Regulation of tight junction assembly and epithelial morphogenesis by the heat shock protein Apg-2

Background  

Tight junctions are required for epithelial barrier formation and participate in the regulation of signalling mechanisms that control proliferation and differentiation. ZO-1 is a tight junction-associated adaptor protein that regulates gene expression, junction assembly and epithelial morphogenesis. We have previously demonstrated that the heat shock protein Apg-2 binds ZO-1 and thereby regulates its role in cell proliferation. Here, we addressed the question whether Apg-2 is also important for junction formation and epithelial morphogenesis.     

Abundance-based Classifier for the Prediction of Mass Spectrometric Peptide Detectability Upon Enrichment (PPA)

The function of a large percentage of proteins is modulated by post-translational modifications (PTMs). Currently, mass spectrometry (MS) is the only proteome-wide technology that can identify PTMs. Unfortunately, the inability to detect a PTM by MS is not proof that the modification is not present. The detectability of peptides varies significantly making MS potentially blind to a large fraction of peptides. Learning from published algorithms that generally focus on predicting the most detectable peptides we developed a tool that incorporates protein abundance into the peptide prediction algorithm with the aim to determine the detectability of every peptide within a protein. We tested our tool, “Peptide Prediction with Abundance” (PPA), on in-house acquired as well as published data sets from other groups acquired on different instrument platforms. Incorporation of protein abundance into the prediction allows us to assess not only the detectability of all peptides but also whether a peptide of interest is likely to become detectable upon enrichment. We validated the ability of our tool to predict changes in protein detectability with a dilution series of 31 purified proteins at several different concentrations. PPA predicted the concentration dependent peptide detectability in 78% of the cases correctly, demonstrating its utility for predicting the protein enrichment needed to observe a peptide of interest in targeted experiments. This is especially important in the analysis of PTMs. PPA is available as a web-based or executable package that can work with generally applicable defaults or retrained from a pilot MS data set.Post-translational modification (PTM)¹ of proteins is a key regulatory mechanism in the vast majority of biological processes. Historically, to follow PTMs, site-specific antibodies had to be generated in a time-consuming and laborious process associated with high failure rates. Mass spectrometry (MS) holds enormous promise in PTM analysis as it is currently the only technique that has the ability to both discover, localize, and quantify proteome-wide modifications (1). Recent advances in instrumentation and method optimization makes it possible to detect the complete yeast proteome within one hour (2), an ever increasing proportion of the human proteome (3–6), and more than 10,000 phosphorylation sites in a single MS experiment (7, 8). As a result one of the major publicly available databases (www.phosphosite.org (9)) has curated >200,000 phosphorylation sites.Although the number of proteins and PTMs that can be identified is impressive, many modifications have still not been identified in any MS-based experiment. The identification and quantification of biologically relevant modifications is challenging for three reasons: (1) many proteins of interest are of very low abundance rendering them difficult to detect and quantify; (2) many modifications sites are present at substoichiometric quantities, further reducing their detectability; and (3) as large scale proteomics is based on the detection of peptides after a proteolytic digest, and the detectability of a peptide is determined by its physiochemical properties (10), many peptides from highly abundant proteins are never detected. This is particularly important, as there is a shift in the use of MS-based proteomics from large scale, unbiased, discovery-focused experiments toward directed experiments for accurate and precise quantification of biologically relevant PTMs. Protein and peptide enrichment strategies and/or targeted MS experiments like single reaction monitoring (SRM) (11) have increased the number of detectable peptides; however, both of these methods are laborious, and often not successful, that is, the peptide carrying the modification of interest is still not observed as it is fundamentally very difficult to detect.Protein enrichment is the method choice for most experimentalists, but there is no current way to determine whether this is likely to succeed prior to engaging in lengthy biochemical and/or analytical experiments. In an effort to gauge the chances of success for detecting a particular peptide we sought to develop an algorithm that can predict both the chances of detecting a particular peptide and, more importantly, what enrichment it would take to detect a particular peptide that is not easily detected. Here we present such a tool that predicts the detectability and estimates an enrichment factor, i.e. an increase in signal over the background that is necessary to actually detect a particular peptide. Our algorithm development was motivated by two premises: (1) In silico methods have been developed that focus on the prediction of easily detectable “proteotypic” peptides (peptides that are likely to provide the best detection sensitivity) with good accuracy (12–15). (2) Comprehensive proteome studies have shown that the number of detected peptides per protein, and thus the sequence coverage, varies with protein abundance (which is the basis for spectral counting-based protein quantification (16, 17)). We find that incorporation of protein abundance in a peptide classification tool improves the accuracy of the prediction of peptide detectability allowing us to predict the detectability of all peptides within a protein as well as the amount of enrichment needed to detect a peptide of interest.We used a set of 120 purified in vitro expressed proteins as a training set to develop a prediction tool. We deliver this in the form of a web-based interface that provides information about: (1) the probability of detecting the different tryptic peptides of a protein, and (2) the fold enrichment that would be required to bring a peptide of interest into the detectable range. This tool will help guide researchers in their efforts to monitor particular peptides and their modified cognates by MS, specifically, in prioritizing their efforts toward enriching proteins where they would be likely to be able to detect a peptide or modification of interest.     

Metagenomic taxonomic classification using extreme learning machines

Next-generation sequencing technologies have allowed researchers to determine the collective genomes of microbial communities co-existing within diverse ecological environments. Varying species abundance, length and complexities within different communities, coupled with discovery of new species makes the problem of taxonomic assignment to short DNA sequence reads extremely challenging. We have developed a new sequence composition-based taxonomic classifier using extreme learning machines referred to as TAC-ELM for metagenomic analysis. TAC-ELM uses the framework of extreme learning machines to quickly and accurately learn the weights for a neural network model. The input features consist of GC content and oligonucleotides. TAC-ELM is evaluated on two metagenomic benchmarks with sequence read lengths reflecting the traditional and current sequencing technologies. Our empirical results indicate the strength of the developed approach, which outperforms state-of-the-art taxonomic classifiers in terms of accuracy and implementation complexity. We also perform experiments that evaluate the pervasive case within metagenome analysis, where a species may not have been previously sequenced or discovered and will not exist in the reference genome databases. TAC-ELM was also combined with BLAST to show improved classification results. Code and Supplementary Results: http://www.cs.gmu.edu/~mlbio/TAC-ELM (BSD License).     

Novel Ocimumoside A and B as anti-stress agents: modulation of brain monoamines and antioxidant systems in chronic unpredictable stress model in rats

Therapies targeting central stress mechanisms are fundamental for the development of successful treatment strategies. Ocimum sanctum (OS) is an Indian medicinal plant traditionally used for the treatment of various stress-related conditions. Previously, we have isolated and characterized three OS compounds; Ocimarin, Ocimumoside A and Ocimumoside B. However, their role in modulating chronic stress-induced central changes is unexplored. Thus, in the present study the efficacy of these OS compounds have been evaluated on the chronic unpredictable stress (CUS)-induced alterations in the monoaminergic and antioxidant systems in the frontal cortex, striatum and hippocampus, along with the changes in the plasma corticosterone levels. CUS (two different types of stressors daily for seven days) resulted in a significant elevation of plasma corticosterone level, which was reversed to control levels by pretreatment with Ocimumoside A and B (40 mg/kg p.o.), while Ocimarin showed no effect. The levels of NA, DA and 5-HT were significantly decreased in all the three brain regions by CUS, with a selective increase of DA metabolites. A significant decrease in the glutathione (GSH) content, the activities of superoxide dismutase and catalase with a significant increase in the glutathione peroxidase activity and lipid peroxidation was observed in all the three regions of the brain by CUS. The OS compounds alone did not cause any significant change in the baseline values of these parameters. However, Ocimumoside A and B (40 mg/kg body p.o.) attenuated these CUS-induced alterations with an efficacy similar to that of standard anti-stress (Panax quinquefolium; 100 mg/kg p.o.) and antioxidant (Melatonin; 20 mg/kg i.p.) drugs. While, Ocimarin failed to modulate these CUS-induced alterations. Therefore, this is the first report which identified the anti-stress activity of novel Ocimumoside A and B at the level of central monoamines and antioxidant properties, implicating their therapeutic importance in the prevention of stress-related disorders.     

1,3,4-Oxadiazole-2(3H)-thione and its analogues: A new class of non-competitive nucleotide pyrophosphatases/phosphodiesterases 1 inhibitors

A series of 1,3,4-oxadiazole-2 (3H)-thiones and 1,3,4-thiadiazole-2 (3H)-thiones were synthesized and evaluated for their inhibitory activities against the two nucleotide pyrophosphatase phosphodiesterase 1 enzymes. Dixon, as well as Lineweaver–Burk plots, and their secondary replots have indicated that the inhibition was of pure non-competitive type, against both snake venom and pure human recombinant enzymes as the V_max values decreases without affecting the K_m values. 5-[4-(t-Butyldimethylsilyloxy)-phenyl]-1,3,4-thiadiazole-2 (3H)-thione (17) and [4-(t-butyldimethylsilyloxy)-phenyl]-1,3,4-oxadiazole-2 (3H)-thione (1) were found to be the most active compounds with IC₅₀ values 66.47 and 368 μM, respectively. The K_i values were 100 μM and 360 μM against the snake venom and human recombinant NPP1 enzyme, respectively. Most active compounds were found to be non-toxic in neutrophil viability assay.     

Molecular Basis of DFNB73: Mutations of BSND Can Cause Nonsyndromic Deafness or Bartter Syndrome

BSND encodes barttin, an accessory subunit of renal and inner ear chloride channels. To date, all mutations of BSND have been shown to cause Bartter syndrome type IV, characterized by significant renal abnormalities and deafness. We identified a BSND mutation (p.I12T) in four kindreds segregating nonsyndromic deafness linked to a 4.04-cM interval on chromosome 1p32.3. The functional consequences of p.I12T differ from BSND mutations that cause renal failure and deafness in Bartter syndrome type IV. p.I12T leaves chloride channel function unaffected and only interferes with chaperone function of barttin in intracellular trafficking. This study provides functional data implicating a hypomorphic allele of BSND as a cause of apparent nonsyndromic deafness. We demonstrate that BSND mutations with different functional consequences are the basis for either syndromic or nonsyndromic deafness.     

Non-enzymatic glycation of proteins: From diabetes to cancer

Incubation of proteins with glucose leads to their non-enzymatic glycation and formation of Amadori products known as an early glycation product. Oxidative cleavage of Amadori products is considered as a major route to advanced glycation endproducts (AGEs) formation in vivo. Non-enzymatic glycation of proteins or Maillard reaction is increased in diabetes mellitus due to hyperglycemia and leads to several complications such as blindness, heart disease, nerve damage, and kidney failure. The early and advanced glycation products are accumulated in plasma and tissues of diabetic patients and cause production of autoantibodies against corresponding products. The advanced glycation products are also associated with other diseases like cancer. This review summarizes current knowledge of these stage specific glycated products as common and early diagnostic biomarkers for the associated diseases and the complications with the aim of a novel therapeutic target for the diseases.     

Synthesis, characterization, and anti-bacterial efficacy of some novel cyclophane amide

Synthesis of macrocyclic di, tetra- and hexaamides with aza and oxy linkages has been achieved and the inhibitory activity of cyclophane amides against human pathogenic bacteria well documented.     

The role of phosphate in the action of thymidine phosphorylase inhibitors: Implications for the catalytic mechanism

The design and synthesis of 5-fluoro-6-[(2-aminoimidazol-1-yl)methyl]uracil (AIFU), a potent inhibitor of thymidine phosphorylase (TP) with K_i-values of 11 nM (ecTP) and 17 nM (hTP), are described. Kinetic studies established that the type of inhibition of TP by AIFU is uncompetitive with respect to inorganic phosphate (or arsenate). The results obtained suggest that AIFU and other zwitterionic thymine analog inhibitors of TP act as transition state analogs, mimicking the anionic thymine leaving group, consistent with an S_N2-type catalytic mechanism, and anchored by their protonated side chains to the enzyme-bound phosphate by electrostatic and H-bonding interactions.