Role of proteolysis in determining potency of Bacillus thuringiensis Cry1Ac delta-endotoxin

Bacillus thuringiensis protein delta-endotoxins are toxic to a variety of different insect species. Larvicidal potency depends on the completion of a number of steps in the mode of action of the toxin. Here, we investigated the role of proteolytic processing in determining the potency of the B. thuringiensis Cry1Ac delta-endotoxin towards Pieris brassicae (family: Pieridae) and Mamestra brassicae (family: Noctuidae). In bioassays, Cry1Ac was over 2,000 times more active against P. brassicae than against M. brassicae larvae. Using gut juice purified from both insects, we processed Cry1Ac to soluble forms that had the same N terminus and the same apparent molecular weight. However, extended proteolysis of Cry1Ac in vitro with proteases from both insects resulted in the formation of an insoluble aggregate. With proteases from P. brassicae, the Cry1Ac-susceptible insect, Cry1Ac was processed to an insoluble product with a molecular mass of approximately 56 kDa, whereas proteases from M. brassicae, the non-susceptible insect, generated products with molecular masses of approximately 58, approximately 40, and approximately 20 kDa. N-terminal sequencing of the insoluble products revealed that both insects cleaved Cry1Ac within domain I, but M. brassicae proteases also cleaved the toxin at Arg423 in domain II. A similar pattern of processing was observed in vivo. When Arg423 was replaced with Gln or Ser, the resulting mutant toxins resisted degradation by M. brassicae proteases. However, this mutation had little effect on toxicity to M. brassicae. Differential processing of membrane-bound Cry1Ac was also observed in qualitative binding experiments performed with brush border membrane vesicles from the two insects and in midguts isolated from toxin-treated insects.     

Vaccination with inactivated virus but not viral DNA reduces virus load following challenge with a heterologous and virulent isolate of feline immunodeficiency virus

It has been shown that cats can be protected against infection with the prototypic Petaluma strain of feline immunodeficiency virus (FIV(PET)) using vaccines based on either inactivated virus particles or replication-defective proviral DNA. However, the utility of such vaccines in the field is uncertain, given the absence of consistent protection against antigenically distinct strains and the concern that the Petaluma strain may be an unrepresentative, attenuated isolate. Since reduction of viral pathogenicity and dissemination may be useful outcomes of vaccination, even in the absence of complete protection, we tested whether either of these vaccine strategies ameliorates the early course of infection following challenge with heterologous and more virulent isolates. We now report that an inactivated virus vaccine, which generates high levels of virus neutralizing antibodies, confers reduced virus loads following challenge with two heterologous isolates, FIV(AM6) and FIV(GL8). This vaccine also prevented the marked early decline in CD4/CD8 ratio seen in FIV(GL8)-infected cats. In contrast, DNA vaccines based on either FIV(PET) or FIV(GL8), which induce cell-mediated responses but no detectable antiviral antibodies, protected a fraction of cats against infection with FIV(PET) but had no measurable effect on virus load when the infecting virus was FIV(GL8). These results indicate that the more virulent FIV(GL8) is intrinsically more resistant to vaccinal immunity than the FIV(PET) strain and that a broad spectrum of responses which includes virus neutralizing antibodies is a desirable goal for lentivirus vaccine development.     

Metabolic Syndrome and Nephrolithiasis Risk: Should the Medical Management of Nephrolithiasis Include the Treatment of Metabolic Syndrome?

This article reviews the relationship between metabolic syndrome (MetS) and nephrolithiasis, as well as the clinical implications for patients with this dual diagnosis. MetS, estimated to affect 25% of adults in the United States, is associated with a fivefold increase in the risk of developing diabetes, a doubling of the risk of acquiring cardiovascular disease, and an increase in overall mortality. Defined as a syndrome, MetS is recognized clinically by numerous constitutive traits, including abdominal obesity, hypertension, dyslipidemia (elevated triglycerides, low high-density lipoprotein cholesterol), and hyperglycemia. Urologic complications of MetS include a 30% higher risk of nephrolithiasis, with an increased percentage of uric acid nephrolithiasis in the setting of hyperuricemia, hyperuricosuria, low urine pH, and low urinary volume. Current American Urological Association and European Association of Urology guidelines suggest investigating the etiology of nephrolithiasis in affected individuals; however, there is no specific goal of treating MetS as part of the medical management. Weight loss and exercise, the main lifestyle treatments of MetS, counter abdominal obesity and insulin resistance and reduce the incidence of cardiovascular events and the development of diabetes. These recommendations may offer a beneficial adjunctive treatment option for nephrolithiasis complicated by MetS. Although definitive therapeutic recommendations must await further studies, it seems both reasonable and justifiable for the urologist, as part of a multidisciplinary team, to recommend these important lifestyle changes to patients with both conditions. These recommendations should accompany the currently accepted management of nephrolithiasis.Key words: Nephrolithiasis, Metabolic syndrome, Uric acid nephrolithiasisMetabolic syndrome (MetS), as defined by the National Cholesterol Education Program and the Adult Treatment Panel III in 2001 (and updated in 2005), represents a growing medical problem affecting more than 22% of US adults.^1–4 It is associated with an almost fivefold increase in the risk of developing diabetes and a doubling of the risk of acquiring cardiovascular disease.⁵ MetS is a clinical disorder defined by the presence of at least three of the following criteria: central obesity (abdominal girth > 102 cm [40 in] men and > 88 cm [35 in] women), low high-density lipoprotein (HDL) cholesterol (< 40 mg/dL in men and < 50 mg/dL in women), hypertriglyceridemia (> 150 mg/dL), hypertension (blood pressure > 130/85 mm Hg), and elevated fasting glucose (> 100 mg/dL).^2,4 The development of MetS appears to result from a complex interaction of genetics, phenotypic visceral fat accumulation (central obesity), insulin resistance, and sedentary behavior.^5,6 Beyond cardiometabolic risks, MetS has a wide range of long-term complications, including nonalcoholic fatty liver disease, polycystic ovarian syndrome, obstructive sleep apnea, hypogonadism, lipodystrophy, microvascular disease, and chronic renal disease.⁶ An important urologic complication of MetS, not routinely cited, is nephrolithiasis.^6–8Nephrolithiasis continues to be a major cause of morbidity and healthcare spending.⁹ A history of kidney stones is approximately twice as common in individuals with three criteria for MetS and three times as common in those with five criteria for MetS, as compared with those with none.¹⁰ These trends were confirmed in a large-scale, nationwide study of 30,448 Japanese patients with urolithiasis, who demonstrated that MetS was associated with a significantly increased risk of hypercalciuria, hyperuricosuria, hyperoxaluria, and hypocitraturia, independent of age and sex.¹¹ Additionally, patients with a history of nephrolithiasis are significantly more likely to have multiple risk factors for cardiovascular disease, premature atherosclerosis, and cardiovascular events.^10,12,13 It is unknown whether this is primarily a reflection of factors associated with nephrolithiasis, such as obesity, hypertension, or glucose intolerance/diabetes, or due to components of MetS, such as insulin resistance.¹⁴ The current American Urological Association (AUA) guidelines on the medical management of kidney stones suggests a need for future research on advising patients to exercise and lose weight, but does not make definitive recommendations on these lifestyle changes.¹⁵     

Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments

Targeted mass spectrometry is an essential tool for detecting quantitative changes in low abundant proteins throughout the proteome. Although selected reaction monitoring (SRM) is the preferred method for quantifying peptides in complex samples, the process of designing SRM assays is laborious. Peptides have widely varying signal responses dictated by sequence-specific physiochemical properties; one major challenge is in selecting representative peptides to target as a proxy for protein abundance. Here we present PREGO, a software tool that predicts high-responding peptides for SRM experiments. PREGO predicts peptide responses with an artificial neural network trained using 11 minimally redundant, maximally relevant properties. Crucial to its success, PREGO is trained using fragment ion intensities of equimolar synthetic peptides extracted from data independent acquisition experiments. Because of similarities in instrumentation and the nature of data collection, relative peptide responses from data independent acquisition experiments are a suitable substitute for SRM experiments because they both make quantitative measurements from integrated fragment ion chromatograms. Using an SRM experiment containing 12,973 peptides from 724 synthetic proteins, PREGO exhibits a 40–85% improvement over previously published approaches at selecting high-responding peptides. These results also represent a dramatic improvement over the rules-based peptide selection approaches commonly used in the literature.Targeted proteomics using selected reaction monitoring (SRM)¹ and parallel reaction monitoring (PRM) is increasingly becoming the gold-standard method for peptide quantitation within complex biological matrices (1, 2). By focusing on monitoring only a handful of transitions (associated precursor and fragment ions) for targeted peptides, SRM experiments filter out background signals, which in turn increases the signal to noise ratio. SRM experiments are almost exclusively performed on triple-quadrupole instruments. These instruments can isolate single transitions as an ion beam and measure that beam with extremely sensitive ion-striking detectors. As a result, SRM experiments generally exhibit significantly more accurate quantitation when compared with similarly powered discovery based proteomics experiments, and frequently benefit from a much wider linear range of quantitation (3). SRM experiments often require less fractionation and can be run in shorter time on less expensive instrumentation. These factors allow researchers to greatly scale up the number of samples they can run, which in turn increases the power of their experiment.However, the process of developing an effective SRM assay is often cumbersome, as subtle differences in peptide sequence can have a profound impact on the physiochemical properties and subsquent SRM responses of a peptide. To successfully develop an SRM assay for a protein of interest, unique peptide sequences must be chosen that also produce a high SRM signal (e.g. high-responding peptides). Once identified, these high-responding peptides are often synthesized or purchased, and independently analyzed to determine the most sensitive transition pairs. Finally, the selected peptide and transition pairs must be tested in complex mixtures to screen for transitions with chemical noise interference and to validate the sensitivity of the assay within a particular sample matrix. Peptides and transitions that survive this lengthy screening process can then undergo absolute quantitation by calibrating the signal intensity against standards of known quantity.Although experimental methods have been developed to empirically determine a set of best responding peptides (4), these strategies can be time consuming and require analytical standards, which are currently unavailable for all proteins. More often than not, representative peptides are essentially chosen at random, using only a small number of criteria, such as having a reasonable length for detection in the mass spectrometer, a lack of methionine, and a preference for peptides containing proline (5). It is not uncommon for SRM assays to fail at the final validation steps simply because the peptides chosen in the first assay creation step happened to be unexpectedly poor responding peptides.In an effort to speed up the process of generating robust assays, several groups (6–9) have designed approaches to predict sets of proteotypic peptides using machine-learning algorithms. Proteotypic peptides are peptides commonly identified in shotgun proteomics experiments for a variety of reasons including high signal, low interference, and search engine compatible fragmentation. Enhanced Signature Peptide (ESP) Predictor (7) was the first successful modification of this prediction approach to use proteotypic peptides as a proxy for high-responding peptides for SRM-based quantitation. In brief, Fusaro et al. built a training data set from data-dependent acquired (DDA) yeast peptides and a proxy for their response was quantitated using extracted precursor ion chromatograms (XICs). The authors calculated 550 physiochemical properties for each peptide based on sequence alone and built a random forest classifier to differentiate between the high and low response groups. Other peptide prediction tools follow the same general methodology for developing training data sets. CONSeQuence (8) applies several machine learning strategies and a pared down list of 50 distinct peptide properties. Alternately, Peptide Prediction with Abundance (9) (PPA) uses a back-propagation neural network (10) trained with 15 distinct peptide properties selected from ESP Predictor''s 550. The authors of CONSeQuence and PPA found that their approaches outperformed the ESP Predictor on a variety of data sets.As with most machine learning-based tools, the generality of the training set to real-world data is key to the effectiveness of the resulting prediction tool. Although MS1 intensities extracted from DDA data can be useful for predicting high-responding peptides (11, 12), several factors make them less than ideal for generalizing to SRM and PRM experiments. In particular, DDA peptides must be identified before being quantified and key biochemical features beneficial for targeted analysis of transitions can reduce overall identification rates by producing fragment spectra that are difficult to interpret with typical search engines. By building training data sets on precursor intensities alone these tools ignore the fact that targeted assays actually use fragment ions for quantification. We propose that constructing training sets from DIA fragment intensities (13) will produce machine-learning tools that are more effective at modeling peptides that produce detectible transitions, rather than just proteotypic peptides.The use of digested proteins in training sets presents additional concerns. The observed variance in peptide intensities is confounded by variation in protein abundance. Converting peptide intensities to ranks can remove the dependence on varying protein levels at the cost of corrupting the training set with proteins that biochemically contain no high-responding peptides. PPA attempts to ease this concern by training with Intensity Based Absolute Quantitation values (14) for DDA peptides estimated from XICs. We hypothesize that constructing a training set from equimolar synthetic peptides removes most adverse effects of digestion from the training set, making it possible to construct a more generalizable tool.     

Quantitative analysis of lignocaine and metabolites in equine urine and plasma by liquid chromatography–tandem mass spectrometry

In this paper, a method for the sensitive and reproducible analysis of lignocaine and its four principal metabolites, monoethylxylidide (MEGX), glycylxylidide (GX), 3-hydroxylignocaine (3-HO-LIG), 4-hydroxylignocaine (4-HO-LIG) in equine urine and plasma samples is presented. The method uses liquid chromatography coupled to tandem mass spectrometry operating in electrospray ionisation positive ion mode (+ESI) via multiple reaction monitoring (MRM). Sample preparation involved solid-phase extraction using a mixed-mode phase. The internal standard adopted was lignocaine-d₁₀. Lignocaine and its metabolites were successfully resolved using an octadecylsilica reversed-phase column using a gradient mobile phase of acetonitrile and 0.1% (v/v) aqueous formic acid at a flow rate of 300 μL/min. Target analytes and the internal standard were determined by using the following transitions; lignocaine, 235.2 > 86.1; 3-HO-LIG and 4-HO-LIG, 251.2 > 86.1; MEGX, 207.1 > 58.1; GX, 179.1 > 122.1; and lignocaine-d₁₀, 245.2 > 96.1. Calibration curves were generated over the range 1–100 ng/mL for plasma samples and 1–1000 ng/mL for urine samples. The method was validated for instrument linearity, repeatability and detection limit (IDL), method linearity, repeatability, detection limit (MDL), quantitation limit (LOQ) and recovery. The method was successfully used to analyse both plasma and urine samples following a subcutaneous administration of lignocaine to a thoroughbred horse.     

Metal Complexes of 3-Thiophene Carboxamides Containing a Pyridine Ring

Complexes of Zn(II), Cu(II) and Co(II) with either N-(2-methylpyridyl)-3-thienyl-alkyl-carboxamide or N-(2-pyridyl)-3-thienylalkyl-carboxamide groups have been prepared and characterized. Crystal structures of ten new complexes are reported and discussed. N-(2-Methylpyridyl)-3-thienyl-alkyl-carboxamide exhibits both uni- and bidentate behavior. With all ligands, bidentate complexation is through the carbonyl oxygen and pyridine nitrogen atoms (O, N) and the amide nitrogen atom remains protonated. The electrochemical behavior and the infrared spectra of selected complexes are discussed.     

Crystallographic and NMR investigation of cobalt-substituted amicyanin

Cobalt(II) amicyanin was prepared by replacing the copper of the type I copper protein amicyanin from Paracoccus denitrificans with cobalt. The structure of the protein and the metal center have been characterized by X-ray crystallography and paramagnetic NMR spectroscopy. The crystal structure indicates that Met98, which provides an axial sulfur ligand in native amicyanin, is no longer bound to the metal in cobalt(II) amicyanin and that a water molecule is recruited from solvent to form the fourth metal ligand. This results in a tetrahedral coordination geometry for the cobalt ion. NMR studies in solution also indicate that the side chain of the methionine residue interacts less strongly with the metal in P. denitrificans amicyanin than in Paracoccus versutus amicyanin. The cobalt(II) amicyanin crystal structure is different from that of cobalt-substituted azurin in which the carbonyl of a glycine residue provides this equivalent ligand. In cobalt(II) amicyanin that residue is a proline, for which the oxygen is structurally inaccessible, so that the water occupies the position held by the glycine carbonyl in cobalt(II) azurin. Such a metal coordination involving water has not previously been reported for a native or metal-substituted type I copper protein.     

Identification, typing, and insecticidal activity of Xenorhabdus isolates from entomopathogenic nematodes in United Kingdom soil and characterization of the xpt toxin loci

Xenorhabdus strains from entomopathogenic nematodes isolated from United Kingdom soils by using the insect bait entrapment method were characterized by partial sequencing of the 16S rRNA gene, four housekeeping genes (asd, ompR, recA, and serC) and the flagellin gene (fliC). Most strains (191/197) were found to have genes with greatest similarity to those of Xenorhabdus bovienii, and the remaining six strains had genes most similar to those of Xenorhabdus nematophila. Generally, 16S rRNA sequences and the sequence types based on housekeeping genes were in agreement, with a few notable exceptions. Statistical analysis implied that recombination had occurred at the serC locus and that moderate amounts of interallele recombination had also taken place. Surprisingly, the fliC locus contained a highly variable central region, even though insects lack an adaptive immune response, which is thought to drive flagellar variation in pathogens of higher organisms. All the X. nematophila strains exhibited a consistent pattern of insecticidal activity, and all contained the insecticidal toxin genes xptA1A2B1C1, which were present on a pathogenicity island (PAI). The PAIs were similar among the X. nematophila strains, except for partial deletions of a peptide synthetase gene and the presence of insertion sequences. Comparison of the PAI locus with that of X. bovienii suggested that the PAI integrated into the genome first and then acquired the xpt genes. The independent mobility of xpt genes was further supported by the presence of xpt genes in X. bovienii strain I73 on a type 2 transposon structure and by the variable patterns of insecticidal activity in X. bovienii isolates, even among closely related strains.     

The contribution of DNA repair and antioxidants in determining cell type-specific resistance to oxidative stress

The aims of this study were; (i) to elucidate the mechanisms involved in determining cell type-specific responses to oxidative stress and (ii) to test the hypothesis that cell types which are subjected to high oxidative burdens in vivo, have greater oxidative stress resistance. Cultures of the retinal pigment epithelium (RPE), corneal fibroblasts, alveolar type II epithelium and skin epidermal cells were studied. Cellular sensitivity to H2O2 was determined by the MTT assay. Cellular antioxidant status (CuZnSOD, MnSOD, GPX, CAT) was analyzed with enzymatic assays and the susceptibility and repair capacities of nuclear and mitochondrial genomes were assessed by QPCR. Cell type-specific responses to H2O2 were observed. The RPE had the greatest resistance to oxidative stress (P>0.05; compared to all other cell types) followed by the corneal fibroblasts (P < 0.05; compared to skin and lung cells). The oxidative tolerance of the RPE coincided with greater CuZnSOD, GPX and CAT enzymatic activity (P < 0.05; compared to other cells). The RPE and corneal fibroblasts both had up-regulated nDNA repair post-treatment (P < 0.05; compared to all other cells). In summary, variations in the synergistic interplay between enzymatic antioxidants and nDNA repair have important roles in influencing cell type-specific vulnerability to oxidative stress. Furthermore, cells located in highly oxidizing microenvironments appear to have more efficient oxidative defence and repair mechanisms.