Comparative analysis of structural variations due to genome shuffling of Bacillus subtilis VS15 for improved cellulase production

Cellulose is one of the most abundant and renewable biomass products used for the production of bioethanol. Cellulose can be efficiently hydrolyzed by Bacillus subtilis VS15, a strain isolate obtained from decomposing logs. A genome shuffling approach was implemented to improve the cellulase activity of Bacillus subtilis VS15. Mutant strains were created using ethyl methyl sulfonate (EMS), N-Methyl-N′ nitro-N-nitrosoguanidine (NTG), and ultraviolet light (UV) followed by recursive protoplast fusion. After two rounds of shuffling, the mutants Gb2, Gc8, and Gd7 were produced that had an increase in cellulase activity of 128%, 148%, and 167%, respectively, in comparison to the wild type VS15. The genetic diversity of the shuffled strain Gd7 and wild type VS15 was compared at whole genome level. Genomic-level comparisons identified a set of eight genes, consisting of cellulase and regulatory genes, of interest for further analyses. Various genes were identified with insertions and deletions that may be involved in improved celluase production in Gd7.. Strain Gd7 maintained the capability of hydrolyzing wheatbran to glucose and converting glucose to ethanol by fermentation with Saccharomyces cerevisiae of the wild type VS17. This ability was further confirmed by the acidified potassium dichromate (K2Cr2O7) method

Retrospective analysis of anthropometric and fitness characteristics associated with long-term career progression in Rugby League.

The current study retrospectively investigated the differences in anthropometric and fitness characteristics of junior rugby league players selected onto a talent identification and development (TID) programme between long-term career progression levels (i.e., amateur, academy, professional)

Development and external validation of a mixed-effects deep learning model to diagnose COVID-19 from CT imaging

BackgroundThe automatic analysis of medical images has the potential improve diagnostic accuracy while reducing the strain on clinicians. Current methods analyzing 3D-like imaging data, such as computerized tomography imaging, often treat each image slice as individual slices. This may not be able to appropriately model the relationship between slices.MethodsOur proposed method utilizes a mixed-effects model within the deep learning framework to model the relationship between slices. We externally validated this method on a data set taken from a different country and compared our results against other proposed methods. We evaluated the discrimination, calibration, and clinical usefulness of our model using a range of measures. Finally, we carried out a sensitivity analysis to demonstrate our methods robustness to noise and missing data.ResultsIn the external geographic validation set our model showed excellent performance with an AUROC of 0.930 (95%CI: 0.914, 0.947), with a sensitivity and specificity, PPV, and NPV of 0.778 (0.720, 0.828), 0.882 (0.853, 0.908), 0.744 (0.686, 0.797), and 0.900 (0.872, 0.924) at the 0.5 probability cut-off point. Our model also maintained good calibration in the external validation dataset, while other methods showed poor calibration.ConclusionDeep learning can reduce stress on healthcare systems by automatically screening CT imaging for COVID-19. Our method showed improved generalizability in external validation compared to previous published methods. However, deep learning models must be robustly assessed using various performance measures and externally validated in each setting. In addition, best practice guidelines for developing and reporting predictive models are vital for the safe adoption of such models

Evolution of chloroplast retrograde signaling facilitates green plant adaptation to land

Chloroplast retrograde signaling networks are vital for chloroplast biogenesis, operation, and signaling, including excess light and drought stress signaling. To date, retrograde signaling has been considered in the context of land plant adaptation, but not regarding the origin and evolution of signaling cascades linking chloroplast function to stomatal regulation. We show that key elements of the chloroplast retrograde signaling process, the nucleotide phosphatase (SAL1) and 3'-phosphoadenosine-5'-phosphate (PAP) metabolism, evolved in streptophyte algae-the algal ancestors of land plants. We discover an early evolution of SAL1-PAP chloroplast retrograde signaling in stomatal regulation based on conserved gene and protein structure, function, and enzyme activity and transit peptides of SAL1s in species including flowering plants, the fern Ceratopteris richardii, and the moss Physcomitrella patens Moreover, we demonstrate that PAP regulates stomatal closure via secondary messengers and ion transport in guard cells of these diverse lineages. The origin of stomata facilitated gas exchange in the earliest land plants. Our findings suggest that the conquest of land by plants was enabled by rapid response to drought stress through the deployment of an ancestral SAL1-PAP signaling pathway, intersecting with the core abscisic acid signaling in stomatal guard cells

Assessing the efficacy of the healthy eating and lifestyle programme (HELP) compared with enhanced standard care of the obese adolescent in the community: study protocol for a randomized controlled trial

Background: The childhood obesity epidemic is one of the foremost UK health priorities. Childhood obesity tracks into adult life and places individuals at considerable risk for diabetes, cardiovascular disease, liver disease and other morbidities. There is widespread need for paediatric lifestyle programmes as change may be easier to accomplish in childhood than later in life. Study Design/Method: The study will evaluate the management of adolescent obesity by conducting a Medical Research Council complex intervention phase III efficacy randomised clinical trial of the Healthy Eating Lifestyle Programme within primary care. The study tests a community delivered multi-component intervention designed for adolescents developed from best practice as identified by National Institute for Health and Clinical Excellence. The hospital based pilot reduced body mass index and improved health-related quality of life. Subjects will be individually randomised to receiving either the Healthy Eating Lifestyle Programme (12 fortnightly family sessions) or enhanced standard care. Baseline and follow up assessments will be undertaken blind to allocation status. A health economic evaluation is also being conducted. 200 obese young people (13-17 years, body mass index > 98th centile for age and sex) will be recruited from primary care within the greater London area. The primary hypothesis is that a motivational and solution-focused family-based weight management programme delivered over 6 months is more efficacious in reducing body mass index in obese adolescents identified in the community than enhanced standard care. The primary outcome will be body mass index at the end of the intervention, adjusted for baseline body mass index, age and sex. The secondary hypothesis is that the Healthy Eating Lifestyle Programme is more efficacious in improving quality of life and psychological function and reducing waist circumference and cardiovascular risk factors in obese adolescents than enhanced standard care assessed at 6 and 12 months post baseline assessment. Improvement in quality of life predicts on-going lifestyle change and maximises the chances of long-term weight reduction. We will explore whether improvement in QOL may be intermediate on the pathway between the intervention and body mass index change

Using genetics to test the causal relationship of total adiposity and periodontitis: Mendelian randomization analyses in the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium

Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI).Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis.Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data.Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide confidence intervals

Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index

A large number of genetic loci are associated with adult body mass index. However, the genetics of childhood body mass index are largely unknown. We performed a meta-analysis of genome-wide association studies of childhood body mass index, using sex-and age-adjusted standard deviation scores. We included 35 668 children from 20 studies in the discovery phase and 11 873 children from 13 studies in the replication phase. In total, 15 loci reached genome-wide significance (P-value &lt;5 x 10(-8)) in the joint discovery and replication analysis, of which 12 are previously identified loci in or close to ADCY3, GNPDA2, TMEM18, SEC16B, FAIM2, FTO, TFAP2B, TNNI3K, MC4R, GPR61, LMX1B and OLFM4 associated with adult body mass index or childhood obesity. We identified three novel loci: rs13253111 near ELP3, rs8092503 near RAB27B and rs13387838 near ADAM23. Per additional risk allele, body mass index increased 0.04 Standard Deviation Score (SDS) [Standard Error (SE) 0.007], 0.05 SDS (SE 0.008) and 0.14 SDS (SE 0.025), for rs13253111, rs8092503 and rs13387838, respectively. A genetic risk score combining all 15 SNPs showed that each additional average risk allele was associated with a 0.073 SDS (SE 0.011, P-value = 3.12 x 10(-10)) increase in childhood body mass index in a population of 1955 children. This risk score explained 2% of the variance in childhood body mass index. This study highlights the shared genetic background between childhood and adult body mass index and adds three novel loci. These loci likely represent age-related differences in strength of the associations with body mass index.</p