The Effect of Chronic Long-Term Intermittent Hypobaric Hypoxia on Bone Mineral Density in Rats: Role of Nitric Oxide

Intermittent hypoxia is the most common pattern of hypoxic exposure in humans. The effect of chronic long-term intermittent hypobaric hypoxia (CLTIHH) on bone metabolism is not investigated. We examined the effect of CLTIHH on bone metabolism and the role of nitric oxide (NO) in this process. The rats were divided into three groups in this study. The animals in groups I and II have been exposed to CLTIHH. The animals in group II were also treated with nitric oxide synthase inhibitor NG-nitro-l-arginine methyl ester. To obtain CLTIHH, rats were placed in a hypobaric chamber (430 mm Hg; 5 h/day, 5 days/week, 5 weeks). The group III (control) rats breathed room air in the same environment. At the begining of the experiments, bone mineral density (BMD) of the animals were measured, and blood samples were collected from the tail vein. After the 5-week CLTIHH period, the same measurements were repeated. Parathyroid hormone, calcium, phosphate, bone alkaline phosphatase (b-ALP), NO, interleukin 1 beta, interleukin 6, and tumor necrosis factor alpha levels were determined. The cytokines, NO levels, and BMD in CLTIHH-induced rats were higher compared with baseline and control values. The cytokines, b-ALP, and BMD increased while NO levels decreased in the group II compared with baseline values. BMD values of group II were lower than group I but higher than control group. Our results suggested that CLTIHH has positive effects on bone density. Intermittent hypoxia protocols may be developed for treatment and prevention of osteopenia and osteoporosis.     

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics.With well-developed algorithms and computational tools for mass spectrometry (MS)¹ data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1–9). Nevertheless, the bottom-up approach is suboptimal for the analysis of protein posttranslational modifications (PTMs) and sequence variants as a result of protein digestion (10). Alternatively, the protein-based top-down proteomics approach analyzes intact proteins, which provides a “bird''s eye” view of all proteoforms (11), including those arising from sequence variations, alternative splicing, and diverse PTMs, making it a disruptive technology for the comprehensive analysis of proteoforms (12–24). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped.The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs.Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28, 29), Mascot Top Down (also known as Big-Mascot) (30), MS-TopDown (31), and MS-Align+ (32), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes “shotgun annotated” databases (33) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32). Mascot Top Down (30) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31) employs the spectral alignment algorithm (35), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax.Recently, new software tools have been developed for proteoform characterization (36, 37). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36). Another software tool, ProSight Lite, developed recently by the Kelleher group (37), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking.Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations.     

Simple and reliable detection of slime production of <Emphasis Type="Italic">Candida</Emphasis><Emphasis Type="Italic">spp</Emphasis>. directly from blood culture bottles: Comparison of visual tube method and transmission electron microscopy

Early detection of slime production may be useful for clinical decision because of its suggestive property for potential pathogenic capacity of a Candida strain especially in patients with a prosthetic device. In this study we aimed to compare the visual tube method (VTM) with transmission electron microscopy (TEM) in order to confirm the reliability of the former method. In order to demonstrate the reproducibility of the tube method and to determine the correct timing for the test, Candida isolates directly obtained from blood culture (DBC) bottles and their two subsequent subcultures were used. The results of this study showed that VTM is a simple and reliable method which can be used in every clinical mycology laboratory, provided that the test is applied on DBC isolates; as the ability of slime production is decreased or lost even after the first subculturing. We suggest that this simple method can be used and may have some contributions to the ongoing studies on the controversial issue concerning removal of biomaterials in candidemic patients.     

Variants in the interleukin-1 alpha and beta genes,and the risk for periodontal disease in dogs

Elevated levels of interleukin-1 (IL-1) have been shown to amplify the inflammatory response against periodontopathogenic bacteria. In humans, polymorphisms in the IL1A and IL1B genes are the most well-studied genetic polymorphisms associated with periodontal disease (PD). In contrast to human, there is a lack of knowledge on the genetic basis of canine PD. A case–control study was conducted in which a molecular analysis of dog IL1A and IL1B genes was performed. Of the eight genetic variants identified, seven in IL1A gene and one in IL1B gene, IL1A/1_g.388A >C and IL1A/1_g.521T >A showed statistically significant differences between groups (adjusted OR (95% CI): 0.15 (0.03–0.76), P= 0.022; 5.76 (1.03–32.1), P= 0.046, respectively). It suggests that in the studied population the IL1A/1_g.388C allele is associated with a decreased PD risk, whereas the IL1A/1_g.521A allele can confer an increased risk. Additionally, the IL1A/2_g.515G >T variation resulted in a change of amino acid, i.e. glycine to valine. In silico analysis suggests that this change can alter protein structure and function, predicting it to be deleterious or damaging. This work suggests that IL1 genetic variants may be important in PD susceptibility in canines.     

Testing the quick meal hypothesis: The effect of pulp on hoarding and seed predation of Hymenaea courbaril by red‐rumped agoutis (Dasyprocta leporina)

Abstract: Red‐rumped agoutis (Dasyprocta leporina) are important seed dispersers/predators of Neotropical large‐seeded plants. Several species of seeds cached by agoutis have an edible reward, in contrast to temperate rodent‐dispersed diaspores. The quick meal hypothesis states that the presence of a reward such as edible pulp will enhance the efficiency of rodents as seed disperses by satiating the animal and, consequently, reducing seed predation and enhancing hoarding. In this study, this hypothesis was tested using as the reference system the pulp and seeds of Hymenaea courbaril. Seeds with and without pulp were offered to agoutis and the behaviour of each individual was recorded. Since the probability of predation and hoarding were complementary, we used the probability of predation. The proportion of agoutis that preyed on at least one seed was similar for seeds with (42.8% of individuals) and without (40.0% of individuals) pulp. In agoutis that preyed upon at least one seed, the probability that they killed a seed did not differ between seeds with (0.17 ± 0.03) and without (0.20 ± 0.08) pulp. Hence, these results do not support the ‘quick meal hypothesis’.     

Extrafloral nectaries as a deterrent mechanism against seed predators in the chemically protected weed Crotalaria pallida (Leguminosae)

Abstract In several plants, extrafloral nectaries (EFN) are located close to the reproductive structures, suggesting that ants may act as a defence against specialized seed predators that overcome chemical defences. Alternatively, ants may also deter herbivores in a generalized manner, thereby protecting the whole plant. In this work, we examined the relationship between the chemically protected weed Crotalaria pallida Ait. (Leguminosae) that bears EFN, its specialized seed predator, the larvae of the arctiid moth Utetheisa ornatrix L. (Arctiidae) and ants. We tested two hypotheses related to the type of deterrence caused by ants. The Seed Predator Deterrence Hypothesis predicts that ant deterrence is directed primarily towards herbivores that destroy seeds and other reproductive structures, without attacking herbivores on vegetative structures. The General Deterrence Hypothesis states that ants are general in their effects, equally deterring herbivores in vegetative and reproductive structures. Our results supported the predictions of the Seed Predator Deterrence Hypothesis, namely, that (i) ant activity on EFN was related to the vulnerability of reproductive structures to attack by U. ornatrix; (ii) ant patrolling was restricted almost entirely to racemes; (iii) ants removed termites used as baits more frequently on racemes than on leaves; and (iv) U. ornatrix larvae were often expulsed from the racemes. These results indicate that EFN can act as another deterrent mechanism in chemically protected plants by promoting the expulsion of specialist seed predators.     

Prediction of indirect interactions in proteins

Background  

Both direct and indirect interactions determine molecular recognition of ligands by proteins. Indirect interactions can be defined as effects on recognition controlled from distant sites in the proteins, e.g. by changes in protein conformation and mobility, whereas direct interactions occur in close proximity of the protein's amino acids and the ligand. Molecular recognition is traditionally studied using three-dimensional methods, but with such techniques it is difficult to predict the effects caused by mutational changes of amino acids located far away from the ligand-binding site. We recently developed an approach, proteochemometrics, to the study of molecular recognition that models the chemical effects involved in the recognition of ligands by proteins using statistical sampling and mathematical modelling.