Developing a genetic manipulation system for the Antarctic archaeon, Halorubrum lacusprofundi: Investigating acetamidase gene function

© 2016 The Author(s). No systems have been reported for genetic manipulation of cold-adapted Archaea. Halorubrum lacusprofundi is an important member of Deep Lake, Antarctica (∼10% of the population), and is amendable to laboratory cultivation. Here we report the development of a shuttle-vector and targeted gene-knockout system for this species. To investigate the function of acetamidase/formamidase genes, a class of genes not experimentally studied in Archaea, the acetamidase gene, amd3, was disrupted. The wild-type grew on acetamide as a sole source of carbon and nitrogen, but the mutant did not. Acetamidase/formamidase genes were found to form three distinct clades within a broad distribution of Archaea and Bacteria. Genes were present within lineages characterized by aerobic growth in low nutrient environments (e.g. haloarchaea, Starkeya) but absent from lineages containing anaerobes or facultative anaerobes (e.g. methanogens, Epsilonproteobacteria) or parasites of animals and plants (e.g. Chlamydiae). While acetamide is not a well characterized natural substrate, the build-up of plastic pollutants in the environment provides a potential source of introduced acetamide. In view of the extent and pattern of distribution of acetamidase/formamidase sequences within Archaea and Bacteria, we speculate that acetamide from plastics may promote the selection of amd/fmd genes in an increasing number of environmental microorganisms

Quick response code secure: a cryptographically secure anti-phishing tool for QR code attacks.

The two-dimensional quick response (QR) codes can be misleading due to the difficulty in differentiating a genuine QR code from a malicious one. Since, the vulnerability is practically part of their design, scanning a malicious QR code can direct the user to cloned malicious sites resulting in revealing sensitive information. In order, to evaluate the vulnerabilities and propose subsequent countermeasures, we demonstrate this type of attack through a simulated experiment, where a malicious QR code directs a user to a phishing site. For our experiment, we cloned Google's web page providing access to their email service (Gmail). Since, the URL is masqueraded into the QR code the unsuspecting user who opens the URL is directed to the malicious site. Our results proved that hackers could easily leverage QR codes into phishing attack vectors targeted at smartphone users, even bypassing web browsers safe browsing feature. In addition, the second part of our paper presents adequate countermeasures and introduces QRCS (Quick Response Code Secure). QRCS is a universal efficient and effective solution focusing exclusively on the authenticity of the originator and consequently, the integrity of QR code by using digital signatures

Conversational Agents for Health and Wellbeing

Conversational agents have increasingly been deployed in healthcare applications. However, significant challenges remain in developing this technology. Recent research in this area has highlighted that: i) patient safety was rarely evaluated; ii) health outcomes were poorly measured, and iii) no standardised evaluation methods were employed. The conversational agents in healthcare are lagging behind the developments in other domains. This one-day workshop aims to create a roadmap for healthcare conversational agents to develop standardised design and evaluation frameworks. This will prioritise health outcomes and patient safety while ensuring a high-quality user experience. In doing so, this workshop will bring together researchers and practitioners from HCI, healthcare and related speech and chatbot domains to collaborate on these key challenges

Clinical Validation of Integrated Nucleic Acid and Protein Detection on an Electrochemical Biosensor Array for Urinary Tract Infection Diagnosis

BACKGROUND: Urinary tract infection (UTI) is a common infection that poses a substantial healthcare burden, yet its definitive diagnosis can be challenging. There is a need for a rapid, sensitive and reliable analytical method that could allow early detection of UTI and reduce unnecessary antibiotics. Pathogen identification along with quantitative detection of lactoferrin, a measure of pyuria, may provide useful information towards the overall diagnosis of UTI. Here, we report an integrated biosensor platform capable of simultaneous pathogen identification and detection of urinary biomarker that could aid the effectiveness of the treatment and clinical management. METHODOLOGY/PRINCIPAL FINDINGS: The integrated pathogen 16S rRNA and host lactoferrin detection using the biosensor array was performed on 113 clinical urine samples collected from patients at risk for complicated UTI. For pathogen detection, the biosensor used sandwich hybridization of capture and detector oligonucleotides to the target analyte, bacterial 16S rRNA. For detection of the protein biomarker, the biosensor used an analogous electrochemical sandwich assay based on capture and detector antibodies. For this assay, a set of oligonucleotide probes optimized for hybridization at 37°C to facilitate integration with the immunoassay was developed. This probe set targeted common uropathogens including E. coli, P. mirabilis, P. aeruginosa and Enterococcus spp. as well as less common uropathogens including Serratia, Providencia, Morganella and Staphylococcus spp. The biosensor assay for pathogen detection had a specificity of 97% and a sensitivity of 89%. A significant correlation was found between LTF concentration measured by the biosensor and WBC and leukocyte esterase (p<0.001 for both). CONCLUSION/SIGNIFICANCE: We successfully demonstrate simultaneous detection of nucleic acid and host immune marker on a single biosensor array in clinical samples. This platform can be used for multiplexed detection of nucleic acid and protein as the next generation of urinary tract infection diagnostics

The Effect of Transposable Element Insertions on Gene Expression Evolution in Rodents

Background:Many genomes contain a substantial number of transposable elements (TEs), a few of which are known to be involved in regulating gene expression. However, recent observations suggest that TEs may have played a very important role in the evolution of gene expression because many conserved non-genic sequences, some of which are know to be involved in gene regulation, resemble TEs. Results:Here we investigate whether new TE insertions affect gene expression profiles by testing whether gene expression divergence between mouse and rat is correlated to the numbers of new transposable elements inserted near genes. We show that expression divergence is significantly correlated to the number of new LTR and SINE elements, but not to the numbers of LINEs. We also show that expression divergence is not significantly correlated to the numbers of ancestral TEs in most cases, which suggests that the correlations between expression divergence and the numbers of new TEs are causal in nature. We quantify the effect and estimate that TE insertion has accounted for ~20% (95% confidence interval: 12% to 26%) of all expression profile divergence in rodents. Conclusions:We conclude that TE insertions may have had a major impact on the evolution of gene expression levels in rodents

Parametric vibration analysis and validation for a novel portable hexapod machine tool attached to surfaces with unequal stiffness

China Scholarship Council; University of Nottingham; UK EPSRC (Robotics and Artificial Intelligence for Nuclear - EP/R026084/1)

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes