrated molecular dynamics, principal component analysis and residue interaction network approach reveals the impact of M184V mutation on HIV reverse transcriptase resistance to lamivudine.

Abstract: The emergence of different drug resistant strains of HIV-1 reverse transcriptase (HIV RT) remains of prime interest in relation to viral pathogenesis as well as drug development. Amongst those mutations, M184V was found to cause a complete loss of ligand fitness. In this study, we report the first account of the molecular impact of M184V mutation on HIV RT resistance to 3TC (lamivudine) using an integrated computational approach. This involved molecular dynamics simulation, binding free energy analysis, principle component analysis (PCA) and residue interaction networks (RINs). Results clearly confirmed that M184V mutation leads to steric conflict between 3TC and the beta branched side chain of valine, decreases the ligand (3TC) binding affinity by ∼7 kcal mol(-1) when compared to the wild type, changes the overall conformational landscape of the protein and distorts the native enzyme residue-residue interaction network. The comprehensive molecular insight gained from this study should be of great importance in understanding drug resistance against HIV RT as well as assisting in the design of novel reverse transcriptase inhibitors with high ligand efficacy on resistant strains.

Adjustment of carbon fluxes to light conditions regulates the daily turnover of starch in plants: a computational model

Abstract: In the light, photosynthesis provides carbon for metabolism and growth. In the dark, plant growth depends on carbon reserves that were accumulated during previous light periods. Many plants accumulate part of their newly-fixed carbon as starch in their leaves in the day and remobilise it to support metabolism and growth at night. The daily rhythms of starch accumulation and degradation are dynamically adjusted to the changing light conditions such that starch is almost but not totally exhausted at dawn. This requires the allocation of a larger proportion of the newly fixed carbon to starch under low carbon conditions, and the use of information about the carbon status at the end of the light period and the length of the night to pace the rate of starch degradation. This regulation occurs in a circadian clock-dependent manner, through unknown mechanisms. We use mathematical modelling to explore possible diurnal mechanisms regulating the starch level. Our model combines the main reactions of carbon fixation, starch and sucrose synthesis, starch degradation and consumption of carbon by sink tissues. To describe the dynamic adjustment of starch to daily conditions, we introduce diurnal regulators of carbon fluxes, which modulate the activities of the key steps of starch metabolism. The sensing of the diurnal conditions is mediated in our model by the timer α and the “dark sensor” β, which integrate daily information about the light conditions and time of the day through the circadian clock. Our data identify the β subunit of SnRK1 kinase as a good candidate for the role of the dark-accumulated component β of our model. The developed novel approach for understanding starch kinetics through diurnal metabolic and circadian sensors allowed us to explain starch time-courses in plants and predict the kinetics of the proposed diurnal regulators under various genetic and environmental perturbations.

Interaction of the 5-fluorouracil analog 5-fluoro-2′-deoxyuridine with ‘N’ and ‘B’ isoforms of human serum albumin: a spectroscopic and calorimetric study

Abstract: Drugs and metabolites are transported in the blood by plasma proteins, such as human serum albumin (HSA). The uridine analog 2′dFUrd, which is a cytotoxic prodrug metabolite of capecitabine, has remarkable activity against solid tumors when administered orally. We report the results of an in vitro experimental study on the interactions of 2′-dFUrd with the N-isoform (at pH 7.4) and B-isoform (at pH 9.0) of HSA, investigated using fluorescence spectroscopy, circular dichroism (CD), isothermal titration calorimetry (ITC), differential scanning calorimetry (DSC), and molecular docking. The binding constant (Kb) was higher for the N-isoform than for the B-isoform. Thermodynamic parameters, such as enthalpy change (ΔH°), entropy change (ΔS°), and Gibbs free energy change (ΔG°), were also calculated for both isoform interactions using calorimetric techniques. The thermostabilities of HSA and the HSA–2′dFUrd complex were found to be higher for the N-isoform. The interaction of 2′dFUrd with HSA was also explored in molecular docking studies, which revealed that 2′dFUrd was bound to the Sudlow site I in subdomain IIA through multiple modes of interaction, such as hydrophobic interactions and hydrogen bonding. These results suggest that 2′dFUrd has higher binding affinity for the N-isoform of HSA.

NMR-based metabolomics and LC-MS/MS quantification reveal metal-specific tolerance and redox homeostasis in Chlorella vulgaris.

Abstract: Live green algae are promising candidates for phytoremediation, but a suitable algal species which bio-accumulates high concentrations of heavy metals, and survives well in industrial water is yet to be identified Potential metabolic engineering may be applied to improve algal phytoremediation performance, but the metal tolerance and bioaccumulation mechanisms in green algae have to be first fully understood In this study, NMR-based metabolomics was used to study the effect of different metal species (copper, cadmium and lead) and metal concentrations in green microalgae, Chlorella vulgaris High Cu concentrations influenced substantial decrease in organic osmolytes (betaine and glycerophosphocholine), which indicated Cu-induced redox imbalance Accompanying redox imbalance, growth inhibition and photosynthesis impairments in Cu-spiked C vulgaris revealed a clear relationship between Cu toxicity and redox homeostasis As these metabolic changes were less prominent in Cd and Pb-spiked cultures, we inferred metal-specific toxicity in C vulgaris, where redox active Cu(2+) is more potent than non-redox active Cd(2+) and Pb(2+) in causing redox imbalance Subsequently, ICP-MS and LC-MS/MS quantification shed light on the metal-specific bioaccumulation and detoxification mechanisms The metal bioconcentration factor (BCF) correlated well with the phytochelatin (PC) content in Cu and Cd-spiked C vulgaris biomass High BCF and PC levels with increasing Cu and Cd exposure concentrations indicated that PCs played a significant role in Cu and Cd bioaccumulation and detoxification In contrast, the undetectable PC levels in Pb-spiked cultures despite high Pb BCF suggest an alternative detoxification mechanism for Pb: either by passive absorption to the algal cell wall or interaction with glutathione (GSH)