SIRT1 Prevents R-Loops during Chronological Aging by Modulating DNA Replication at rDNA Loci.

In metazoans, the largest sirtuin, SIRT1, is a nuclear protein implicated in epigenetic modifications, circadian signaling, DNA recombination, replication, and repair. Our previous studies have demonstrated that SIRT1 binds replication origins and inhibits replication initiation from a group of potential initiation sites (dormant origins). We studied the effects of aging and SIRT1 activity on replication origin usage and the incidence of transcription-replication collisions (creating R-loop structures) in adult human cells obtained at different time points during chronological aging and in cancer cells. In primary, untransformed cells, SIRT1 activity declined and the prevalence of R-loops rose with chronological aging. Both the reduction in SIRT1 activity and the increased abundance of R-loops were also observed during the passage of primary cells in culture. All cells, regardless of donor age or transformation status, reacted to the short-term, acute chemical inhibition of SIRT1 with the activation of excessive replication initiation events coincident with an increased prevalence of R-loops. However, cancer cells activated dormant replication origins, genome-wide, during long-term proliferation with mutated or depleted SIRT1, whereas, in primary cells, the aging-associated SIRT1-mediated activation of dormant origins was restricted to rDNA loci. These observations suggest that chronological aging and the associated decline in SIRT1 activity relax the regulatory networks that protect cells against excess replication and that the mechanisms protecting from replication-transcription collisions at the rDNA loci manifest as differentially enhanced sensitivities to SIRT1 decline and chronological aging.

Rapid evolution of diet choice in an introduced population of Trinidadian guppies.

Eco-evolutionary theory has brought an interest in the rapid evolution of functional traits. Among them, diet is an important determinant of ecosystem structure, affecting food web dynamics and nutrient cycling. However, it is largely unknown whether diet, or diet preference, has a hereditary basis and can evolve on contemporary timescales. Here, we study the diet preferences of Trinidadian guppies Poecilia reticulata collected from directly below an introduction site of fish transplanted from a high-predation environment into a low predation site where their densities and competition increased. Behavioural assays on F2 common garden descendants of the ancestral and derived populations showed that diet preference has rapidly evolved in the introduced population in only 12 years (approx. 36 generations). Specifically, we show that the preference for high-quality food generally found in high-predation guppies is lost in the newly derived low-predation population, who show an inertia toward the first encountered food. This result is predicted by theory stating that organisms should evolve less selective diets under higher competition. Demonstrating that diet preference can show rapid and adaptive evolution is important to our understanding of eco-evolutionary feedbacks and the role of evolution in ecosystem dynamics.

Elemental assessment of vegetation via portable X-ray fluorescence (PXRF) spectrometry.

Elemental concentrations in vegetation are of critical importance, whether establishing plant essential element concentrations (toxicity vs. deficiency) or investigating deleterious elements (e.g., heavy metals) differentially extracted from the soil by plants. Traditionally, elemental analysis of vegetation has been facilitated by acid digestion followed by quantification via inductively coupled plasma (ICP) or atomic absorption (AA) spectroscopy. Previous studies have utilized portable X-ray fluorescence (PXRF) spectroscopy to quantify elements in soils, but few have evaluated the vegetation. In this study, a PXRF spectrometer was employed to scan 228 organic material samples (thatch, deciduous leaves, grasses, tree bark, and herbaceous plants) from smelter-impacted areas of Romania, as well as National Institute of Standards and Technology (NIST) certified reference materials, to demonstrate the application of PXRF for elemental determination in vegetation. Samples were scanned in three conditions: as received from the field (moist), oven dry (70 °C), and dried and powdered to pass a 2 mm sieve. Performance metrics of PXRF models relative to ICP atomic emission spectroscopy were developed to asses optimal scanning conditions. Thatch and bark samples showed the highest mean PXRF and ICP concentrations (e.g., Zn, Pb, Cd, Fe), with the exceptions of K and Cl. Validation statistics indicate that the stable validation predictive capacity of PXRF increased in the following order: oven dry intact < field moist < oven dried and powdered. Even under field moist conditions, PXRF could reasonably be used for the determination of Zn (coefficient of determination, R2val 0.86; residual prediction deviation, RPD 2.72) and Cu (R2val 0.77; RPD 2.12), while dried and powdered samples allowed for stable validation prediction of Pb (R2val 0.90; RPD 3.29), Fe (R2val 0.80; RPD 2.29), Cd (R2val 0.75; RPD 2.07) and Cu (R2val 0.98; RPD of 8.53). Summarily, PXRF was shown to be a useful approach for quickly assessing the elemental concentration in vegetation. Future PXRF/vegetation research should explore additional elements and investigate its usefulness in evaluating phytoremediation effectiveness.

Compost salinity assessment via portable X-ray fluorescence (PXRF) spectrometry.

Compost salinity is an ongoing concern for compost producers, especially with certain feedstocks and in arid or semiarid regions. Current testing protocols call for sampling and testing ex-situ via 1:5 (w/v) slurries via electrical conductance. For this research an alternate approach has been proposed, the use of portable X-ray fluorescence (PXRF) spectrometry. Adapting methods developed for soil and water salinity analysis via PXRF, elemental data was used as a proxy for the prediction of compost salinity. In total, 74 compost samples were scanned with PXRF followed by traditional laboratory analysis. Results indicated a strong correlation between the datasets (R2 0.80; RMSE 1.04 dS m-1), similar to findings for soil and water salinity. Furthermore, using the same elemental dataset, compost pH was reasonably predicted (R2 0.63; RMSE 0.35). PXRF has the benefit of being able to be conducted in-situ or in the laboratory. And, multiple chemical parameters of interest can potentially be predicted from the same dataset. In conclusion, PXRF shows promise for rapid, in-situ salinity determination of composted products.