Predicting changes in protein stability caused by mutation using sequence‐and structure‐based methods in a CAGI5 blind challenge

Predicting the impact of mutations on proteins remains an important problem. As part of the CAGI5 frataxin challenge, we evaluate the accuracy with which Provean, FoldX, and ELASPIC can predict changes in the Gibbs free energy of a protein using a limited data set of eight mutations. We find that different methods have distinct strengths and limitations, with no method being strictly superior to other methods on all metrics. ELASPIC achieves the highest accuracy while also providing a web interface which simplifies the evaluation and analysis of mutations. FoldX is slightly less accurate than ELASPIC but is easier to run locally, as it does not depend on external tools or datasets. Provean achieves reasonable results while being computational less expensive than the other methods and not requiring a structure of the protein. In addition to methods submitted to the CAGI5 community experiment, and with the aim to inform about other methods with high accuracy, we also evaluate predictions made by Rosetta's ddg_monomer protocol, Rosetta's cartesian_ddg protocol, and thermodynamic integration calculations using Amber package. ELASPIC still achieves the highest accuracy, while Rosetta's catesian_ddg protocol appears to perform best in capturing the overall trend in the data.     

Myoarchitectural disarray of hypertrophic cardiomyopathy begins pre‐birth

Myoarchitectural disarray – the multiscalar disorganisation of myocytes, is a recognised histopathological hallmark of adult human hypertrophic cardiomyopathy (HCM). It occurs before the establishment of left ventricular hypertrophy (LVH) but its early origins and evolution around the time of birth are unknown. Our aim is to investigate whether myoarchitectural abnormalities in HCM are present in the fetal heart. We used wild‐type, heterozygous and homozygous hearts (n = 56) from a Mybpc3‐targeted knock‐out HCM mouse model and imaged the 3D micro‐structure by high‐resolution episcopic microscopy. We developed a novel structure tensor approach to extract, display and quantify myocyte orientation and its local angular uniformity by helical angle, angle of intrusion and myoarchitectural disarray index, respectively, immediately before and after birth. In wild‐type, we demonstrate uniformity of orientation of cardiomyocytes with smooth transitions of helical angle transmurally both before and after birth but with traces of disarray at the septal insertion points of the right ventricle. In comparison, heterozygous mice free of LVH, and homozygous mice showed not only loss of the normal linear helical angulation transmural profiles observed in wild‐type but also fewer circumferentially arranged myocytes at birth. Heterozygous and homozygous showed more disarray with a wider distribution than in wild‐type before birth. In heterozygous mice, disarray was seen in the anterior, septal and inferior walls irrespective of stage, whereas in homozygous mice it extended to the whole LV circumference including the lateral wall. In conclusion, myoarchitectural disarray is detectable in the fetal heart of an HCM mouse model before the development of LVH.     

Lateral patellar maltracking due to trochlear dysplasia: A computational study

BackgroundThe study focuses on the influence of trochlear dysplasia on patellar tracking related to patellar instability.MethodsKnee extension against gravity and dual-limb squatting were simulated with seven models representing knees being treated for recurrent instability. Trochlear depth was altered to represent lateral trochlear inclination (LTI) values of 6°, 12° and 24°. Repeated measures analyses compared patellar lateral shift (bisect offset index) across different LTI values. Peak bisect offset index during extension and squatting was correlated with patella alta (Caton–Deschamps index) and maximum lateral position of the tibial tuberosity.ResultsBisect offset index varied significantly (p < 0.05) between different LTI values at multiple flexion angles throughout simulated knee extension and squatting. Average bisect offset values were 1.02, 0.95, and 0.86 for LTI = 6°, 12°, and 24°, respectively, at 0° of flexion for knee extension. The strongest correlation occurred between peak bisect offset index and lateral position of the tibial tuberosity for knee squatting with LTI = 6° (r² = 0.81, p = 0.006). The strength of the correlation decreased as LTI increased. Caton–Deschamps was only significantly correlated with patellar tracking for LTI = 24° during knee squatting.ConclusionsA shallow trochlear groove increases lateral patellar maltracking. A lateral tibial tuberosity in combination with trochlear dysplasia increases lateral patellar tracking and the risk of patellar instability. Patella alta has relatively little influence on patellar tracking in combination with trochlear dysplasia due to the limited articular constraint provided by the trochlear groove.     

Integration of vascular biology and magnetic resonance imaging in the understanding of atherothrombosis and acute coronary syndromes

Summary.  The interaction between the vulnerable atherosclerotic plaque prone to disruption and thrombus formation is the cornerstone of acute coronary syndrome (ACS). Although distinct from one another, the atherosclerotic and thrombotic processes appear to be interdependent, hence the term atherothrombosis. Inflammation is a crucial common pathophysiological mechanism. Overall, the association of plaque vulnerability and ACS has been well documented. Given the multifactorial origin of atherothrombosis the best preventive approach should be aggressive management of all the risk factors. New interventions should be directed toward decreasing vulnerability of the lesions thereby decreasing the risk of ACS.     

The use of databases,data mining and immunoinformatics in vaccinology: where are we?

Introduction: Vaccinology has evolved from a sub-discipline focussed on simplistic vaccine development based on antibody-mediated protection to a separate discipline involving epidemiology, host and pathogen biology, immunology, genomics, proteomics, structure biology, protein engineering, chemical biology, and delivery systems. Data mining in combination with bioinformatics has provided a scaffold linking all these disciplines to the design of vaccines and vaccine adjuvants.

Areas covered: This review provides background knowledge on immunological aspects which have been exploited with informatics for the in silico analysis of immune responses and the design of vaccine antigens. Furthermore, the article presents various databases and bioinformatics tools, and discusses B and T cell epitope predictions, antigen design, adjuvant research and systems immunology, highlighting some important examples, and challenges for the future.

Expert opinion: Informatics and data mining have not only reduced the time required for experimental immunology, but also contributed to the identification and design of novel vaccine candidates and the determination of biomarkers and pathways of vaccine response. However, more experimental data is required for benchmarking immunoinformatic tools. Nevertheless, developments in immunoinformatics and reverse vaccinology, which are nascent fields, are likely to hasten vaccine discovery, although the path to regulatory approval is likely to remain a necessary impediment.     

Analogue synthesis reveals decoupling of antibiofilm and β‐lactam potentiation activities of a lead 2‐aminoimidazole adjuvant against Mycobacterium smegmatis

Biofilm formation is one of the many mechanisms bacteria utilize to survive antibiotic treatment. It has been demonstrated that when Mycobacterium tuberculosis exists in a biofilm in vitro, it expresses phenotypic resistance to antimicrobial drugs. As the in vivo survival of M. tuberculosis following drug treatment is potentially linked to a biofilm‐like expression of drug tolerance, it is hypothesized that biofilm dispersion should increase antibiotic susceptibility and reduce the duration of the current antibiotic treatment regimen. Previously, we have identified a 2‐aminoimidazole (2‐AI) compound capable of dispersing and inhibiting M. tuberculosis and M. smegmatis biofilms in vitro. Additionally, this compound potentiated the activity of carbenicillin against M. tuberculosis and, to a lesser degree, M. smegmatis. Here, we describe a SAR study on this compound evaluating each derivative for biofilm dispersion and β‐lactam potentiation capabilities against M. smegmatis. This study identified a compound that improved upon the biofilm dispersion capabilities of the lead compound. Interestingly, a different compound was identified with an increased ability to potentiate a subset of β‐lactam antibiotics. These compounds indicate that biofilm dispersion and potentiation capabilities may not be associated.     

Advances in computational modeling approaches of pituitary gonadotropin signaling

Introduction: Pituitary gonadotropins play an essential and pivotal role in the control of human and animal reproduction within the hypothalamic–pituitary–gonadal (HPG) axis. The computational modeling of pituitary gonadotropin signaling encompasses phenomena of different natures such as the dynamic encoding of gonadotropin secretion, and the intracellular cascades triggered by gonadotropin binding to their cognate receptors, resulting in a variety of biological outcomes.

Areas covered: The authors provide an overview of the historical and ongoing issues in modeling and data analysis related to gonadotropin secretion in the field of both physiology and neuroendocrinology. They mention the different mathematical formalisms involved, their interest and limits. They also discuss open statistical questions in signal analysis associated with key endocrine issues and review recent advances in the modeling of the intracellular pathways activated by gonadotropins, which yields promising development for innovative approaches in drug discovery.

Expert opinion: The greatest challenge to be tackled in computational modeling of pituitary gonadotropin signaling is the embedding of gonadotropin signaling within its natural multi-scale environment, from the single cell level, to the organic and whole HPG level. The development of modeling approaches of G protein-coupled receptor signaling, together with multicellular systems biology may lead to unexampled mechanistic understanding with critical expected fallouts in the therapeutic management of reproduction.     

基因工程课程内容的更新与教学方法的反思

基因工程课程是生物工程、生物技术和生物制药等专业的必修课,包括基因操作原理与基因工程实践两部分内容。它为分子生物学研究提供技术支持,为工程应用提供理论指导。随着DNA合成与测序技术的发展以及新型DNA组装与编辑技术的兴起,基因工程的概念持续升级,基因工程的课程内容和教学方法都需要进行相应的更新与改革。本文就此内容展开论述。     

Association of CD14, IL1B, IL6, IL10 and TNFA functional gene polymorphisms with symptomatic dental abscesses

AIM: To investigate in individuals with symptomatic dental abscesses the occurrence of functional polymorphisms within five genes involved with the immune response. The functional gene polymorphisms analysed were CD14 (-260 C/T), IL1B (+3954 C/T), IL6 (-174 G/C,), IL10 (-1082 G/A) and TNFA (-308 G/A). METHODOLOGY: Genomic DNA obtained from oral swabs from individuals with symptomatic dental abscesses and asymptomatic inflammatory periapical lesions, without previous exacerbation, was submitted to restriction fragment length polymorphism (RFLP) analyses to determine each individual genotype. The chi-square and principal components analysis tests were used for statistical analysis. RESULTS: A significant association was observed between the occurrence of the GG genotype or the G allele expression of the polymorphic locus-174 (G/C) of the IL6 gene, and the presence of the symptomatic dental abscesses in women and in individuals < or =35 years old. The principal components analysis suggested predominance of the symptomatic dental abscesses in individuals displaying: high-producer IL6 genotype; intermediate and high-producer IL1B genotypes and low-producer TNFA genotype. CONCLUSIONS: The present study suggests that genetic factors are associated with susceptibility to develop symptomatic dental abscesses.     

Oral Cancer: Risk Factors and Molecular Pathogenesis

Introduction  

Oral cancer is one of the most common cancers and it constitutes a major health problem particularly in developing countries. It is one of the leading causes of death. Tobacco and alcohol consumption appears to be the major determinants of oral cancer.