Mechanisms of amino acid-mediated lifespan extension in Caenorhabditis elegans

Background

Little is known about the role of amino acids in cellular signaling pathways, especially as it pertains to pathways that regulate the rate of aging. However, it has been shown that methionine or tryptophan restriction extends lifespan in higher eukaryotes and increased proline or tryptophan levels increase longevity in C. elegans. In addition, leucine strongly activates the TOR signaling pathway, which when inhibited increases lifespan.

Results

Therefore each of the 20 proteogenic amino acids was individually supplemented to C. elegans and the effects on lifespan were determined. All amino acids except phenylalanine and aspartate extended lifespan at least to a small extent at one or more of the 3 concentrations tested with serine and proline showing the largest effects. 11 of the amino acids were less potent at higher doses, while 5 even decreased lifespan. Serine, proline, or histidine-mediated lifespan extension was greatly inhibited in eat-2 worms, a model of dietary restriction, in daf-16/FOXO, sir-2.1, rsks-1 (ribosomal S6 kinase), gcn-2, and aak-2 (AMPK) longevity pathway mutants, and in bec-1 autophagy-defective knockdown worms. 8 of 10 longevity-promoting amino acids tested activated a SKN-1/Nrf2 reporter strain, while serine and histidine were the only amino acids from those to activate a hypoxia-inducible factor (HIF-1) reporter strain. Thermotolerance was increased by proline or tryptophan supplementation, while tryptophan-mediated lifespan extension was independent of DAF-16/FOXO and SKN-1/Nrf2 signaling, but tryptophan and several related pyridine-containing compounds induced the mitochondrial unfolded protein response and an ER stress response. High glucose levels or mutations affecting electron transport chain (ETC) function inhibited amino acid-mediated lifespan extension suggesting that metabolism plays an important role. Providing many other cellular metabolites to C. elegans also increased longevity suggesting that anaplerosis of tricarboxylic acid (TCA) cycle substrates likely plays a role in lifespan extension.

Conclusions

Supplementation of C. elegans with 18 of the 20 individual amino acids extended lifespan, but lifespan often decreased with increasing concentration suggesting hormesis. Lifespan extension appears to be caused by altered mitochondrial TCA cycle metabolism and respiratory substrate utilization resulting in the activation of the DAF-16/FOXO and SKN-1/Nrf2 stress response pathways.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0167-2) contains supplementary material, which is available to authorized users.     

Concepts of pathogenesis in psoriatic arthritis: genotype determines clinical phenotype

This review focuses on the genetic features of psoriatic arthritis (PsA) and their relationship to phenotypic heterogeneity in the disease, and addresses three questions: what do the recent studies on human leukocyte antigen (HLA) tell us about the genetic relationship between cutaneous psoriasis (PsO) and PsA – that is, is PsO a unitary phenotype; is PsA a genetically heterogeneous or homogeneous entity; and do the genetic factors implicated in determining susceptibility to PsA predict clinical phenotype? We first discuss the results from comparing the HLA typing of two PsO cohorts: one cohort providing the dermatologic perspective, consisting of patients with PsO without evidence of arthritic disease; and the second cohort providing the rheumatologic perspective, consisting of patients with PsA. We show that these two cohorts differ considerably in their predominant HLA alleles, indicating the heterogeneity of the overall PsO phenotype. Moreover, the genotype of patients in the PsA cohort was shown to be heterogeneous with significant elevations in the frequency of haplotypes containing HLA-B*08, HLA-C*06:02, HLA-B*27, HLA-B*38 and HLA-B*39. Because different genetic susceptibility genes imply different disease mechanisms, and possibly different clinical courses and therapeutic responses, we then review the evidence for a phenotypic difference among patients with PsA who have inherited different HLA alleles. We provide evidence that different alleles and, more importantly, different haplotypes implicated in determining PsA susceptibility are associated with different phenotypic characteristics that appear to be subphenotypes. The implication of these findings for the overall pathophysiologic mechanisms involved in PsA is discussed with specific reference to their bearing on the discussion of whether PsA is conceptualised as an autoimmune process or one that is based on entheseal responses.     

The biological basis of degenerative disc disease: proteomic and biomechanical analysis of the canine intervertebral disc

IntroductionIn the present study, we sought to quantify and contrast the secretome and biomechanical properties of the non-chondrodystrophic (NCD) and chondrodystrophic (CD) canine intervertebral disc (IVD) nucleus pulposus (NP).MethodsWe used iTRAQ proteomic methods to quantify the secretome of both CD and NCD NP. Differential levels of proteins detected were further verified using immunohistochemistry, Western blotting, and proteoglycan extraction in order to evaluate the integrity of the small leucine-rich proteoglycans (SLRPs) decorin and biglycan. Additionally, we used robotic biomechanical testing to evaluate the biomechanical properties of spinal motion segments from both CD and NCD canines.ResultsWe detected differential levels of decorin, biglycan, and fibronectin, as well as of other important extracellular matrix (ECM)-related proteins, such as fibromodulin and HAPLN1 in the IVD NP obtained from CD canines compared with NCD canines. The core proteins of the vital SLRPs decorin and biglycan were fragmented in CD NP but were intact in the NP of the NCD animals. CD and NCD vertebral motion segments demonstrated significant differences, with the CD segments having less stiffness and a more varied range of motion.ConclusionsThe CD NP recapitulates key elements of human degenerative disc disease. Our data suggest that at least some of the compromised biomechanical properties of the degenerative disc arise from fibrocartilaginous metaplasia of the NP secondary to fragmentation of SLRP core proteins and associated degenerative changes affecting the ECM. This study demonstrates that the degenerative changes that naturally occur within the CD NP make this animal a valuable animal model with which to study IVD degeneration and potential biological therapeutics.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0733-z) contains supplementary material, which is available to authorized users.     

Phytoaccumulation of Heavy Metals in Natural Plants Thriving on Wastewater Effluent at Hattar Industrial Estate,Pakistan

The objective of this research was to compare the potential of native plants for the phytoaccumulation of heavy metals (HM). Thirteen predominant plant species (including trees, bushes and grasses) namely Ricinus communis, Ipomoea carnea, Cannabis sativa, Parthenium hysterophorus, Acacia nilotica, Dalbergia sissoo, Acacia modesta, Solanum nigrum, Xanthium stromarium, Chenopodium album, Cynodon dactylon, Eleusine indica, and Dactyloctenium aegyptium were collected from the wastewater originated from Hattar industrial estate of Pakistan, Plants shoots and roots were analyzed for heavy metals / metalloid: Pb, Cr, Cd, Zn, Fe, Ni, and As. Among plant species, the accumulation potential for HM varied depending on the type of element. Regardless of the plant species, HM concentrations varied in the order of Fe > Zn > Cr > Pb > Ni > Cd > As. Tree species of R. communis, A. nilotica, A. modesta, and D. sissoo exhibited an enhanced concentrations of metals. Accumulation pattern of Fe, Pb, Cd, and As in plants could be related to the HM composition of soil and wastewater. Most of the species exhibited higher HM composition in the root as compared to shoot. The species that found with greater ability to absorb HM in the root, got higher HM concentrations in its shoot. Shoot tissue concentrations of HM were attained by the species as D. sissoo > A. modesta > A. nilotica > R. communis > I. carnea > C. album > E. indica > P. hysterophorus > S. nigrum > C. sativa > D. aegyptium > X. strumarium > C. dactylon. Based on results, tree plants were noticed as higher accumulators of HM in polluted soils.     

Contrasting Effects of Farmyard Manure (FYM) and Compost for Remediation of Metal Contaminated Soil

We investigated effect of farm yard manure (FYM) and compost applied to metal contaminated soil at rate of 1% (FYM-1, compost-1), 2% (FYM-2, compost-2), and 3% (FYM-3, compost-3). FYM significantly (P < 0.001) increased dry weights of shoots and roots while compost increased root dry weight compared to control. Amendments significantly increased nickel (Ni) in shoots and roots of maize except compost applied at 1%. FYM-3 and -1 caused maximum Ni in shoots (11.42 mg kg^?1) and roots (80.92 mg kg^?1), respectively while compost-2 caused maximum Ni (14.08 mg kg^?1) and (163.87 mg kg^?1) in shoots and roots, respectively. Plants grown in pots amended with FYM-2 and compost-1 contained minimum Cu (30.12 and 30.11 mg kg^?1) in shoots, respectively. FYM-2 and compost-2 caused minimum zinc (Zn) (59.08 and 66.0 mg kg^?1) in maize shoots, respectively. FYM-2 caused minimum Mn in maize shoots while compost increased Mn in shoots and roots compared to control. FYM and compost increased the ammonium bicarbonate diethylene triamine penta acetic acid (AB-DTPA) extractable Ni and Mn in the soil and decreased Cu and Zn. Lower remediation factors for all metals with compost indicated that compost was effective to stabilize the metals in soil compared to FYM.     

Transcriptomic Identification of ADH1B as a Novel Candidate Gene for Obesity and Insulin Resistance in Human Adipose Tissue in Mexican Americans from the Veterans Administration Genetic Epidemiology Study (VAGES)

Type 2 diabetes (T2D) is a complex metabolic disease that is more prevalent in ethnic groups such as Mexican Americans, and is strongly associated with the risk factors obesity and insulin resistance. The goal of this study was to perform whole genome gene expression profiling in adipose tissue to detect common patterns of gene regulation associated with obesity and insulin resistance. We used phenotypic and genotypic data from 308 Mexican American participants from the Veterans Administration Genetic Epidemiology Study (VAGES). Basal fasting RNA was extracted from adipose tissue biopsies from a subset of 75 unrelated individuals, and gene expression data generated on the Illumina BeadArray platform. The number of gene probes with significant expression above baseline was approximately 31,000. We performed multiple regression analysis of all probes with 15 metabolic traits. Adipose tissue had 3,012 genes significantly associated with the traits of interest (false discovery rate, FDR ≤ 0.05). The significance of gene expression changes was used to select 52 genes with significant (FDR ≤ 10^-4) gene expression changes across multiple traits. Gene sets/Pathways analysis identified one gene, alcohol dehydrogenase 1B (ADH1B) that was significantly enriched (P < 10^-60) as a prime candidate for involvement in multiple relevant metabolic pathways. Illumina BeadChip derived ADH1B expression data was consistent with quantitative real time PCR data. We observed significant inverse correlations with waist circumference (2.8 x 10^-9), BMI (5.4 x 10^-6), and fasting plasma insulin (P < 0.001). These findings are consistent with a central role for ADH1B in obesity and insulin resistance and provide evidence for a novel genetic regulatory mechanism for human metabolic diseases related to these traits.     

Cultivation-Based and Molecular Assessment of Bacterial Diversity in the Rhizosheath of Wheat under Different Crop Rotations

A field study was conducted to compare the formationand bacterial communities of rhizosheaths of wheat grown under wheat-cotton and wheat-rice rotation and to study the effects of bacterial inoculation on plant growth. Inoculation of Azospirillum sp. WS-1 and Bacillus sp. T-34 to wheat plants increased root length, root and shoot dry weight and dry weight of rhizosheathsoil when compared to non-inoculated control plants, and under both crop rotations. Comparing both crop rotations, root length, root and shoot dry weight and dry weight of soil attached with roots were higher under wheat-cotton rotation. Organic acids (citric acid, malic acid, acetic acid and oxalic acid) were detected in rhizosheaths from both rotations, with malic acid being most abundant with 24.8±2 and 21.3±1.5 μg g^-1 dry soil in wheat-cotton and wheat-rice rotation, respectively. Two sugars (sucrose, glucose) were detected in wheat rhizosheath under both rotations, with highest concentrations of sucrose (4.08±0.5 μg g^-1and 7.36±1.0 μg g^-1) and glucose (3.12±0.5 μg g^-1 and 3.01± μg g^-1) being detected in rhizosheaths of non-inoculated control plants under both rotations. Diversity of rhizosheath-associated bacteria was evaluated by cultivation, as well as by 454-pyrosequencing of PCR-tagged 16S rRNA gene amplicons. A total of 14 and 12 bacterial isolates predominantly belonging to the genera Arthrobacter, Azospirillum, Bacillus, Enterobacter and Pseudomonaswere obtained from the rhizosheath of wheat grown under wheat-cotton and wheat-rice rotation, respectively. Analysis of pyrosequencing data revealed Proteobacteria, Bacteriodetes and Verrucomicrobia as the most abundant phyla in wheat-rice rotation, whereas Actinobacteria, Firmicutes, Chloroflexi, Acidobacteria, Planctomycetes and Cyanobacteria were predominant in wheat-cotton rotation. From a total of 46,971 sequences, 10.9% showed ≥97% similarity with 16S rRNA genes of 32 genera previously shown to include isolates with plant growth promoting activity (nitrogen fixation, phosphate-solubilization, IAA production). Among these, the most predominant genera were Arthrobacter, Azoarcus, Azospirillum, Bacillus, Cyanobacterium, Paenibacillus, Pseudomonas and Rhizobium.     

Metabolite Profiling of Low-P Tolerant and Low-P Sensitive Maize Genotypes under Phosphorus Starvation and Restoration Conditions

Background

Maize (Zea mays L.) is one of the most widely cultivated crop plants. Unavoidable economic and environmental problems associated with the excessive use of phosphatic fertilizers demands its better management. The solution lies in improving the phosphorus (P) use efficiency to sustain productivity even at low P levels. Untargeted metabolomic profiling of contrasting genotypes provides a snap shot of whole metabolome which differs under specific conditions. This information provides an understanding of the mechanisms underlying tolerance to P stress and the approach for increasing P-use-efficiency.

Methodology/Principal Findings

A comparative metabolite-profiling approach based on gas chromatography-mass spectrometry (GC/MS) was applied to investigate the effect of P starvation and its restoration in low-P sensitive (HM-4) and low-P tolerant (PEHM-2) maize genotypes. A comparison of the metabolite profiles of contrasting genotypes in response to P-deficiency revealed distinct differences among low-P sensitive and tolerant genotypes. Another set of these genotypes were grown under P-restoration condition and sampled at different time intervals (3, 5 and 10 days) to investigate if the changes in metabolite profile under P-deficiency was restored. Significant variations in the metabolite pools of these genotypes were observed under P-deficiency which were genotype specific. Out of 180 distinct analytes, 91 were identified. Phosphorus-starvation resulted in accumulation of di- and trisaccharides and metabolites of ammonium metabolism, specifically in leaves, but decreased the levels of phosphate-containing metabolites and organic acids. A sharp increase in the concentrations of glutamine, asparagine, serine and glycine was observed in both shoots and roots under low-P condition.

Conclusion

The new insights generated on the maize metabolome in resposne to P-starvation and restoration would be useful towards improvement of the P-use efficiency in maize.     

An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification

A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients’ benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.