Substrate entering and product leaving trajectories predict an engulfing dynamic for the major conformational change of the β-lactam acylase

It is still a major challenge to acquire insight into the conformational changes between the ground state and the transition state of an enzyme, although conformational fluctuation within interconverting conformers has been widely investigated (1-4). Here, we utilize different enzymatic reactions in b-lactam acylase to figure out the substrate/product trajectories in the enzyme, thereby probing the overall conformational changes in transition state. First, an auto-proteolytic intermediate of cephalosporin acylase (EC 3.5.1.11) with partial spacer segment was identified. As a final proteolytic step, the deletion of this spacer segment was revealed to be a first-order reaction, suggesting an intramolecular Ntn mechanism for the auto-proteolysis. Accordingly, the different proteolytic sites in the acylase precursor indicate a substrate entering pathway along the spacer peptide. Second, bromoacyl-7ACA can interact with penicillin G acylase (EC 3.5.1.11) in two distinguish aspects, to be hydrolyzed as a substrate analogue and to affinity alkylate the conserved Trpb4 as a product analogue. The kinetic correlation between these two reactions suggests a channel opening from Serb1 to Trpb4, responsible for the main product leaving. These two reaction trajectories relaying at the active centre, together with the crystal structures (5-10), predict an engulfing dynamic involving pocket constriction and channel opening

Evaluation of Toxoplasma gondii as a live vaccine vector in susceptible and resistant hosts

<p>Abstract</p> <p>Background</p> <p><it>Toxoplasma gondii </it>has been shown to trigger strong cellular immune responses to heterologous antigens expressed by the parasite in the inbred mouse model <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. We studied the immune response induced by <it>T. gondii </it>as an effective vaccine vector in chickens and rabbits.</p> <p>Results</p> <p><it>T. gondii </it>RH strain was engineered to express the yellow fluorescent protein (YFP) in the cytoplasm. A subcutaneous injection of the transgenic <it>T. gondii </it>YFP in chickens afforded partial protection against the infection of transgenic <it>E. tenella </it>YFP. <it>T. gondii </it>YFP induced low levels of antibodies to YFP in chickens, suggesting that YFP specific cellular immune response was probably responsible for the protective immunity against <it>E. tenella </it>YFP infection. The measurement of T-cell response and IFN-γ production further confirmed that YFP specific Th1 mediated immune response was induced by <it>T. gondii </it>YFP in immunized chickens. The transgenic <it>T. gondii </it>stimulated significantly higher YFP specific IgG titers in rabbits than in chickens, suggesting greater immunogenicity in a <it>T. gondii </it>susceptible species than in a resistant species. Priming with <it>T. gondii </it>YFP and boosting with the recombinant YFP can induce a strong anti-YFP antibody response in both animal species.</p> <p>Conclusions</p> <p>Our findings suggest that <it>T. gondii </it>can be used as an effective vaccine vector and future research should focus on exploring avirulent no cyst-forming strains of <it>T. gondii </it>as a live vaccine vector in animals.</p

DSHGT: Dual-Supervisors Heterogeneous Graph Transformer -- A pioneer study of using heterogeneous graph learning for detecting software vulnerabilities

Vulnerability detection is a critical problem in software security and attracts growing attention both from academia and industry. Traditionally, software security is safeguarded by designated rule-based detectors that heavily rely on empirical expertise, requiring tremendous effort from software experts to generate rule repositories for large code corpus. Recent advances in deep learning, especially Graph Neural Networks (GNN), have uncovered the feasibility of automatic detection of a wide range of software vulnerabilities. However, prior learning-based works only break programs down into a sequence of word tokens for extracting contextual features of codes, or apply GNN largely on homogeneous graph representation (e.g., AST) without discerning complex types of underlying program entities (e.g., methods, variables). In this work, we are one of the first to explore heterogeneous graph representation in the form of Code Property Graph and adapt a well-known heterogeneous graph network with a dual-supervisor structure for the corresponding graph learning task. Using the prototype built, we have conducted extensive experiments on both synthetic datasets and real-world projects. Compared with the state-of-the-art baselines, the results demonstrate promising effectiveness in this research direction in terms of vulnerability detection performance (average F1 improvements over 10\% in real-world projects) and transferability from C/C++ to other programming languages (average F1 improvements over 11%)

Genetic polymorphisms of TLR3 are associated with Nasopharyngeal carcinoma risk in Cantonese population

<p>Abstract</p> <p>Background</p> <p>Nasopharyngeal carcinoma is endemic in Southern China, displays a strong relationship with genetic susceptibility and associates with Epstein-Barr virus infection. Toll-like receptor 3 (TLR3) plays an important role in the antivirus response. Therefore, we examined the association between <it>TLR3 </it>gene polymorphisms and NPC susceptibility.</p> <p>Methods</p> <p>We performed a case-control study of 434 NPC cases and 512 healthy controls matched on age, sex and residence. Both cases and controls are of Cantonese origin from Southern China. Genetic variants in <it>TLR3 </it>were determined by polymerase chain reaction (PCR)-based DNA direct sequencing and four SNPs were genotyped in all samples.</p> <p>Results</p> <p>Our results showed that allele C for SNP 829A/C increased NPC risk significantly ((p = 0.0068, OR = 1.49, 95%CI:1.10–2.00). When adjusted for age, gender and VCA-IgA antibody titers, the NPC risk was reduced significantly among individuals who carried the haplotype "ATCT" compared to those who carried the most common haplotype "ACCT" (p = 0.0054, OR = 0.028; 95% CI (0.002–0.341).</p> <p>Conclusion</p> <p>The <it>TLR3 </it>polymorphisms may be relevant to NPC susceptibility in the Cantonese population, although the reduction in NPC risk is modest and the biological mechanism of the observed association merits further investigation.</p

Human Microbe-Disease Association Prediction Based on Adaptive Boosting

There are countless microbes in the human body, and they play various roles in the physiological process. There is growing evidence that microbes are closely associated with human diseases. Researching disease-related microbes helps us understand the mechanisms of diseases and provides new strategies for diseases diagnosis and treatment. Many computational models have been proposed to predict disease-related microbes, in this paper, we developed a model of Adaptive Boosting for Human Microbe-Disease Association prediction (ABHMDA) to reveal the associations between diseases and microbes by calculating the relation probability of disease-microbe pair using a strong classifier. Our model could be applied to new diseases without any known related microbes. In order to assess the prediction power of the model, global and local leave-one-out cross validation (LOOCV) were implemented. As shown in the results, the global and local LOOCV values reached 0.8869 and 0.7910, respectively. What’s more, 10, 10, and 8 out of the top 10 microbes predicted to be most likely to be associated with Asthma, Colorectal carcinoma and Type 1 diabetes were all verified by relevant literatures or database HMDAD, respectively. The above results verify the superior predictive performance of ABHMDA

Prevalence and clinical characteristics of lower limb atherosclerotic lesions in newly diagnosed patients with ketosis-onset diabetes: a cross-sectional study

BACKGROUND: The clinical features of atherosclerotic lesions in ketosis-onset diabetes are largely absent. We aimed to compare the characteristics of lower limb atherosclerotic lesions among type 1, ketosis-onset and non-ketotic type 2 diabetes. METHODS: A cross-sectional study was performed in newly diagnosed Chinese patients with diabetes, including 53 type 1 diabetics with positive islet-associated autoantibodies, 208 ketosis-onset diabetics without islet-associated autoantibodies, and 215 non-ketotic type 2 diabetics. Sixty-two subjects without diabetes were used as control. Femoral intima-media thickness (FIMT), lower limb atherosclerotic plaque and stenosis were evaluated and compared among the four groups based on ultrasonography. The risk factors associated with lower limb atherosclerotic plaque were evaluated via binary logistic regression in patients with diabetes. RESULTS: After adjusting for age and sex, the prevalence of lower limb plaque in the patients with ketosis-onset diabetes (47.6%) was significantly higher than in the control subjects (25.8%, p = 0.013), and showed a higher trend compared with the patients with type 1 diabetes (39.6%, p = 0.072), but no difference was observed in comparison to the patients with non-ketotic type 2 diabetes (62.3%, p = 0.859). The mean FIMT in the ketosis-onset diabetics (0.73 ± 0.17 mm) was markedly greater than that in the control subjects (0.69 ± 0.13 mm, p = 0.045) after controlling for age and sex, but no significant differences were found between the ketosis-onset diabetics and the type 1 diabetics (0.71 ± 0.16 mm, p = 0.373), and the non-ketotic type 2 diabetics (0.80 ± 0.22 mm, p = 0.280), respectively. Age and FIMT were independent risk factors for the presence of lower limb plaque in both the ketosis-onset and non-ketotic type 2 diabetic patients, while sex and age in the type 1 diabetic patients. CONCLUSIONS: The prevalence and risk of lower limb atherosclerotic plaque in the ketosis-onset diabetes were remarkably higher than in the control subjects without diabetes. The features and risk factors of lower limb atherosclerotic lesions in the ketosis-onset diabetes resembled those in the non-ketotic type 2 diabetes, but different from those in the type 1 diabetes. Our findings provide further evidences to support the classification of ketosis-onset diabetes as a subtype of type 2 diabetes rather than idiopathic type 1 diabetes