Labeling, detection and identification of newly synthesized proteomes with bioorthogonal non-canonical amino-acid tagging

A major aim of proteomics is the identification of proteins in a given proteome at a given metabolic state. This protocol describes the step-by-step labeling, purification and detection of newly synthesized proteins in mammalian cells using the non-canonical amino acid azidohomoalanine (AHA). In this method, metabolic labeling of newly synthesized proteins with AHA endows them with the unique chemical functionality of the azide group. In the subsequent click chemistry tagging reaction, azide-labeled proteins are covalently coupled to an alkyne-bearing affinity tag. After avidin-based affinity purification and on-resin trypsinization, the resulting peptide mixture is subjected to tandem mass spectrometry for identification. In combination with deuterated leucine-based metabolic colabeling, candidate proteins can be immediately validated. Bioorthogonal non-canonical amino-acid tagging can be combined with any subcellular fractionation, immunopurification or other proteomic method to identify specific subproteomes, thereby reducing sample complexity and enabling the identification of subtle changes in a proteome. This protocol can be completed in 5 days.     

Effect on digestion and performance of dietary protein content and of increased substitution of lucerne hay with soya-bean protein concentrate in starter diets for young rabbits

The aim of this work was to study the effect of protein source / availability on the intestinal microbiota, digestive traits and nutritional performance of early-weaned rabbits. The effects of supplemental antibiotics in the drinking water were also evaluated. Four isoenergetic and isofibrous diets were formulated: a control diet with a high protein (207 g/kg dry matter (DM)) and lucerne hay content (HPHL), a diet with low crude protein (CP) (179 g/kg DM) and high lucerne hay content (LPHL) and low protein diets in which the lucerne hay in diet LPHL was replaced partially (LPML) or totally (LPLL) with soya-bean protein concentrate. Rabbits, weaned at 25 days (52 per diet), were fed the experimental diets for a 2-week period and thereafter received a commercial diet until 56 days of age. The incidence of mortality was investigated using 70 animals per diet without supplemental medication. The profile of the ileal microbiota was studied at 35 days of age in rabbits treated (18 per diet) or not (12 per diet) with antibiotic. As expected, supplementation with antibiotics effectively reduced fattening mortality rate and microbial biodiversity. However, lowering of also the dietary CP content led to a reduction in the mortality rate ( P < 0.05), both in animals treated with (by 80%) or without (by 39%) antibiotics. In addition, there was a reduction ( P < 0.05) in the frequency of Clostridium perfringens in non-medicated animals. Neither jejunal morphology nor growth performance, over the whole fattening period, was affected by dietary CP content of the experimental diets. However, with HPHL, feed efficiency was higher (by 4.8%; P < 0.01) than with LPHL diets. Substitution of lucerne hay with soya-bean meal in low protein diets did not affect apparent faecal or ileal digestibility of DM and CP. However, the ileal digestibility of cystine, alanine, aspartic acid, and proline was lowered ( P < 0.05) with increasing substitution by soya bean. Nevertheless, ileal CP flow, incidence of mortality and presence of C. perfringens were unaffected. Our results suggest that a reduction in dietary CP, resulting in reduced lumenal flows of nitrogen through the ileum, may be beneficial for young rabbits and limit the numbers of potentially harmful bacteria in the lower gut. Modulation of dietary CP should be contemplated as a strategy to increase the intestinal health in rabbits.     

Effect of botanical composition of silages on rumen fatty acid metabolism and fatty acid composition in longissimus muscle and subcutaneous fat of lambs

To study the effect of feeding silages with different botanical composition, on rumen and lamb fat, 30 male lambs were assigned to five different silage groups for 11 weeks: botanically diverse silage (BDS); white clover silage (WCS); red clover silage (RCS), intensive English ryegrass silage (IRS) and crushed linseed and maize silage (MSL). Besides the silages, animals received organic wheat and barley and the MSL group additionally received bicarbonate (15 g/day). Silages were sampled when the bales were opened and analysed for fatty acid (FA) content and chemical composition. At slaughter, ruminal contents were sampled and 24 h after slaughter, longissimus muscle and subcutaneous (SC) fat were sampled. All samples were analysed for FA composition. The MSL group ingested the highest amount of FA (35.8 g/day v. 13.5, 19.4, 17.2 and 30.4 g/day for MSL v. BDS, WCS, RCS and IRS, respectively) and the sum of the major polyunsaturated FA, C18:2 n-6 and C18:3 n-3, was similar for groups BDS, WCS, RCS and MSL (61.3 g/100 g, 62.3 g/100 g, 62.3 g/100 g, 63.7 g/100 g of FA methylesters (FAME), respectively), while group IRS ingested higher proportions of these FA (74.5 g/100 g of FAME). Rumen data showed that animals fed BDS presented higher proportions of biohydrogenation intermediates, particularly C18:1 t11 and CLA c9t11, suggesting partial inhibition of rumen biohydrogenation. In the MSL group, the content of C18:3 n-3 in the rumen was highest, most probably due to reduced lipolysis and hence biohydrogenation through the combined effect of esterified C18:3 n-3 and seed protection. Additionally, C18:3 n-3 proportions were higher in rumen contents of RCS animals compared with WCS animals, which could be due to the activity of the polyphenol oxidase enzyme in the RC silages. Proportions of C18:3 n-3 were similar between treatments both for SC and intramuscular (IM) fat, whereas CLA c9t11 content was higher in the SC fat of BDS animals and lower in the IM fat of IRS animals compared with the other forage groups. No differences were found for C20:4 n-6, C20:5 n-3, C22:5 n-3 and C22:6 n-3 in the IM fat of the animals. Nevertheless, indices for desaturation and elongation activity in muscle of BDS animals suggest some stimulation of the first three steps of desaturation and elongation (Δ6-desaturase, elongase and Δ5-desaturase) of long-chain FA.     

Habitat fragmentation, variable edge effects, and the landscape-divergence hypothesis

Edge effects are major drivers of change in many fragmented landscapes, but are often highly variable in space and time. Here we assess variability in edge effects altering Amazon forest dynamics, plant community composition, invading species, and carbon storage, in the world's largest and longest-running experimental study of habitat fragmentation. Despite detailed knowledge of local landscape conditions, spatial variability in edge effects was only partially foreseeable: relatively predictable effects were caused by the differing proximity of plots to forest edge and varying matrix vegetation, but windstorms generated much random variability. Temporal variability in edge phenomena was also only partially predictable: forest dynamics varied somewhat with fragment age, but also fluctuated markedly over time, evidently because of sporadic droughts and windstorms. Given the acute sensitivity of habitat fragments to local landscape and weather dynamics, we predict that fragments within the same landscape will tend to converge in species composition, whereas those in different landscapes will diverge in composition. This 'landscape-divergence hypothesis', if generally valid, will have key implications for biodiversity-conservation strategies and for understanding the dynamics of fragmented ecosystems.     

Components of metabolic syndrome predicting diabetes: no role of inflammation or dyslipidemia

Objective: The diagnostic criteria and the clinical usefulness of the metabolic syndrome (MetSy) are currently questioned. The objective was to describe the structure of MetSy and to evaluate its components for prediction of diabetes type 2 (T2DM). Research Methods and Procedures: This was a case‐referent study nested within a population‐based health survey. Among 33,336 participants, we identified 177 initially non‐diabetic individuals who developed T2DM after 0.1 to 10.5 years (mean, 5.4 years), and, for each diabetes case, two referents matched for sex, age, and year of health survey. Baseline variables included oral glucose tolerance test, BMI, blood pressure, blood lipids, adipokines, inflammatory markers, insulin resistance, and β‐cell function. Exploratory and confirmative factor analyses were applied to hypothesize the structure of the MetSy. The prediction of T2DM by the different factors was evaluated by multivariate logistic regression analysis. Results: A hypothetical five‐factor model of intercorrelated composite factors was generated. The inflammation, dyslipidemia, and blood pressure factors were predicitive only in univariate analysis. In multivariable analyses, two factors independently and significantly predicted T2DM: an obesity/insulin resistance factor and a glycemia factor. The composite factors did not improve the prediction of T2DM compared with single variables. Among the original variables, fasting glucose, proinsulin, BMI, and blood pressure values were predictive of T2DM. Discussion: Our data support the concept of a MetSy, and we propose five separate clusters of components. The inflammation and dyslipidemia factors were not independently associated with diabetes risk. In contrast, obesity and accompanying insulin resistance and β‐cell decompensation seem to be two core perturbations promoting and predicting progression to T2DM.     

Sting_RDB: a relational database of structural parameters for protein analysis with support for data warehousing and data mining

An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one's ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting_RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting_RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting_RDB toward data quality assessment. To the best of our knowledge, Sting_RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting_RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting_rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented. Further details are accessible at the Sting_RDB demo web page: http://www.cbi.cnptia.embrapa.br/StingRDB.     

Effects of sample re-sequencing and trimming on the quality and size of assembled consensus sequences

The production of nucleic acid sequences by automatic DNA sequencer machines is always associated with some base-calling errors. In order to produce a high-quality DNA sequence from a molecule of interest, researchers normally sequence the same sample many times. Considering base-calling errors as rare events, re-sequencing the same molecule and assembling the reads produced are frequently thought to be a good way to generate reliable sequences. However, a relevant question on this issue is: how many times the sample needs to be re-sequenced to minimize costs and achieve a high-fidelity sequence? We examined how both the number of re-sequenced reads and PHRED trimming parameters affect the accuracy and size of final consensus sequences. Hundreds of single-pool reaction pUC18 reads were generated and assembled into consensus sequences with CAP3 software. Using local alignment against the published pUC18 cloning vector sequence, the position and number of errors in the consensus were identified and stored in MySQL databases. Stringent PHRED trimming parameters proved to be efficient for the reduction of errors; however, this procedure also decreased consensus size. Moreover, re-sequencing did not have a clear effect on the removal of consensus errors, although it was able to slightly increase consensus.