Genetic and geographic origin of domesticated peanut as evidenced by 5S rDNA and chloroplast DNA sequences

The history of the cultivated peanut involves natural evolution and human domestication. Despite the economic importance of peanuts and the many studies carried out on their cytology and genetic variability, current knowledge on the origin of the cultigen is still very limited compared with other major crops. In this context, we analyzed the polymorphisms of some non-coding cpDNA regions and the non-transcribed spacer of the nuclear 5S rDNA of the six botanical varieties of the two subspecies of the cultigen, of the wild tetraploid A. monticola, and of the nine diploid species so far proposed as the most probable relatives of the peanut, to gain more insight into the genetic and geographic origin of this legume crop. The analysis showed complete homology in the sequences of all the peanut and A. monticola samples. These results strongly suggest that the six botanical varieties of the cultigen have a single genetic origin and that A. monticola should be regarded as the immediate tetraploid ancestor from which A. hypogaea has arisen upon domestication. Here we provide results from the first sequence-based analysis in which the maternal (A. duranensis) and paternal (A. ipa?nsis) wild diploid species of the AABB tetraploids of Arachis were unequivocally identified. Not only that, but the combination of cpDNA and NTS 5S rDNA identified the population of A. duranensis from Río Seco, Salta, Argentina, and the only known population of A. ipa?nsis from Villa Montes, Tarija, Bolivia, as those to which the genome donors of the peanut could have belonged.     

Soil Bacterial Consortia and Previous Exposure Enhance the Biodegradation of Sulfonamides from Pig Manure

Persistence or degradation of synthetic antibiotics in soil is crucial in assessing their environmental risks. Microbial catabolic activity in a sandy loamy soil with pig manure using 12C- and 14C-labelled sulfamethazine (SMZ) respirometry showed that SMZ was not readily degradable. But after 100 days, degradation in sulfadiazine-exposed manure was 9.2%, far greater than soil and organic manure (0.5% and 0.11%, respectively, p < 0.05). Abiotic degradation was not detected suggesting microbial catabolism as main degradation mechanism. Terminal restriction fragment length polymorphism showed biodiversity increases within 1 day of SMZ spiking and especially after 200 days, although some species plummeted. A clone library from the treatment with highest degradation showed that most bacteria belonged to α, β and γ classes of Proteobacteria, Firmicutes, Bacteroidetes and Acidobacteria. Proteobacteria (α, β and γ), Firmicutes and Bacteroidetes which were the most abundant classes on day 1 also decreased most following prolonged exposure. From the matrix showing the highest degradation rate, 17 SMZ-resistant isolates biodegraded low levels of 14C-labelled SMZ when each species was incubated separately (0.2-1.5%) but biodegradation was enhanced when the four isolates with the highest biodegradation were incubated in a consortium (Bacillus licheniformis, Pseudomonas putida, Alcaligenes sp. and Aquamicrobium defluvium as per 16S rRNA gene sequencing), removing up to 7.8% of SMZ after 20 days. One of these species (B. licheniformis) was a known livestock and occasional human pathogen. Despite an environmental role of these species in sulfonamide bioremediation, the possibility of horizontal transfer of pathogenicity and resistance genes should caution against an indiscriminate use of these species as sulfonamide degraders.     

Low-dosage inhibition of Dll4 signaling promotes wound healing by inducing functional neo-angiogenesis

Recent findings regarding Dll4 function in physiological and pathological conditions indicate that this Notch ligand may constitute an important therapeutic target. Dll4 appears to be a major anti-angiogenic agent, occupying a central role in various angiogenic pathways. The first trials of anti-Dll4 therapy in mice demonstrated a paradoxical effect, as it reduced tumor perfusion and growth despite leading to an increase in vascular density. This is seen as the result of insufficient maturation of the newly formed vasculature causing a circulatory defect and increased tumor hypoxia. As Dll4 function is known to be closely dependent on expression levels, we envisioned that the therapeutic anti-Dll4 dosage could be modulated to result in the increase of adequately functional blood vessels. This would be useful in conditions where vascular function is a limiting factor for recovery, like wound healing and tissue hypoxia, especially in diabetic patients. Our experimental results in mice confirmed this possibility, revealing that low dosage inhibition of Dll4/Notch signaling causes improved vascular function and accelerated wound healing.     

Identification of olive (Olea europaea) seed and pulp proteins by nLC-MS/MS via combinatorial peptide ligand libraries

Different types of extraction protocols are described for identifying proteins in seed and pulp of olive (Olea europea), by employing both conventional extraction methods and capture with ProteoMiner as well as with in house-made combinatorial peptide ligand libraries (HM-CPLLs) at pH 7.4 and at pH 2.2. Thanks to the use of CPLLs, able to dramatically amplify the signal of low-abundance species, a quite large number of compounds has been indeed identified: 61 in the seed (vs. only four reported in current literature) and 231 in the pulp (vs. 56 described so far), the deepest investigation up to the present of the olive proteome. In the seed, it highlights the presence of seed storage proteins, oleosins and histones. In the pulp, the allergenic thaumatin-like protein (Ole e 13) was confirmed, among the other 231, as the most abundant protein in the olive pulp. The present research has also been undertaken with the aim of identifying proteins in olive oil and ascertaining the relative contribution of seed and pulp proteins in their presence, if any, in oils.     

Relation between augmentation index and adiponectin during one-year metformin treatment for nonalcoholic steatohepatosis: effects beyond glucose lowering?

ABSTRACT: BACKGROUND: Insulin resistance (IR) is the major driving force behind development and progression of atherosclerosis in patients with nonalcoholic fatty liver disease (NAFLD). Therefore, correction of IR is a relevant therapeutic target. We performed the current trial to evaluate whether 12- month metformin therapy improves vascular stiffness in patients with NAFLD and to assess if this improvement is associated with change in glucose control, insulin resistance or circulating adiponectin. METHODS: In randomized, placebo controlled study, 63 patients with NAFLD were assigned to one of two groups: Group 1 received daily metformin; Group 2 received placebo. Central aortic augmentation index (AI) was performed using SphygmoCor (version 7.1, AtCor Medical, Sydney, Australia) at baseline, at 4-and 12-month treatment period. Metabolic parameters, insulin resistance markers and serum adiponectin levels were determined. RESULTS: In placebo group: AI did not improve during the treatment period. Liver function and adiponectin levels did not change during the study. In multiple linear regression analysis, the independent predictors of arterial stiffness improvement were metformin treatment and increase in circulating adiponectin levels. Among metformin treated patients: AI decreased significantly during the study. ALP and ALT decreased during initial 4-month treatment period, however raised to the pretreatment levels after 12 months. Serum adiponectin level tended to increase during treatment period with metformin. CONCLUSIONS: Metformin treatment was associated with significant decrease in AI during one year treatment in NAFLD patients. These beneficial vascular effects was associated with exposure to metformin per se as well as change in adiponectin levels suggesting that metformin may mediate its vascular effects via glicemic control-independent mechanisms.     

Direct maximization of protein identifications from tandem mass spectra

The goal of many shotgun proteomics experiments is to determine the protein complement of a complex biological mixture. For many mixtures, most methodological approaches fall significantly short of this goal. Existing solutions to this problem typically subdivide the task into two stages: first identifying a collection of peptides with a low false discovery rate and then inferring from the peptides a corresponding set of proteins. In contrast, we formulate the protein identification problem as a single optimization problem, which we solve using machine learning methods. This approach is motivated by the observation that the peptide and protein level tasks are cooperative, and the solution to each can be improved by using information about the solution to the other. The resulting algorithm directly controls the relevant error rate, can incorporate a wide variety of evidence and, for complex samples, provides 18-34% more protein identifications than the current state of the art approaches.