Mol Biosyst [JOURNAL]
Sun
200 papers
Protein subcellular localization prediction using multiple kernel learning based support vector machine.
Hasan MA, Ahmad S, Molla MK
Mol Biosyst · 2017 Mar · PMID 28247893 · Publisher ↗
Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As...
Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As the number of newly discovered proteins has been growing exponentially, which in turns, makes the subcellular localization prediction by purely laboratory tests prohibitively laborious and expensive. In this context, to tackle the challenges, computational methods are being developed as an alternative choice to aid biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging issue, particularly, when query proteins have multi-label characteristics, i.e., if they exist simultaneously in more than one subcellular location or if they move between two or more different subcellular locations. To date, to address this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM) has been employed to provide potential solutions to the protein subcellular localization prediction problem. However, the practicability of an SVM is affected by the challenges of selecting an appropriate kernel and selecting the parameters of the selected kernel. To address this difficulty, in this study, we aimed to develop an efficient multi-label protein subcellular localization prediction system, named as MKLoc, by introducing multiple kernel learning (MKL) based SVM. We evaluated MKLoc using a combined dataset containing 5447 single-localized proteins (originally published as part of the Höglund dataset) and 3056 multi-localized proteins (originally published as part of the DBMLoc set). Note that this dataset was used by Briesemeister et al. in their extensive comparison of multi-localization prediction systems. Finally, our experimental results indicate that MKLoc not only achieves higher accuracy than a single kernel based SVM system but also shows significantly better results than those obtained from other top systems (MDLoc, BNCs, YLoc+). Moreover, MKLoc requires less computation time to tune and train the system than that required for BNCs and single kernel based SVM.
Steady state statistical correlations predict bistability in reaction motifs.
Chakravarty S, Barik D
Mol Biosyst · 2017 Mar · PMID 28246663 · Publisher ↗
Various cellular decision making processes are regulated by bistable switches that take graded input signals and convert them to binary all-or-none responses. Traditionally, a bistable switch generated by a positive feed...
Various cellular decision making processes are regulated by bistable switches that take graded input signals and convert them to binary all-or-none responses. Traditionally, a bistable switch generated by a positive feedback loop is characterized either by a hysteretic signal response curve with two distinct signaling thresholds or by characterizing the bimodality of the response distribution in the bistable region. To identify the intrinsic bistability of a feedback regulated network, here we propose that bistability can be determined by correlating higher order moments and cumulants (≥2) of the joint steady state distributions of two components connected in a positive feedback loop. We performed stochastic simulations of four feedback regulated models with intrinsic bistability and we show that for a bistable switch with variation of the signal dose, the steady state variance vs. covariance adopts a signatory cusp-shaped curve. Further, we find that the (n + 1)th order cross-cumulant vs. nth order cross-cumulant adopts a closed loop structure for at least n = 3. We also propose that our method is capable of identifying systems without intrinsic bistability even though the system may show bimodality in the marginal response distribution. The proposed method can be used to analyze single cell protein data measured at steady state from experiments such as flow cytometry.
Construction and simulation of the Bradyrhizobium diazoefficiens USDA110 metabolic network: a comparison between free-living and symbiotic states.
Yang Y, Hu XP, Ma BG
Mol Biosyst · 2017 Feb · PMID 28244516 · Publisher ↗
Bradyrhizobium diazoefficiens is a rhizobium able to convert atmospheric nitrogen into ammonium by establishing mutualistic symbiosis with soybean. It has been recognized as an important parent strain for microbial agent...
Bradyrhizobium diazoefficiens is a rhizobium able to convert atmospheric nitrogen into ammonium by establishing mutualistic symbiosis with soybean. It has been recognized as an important parent strain for microbial agents and is widely applied in agricultural and environmental fields. In order to study the metabolic properties of symbiotic nitrogen fixation and the differences between a free-living cell and a symbiotic bacteroid, a genome-scale metabolic network of B. diazoefficiens USDA110 was constructed and analyzed. The metabolic network, iYY1101, contains 1031 reactions, 661 metabolites, and 1101 genes in total. Metabolic models reflecting free-living and symbiotic states were determined by defining the corresponding objective functions and substrate input sets, and were further constrained by high-throughput transcriptomic and proteomic data. Constraint-based flux analysis was used to compare the metabolic capacities and the effects on the metabolic targets of genes and reactions between the two physiological states. The results showed that a free-living rhizobium possesses a steady state flux distribution for sustaining a complex supply of biomass precursors while a symbiotic bacteroid maintains a relatively condensed one adapted to nitrogen-fixation. Our metabolic models may serve as a promising platform for better understanding the symbiotic nitrogen fixation of this species.
EnhancerPred2.0: predicting enhancers and their strength based on position-specific trinucleotide propensity and electron-ion interaction potential feature selection.
He W, Jia C
Mol Biosyst · 2017 Mar · PMID 28239713 · Publisher ↗
Enhancers are cis-acting elements that play major roles in upregulating eukaryotic gene expression by providing binding sites for transcription factors and their complexes. Because enhancers are highly cell/tissue specif...
Enhancers are cis-acting elements that play major roles in upregulating eukaryotic gene expression by providing binding sites for transcription factors and their complexes. Because enhancers are highly cell/tissue specific, lack common motifs, and are far from the target gene, the systematic and precise identification of enhancer regions in DNA sequences is a big challenge. In this study, we developed an enhancer prediction method called EnhancerPred2.0 by combining position-specific trinucleotide propensity (PSTNP) information with the electron-ion interaction potential (EIIP) values for trinucleotides, to predict enhancers and their subgroups. To obtain the optimal combination of features, F-score values were used in a two-step wrapper-based feature selection method, which was applied in a high dimensional feature vector from PSTNP and EIIP. Finally, 126 optimized features from PSTNP combined with 32 optimized features from EIIP yielded the best performance for identifying enhancers and non-enhancers, with an overall accuracy (Acc) of 88.27% and a Matthews correlation coefficient (MCC) of 0.77. Additionally, 198 features from PSTNP combined with 37 features from EIIP yielded the best performance for identifying strong and weak enhancers, with an overall Acc of 98.05% and a MCC of 0.96. Rigorous jackknife tests indicated that EnhancerPred2.0 was significantly better than the existing enhancer prediction methods in both overall accuracy and stability.
DNA condensation in live E. coli provides evidence for transertion.
Gorle AK, Bottomley AL, Harry EJ … +3 more , Collins JG, Keene FR, Woodward CE
Mol Biosyst · 2017 Mar · PMID 28232991 · Publisher ↗
Condensation studies of chromosomal DNA in E. coli with a tetranuclear ruthenium complex are carried out and images obtained with wide-field fluorescence microscopy. Remarkably different condensate morphologies resulted,...
Condensation studies of chromosomal DNA in E. coli with a tetranuclear ruthenium complex are carried out and images obtained with wide-field fluorescence microscopy. Remarkably different condensate morphologies resulted, depending upon the treatment protocol. The occurrence of condensed nucleoid spirals in live bacteria provides evidence for the transertion hypothesis.
Elucidating the biosynthetic pathways of volatile organic compounds in Mycobacterium tuberculosis through a computational approach.
Bhatter P, Raman K, Janakiraman V
Mol Biosyst · 2017 Mar · PMID 28225105 · Publisher ↗
Microbial volatile organic compounds (VOCs) have gained prominence in the recent past for their potential use as disease markers. The discovery of microbial VOCs has benefited 'difficult to detect' diseases such as tuber...
Microbial volatile organic compounds (VOCs) have gained prominence in the recent past for their potential use as disease markers. The discovery of microbial VOCs has benefited 'difficult to detect' diseases such as tuberculosis (TB). Few of the identified VOCs of Mycobacterium tuberculosis (Mtb) are currently being explored for their diagnostic potential. However, very little is known about the biosynthesis of these small lipophilic molecules. Here, we propose putative biosynthetic pathways in Mycobacterium tuberculosis for three VOCs, namely methyl nicotinate, methyl phenylacetate and methyl p-anisate, using computational approaches. In particular, we identify S-adenosyl methionine (SAM) transferases that play a crucial role in esterification of the acids to the final product. Our results provide important insights into the specificity of these pathways to Mtb species.
Urinary metabolic signatures and early triage of acute radiation exposure in rat model.
Zhao M, Lau KK, Zhou X … +3 more , Wu J, Yang J, Wang C
Mol Biosyst · 2017 Mar · PMID 28225098 · Publisher ↗
After a large-scale radiological accident, early-response biomarkers to assess radiation exposure over a broad dose range are not only the basis of rapid radiation triage, but are also the key to the rational use of limi...
After a large-scale radiological accident, early-response biomarkers to assess radiation exposure over a broad dose range are not only the basis of rapid radiation triage, but are also the key to the rational use of limited medical resources and to the improvement of treatment efficiency. Because of its high throughput, rapid assays and minimally invasive sample collection, metabolomics has been applied to research into radiation exposure biomarkers in recent years. Due to the complexity of radiobiological effects, most of the potential biomarkers are both dose-dependent and time-dependent. In reality, it is very difficult to find a single biomarker that is both sensitive and specific in a given radiation exposure scenario. Therefore, a multi-parameters approach for radiation exposure assessment is more realistic in real nuclear accidents. In this study, untargeted metabolomic profiling based on gas chromatography-mass spectrometry (GC-MS) and targeted amino acid profiling based on LC-MS/MS were combined to investigate early urinary metabolite responses within 48 h post-exposure in a rat model. A few of the key early-response metabolites for radiation exposure were identified, which revealed the most relevant metabolic pathways. Furthermore, a panel of potential urinary biomarkers was selected through a multi-criteria approach and applied to early triage following irradiation. Our study suggests that it is feasible to use a multi-parameters approach to triage radiation damage, and the urinary excretion levels of the relevant metabolites provide insights into radiation damage and repair.
Understanding the microscopic binding mechanism of hydroxylated and sulfated polybrominated diphenyl ethers with transthyretin by molecular docking, molecular dynamics simulations and binding free energy calculations.
Cao H, Sun Y, Wang L … +3 more , Zhao C, Fu J, Zhang A
Mol Biosyst · 2017 Mar · PMID 28217795 · Publisher ↗
Polybrominated diphenyl ethers (PBDEs), one typical type of persistent environmental contaminant, have toxicological effects such as disrupting thyroid homeostasis in the human body. The high binding affinities of hydrox...
Polybrominated diphenyl ethers (PBDEs), one typical type of persistent environmental contaminant, have toxicological effects such as disrupting thyroid homeostasis in the human body. The high binding affinities of hydroxylated metabolites of PBDEs (OH-PBDEs) with transthyretin (TTR) were considered to be one major reason for their extraordinary capacity of passing through the blood-brain barrier via competitive thyroid hormone (T4) transport protein binding. Recent findings showed that sulfated PBDEs can be formed in human liver cytosol as phase-II metabolites. However, experimentally determined data for the TTR binding potential of the sulfated PBDEs are still not available. Therefore, molecular docking and molecular dynamics (MD) simulations were employed in the present study to probe the molecular basis of TTR interacting with hydroxylated and sulfated PBDEs at the atomic level. The docking scores of LeDock were used to construct the structure-based predictive model. The calculated results showed that the sulfated PBDEs have stronger affinity for TTR than the corresponding OH-PBDEs. Further analysis of structural characteristics based on MD simulations indicated that upon the binding of PBDE metabolites, the stability of TTR was enhanced and the dissociation rate of the tetrameric protein structure was potentially decreased. Subsequent binding free energy calculations implied that van der Waals interactions are the dominant forces for the binding of these metabolites of PBDEs at the T4 site of TTR. The residues Ser117/Ser117' and Lys15/Lys15' were identified, by both residue energy decomposition and computational alanine-scanning mutagenesis methods, as key residues which play an important role in determining the binding orientations of the -OSO group of sulfated PBDEs by formation of either hydrogen bonds or electrostatic interactions, respectively. In general, the combination of docking calculations with MD simulations provided a theoretically toxicological assessment for the metabolites of PBDEs, deep insight into the recognition mechanism of TTR for these compounds, and thus more comprehensive understanding of the thyroid-related toxic effects of PBDEs as well.
Mass spectrometry for the discovery of biomarkers of sepsis.
Ludwig KR, Hummon AB
Mol Biosyst · 2017 Mar · PMID 28207922 · Full text
Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ fa...
Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ failure and death. Diagnostic criteria for sepsis are nonspecific and hinder a timely diagnosis in patients. Therefore, there is currently a large effort to detect biomarkers that can aid physicians in the diagnosis and prognosis of sepsis. Mass spectrometry is often the method of choice to detect metabolomic and proteomic changes that occur during sepsis progression. These "omics" strategies allow for untargeted profiling of thousands of metabolites and proteins from human biological samples obtained from septic patients. Differential expression of or modifications to these metabolites and proteins can provide a more reliable source of diagnostic biomarkers for sepsis. Here, we focus on the current knowledge of biomarkers of sepsis and discuss the various mass spectrometric technologies used in their detection. We consider studies of the metabolome and proteome and summarize information regarding potential biomarkers in both general and neonatal sepsis.
Predicting brain network changes in Alzheimer's disease with link prediction algorithms.
Sulaimany S, Khansari M, Zarrineh P … +4 more , Daianu M, Jahanshad N, Thompson PM, Masoudi-Nejad A
Mol Biosyst · 2017 Mar · PMID 28197591 · Full text
Link prediction is a promising research area for modeling various types of networks and has mainly focused on predicting missing links. Link prediction methods may be valuable for describing brain connectivity, as it cha...
Link prediction is a promising research area for modeling various types of networks and has mainly focused on predicting missing links. Link prediction methods may be valuable for describing brain connectivity, as it changes in Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI). Here, we analyzed 3-tesla whole-brain diffusion-weighted images from 202 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) - 50 healthy controls, 72 with earlyMCI (eMCI) and 38 with lateMCI (lMCI) and 42 AD patients. We introduce a novel approach for Mixed Link Prediction (MLP) to test and define the percent of predictability of each heightened stage of dementia from its previous, less impaired stage, in the simplest case. Using well-known link prediction algorithms as the core of MLP, we propose a new approach that predicts stages of cognitive impairment by simultaneously adding and removing links in the brain networks of elderly individuals. We found that the optimal algorithm, called "Adamic and Adar", had the best fit and most accurately predicted the stages of AD from their previous stage. When compared to the other link prediction algorithms, that mainly only predict the added links, our proposed approach can more inclusively simulate the brain changes during disease by both adding and removing links of the network. Our results are also in line with computational neuroimaging and clinical findings and can be improved for better results.
Phenylephrine-induced cardiac hypertrophy is attenuated by a histone acetylase inhibitor anacardic acid in mice.
Peng C, Luo X, Li S … +1 more , Sun H
Mol Biosyst · 2017 Mar · PMID 28194469 · Publisher ↗
Cardiac hypertrophy is a complex process involving highly coordinated but tight regulation of multiple elements, such as in epigenetics, which make an important contribution to myocardium remodeling and cardiac hypertrop...
Cardiac hypertrophy is a complex process involving highly coordinated but tight regulation of multiple elements, such as in epigenetics, which make an important contribution to myocardium remodeling and cardiac hypertrophy. Epigenetic regulations, particularly histone acetylation, have been implicated in cardiac hypertrophy, however, the exact mechanism is still largely unknown. In the present study, we explored the potential attenuating effects of Chinese herbal extract anacardic acid on phenylephrine-induced cardiac hypertrophy and the underlying mechanism. The mouse cardiac hypertrophy model was established and the hearts were collected from C57BL/6 mice for further analyses. The data showed that anacardic acid modulated the cardiac genes expression and attenuated the phenylephrine-induced cardiac hypertrophy via the suppression of histone acetylases activity and downstream cardiac genes. In addition, anacardic acid abrogated histone and MEF2A acetylation and DNA-binding activity by blocking p300-HAT and PCAF-HAT activities. In addition, anacardic acid normalized the cardiac hypertrophy-related genes expressions (ANP, BNP, cTnT, cTnI, β-MHC, and Cx43) induced by phenylephrine at the level of transcription and translation. In addition, anacardic acid did not affect the blood routine index, hepatic function, renal function, and myocardial enzymes. Therefore, anacardic acid may prove to be a candidate drug to cure hypertrophic cardiomyopathy.
Designing an efficient multi-epitope oral vaccine against Helicobacter pylori using immunoinformatics and structural vaccinology approaches.
Nezafat N, Eslami M, Negahdaripour M … +2 more , Rahbar MR, Ghasemi Y
Mol Biosyst · 2017 Mar · PMID 28194462 · Publisher ↗
Helicobacter pylori is the cunning bacterium that can live in the stomachs of many people without any symptoms, but gradually can lead to gastric cancer. Due to various obstacles, which are related to anti-H. pylori anti...
Helicobacter pylori is the cunning bacterium that can live in the stomachs of many people without any symptoms, but gradually can lead to gastric cancer. Due to various obstacles, which are related to anti-H. pylori antibiotic therapy, recently developing an anti-H. pylori vaccine has attracted more attention. In this study, different immunoinformatics and computational vaccinology approaches were employed to design an efficient multi-epitope oral vaccine against H. pylori. Our multi-epitope vaccine is composed of heat labile enterotoxin IIc B (LT-IIc) that is used as a mucosal adjuvant to enhance vaccine immunogenicity for oral immunization, cartilage oligomeric matrix protein (COMP) to increase vaccine stability in acidic pH of gut, one experimentally protective antigen, OipA, and two hypothetical protective antigens, HP0487 and HP0906, and "CTGKSC" peptide motif that target epithelial microfold cells (M cells) to enhance vaccine uptake from the gut barrier. All the aforesaid segments were joined to each other by proper linkers. The vaccine construct was modeled, validated, and refined by different programs to achieve a high-quality 3D structure. The resulting high-quality model was applied for conformational B-cell epitopes selection and docking analyses with a toll-like receptor 2 (TLR2). Moreover, molecular dynamics studies demonstrated that the protein-TLR2 docked model was stable during simulation time. We believe that our vaccine candidate can induce mucosal sIgA and IgG antibodies, and Th1/Th2/Th17-mediated protective immunity that are crucial for eradicating H. pylori infection. In sum, the computational results suggest that our newly designed vaccine could serve as a promising anti-H. pylori vaccine candidate.
Effect of flexible linker length on the activity of fusion protein 4-coumaroyl-CoA ligase::stilbene synthase.
Guo H, Yang Y, Xue F … +10 more , Zhang H, Huang T, Liu W, Liu H, Zhang F, Yang M, Liu C, Lu H, Zhang Y, Ma L
Mol Biosyst · 2017 Feb · PMID 28181620 · Publisher ↗
In order to elucidate the effect of flexible linker length on the catalytic efficiency of fusion proteins, two short flexible peptide linkers of various lengths were fused between Arabidopsis thaliana 4-coumaroyl-CoA lig...
In order to elucidate the effect of flexible linker length on the catalytic efficiency of fusion proteins, two short flexible peptide linkers of various lengths were fused between Arabidopsis thaliana 4-coumaroyl-CoA ligase (4CL) and Polygonum cuspidatum stilbene synthase (STS) to generate fusion proteins 4CL-(GSG)-STS (n ≤ 5) and 4CL-(GGGGS)-STS (n ≤ 4). The fusion proteins were expressed in both Escherichia coli and Saccharomyces cerevisiae, and their bioactivities were tested in vitro and in vivo using purified proteins and engineered strains, respectively. The catalytic efficiency of the fusions decreased gradually with the increase of GSG or GGGGS repeats. In both engineered S. cerevisiae and E. coli in vivo experiments, the capacity of resveratrol production decreased gradually with increasing linker length. In silico analysis showed that the prediction of homology models of fusion proteins was consistent with the in vitro and in vivo results.
Non-active site mutations disturb the loop dynamics, dimerization, viral budding and egress of VP40 of the Ebola virus.
Balmith M, Soliman ME
Mol Biosyst · 2017 Feb · PMID 28170013 · Publisher ↗
The first account of the dynamic features of the loop region of VP40 of the Ebola virus (EboV) using accelerated molecular dynamics (aMD) simulations is reported herein. Due to its major role in the Ebola life cycle, VP4...
The first account of the dynamic features of the loop region of VP40 of the Ebola virus (EboV) using accelerated molecular dynamics (aMD) simulations is reported herein. Due to its major role in the Ebola life cycle, VP40 is considered a promising therapeutic target. The available experimental data on the N-terminal domain (NTD) loop indicates that mutations K127A, T129A and N130A demonstrate an unrecognized role for NTD-plasma membrane (PM) interaction for efficient VP40-PM localization, oligomerization, matrix assembly and egress. Despite experimental results, the molecular description of VP40 and the information it can provide still remain vague. Therefore, to gain further molecular insight into the effect of mutations on the loop region of VP40 and its effects on the overall protein conformation and VP40 dimerization, aMD simulations and post-dynamic analyses were employed for wildtype (WT) and mutant systems. The results showed significant variations in the presence of mutations as per RMSF, RMSD, R, PCA and distance calculations in comparison to the WT. These results could provide researchers with insight with regards to the conformational aspects concerning VP40 and its close relation to the experimental data. We believe that the results presented in this study will ultimately provide a useful understanding of the structural landscape of the loop region of VP40, which would contribute towards the discovery of novel EboV inhibitors.
Gene essentiality prediction based on fractal features and machine learning.
Yu Y, Yang L, Liu Z … +1 more , Zhu C
Mol Biosyst · 2017 Feb · PMID 28145541 · Publisher ↗
Essential genes are required for the viability of an organism. Accurate and rapid identification of new essential genes is of substantial theoretical interest to synthetic biology and has practical applications in biomed...
Essential genes are required for the viability of an organism. Accurate and rapid identification of new essential genes is of substantial theoretical interest to synthetic biology and has practical applications in biomedicine. Fractals provide facilitated access to genetic structure analysis on a different scale. In this study, machine learning-based methods using solely fractal features are presented and the problem of predicting essential genes in bacterial genomes is evaluated. Six fractal features were investigated to learn the parameters of five supervised classification methods for the binary classification task. The optimal parameters of these classifiers are determined via grid-based searching technique. All the currently available identified genes from the database of essential genes were utilized to build the classifiers. The fractal features were proven to be more robust and powerful in the prediction performance. In a statistical sense, the ELM method shows superiority in predicting the essential genes. Non-parameter tests of the average AUC and ACC showed that the fractal feature is much better than other five compared features sets. Our approach is promising and convenient to identify new bacterial essential genes.
Identification of novel inhibitors of the translationally controlled tumor protein (TCTP): insights from molecular dynamics.
Kumar R, Maurya R, Saran S
Mol Biosyst · 2017 Feb · PMID 28128835 · Publisher ↗
The translationally controlled tumor protein (TCTP) is a highly conserved multifunctional protein, preferentially expressed in mitotically active tissues and is a potential biomarker and a therapeutic target for lung can...
The translationally controlled tumor protein (TCTP) is a highly conserved multifunctional protein, preferentially expressed in mitotically active tissues and is a potential biomarker and a therapeutic target for lung cancers. An understanding of the biology of this molecule and model systems for the screening of drugs is still awaited. In the absence of complete crystal structure, NMR structures as templates were used for homology modeling and MD optimization of both Dictyostelium discoideum and human TCTPs, which was followed by pocket-site prediction, ligand screening and docking. Rescoring of TCTP-ligand complexes was done using MD and MM-PBSA approaches. D. discoideum TCTP was expressed under a constitutive promoter and the endogenous RNA in multicellular structures formed was localized by in situ hybridization. Based on the interactions and binding energy scores, two novel compounds were identified as the best potential inhibitors that could be further used for the development of drug candidates. Inhibition of cell proliferation was observed in the strain overexpressing Dictyostelium TCTP and in situ hybridization results show them to be localized in the prestalk (dying cell population) cells. D. discoideum and human TCTPs share similar dynamic behaviors; overexpression of Dictyostelium TCTP inhibits cell proliferation. D. discoideum could be used as a model system for understanding the biology of this molecule and also for drug screening.
Regulation of lipids is central to replicative senescence.
Lizardo DY, Lin YL, Gokcumen O … +1 more , Atilla-Gokcumen GE
Mol Biosyst · 2017 Feb · PMID 28128379 · Publisher ↗
Cellular replicative senescence, a state of permanent cell-cycle arrest, has been linked to organismal aging, tissue repair and tumorigenesis. In this study, we comparatively investigated the global lipid profiles and mR...
Cellular replicative senescence, a state of permanent cell-cycle arrest, has been linked to organismal aging, tissue repair and tumorigenesis. In this study, we comparatively investigated the global lipid profiles and mRNA content of proliferating and senescent-state BJ fibroblasts. We found that both expression levels of lipid-regulating genes and the abundance of specific lipid families, are actively regulated. We further found that 19 specific polyunsaturated triacylglycerol species constituted the most prominent changes in lipid composition during replicative senescence. Based on the transcriptome analysis, we propose that the activation of CD36-mediated fatty acid uptake and diversion to glycerolipid biosynthesis could be responsible for the accumulation of triacylglycerols during replicative senescence. This, in turn, could be a cellular mechanism to prevent lipotoxicity under increased oxidative stress conditions observed in this process. Our results indicate that regulation of specific lipid species has a central role during replicative senescence.
Small RNA sequencing revealed dysregulated piRNAs in Alzheimer's disease and their probable role in pathogenesis.
Roy J, Sarkar A, Parida S … +2 more , Ghosh Z, Mallick B
Mol Biosyst · 2017 Feb · PMID 28127595 · Publisher ↗
PIWI-interacting RNAs (piRNAs), ∼23-36 nucleotide-long small non-coding RNAs, earlier believed to be germline-specific, have now been identified in somatic cells including neural cells. However, piRNAs have not yet been...
PIWI-interacting RNAs (piRNAs), ∼23-36 nucleotide-long small non-coding RNAs, earlier believed to be germline-specific, have now been identified in somatic cells including neural cells. However, piRNAs have not yet been studied in the human brain (HB) and Alzheimer's disease (AD)-affected brain. In this study, by next-generation small RNA sequencing, 564 and 451 piRNAs were identified in the HB and AD-affected brain respectively. The majority of the neuronal piRNAs have intronic origin wherein primary piRNAs are mostly from the negative strand. piRNAs originating from the coding sequence of mRNAs and tRNAs are highly conserved compared to other genomic contexts. We found 1923 mRNAs significantly down-regulated in AD as the predicted targets of 125 up-regulated piRNAs. The filtering of targets based on our criteria coupled with pathway enrichment analysis of all the predicted targets resulted in five most significant AD-associated pathways enriched with four genes (CYCS, LIN7C, KPNA6, and RAB11A) found to be regulated by four piRNAs. The qRT-PCR study verified the reciprocal expression of piRNAs and their targets. This study provides the first evidence of piRNAs in the HB and AD which will provide the foundation for future studies to unravel the regulatory role of piRNAs in the human brain and associated diseases. The sequencing data have been submitted to the GEO database (Accession no. GSE85075).
Solid support resins and affinity purification mass spectrometry.
Havis S, Moree WJ, Mali S … +1 more , Bark SJ
Mol Biosyst · 2017 Feb · PMID 28124051 · Publisher ↗
Co-affinity purification-mass spectrometry (CoAP-MS) is a primary technology for elucidating the protein-protein interactions that form the basis of all biological processes. A critical component of CoAP-MS is the affini...
Co-affinity purification-mass spectrometry (CoAP-MS) is a primary technology for elucidating the protein-protein interactions that form the basis of all biological processes. A critical component of CoAP-MS is the affinity purification (AP) of the bait protein, usually by immobilization of an antibody to a solid-phase resin. This Minireview discusses common resins, reagents, tagging methods, and their consideration for successful AP of tagged proteins. We discuss our experiences with different solid supports, their impact in AP experiments, and propose areas where chemistry can advance this important technology.
Super RLuc8-sFv; a new luciferase-labeled probe for detection of human CD4+ cells.
Safavi A, Emamzadeh R, Nazari M … +3 more , Ehsani M, Zarkesh-Esfahani SH, Rahgozar S
Mol Biosyst · 2017 Feb · PMID 28112328 · Publisher ↗
The human immunodeficiency virus (HIV) destroys CD4+ lymphocytes and monitoring these cells is one of the best techniques for studying HIV infection. In the present study a novel bioluminescent probe, super RLuc8-sFv, is...
The human immunodeficiency virus (HIV) destroys CD4+ lymphocytes and monitoring these cells is one of the best techniques for studying HIV infection. In the present study a novel bioluminescent probe, super RLuc8-sFv, is developed in order to detect human CD4+ cells by fusion of an anti-human CD4 sFv to the C-terminus of super RLuc8. The results indicate that the probe can bind to CD4+ cells via its sFv domain; also it emits visible light through its signalling domain. Super RLuc8-sFv provides a new gateway for detection of human CD4+ cells using luminometric-based assays and may reduce the difficulties involved in, and the cost of, HIV-related diagnostic tests.
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