<i>In vitro</i> biochemical characterization of all barley endosperm starch synthases

Starch is the main storage polysaccharide in cereals and the major source of calories in the human diet. It is synthesized by a panel of enzymes including five classes of starch synthases (SSs). While the overall starch synthase (SS) reaction is known, the functional differences between the five SS classes are poorly understood. Much of our knowledge comes from analyzing mutant plants with altered SS activities, but the resulting data are often difficult to interpret as a result of pleitropic effects, competition between enzymes, overlaps in enzyme activity and disruption of multi-enzyme complexes. Here we provide a detailed biochemical study of the activity of all five classes of SSs in barley endosperm. Each enzyme was produced recombinantly in E. coli and the properties and modes of action in vitro were studied in isolation from other SSs and other substrate modifying activities. Our results define the mode of action of each SS class in unprecedented detail; we analyze their substrate selection, temperature dependence and stability, substrate affinity and temporal abundance during barley development. Our results are at variance with some generally accepted ideas about starch biosynthesis and might lead to the reinterpretation of results obtained in planta. In particular, they indicate that granule bound SS is capable of processive action even in the absence of a starch matrix, that SSI has no elongation limit, and that SSIV, believed to be critical for the initiation of starch granules, has maltoligosaccharides and not polysaccharides as its preferred substrates

Machine-driven parameter screen of biochemical reactions

The development of complex methods in molecular biology is a laborious, costly, iterative and often intuition-bound process where optima are sought in a multidimensional parameter space through step-by-step optimizations. The difficulty of miniaturizing reactions under the microliter volumes usually handled in multiwell plates by robots, plus the cost of the experiments, limit the number of parameters and the dynamic ranges that can be explored. Nevertheless, because of non-linearities of the response of biochemical systems to their reagent concentrations, broad dynamic ranges are necessary. Here we use a high-performance nanoliter handling platform and computer generation of liquid transfer programs to explore in quadruplicates 648 combinations of 4 parameters of a biochemical reaction, the reverse-transcription, which lead us to uncover non-linear responses, parameter interactions and novel mechanistic insights. With the increased availability of computer-driven laboratory platforms for biotechnology, our results demonstrate the feasibility and advantage of methods development based on reproducible, computer-aided exhaustive characterization of biochemical systems

An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems

Image velocimetry has proven to be a promising technique for monitoring river flows using remotely operated platforms such as Unmanned Aerial Systems (UAS). However, the application of various image velocimetry algorithms has not been extensively assessed. Therefore, a sensitivity analysis has been conducted on five different image velocimetry algorithms including Large Scale Particle Image Velocimetry (LSPIV), Large-Scale Particle Tracking Velocimetry (LSPTV), Kanade−Lucas Tomasi Image Velocimetry (KLT-IV or KLT), Optical Tracking Velocimetry (OTV) and Surface Structure Image Velocimetry (SSIV), during low river flow conditions (average surface velocities of 0.12−0.14 m s - 1 , Q60) on the River Kolubara, Central Serbia. A DJI Phantom 4 Pro UAS was used to collect two 30-second videos of the surface flow. Artificial seeding material was distributed homogeneously across the rivers surface, to enhance the conditions for image velocimetry techniques. The sensitivity analysis was performed on comparable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate. Results highlighted that KLT and SSIV were sensitive to changing the feature extraction rate; however, changing the particle identification area did not affect the surface velocity results significantly. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area presented higher variability in the results, while changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area. This analysis has led to the conclusions that for surface velocities of approximately 0.12 m s - 1 image velocimetry techniques can provide results comparable to traditional techniques such as ADCPs. However, LSPIV, LSPTV and OTV require additional effort for calibration and selecting the appropriate parameters when compared to KLT-IV and SSIV. Despite the varying levels of sensitivity of each algorithm to changing parameters, all configuration image velocimetry algorithms provided results that were within 0.05 m s - 1 of the ADCP measurements, on average

Sampling error and fixed effect estimation bias. A Montecarlo simulation

Identification of optimal cell size per region to reduce attenuation bias by 90% in fixed effects mode

Methods of partitioning, biogenesis, and selecting for natural and engineered CoA-RNA

More than a decade ago, RNAs with NAD+, CoA, and acylated CoA caps were identified. Since then, studies have described NAD+'s protective, cap-like function in bacteria and its role in promoting mRNA degradation in eukaryotic cells. However, the identities, functional roles, and mechanisms of biogenesis of CoA-RNA have not yet been explored. NAD-RNAs are generated primarily by co-transcriptional capping where NAD+ is inserted into the +1 position of transcripts in place of ATP. However, this co-transcriptional model is unlikely to generate CoA-RNAs in cells because the required non-canonical initiator nucleotide for co-transcription, 3' dephospho CoA (dpCoA), is estimated to be ~200 fold less concentrated in cells than NAD+ and is therefore unlikely to outcompete ATP for the +1 position of transcripts. Thus, this work demonstrates that post-transcriptional capping by enzyme phosphopantetheine adenylyltransferase (PPAT) is a possible mechanism to generate CoA-RNA. Additionally, because having a reliable method to partition CoA-RNAs from other total RNA is a crucial step for studying and making use of them, this work describes the development of a CoA Capture Seq method for separating CoA-RNAs from total RNA. Although the CoA Capture Seq method described in this work needs further optimization before it is suitable for identifying endogenous CoA-RNAs, it was adapted and used successfully to establish in vivo post-transcriptional capping of RNAs by PPAT to generate CoA-RNAs. I further investigated methods of in vivo biogenesis of CoA-RNA by performing a selection under in vivo like conditions to select for RNAs capable of capping themselves with 4' phosphopantetheine (pPant) to become CoA-RNAs (CoAzymes) and RNAs which serve as the best substrate to be capped enzymatically by PPAT. The selection conditions were designed to mimic intracellular conditions (neutral pH, fewer number of ions included, lower ion concentrations, etc) to increase the probability of selecting for RNAs which retained functionality in cells. Before starting the selection, five different reverse-transcriptases (RTs) were tested and optimized under various reaction conditions with RNA library templates of varying structure, to determine which RT introduced the least amount of inter-library bias. The RT analysis revealed that BST 3.0 DNA Polymerase was the best choice for the RT step of the selection due to its excellent processivity, significant yield, and low-inter library bias. After 12 rounds of selection, no significant increase in CoAzyme or PPAT capping activity was observed, thus selection rounds were prepared for HTS to evaluate the library pool's progression throughout the course of the selection. Unfortunately, the HTS analysis revealed no convergence or enrichment of specific sequences or clusters of sequences. Additionally the diversity of sequence reads in each round was also inconsistent and the enrichment analysis revealed the inconsistencies in population structure throughout the selection. These data suggest the selection failed, which is likely related to the overly stringent selection parameters, especially the buffer conditions. Overall, this work illustrates the importance of selection parameters, especially the selection buffer and using RTs that introduce minimal bias, for successful selection outcomes.Includes bibliographical references

A Mendelian randomization study of testosterone and cognition in men

Testosterone replacement for older men is increasingly common, with some observations suggesting a protective effect on cognitive function. We examined the association of endogenous testosterone with cognitive function among older men in a Mendelian randomization study using a separate-sample instrumental variable (SSIV) analysis estimator to minimize confounding and reverse causality. A genetic score predicting testosterone was developed in 289 young Chinese men from Hong Kong, based on selected testosterone-related single nucleotide polymorphisms (rs10046, rs1008805 and rs1256031). The association of genetically predicted testosterone with delayed 10-word recall score and Mini-Mental State Examination (MMSE) score was assessed at baseline and follow-up using generalized estimating equation among 4,212 older Chinese men from the Guangzhou Biobank Cohort Study. Predicted testosterone was not associated with delayed 10-word recall score (−0.02 per nmol/L testosterone, 95% confidence interval (CI) −0.06–0.02) or MMSE score (0.06, 95% CI −0.002–0.12). These estimates were similar after additional adjustment for age, education, smoking, use of alcohol, body mass index and the Framingham score. Our findings do not corroborate observed protective effects of testosterone on cognitive function among older men

Identification and reproducibility of diagnostic DNA markers for tuber starch and yield optimization in a novel association mapping population of potato (Solanum tuberosum L.)

KEY MESSAGE: SNPs in candidate genesPain-1,InvCD141(invertases),SSIV(starch synthase),StCDF1(transcription factor),LapN(leucine aminopeptidase), and cytoplasm type are associated with potato tuber yield, starch content and/or starch yield. ABSTRACT: Tuber yield (TY), starch content (TSC), and starch yield (TSY) are complex characters of high importance for the potato crop in general and for industrial starch production in particular. DNA markers associated with superior alleles of genes that control the natural variation of TY, TSC, and TSY could increase precision and speed of breeding new cultivars optimized for potato starch production. Diagnostic DNA markers are identified by association mapping in populations of tetraploid potato varieties and advanced breeding clones. A novel association mapping population of 282 genotypes including varieties, breeding clones and Andean landraces was assembled and field evaluated in Northern Spain for TY, TSC, TSY, tuber number (TN) and tuber weight (TW). The landraces had lower mean values of TY, TW, TN, and TSY. The population was genotyped for 183 microsatellite alleles, 221 single nucleotide polymorphisms (SNPs) in fourteen candidate genes and eight known diagnostic markers for TSC and TSY. Association test statistics including kinship and population structure reproduced five known marker–trait associations of candidate genes and discovered new ones, particularly for tuber yield and starch yield. The inclusion of landraces increased the number of detected marker–trait associations. Integration of the present association mapping results with previous QTL linkage mapping studies for TY, TSC, TSY, TW, TN, and tuberization revealed some hot spots of QTL for these traits in the potato genome. The genomic positions of markers linked or associated with QTL for complex tuber traits suggest high multiplicity and genome wide distribution of the underlying genes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00122-016-2665-7) contains supplementary material, which is available to authorized users