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.     

Chemical signals driving bacterial–fungal interactions

Microorganisms reside in diverse environmental communities where interactions become indispensable due to close physical associations. These interactions are driven by chemical communication among different microbial kingdoms, particularly between fungi and bacteria. Knowledge about these communication signals provides useful information about the nature of microbial interactions and allows predictions of community development in diverse environments. Here, we provide an update on the role of small signalling molecules in fungal–bacterial interactions with focus on agricultural and medicinal environments. This review highlights the range of – and response to – diverse biochemicals produced by both kingdoms with view to harnessing their properties towards drug discovery applications.     

Effects of Pioglitazone Mediated Activation of PPAR-γ on CIDEC and Obesity Related Changes in Mice

Objective

Obesity is a metabolic disorder that can lead to high blood pressure, increased blood cholesterol and triglycerides, insulin resistance, and diabetes mellitus. The aim was to study the effects of pioglitazone mediated sensitization of peroxisome proliferator-activated receptor gamma (PPAR-γ) on the relationship of Cell death-inducing DFFA-like effector C (CIDEC) with obesity related changes in mice.

Methods

Sixty C57B/L6 mice weighing 10–12g at 3 weeks of age were randomly divided into 3 groups. Mice in Group 1 were fed on normal diet (ND) while Group 2 mice were given high fat diet (HFD), and Group 3 mice were given high fat diet and treated with Pioglitazone (HFD+P). Body weight, length and level of blood sugar were measured weekly. Quantitative real-time PCR, fluorescence microscopy, and ELISA were performed to analyze the expression of CIDEC and PPAR-γ in visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT).

Results

Body weight and length of mice increased gradually with time in all groups. Blood sugar in HFD mice started to increase significantly from the mid of late phase of obesity while pioglitazone attenuated blood sugar level in HFD+P mice. The mRNA expressions and protein levels of PPAR-γ and CIDEC genes started to increase in HFD mice as compared to ND mice and decreased gradually during the late phase of obesity in VAT. Pioglitazone enhanced the expression of PPAR-γ and CIDEC genes in HFD+P mice even during the late phase of obesity.

Conclusion

It is insinuated that VAT is associated with late phase obesity CIDEC decrease and insulin resistance, while pioglitazone enhances CIDEC through activation of PPAR-γ, increases its expression, and decreases lipolysis, hence preventing an increase of blood sugar in mice exposed to HFD.     

Low doses of vanadate and Trigonella synergistically regulate Na+/K+-ATPase activity and GLUT4 translocation in alloxan-diabetic rats

Oral administration of vanadate to diabetic animals have been shown to stabilize the glucose homeostasis and restore altered metabolic pathways. However, vanadate exerts these effects at relatively high doses with several toxic effects. Low doses of vanadate are relatively safe but unable to elicit any antidiabetic effects. The present study explored the prospect of using low doses of vanadate with Trigonella foenum graecum, seed powder (TSP), another antidiabetic agent, and to evaluate their antidiabetic effect in diabetic rats. Alloxan diabetic rats were treated with insulin, vanadate, TSP and low doses of vanadate with TSP for three weeks. The effect of these antidiabetic compounds was examined on general physiological parameters, Na⁺/K⁺ ATPase activity, membrane lipid peroxidation and membrane fluidity in liver, kidney and heart tissues. Expression of glucose transporter (GLUT4) protein was also examined by immunoblotting method in experimental rat heart after three weeks of diabetes induction. Diabetic rats showed high blood glucose levels. Activity of Na⁺/K⁺ ATPase decreased in diabetic liver and heart. However, kidney showed a significant increase in Na⁺/K⁺ ATPase activity. Diabetic rats exhibited an increased level of lipid peroxidation and decreased membrane fluidity. GLUT4 distribution was also significantly lowered in heart of alloxan diabetic rats. Treatment of diabetic rats with insulin, TSP, vanadate and a combined therapy of lower dose of vanadate with TSP revived normoglycemia and restored the altered level of Na⁺/K⁺ ATPase, lipid peroxidation and membrane fluidity and also induced the redistribution of GLUT4 transporter. TSP treatment alone is partially effective in restoring the above diabetes-induced alterations. Combined therapy of vanadate and TSP was the most effective in normalization of altered membrane linked functions and GLUT4 distribution without any harmful side effect.     

Authentication of Angelica anomala Avé-Lall cultivars through DNA barcodes

Angelica anomala Avé-Lall (Chuanbaizhi in Chinese) is an important medicinal plant which can be used in traditional Chinese medicines; however, there are no authentic and universal methods to differentiate this Sichuan famous-region drug of A. anomala from a large number of non-famous-region and false drugs. It has been demonstrated that DNA barcoding is a molecular diagnostic method for species identification, which uses a single standardized DNA fragment. In this study, we tested five DNA barcoding candidates (matK, ITS, ITS2, rbcL, and psbA-trnH), and we found that ITS was the best candidate to authenticate the famous-region drug of A. anomala. Moreover, through comparative analysis of these five DNA barcodes between A. anomala and Angelica dahurica, we found that ITS had the most and ITS2 had more variable regions, but the psbA-trnH, rbcL, and matK regions were identical. Hence, we suggest ITS as the DNA barcoding to identify A. anomala and A. dahurica. Moreover, we are determined to adopt the A. anomala as the accurate Latin name of Chuanbaizhi.     

Proteolytic activity of largomycin

Largomycin, an antibiotic and antitumor protein, purified from the culture broth of Streptomyces pluricolorescens, displayed specific proteolytic activity. Pure largomycin did not degrade a number of substrates commonly used for detection of aminopeptidase, endopeptidase and carboxypeptidase activity. Pure largomycin degraded angiotensin II, bradykinin, a few dipeptides and a number of proteins of KB cell plasma membranes. The biological activity and the proteolytic activity of largomycin showed similar temperature-dependent patterns, suggesting that one protein is responsible for both activities. The apoprotein of largomycin, which did not show antibiotic activity, contained the proteolytic activity.     

A Novel C-Terminal CIB2 (Calcium and Integrin Binding Protein 2) Mutation Associated with Non-Syndromic Hearing Loss in a Hispanic Family

Hearing loss is a complex disorder caused by both genetic and environmental factors. Previously, mutations in CIB2 have been identified as a common cause of genetic hearing loss in Pakistani and Turkish populations. Here we report a novel (c.556C>T; p.(Arg186Trp)) transition mutation in the CIB2 gene identified through whole exome sequencing (WES) in a Caribbean Hispanic family with non-syndromic hearing loss. CIB2 belongs to the family of calcium-and integrin-binding (CIB) proteins. The carboxy-termini of CIB proteins are associated with calcium binding and intracellular signaling. The p.(Arg186Trp) mutation is localized within predicted type II PDZ binding ligand at the carboxy terminus. Our ex vivo studies revealed that the mutation did not alter the interactions of CIB2 with Whirlin, nor its targeting to the tips of hair cell stereocilia. However, we found that the mutation disrupts inhibition of ATP-induced Ca²⁺ responses by CIB2 in a heterologous expression system. Our findings support p.(Arg186Trp) mutation as a cause for hearing loss in this Hispanic family. In addition, it further highlights the necessity of the calcium binding property of CIB2 for normal hearing.     

Surfactant-assisted bio-conjugated synthesis of silver nanoparticles (AgNPs)

A simple one-spot synthetic route for the production of Ag-nanoparticles using aqueous extract of citrus lemon is being reported in presence of shape-directing cetyltrimethylammonium bromide (CTAB). To our knowledge, this is the first report where the biomolecules form a layer around a group of the Ag-nanoparticles in which the inner layer is bound to the AgNPs surface via the hydroxyl groups of citric acid. The appearance of a sharp surface plasmon resonance band in the UV–visible region might be due to the formation of spherical Ag-nanoparticles. Agglomeration number (N _Ag), the average number of silver atoms per nanoparticle (N), molar concentrations of nanoparticle (C) in solution, extinction coefficient (ε) and increase in the Fermi energy (ΔE _F) were calculated using Mie theory and discussed. Interestingly, reaction mixture became turbid at higher [CTAB] due to the uncontrolled growth of Ag-nanoparticles. The transmission electron microscopic images of nanoparticles, recorded at different magnifications.     

Measurement of H2O2 within living Drosophila during aging using a ratiometric mass spectrometry probe targeted to the mitochondrial matrix

Hydrogen peroxide (H(2)O(2)) is central to mitochondrial oxidative damage and redox signaling, but its roles are poorly understood due to the difficulty of measuring mitochondrial H(2)O(2) in vivo. Here we report a ratiometric mass spectrometry probe approach to assess mitochondrial matrix H(2)O(2) levels in vivo. The probe, MitoB, comprises a triphenylphosphonium (TPP) cation driving its accumulation within mitochondria, conjugated to an arylboronic acid that reacts with H(2)O(2) to form a phenol, MitoP. Quantifying the MitoP/MitoB ratio by liquid chromatography-tandem mass spectrometry enabled measurement of a weighted average of mitochondrial H(2)O(2) that predominantly reports on thoracic muscle mitochondria within living flies. There was an increase in mitochondrial H(2)O(2) with age in flies, which was not coordinately altered by interventions that modulated life span. Our findings provide approaches to investigate mitochondrial ROS in vivo and suggest that while an increase in overall mitochondrial H(2)O(2) correlates with aging, it may not be causative.