A novel class of modular transporters for vitamins in prokaryotes

The specific and tightly controlled transport of numerous nutrients and metabolites across cellular membranes is crucial to all forms of life. However, many of the transporter proteins involved have yet to be identified, including the vitamin transporters in various human pathogens, whose growth depends strictly on vitamin uptake. Comparative analysis of the ever-growing collection of microbial genomes coupled with experimental validation enables the discovery of such transporters. Here, we used this approach to discover an abundant class of vitamin transporters in prokaryotes with an unprecedented architecture. These transporters have energy-coupling modules comprised of a conserved transmembrane protein and two nucleotide binding proteins similar to those of ATP binding cassette (ABC) transporters, but unlike ABC transporters, they use small integral membrane proteins to capture specific substrates. We identified 21 families of these substrate capture proteins, each with a different specificity predicted by genome context analyses. Roughly half of the substrate capture proteins (335 cases) have a dedicated energizing module, but in 459 cases distributed among almost 100 gram-positive bacteria, including numerous human pathogens, different and unrelated substrate capture proteins share the same energy-coupling module. The shared use of energy-coupling modules was experimentally confirmed for folate, thiamine, and riboflavin transporters. We propose the name energy-coupling factor transporters for the new class of membrane transporters.     

Diatrack particle tracking software: Review of applications and performance evaluation

Object tracking is an instrumental tool supporting studies of cellular trafficking. There are three challenges in object tracking: the identification of targets; the precise determination of their position and boundaries; and the assembly of correct trajectories. This last challenge is particularly relevant when dealing with densely populated images with low signal‐to‐noise ratios—conditions that are often encountered in applications such as organelle tracking, virus particle tracking or single‐molecule imaging. We have developed a set of methods that can handle a wide variety of signal complexities. They are compiled into a free software package called Diatrack. Here we review its main features and utility in a range of applications, providing a survey of the dynamic imaging field together with recommendations for effective use. The performance of our framework is shown to compare favorably to a wide selection of custom‐developed algorithms, whether in terms of localization precision, processing speed or correctness of tracks.      

Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology

Understanding the drivers of phenological events is vital for forecasting species’ responses to climate change. We developed flexible Bayesian survival regression models to assess a 29‐year, individual‐level time series of flowering phenology from four taxa of Japanese cherry trees (Prunus spachiana, Prunus × yedoensis, Prunus jamasakura, and Prunus lannesiana), from the Tama Forest Cherry Preservation Garden in Hachioji, Japan. Our modeling framework used time‐varying (chill and heat units) and time‐invariant (slope, aspect, and elevation) factors. We found limited differences among taxa in sensitivity to chill, but earlier flowering taxa, such as P. spachiana, were more sensitive to heat than later flowering taxa, such as P. lannesiana. Using an ensemble of three downscaled regional climate models under the A1B emissions scenario, we projected shifts in flowering timing by 2100. Projections suggest that each taxa will flower about 30 days earlier on average by 2100 with 2–6 days greater uncertainty around the species mean flowering date. Dramatic shifts in the flowering times of cherry trees may have implications for economically important cultural festivals in Japan and East Asia. The survival models used here provide a mechanistic modeling approach and are broadly applicable to any time‐to‐event phenological data, such as plant leafing, bird arrival time, and insect emergence. The ability to explicitly quantify uncertainty, examine phenological responses on a fine time scale, and incorporate conditions leading up to an event may provide future insight into phenologically driven changes in carbon balance and ecological mismatches of plants and pollinators in natural populations and horticultural crops.     

Purine and pyrimidine metabolism in human T lymphocytes. Regulation of deoxyribonucleotide metabolism

Purine and pyrimidine deoxyribonucleoside metabolism was studied in G1 and S phase human thymocytes and compared with that of the more mature T lymphocytes from peripheral blood. Both thymocyte populations have much higher intracellular deoxyribonucleoside triphosphate (dNTP) pools than peripheral blood T lymphocytes. The smallest dNTP pool in S phase thymocytes is dCTP (5.7 pmol/10(6) cells) and the largest is dTTP (48 pmol/10(6) cells), whereas in G1 thymocytes, dATP and dGTP comprise the smallest pools. While both G1 and S phase thymocytes have active deoxyribonucleoside salvage pathways, only S phase thymocytes have significant ribonucleotide reduction activity. We have studied ribonucleotide reduction and deoxyribonucleoside salvage in S phase thymocytes in the presence of extracellular deoxyribonucleosides. Based on these studies, we propose a model for the interaction of deoxyribonucleoside salvage and ribonucleotide reduction in S phase thymocytes. According to this model, extracellular deoxycytidine at micromolar concentrations is efficiently salvaged by deoxycytidine kinase. However, due to feedback inhibition of deoxycytidine kinase by dCTP, the maximal level of dCTP which can be achieved is limited. The salvage of both deoxyadenosine and deoxyguanosine (up to 10(-4) M) is completely inhibited in the presence of micromolar concentrations of deoxycytidine, whereas the salvage of thymidine is unregulated resulting in large increases in dTTP levels. Moreover, significant amounts of the salvaged deoxycytidine is used for dTTP synthesis resulting in further increase of dTTP pools. The accumulated dTTP inhibits the reduction of UDP and CDP while stimulating GDP reduction and subsequently also ADP reduction. The end result of the proposed model is that S phase thymocytes in the presence of a wide range of extracellular deoxyribonucleoside concentrations synthesize their pyrimidine dNTP by the salvage pathway, whereas purine dNTPs are synthesized primarily by ribonucleotide reduction. Using the proposed model, it is possible to predict the relative intracellular dNTP pools found in fresh S phase thymocytes.     

Environmental factors function as constraints on soil nitrous oxide fluxes in bioenergy feedstock cropping systems

Nitrous oxide (N₂O) is a potent greenhouse gas and major component of the net global warming potential of bioenergy feedstock cropping systems. Numerous environmental factors influence soil N₂O production, making direct correlation difficult to any one factor of N₂O fluxes under field conditions. We instead employed quantile regression to evaluate whether soil temperature, water‐filled pore space (WFPS), and concentrations of soil nitrate () and ammonium () determined upper bounds for soil N₂O flux magnitudes. We collected data over 6 years from a range of bioenergy feedstock cropping systems including no‐till grain crops, perennial warm‐season grasses, hybrid poplar, and polycultures of tallgrass prairie species each with and without nitrogen (N) addition grown at two sites. The upper bounds for soil N₂O fluxes had a significant and positive correlation with all four environmental factors, although relatively large fluxes were still possible at minimal values for nearly all factors. The correlation with was generally weaker, suggesting it is less important than in driving large fluxes. Quantile regression slopes were generally lower for unfertilized perennials than for other systems, but this may have resulted from a perpetual state of nitrogen limitation, which prevented other factors from being clear constraints. This framework suggests efforts to reduce concentrations of in the soil may be effective at reducing high‐intensity periods—”hot moments”—of N₂O production.     

Quantification of atherosclerotic plaque activity and vascular inflammation using [18-F] fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT)

Conventional non-invasive imaging modalities of atherosclerosis such as coronary artery calcium (CAC) and carotid intimal medial thickness (C-IMT) provide information about the burden of disease. However, despite multiple validation studies of CAC, and C-IMT, these modalities do not accurately assess plaque characteristics, and the composition and inflammatory state of the plaque determine its stability and, therefore, the risk of clinical events. [(18)F]-2-fluoro-2-deoxy-D-glucose (FDG) imaging using positron-emission tomography (PET)/computed tomography (CT) has been extensively studied in oncologic metabolism. Studies using animal models and immunohistochemistry in humans show that FDG-PET/CT is exquisitely sensitive for detecting macrophage activity, an important source of cellular inflammation in vessel walls. More recently, we and others have shown that FDG-PET/CT enables highly precise, novel measurements of inflammatory activity of activity of atherosclerotic plaques in large and medium-sized arteries. FDG-PET/CT studies have many advantages over other imaging modalities: 1) high contrast resolution; 2) quantification of plaque volume and metabolic activity allowing for multi-modal atherosclerotic plaque quantification; 3) dynamic, real-time, in vivo imaging; 4) minimal operator dependence. Finally, vascular inflammation detected by FDG-PET/CT has been shown to predict cardiovascular (CV) events independent of traditional risk factors and is also highly associated with overall burden of atherosclerosis. Plaque activity by FDG-PET/CT is modulated by known beneficial CV interventions such as short term (12 week) statin therapy as well as longer term therapeutic lifestyle changes (16 months). The current methodology for quantification of FDG uptake in atherosclerotic plaque involves measurement of the standardized uptake value (SUV) of an artery of interest and of the venous blood pool in order to calculate a target to background ratio (TBR), which is calculated by dividing the arterial SUV by the venous blood pool SUV. This method has shown to represent a stable, reproducible phenotype over time, has a high sensitivity for detection of vascular inflammation, and also has high inter-and intra-reader reliability. Here we present our methodology for patient preparation, image acquisition, and quantification of atherosclerotic plaque activity and vascular inflammation using SUV, TBR, and a global parameter called the metabolic volumetric product (MVP). These approaches may be applied to assess vascular inflammation in various study samples of interest in a consistent fashion as we have shown in several prior publications.