Identification and characterization of the sucrose synthase 2 gene (Sus2) in durum wheat

Sucrose transport is the central system for the allocation of carbon resources in vascular plants. Sucrose synthase (SUS), which reversibly catalyzes sucrose synthesis and cleavage, represents a key enzyme in the control of the flow of carbon into starch biosynthesis. In the present study the genomic identification and characterization of the Sus2-2A and Sus2-2B genes coding for SUS in durum wheat (cultivars Ciccio and Svevo) is reported. The genes were analyzed for their expression in different tissues and at different seed maturation stages, in four tetraploid wheat genotypes (Svevo, Ciccio, Primadur, and 5-BIL42). The activity of the encoded proteins was evaluated by specific activity assays on endosperm extracts and their structure established by modeling approaches. The combined results of sucrose synthase 2 expression and activity levels were then considered in the light of their possible involvement in starch yield

A-GAME: Improving the assembly of pooled functional metagenomics sequence data

Background: Expression screening of environmental DNA (eDNA) libraries is a popular approach for the identification and characterization of novel microbial enzymes with promising biotechnological properties. In such "functional metagenomics" experiments, inserts, selected on the basis of activity assays, are sequenced with high throughput sequencing technologies. Assembly is followed by gene prediction, annotation and identification of candidate genes that are subsequently evaluated for biotechnological applications. Results: Here we present A-GAME (A GAlaxy suite for functional MEtagenomics), a web service incorporating state of the art tools and workflows for the analysis of eDNA sequence data. We illustrate the potential of A-GAME workflows using real functional metagenomics data, showing that they outperform alternative metagenomics assemblers. Dedicated tools available in A-GAME allow efficient analysis of pooled libraries and rapid identification of candidate genes, reducing sequencing costs and saving the need for laborious manual annotation. Conclusion: In conclusion, we believe A-GAME will constitute a valuable resource for the functional metagenomics community. A-GAME is publicly available at http://beaconlab.it/agame

Relation between drug therapy-based comorbidity indices, Charlson's comorbidity index, polypharmacy and mortality in three samples of older adults.

Background: Comorbidity indexes were designed in order to measure how the disease burden of a patient is related to different clinical outcomes such as mortality, especially in older and intensively treated people. Charlson's Comorbidity Index (CCI) is the most widely used rating system, based on diagnoses, but when this information is not available therapy-based comorbidity indices (TBCI) are an alternative: among them, Drug Derived Complexity Index (DDCI), Medicines Comorbidity Index (MCI), and Chronic Disease Score (CDS) are available. Aims: This study assessed the predictive power for 1-year mortality of these comorbidity indices and polypharmacy. Methods: Survival analysis and Receiver Operating Characteristic (ROC) analysis were conducted on three Italian cohorts: 2,389 nursing home residents (Korian), 4,765 and 633 older adults admitted acutely to geriatric or internal medicine wards (REPOSI and ELICADHE). Results: Cox's regression indicated that the highest levels of the CCI are associated with an increment of 1-year mortality risk as compared to null score for all the three samples. DDCI and excessive polypharmacy gave similar results but MCI and CDS were not always statistically significant. The predictive power with the ROC curve of each comorbidity index was poor and similar in all settings. Conclusion: On the whole, comorbidity indices did not perform well in our three settings, although the highest level of each index was associated with higher mortality