The no-SCAR (Scarless Cas9 Assisted Recombineering) system for genome editing in Escherichia coli

Genome engineering methods in E. coli allow for easy to perform manipulations of the chromosome in vivo with the assistance of the λ-Red recombinase system. These methods generally rely on the insertion of an antibiotic resistance cassette followed by removal of the same cassette, resulting in a two-step procedure for genomic manipulations. Here we describe a method and plasmid system that can edit the genome of E. coli without chromosomal markers. This system, known as Scarless Cas9 Assisted Recombineering (no-SCAR), uses λ-Red to facilitate genomic integration of donor DNA and double stranded DNA cleavage by Cas9 to counterselect against wild-type cells. We show that point mutations, gene deletions, and short sequence insertions were efficiently performed in several genomic loci in a single-step with regards to the chromosome and did not leave behind scar sites. The single-guide RNA encoding plasmid can be easily cured due to its temperature sensitive origin of replication, allowing for iterative chromosomal manipulations of the same strain, as is often required in metabolic engineering. In addition, we demonstrate the ability to efficiently cure the second plasmid in the system by targeting with Cas9, leaving the cells plasmid-free.Shell Global Solutions (US)National Institute of Food and Agriculture (U.S.) (Postdoctoral Fellowship 2013-67012-21022

Scarless Cas9 Assisted Recombineering (no‐SCAR) in Escherichia coli, an Easy‐to‐Use System for Genome Editing

The discovery and development of genome editing systems that leverage the site‐specific DNA endonuclease system CRISPR/Cas9 has fundamentally changed the ease and speed of genome editing in many organisms. In eukaryotes, the CRISPR/Cas9 system utilizes a “guide” RNA to enable the Cas9 nuclease to make a double‐strand break at a particular genome locus, which is repaired by non‐homologous end joining (NHEJ) repair enzymes, often generating random mutations in the process. A specific alteration of the target genome can also be generated by supplying a DNA template in vivo with a desired mutation, which is incorporated by homology‐directed repair. However, E. coli lacks robust systems for double‐strand break repair. Thus, in contrast to eukaryotes, targeting E. coli chromosomal DNA with Cas9 causes cell death. However, Cas9‐mediated killing of bacteria can be exploited to select against cells with a specified genotype within a mixed population. In combination with the well described λ‐Red system for recombination in E. coli, we created a highly efficient system for marker‐free and scarless genome editing.National Institute of Food and Agriculture (U.S.) (Award 2013-67012-21022)United States. Army Research Office (Grant W911NF-09-0001

Natural infection of Run1-positive vines by naïve genotypes of Erysiphe necator

The Run1 locus for dominant resistance to powdery mildew (Erysiphe necator) has been successfully introgressed into Euvitis from Vitis rotundifolia. In the current study, Run1 vines were hybridized with breeding lines at Cornell University, and the presence of the locus was assayed using the markers GLP1-12 and VMC8g9. Signs of powdery mildew were observed on 14 of 113 Run1-positive seedlings in October 2010 in Geneva, N.Y. Severity of infection was lower for Run1-positive than for Run1-negative seedlings. Presence of mature cleistothecia suggested infection by at least two pathogen genotypes, which since V. rotundifolia is not grown within 800+ km of Geneva, N.Y., evolved from a pathogen population naïve to Run1 resistance. Therefore, caution in the deployment of the Run1 locus in new resistant cultivars is suggested so the effectiveness of Run1 does not diminish over time.

Reactions to uncertainty and the accuracy of diagnostic mammography.

BackgroundReactions to uncertainty in clinical medicine can affect decision making.ObjectiveTo assess the extent to which radiologists' reactions to uncertainty influence diagnostic mammography interpretation.DesignCross-sectional responses to a mailed survey assessed reactions to uncertainty using a well-validated instrument. Responses were linked to radiologists' diagnostic mammography interpretive performance obtained from three regional mammography registries.ParticipantsOne hundred thirty-two radiologists from New Hampshire, Colorado, and Washington.MeasurementMean scores and either standard errors or confidence intervals were used to assess physicians' reactions to uncertainty. Multivariable logistic regression models were fit via generalized estimating equations to assess the impact of uncertainty on diagnostic mammography interpretive performance while adjusting for potential confounders.ResultsWhen examining radiologists' interpretation of additional diagnostic mammograms (those after screening mammograms that detected abnormalities), a 5-point increase in the reactions to uncertainty score was associated with a 17% higher odds of having a positive mammogram given cancer was diagnosed during follow-up (sensitivity), a 6% lower odds of a negative mammogram given no cancer (specificity), a 4% lower odds (not significant) of a cancer diagnosis given a positive mammogram (positive predictive value [PPV]), and a 5% higher odds of having a positive mammogram (abnormal interpretation).ConclusionMammograms interpreted by radiologists who have more discomfort with uncertainty have higher likelihood of being recalled

Functional consequences of seven novel mutations in the CYP11B1 Gene: four mutations associated with nonclassic and three mutations causing classic 11 -Hydroxylase Deficiency

Context: Steroid 11β-hydroxylase (CYP11B1) deficiency (11OHD) is the second most common form of congenital adrenal hyperplasia (CAH). Cases of nonclassic 11OHD are rare compared with the incidence of nonclassic 21-hydroxylase deficiency. Objective: The aim of the study was to analyze the functional consequences of seven novel CYP11B1 mutations (p.M88I, p.W116G, p.P159L, p.A165D, p.K254_A259del, p.R366C, p.T401A) found in three patients with classic 11OHD, two patients with nonclassic 11OHD, and three heterozygous carriers for CYP11B1 mutations. Methods: We conducted functional studies employing a COS7 cell in vitro expression system comparing wild-type (WT) and mutant CYP11B1 activity. Mutants were examined in a computational three-dimensional model of the CYP11B1 protein. Results: All mutations (p.W116G, p.A165D, p.K254_A259del) found in patients with classic 11OHD have absent or very little 11β-hydroxylase activity relative to WT. The mutations detected in patients with nonclassic 11OHD showed partial functional impairment, with one patient being homozygous (p.P159L; 25% of WT) and the other patient compound heterozygous for a novel mild p.M88I (40% of WT) and the known severe p.R383Q mutation. The two mutations detected in heterozygous carriers (p.R366C, p.T401A) also reduced CYP11B1 activity by 23 to 37%, respectively. Conclusion: Functional analysis results allow for the classification of novel CYP11B1 mutations as causative for classic and nonclassic 11OHD, respectively. Four partially inactivating mutations are predicted to result in nonclassic 11OHD. These findings double the number of mild CYP11B1 mutations previously described as associated with mild 11OHD. Our data are important to predict phenotypic expression and provide important information for clinical and genetic counseling i

The determinants of food choice

Health nudge interventions to steer people into healthier lifestyles are increasingly applied by governments worldwide, and it is natural to look to such approaches to improve health by altering what people choose to eat. However, to produce policy recommendations that are likely to be effective, we need to be able to make valid predictions about the consequences of proposed interventions, and for this, we need a better understanding of the determinants of food choice. These determinants include dietary components (e.g. highly palatable foods and alcohol), but also diverse cultural and social pressures, cognitive-affective factors (perceived stress, health attitude, anxiety and depression), and familial, genetic and epigenetic influences on personality characteristics. In addition, our choices are influenced by an array of physiological mechanisms, including signals to the brain from the gastrointestinal tract and adipose tissue, which affect not only our hunger and satiety but also our motivation to eat particular nutrients, and the reward we experience from eating. Thus, to develop the evidence base necessary for effective policies, we need to build bridges across different levels of knowledge and understanding. This requires experimental models that can fill in the gaps in our understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that encapsulate scientific knowledge from diverse disciplines, and which embed understanding in a way that enables policy-relevant predictions to be made. Here we review recent developments in these areas.</p

Virtual Fencing Predictable for Cattle? A Simple Method to Test Whether and How Fast Cattle Can Learn the Association Between Acoustic Signal and Electric Pulse

Virtual fencing (VF) offers promising future prospects for improved grazing management as it has the potential to simplify fencing. VF lines are easily drawn and shifted via GPS coordinates. A VF collar emits an acoustic signal when the animal approaches the VF line. The signal stops immediately when the animal turns around. If the animal continues to move towards the VF line, a short electric pulse is emitted. A teaching and an operating mode are provided by the VF collars. The animals automatically change mode when they respond correctly to 20 consecutive acoustic signals without receiving an electric pulse. A prerequisite for using the technology is the ability of the grazing animal to learn to predict the electric pulse, therefore we used the time until mode change (from teaching to operating) to evaluate the learning ability and speed of 16 Fleckvieh heifers equally divided into two groups. All heifers were naive to VF prior to the study (conducted 05.07-16.07.2021). On the first day, the two groups were equipped with VF collars (® Nofence, AS, Batnfjordsøra Norway) and assigned to two adjacent pastures. On day eight, the collars were deactivated for a short time and then activated to start in teaching mode again to analyze differences in mode change speed when they were naive to the technology or experienced. The animals remained on the same pasture after reactivation of the collars. We investigated the time to reach theoperating mode (Δ) for each consecutive round (days one and eight) and found a significant difference (p \u3c 0.0001). Average Δ was 49.32 ± 0.41 h and 2.31± 0.41 h for round one and two, respectively. The faster mode change speed of the second round suggested successful learning. Given our study results, cattle learned to predict (and avoid) the electric pulse of VF collars