Theoretical evidence that root penetration ability interacts with soil compaction regimes to affect nitrate capture

Background and AimsAlthough root penetration of strong soils has been intensively studied at the scale of individual root axes, interactions between soil physical properties and soil foraging by whole plants are less clear. Here we investigate how variation in the penetration ability of distinct root classes and bulk density profiles common to real-world soils interact to affect soil foraging strategies.MethodsWe utilize the functional–structural plant model ‘OpenSimRoot’ to simulate the growth of maize (Zea mays) root systems with variable penetration ability of axial and lateral roots in soils with (1) uniform bulk density, (2) plow pans and (3) increasing bulk density with depth. We also modify the availability and leaching of nitrate to uncover reciprocal interactions between these factors and the capture of mobile resources.Key ResultsSoils with plow pans and bulk density gradients affected overall size, distribution and carbon costs of the root system. Soils with high bulk density at depth impeded rooting depth and reduced leaching of nitrate, thereby improving the coincidence of nitrogen and root length. While increasing penetration ability of either axial or lateral root classes produced root systems of comparable net length, improved penetration of axial roots increased allocation of root length in deeper soil, thereby amplifying N acquisition and shoot biomass. Although enhanced penetration ability of both root classes was associated with greater root system carbon costs, the benefit to plant fitness from improved soil exploration and resource capture offset these.ConclusionsWhile lateral roots comprise the bulk of root length, axial roots function as a scaffold determining the distribution of these laterals. In soils with high soil strength and leaching, root systems with enhanced penetration ability of axial roots have greater distribution of root length at depth, thereby improving capture of mobile resources.     

Topographic and Bioclimatic Determinants of the Occurrence of Forest and Grassland in Tropical Montane Forest-Grassland Mosaics of the Western Ghats,India

The objective of this analysis was to identify topographic and bioclimatic factors that predict occurrence of forest and grassland patches within tropical montane forest-grassland mosaics. We further investigated whether interactions between topography and bioclimate are important in determining vegetation pattern, and assessed the role of spatial scale in determining the relative importance of specific topographic features. Finally, we assessed the role of elevation in determining the relative importance of diverse explanatory factors. The study area consists of the central and southern regions of the Western Ghats of Southern India, a global biodiversity hotspot. Random forests were used to assess prediction accuracy and predictor importance. Conditional inference classification trees were used to interpret predictor effects and examine potential interactions between predictors. GLMs were used to confirm predictor importance and assess the strength of interaction terms. Overall, topographic and bioclimatic predictors classified vegetation pattern with approximately 70% accuracy. Prediction accuracy was higher for grassland than forest, and for mosaics at higher elevations. Elevation was the most important predictor, with mosaics above 2000m dominated largely by grassland. Relative topographic position measured at a local scale (within a 300m neighbourhood) was another important predictor of vegetation pattern. In high elevation mosaics, northness and concave land surface curvature were important predictors of forest occurrence. Important bioclimatic predictors were: dry quarter precipitation, annual temperature range and the interaction between the two. The results indicate complex interactions between topography and bioclimate and among topographic variables. Elevation and topography have a strong influence on vegetation pattern in these mosaics. There were marked regional differences in the roles of various topographic and bioclimatic predictors across the range of study mosaics, indicating that the same pattern of grass and forest seems to be generated by different sets of mechanisms across the region, depending on spatial scale and elevation.     

Protein microarrays and novel detection platforms

The field of proteomics has undergone rapid advancements over the last decade and protein microarrays have emerged as a promising technological platform for the challenging task of studying complex proteomes. This gel-free approach has found an increasing number of applications due to its ability to rapidly and efficiently study thousands of proteins simultaneously. Different protein microarrays, including capture arrays, reverse-phase arrays, tissue microarrays, lectin microarrays and cell-free expression microarrays, have emerged, which have demonstrated numerous applications for proteomics studies including biomarker discovery, protein interaction studies, enzyme-substrate profiling, immunological profiling and vaccine development, among many others. The need to detect extremely low-abundance proteins in complex mixtures has provided motivation for the development of sensitive, real-time and multiplexed detection platforms. Conventional label-based approaches like fluorescence, chemiluminescence and use of radioactive isotopes have witnessed substantial advancements, with techniques like quantum dots, gold nanoparticles, dye-doped nanoparticles and several bead-based methods now being employed for protein microarray studies. In order to overcome the limitations posed by label-based technologies, several label-free approaches like surface plasmon resonance, carbon nanotubes and nanowires, and microcantilevers, among others, have also advanced in recent years, and these methods detect the query molecule itself. The scope of this article is to outline the protein microarray techniques that are currently being used for analytical and function-based proteomics and to provide a detailed analysis of the key technological advances and applications of various detection systems that are commonly used with microarrays.     

Reactive metabolites of desipramine and clomipramine: The kinetics of formation and reactivity with DNA

Tricyclic antidepressants (TCAs), along with phenothyazines and some industrial chemicals, are shown to react with enzymes that exhibit peroxidase activity. These reactions result in the formation of reactive intermediates having unpaired electrons. The peroxidase oxidation and reactivity of two TCAs, desipramine and clomipramine, were investigated. As a model of peroxidase, horseradish peroxidase (HRP) was employed. The products of the peroxidase catalyzed oxidation of desipramine and clomipramine were identified as N-dealkylated compounds iminodibenzyl and 3-chloroiminodibenzyl using the GC/MS technique. Both drugs formed broad UV/vis absorption spectra in the presence of HRP and H(2)O(2), indicating the formation of a radical cations-reactive intermediate of the oxidation reaction. The dynamics of the formation of the desipramine intermediate was studied using UV/vis spectroscopy. The extinction coefficient was measured for the reactive intermediate, 7.80×10(3)M(-1)cm(-1), as well as the apparent Michaelis-Menten and catalytic constants, 4.4mM and 2.3s(-1), respectively. Both desipramine and clomipramine degraded DNA in the presence of HRP/H(2)O(2), as was revealed by agarose gel electrophoresis and PCI extraction. Manipulating the kinetic parameters of drug's radical formation and determining the extent of degradation to biomolecules could be potentially used for designing effective agents exhibiting specific reactivity.     

Hepatic stearoyl-CoA desaturase-1 deficiency protects mice from carbohydrate-induced adiposity and hepatic steatosis

Stearoyl-CoA desaturase-1 (SCD1), a critical regulator of energy metabolism, catalyzes the synthesis of monounsaturated fats. To understand the tissue-specific role of SCD1 in energy homeostasis, we used Cre-lox technology to generate mice with a liver-specific knockout of Scd1 (LKO). LKO mice were protected from high-carbohydrate, but not high-fat (HF), diet-induced adiposity and hepatic steatosis. Additionally, on a high-sucrose, very low-fat (HSVLF) diet, lipogenesis and levels of nuclear SREBP-1 and ChREBP were significantly decreased in the livers of LKO relative to Scd1^lox/lox (Lox) mice. HSVLF feeding in LKO mice caused hypoglycemia and hepatic carbohydrate reduction due to an impairment of gluconeogenesis. Oleate, but not stearate, supplementation normalized adiposity, gluconeogenesis, triglyceride secretion, and hepatic lipogenesis of LKO mice. These results indicate that hepatic SCD1 expression (and thus, oleate) is required for carbohydrate-induced adiposity, but SCD1 inhibition in extrahepatic tissues is required to protect mice from HF-induced obesity and insulin resistance.     

Stearoyl-CoA desaturase-1 deficiency attenuates obesity and insulin resistance in leptin-resistant obese mice

Obesity and adiposity greatly increase the risk for secondary conditions such as insulin resistance. Mice deficient in the enzyme stearoyl-CoA desaturase-1 (SCD1) are lean and protected from diet-induced obesity and insulin resistance. In order to determine the effect of SCD1 deficiency on various mouse models of obesity, we introduced a global deletion of the Scd1 gene into leptin-deficient ob/ob mice, leptin-resistant Agouti (A^y/a) mice, and high-fat diet-fed obese (DIO) mice. SCD1 deficiency lowered body weight, adiposity, hepatic lipid accumulation, and hepatic lipogenic gene expression in all three mouse models. However, glucose tolerance, insulin, and leptin sensitivity were improved by SCD1 deficiency only in A^y/a and DIO mice, but not ob/ob mice. These data uncouple the effects of SCD1 deficiency on weight loss from those on insulin sensitivity and suggest a beneficial effect of SCD1 inhibition on insulin sensitivity in obese mice that express a functional leptin gene.     

Rapid quantification of DNA libraries for next-generation sequencing

The next-generation DNA sequencing workflows require an accurate quantification of the DNA molecules to be sequenced which assures optimal performance of the instrument. Here, we demonstrate the use of qPCR for quantification of DNA libraries used in next-generation sequencing. In addition, we find that qPCR quantification may allow improvements to current NGS workflows, including reducing the amount of library DNA required, increasing the accuracy in quantifying amplifiable DNA, and avoiding amplification bias by reducing or eliminating the need to amplify DNA before sequencing.     

DNA-based Fish Species Identification Protocol

We have developed a fast, simple, and accurate DNA-based screening method to identify the fish species present in fresh and processed seafood samples. This versatile method employs PCR amplification of genomic DNA extracted from fish samples, followed by restriction fragment length polymorphism (RFLP) analysis to generate fragment patterns that can be resolved on the Agilent 2100 Bioanalyzer and matched to the correct species using RFLP pattern matching software.The fish identification method uses a simple, reliable, spin column- based protocol to isolate DNA from fish samples. The samples are treated with proteinase K to release the nucleic acids into solution. DNA is then isolated by suspending the sample in binding buffer and loading onto a micro- spin cup containing a silica- based fiber matrix. The nucleic acids in the sample bind to the fiber matrix. The immobilized nucleic acids are washed to remove contaminants, and total DNA is recovered in a final volume of 100 μl. The isolated DNA is ready for PCR amplification with the provided primers that bind to sequences found in all fish genomes. The PCR products are then digested with three different restriction enzymes and resolved on the Agilent 2100 Bioanalyzer. The fragment lengths produced in the digestion reactions can be used to determine the species of fish from which the DNA sample was prepared, using the RFLP pattern matching software containing a database of experimentally- derived RFLP patterns from commercially relevant fish species.Download video file.^{(106M, mp4)}