Microbial and non-microbial volatile fingerprints : potential clinical applications of electronic nose for early diagnoses and detection of diseases

This is the first study to explore the potential applications of using qualitative volatile fingerprints (electronic nose) for early detection and diagnosis of diseases such as dermatophytosis, ventilator associated pneumonia and upper gastrointestinal cancer. The investigations included in vitro analysis of various dermatophyte species and strains, antifungal screening, bacterial cultures and associated clinical specimens and oesophageal cell lines. Mass spectrometric analyses were attempted to identify possible markers. The studies that involved e-nose comparisons indicated that the conducting polymer system was unable to differentiate between any of the treatments over the experimental period (120 hours). Metal oxide-based sensor arrays were better suited and differentiated between four dermatophyte species within 96 hours of growth using principal component analysis and cluster analysis (Euclidean distance and Ward’s linkage) based on their volatile profile patterns. Studies on the sensitivity of detection showed that for Trichophyton mentagrophytes and T. rubrum it was possible to differentiate between log3, log5 and log7 inoculum levels within 96 hours. The probabilistic neural network model had a high prediction accuracy of 88 to 96% depending on the number of sensors used. Temporal volatile production patterns studied at a species level for a Microsporum species, two Trichophyton species and at a strain level for the two Trichophyton species; showed possible discrimination between the species from controls after 120 hours. The predictive neural network model misclassified only one sample. Data analysis also indicated probable differentiation between the strains of T. rubrum while strains of T. mentagrophytes clustered together showing good similarity between them. Antifungal treatments with itraconazole on T. mentagrophytes and T. rubrum showed that the e-nose could differentiate between untreated fungal species from the treated fungal species at both temperatures (25 and 30°C). However, the different antifungal concentrations of 50% fungal inhibition and 2 ppm could not be separated from each other or the controls based on their volatiles. Headspace analysis of bacterial cultures in vitro indicated that the e-nose could differentiate between the microbial species and controls in 83% of samples (n=98) based on a four group model (gram-positive, gram-negative, fungi and no growth). Volatile fingerprint analysis of the bronchoalveolar lavage fluid accurately separated growth and no growth in 81% of samples (n=52); however only 63% classification accuracy was achieved with a four group model. 12/31 samples were classified as infected by the e-nose but had no microbiological growth, further analysis suggested that the traditional clinical pulmonary infection score (CPIS) system correlated with the e-nose prediction of infection in 68% of samples (n=31). No clear distinction was observed between various human cell lines (oesophageal and colorectal) based on volatile fingerprints within one to four hours of incubation, although they were clearly separate from the blank media. However, after 24 hours one of the cell lines could be clearly differentiated from the others and the controls. The different gastrointestinal pathologies (forming the clinical samples) did not show any specific pattern and thus could not be distinguished. Mass spectrometric analysis did not detect distinct markers within the fungal and cell line samples, but potential identifiers in the fungal species such as 3-Octanone, 1-Octen-3-ol and methoxybenzene including high concentration of ammonia, the latter mostly in T. mentagrophytes, followed by T. rubrum and Microsporum canis, were found. These detailed studies suggest that the approach of qualitative volatile fingerprinting shows promise for use in clinical settings, enabling rapid detection/diagnoses of diseases thus eventually reducing the time to treatment significantly.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Biosensor technology for the screening of cancer risk biomarkers related to diet

Colorectal cancer is one of the most common cancers found in the developing countries. Recently, it has been indicated that a diet with a high intake of red and processed meat increases the risk of colorectal cancer. This is mainly because high red meat consumption is known to enhance the endogenous formation of N-nitroso compounds, which are potent carcinogens. Studies have detected the presence of O6-carboxymethyldeoxyguanosine (O6CMdG), a DNA adduct due to the nitrosation of glycine, in human exfoliated colonocytes and human blood. O6CMdG in DNA, is resistant to repair proteins and may be a potential urinary biomarker of colorectal cancer risk. The aim of our present research is to develop analytical methodologies for the measurement of this adduct in urine and correlate it to dietary studies. Samples are from previous studies of human volunteers carried out at MRC Dunn Human Nutrition Unit at Cambridge in which high read meat diets were consumed over a period of 15 days and various samples collected including 24 h urine samples. The ideal method for the routine screening in the general population of cancer risk biomarkers should be simple, fast, easy to perform and cost-effective. Biosensor technology fulfil this need, in particular thick film technology using screen-printing procedure allows inexpensive mass-production of disposable electrochemical sensors for point-of-care analyses. An immunosensor based on an indirect competitive assay is being developed and validated for the detection of O6CMdG in synthetic urine. The detection of this DNA adduct is based on competition for binding to a polyclonal antibody with an ovalbumin conjugate, followed by incubation with a secondary antibody labelled with horseradish peroxidise

Heritable genetic variants in key cancer genes link cancer risk with anthropometric traits

Background Height and other anthropometric measures are consistently found to associate with differential cancer risk. However, both genetic and mechanistic insights into these epidemiological associations are notably lacking. Conversely, inherited genetic variants in tumour suppressors and oncogenes increase cancer risk, but little is known about their influence on anthropometric traits. Methods By integrating inherited and somatic cancer genetic data from the Genome-Wide Association Study Catalog, expression Quantitative Trait Loci databases and the Cancer Gene Census, we identify SNPs that associate with different cancer types and differential gene expression in at least one tissue type, and explore the potential pleiotropic associations of these SNPs with anthropometric traits through SNP-wise association in a cohort of 500,000 individuals. Results We identify three regulatory SNPs for three important cancer genes, FANCA, MAP3K1 and TP53 that associate with both anthropometric traits and cancer risk. Of particular interest, we identify a previously unrecognised strong association between the rs78378222[C] SNP in the 3' untranslated region (3'-UTR) of TP53 and both increased risk for developing non-melanomatous skin cancer (OR=1.36 (95% 1.31 to 1.41), adjusted p=7.62E−63), brain malignancy (OR=3.12 (2.22 to 4.37), adjusted p=1.43E−12) and increased standing height (adjusted p=2.18E−24, beta=0.073±0.007), lean body mass (adjusted p=8.34E−37, beta=0.073±0.005) and basal metabolic rate (adjusted p=1.13E−31, beta=0.076±0.006), thus offering a novel genetic link between these anthropometric traits and cancer risk. Conclusion Our results clearly demonstrate that heritable variants in key cancer genes can associate with both differential cancer risk and anthropometric traits in the general population, thereby lending support for a genetic basis for linking these human phenotypes

Cytokines and inflammatory mediators: 25. Certolizumab Pegol has a Different Profile from the other Anti-TNFS, Including Golimumab, in a Variety of in Vitro Assays

Background: Activities of the anti-TNFs, certolizumab pegol (CZP), etanercept (ETA), infliximab (IFX) and adalimumab (ADA), have been compared in a range of in vitro assays. CZP is the only licensed PEGylated Fab' anti-TNF; ETA is a fusion protein with an IgG1 Fc, and IFX and ADA are both antibodies with an IgG1 Fc. Golimumab (GLM) is a monoclonal IgG1 TNF inhibitor recently approved for a number of indications; it is thus of interest to assess the in vitro activity of GLM. In vitro assays previously used were neutralisation of TNF in the L929 bioassay, inhibition of LPS-driven cytokine production by monocytes, induction of apoptosis in activated lymphocytes and monocytes, and induction of neutrophil necrosis. Methods: Neutralisation of human TNF was assessed in the L929 bioassay using a range of concentrations of the anti-TNFs and a fixed concentration of TNF (100 pg/mL). Activity of the anti-TNFs at inhibiting LPS-driven IL-1β secretion by monocytes was assessed by incubating peripheral blood monocytes with various concentrations of the anti-TNF for 1 hour (hr) and then washing the cells. LPS was added for 4 hrs, the supernatants collected and the IL-1β level measured by ELISA. To assess induction of apoptosis, peripheral blood lymphocytes were activated for 2 days with 2 μg/mL CD3/CD28 and monocytes with 300 U/mL IL-4 and GMCSF for 3 days. The effect of the anti-TNFs on apoptosis was assessed by Annexin V staining using flow cytometry 24 hrs later. The effect of the anti-TNFs on neutrophil necrosis was determined by measuring myeloperoxidase release after 12 hrs. An isotype-matched control was used in all assays except the L929 bioassay. Results: IC90 neutralisation activity of the anti-TNFs in the L929 bioassay was 0.3 ng/mL for ETA, 4 ng/mL for GLM, 15 ng/mL for ADA, and 20 ng/mL for IFX, compared with 2.5 ng/mL for CZP. CZP was the most potent inhibitor of LPS-driven IL-1β secretion (IC50 ∼0.1 ng/mL), followed by GLM (20 ng/mL) and IFX (50 ng/mL). GLM, ADA, IFX and ETA induced apoptosis of monocytes and lymphocytes to a similar degree reaching a level of 23% and ∼40% at 100 μg/mL, respectively. CZP caused no increase in apoptosis above the levels seen with the isotype-matched control. In the neutrophil necrosis assay, ADA,IFX and GLM caused ∼70% necrosis at 100 μg/mL, and ETA 48%. CZP did not increase the level of necrosis above the level of the control. Conclusions: Bioactivity of the IgG1 molecules GLM, IFX and ADA in neutralising human TNF was inferior to that of CZP and ETA. CZP, the only PEGylated anti-TNF, had a different profile to the other anti-TNFs as it was the most potent at inhibiting LPS-driven IL-1β production by monocytes, did not induce apoptosis of activated monocytes and lymphocytes, and did not cause neutrophil necrosis. The clinical relevance of these in vitro effects is unknown. Nevertheless, these assays show interesting in vitro differences between the anti-TNFs. Disclosure statement: G.F. and A.N. are employees of UC

Foxp2 Regulates Gene Networks Implicated in Neurite Outgrowth in the Developing Brain

Forkhead-box protein P2 is a transcription factor that has been associated with intriguing aspects of cognitive function in humans, non-human mammals, and song-learning birds. Heterozygous mutations of the human FOXP2 gene cause a monogenic speech and language disorder. Reduced functional dosage of the mouse version (Foxp2) causes deficient cortico-striatal synaptic plasticity and impairs motor-skill learning. Moreover, the songbird orthologue appears critically important for vocal learning. Across diverse vertebrate species, this well-conserved transcription factor is highly expressed in the developing and adult central nervous system. Very little is known about the mechanisms regulated by Foxp2 during brain development. We used an integrated functional genomics strategy to robustly define Foxp2-dependent pathways, both direct and indirect targets, in the embryonic brain. Specifically, we performed genome-wide in vivo ChIP–chip screens for Foxp2-binding and thereby identified a set of 264 high-confidence neural targets under strict, empirically derived significance thresholds. The findings, coupled to expression profiling and in situ hybridization of brain tissue from wild-type and mutant mouse embryos, strongly highlighted gene networks linked to neurite development. We followed up our genomics data with functional experiments, showing that Foxp2 impacts on neurite outgrowth in primary neurons and in neuronal cell models. Our data indicate that Foxp2 modulates neuronal network formation, by directly and indirectly regulating mRNAs involved in the development and plasticity of neuronal connections

Fumarate is cardioprotective via activation of the Nrf2 antioxidant pathway

The citric acid cycle (CAC) metabolite fumarate has been proposed to be cardioprotective; however, its mechanisms of action remain to be determined. To augment cardiac fumarate levels and to assess fumarate's cardioprotective properties, we generated fumarate hydratase (Fh1) cardiac knockout (KO) mice. These fumarate-replete hearts were robustly protected from ischemia-reperfusion injury (I/R). To compensate for the loss of Fh1 activity, KO hearts maintain ATP levels in part by channeling amino acids into the CAC. In addition, by stabilizing the transcriptional regulator Nrf2, Fh1 KO hearts upregulate protective antioxidant response element genes. Supporting the importance of the latter mechanism, clinically relevant doses of dimethylfumarate upregulated Nrf2 and its target genes, hence protecting control hearts, but failed to similarly protect Nrf2-KO hearts in an in vivo model of myocardial infarction. We propose that clinically established fumarate derivatives activate the Nrf2 pathway and are readily testable cytoprotective agents. © 2012 Elsevier Inc

Fungal volatile fingerprints: discrimination between dermatophyte species and strains by means of an electronic nose.

The potential of an electronic nose (e-nose) consisting of a hybrid gas sensor array system has been examined for species discrimination and strain identification of dermatophytes which are causative pathogens for human and animal infection. Temporal volatile production patterns have been studied at a species level for a Microsporum species, two Trichophyton species and at a strain level for the two Trichophyton species. After about 120 h principal component analysis (PCA) and cluster analysis showed possible discrimination between the species from controls. Data analysis also indicated probable differentiation between the strains of T. rubrum. The same could not however be achieved for the strains of T. mentagrophytes during preliminary experiments for the same time period, signifying a good similarity between the strains of this particular species based on their volatile fingerprints. This study suggests that volatile production patterns shows promise for species and strain identification of these dermatophytic fungi thereby facilitating early diagnosis and early management of patients

Microbial and non-microbial volatile fingerprints: Potential clinical applications of electronic nose for early diagnoses and detection of diseases

This is the first study to explore the potential applications of using qualitative volatile fingerprints (electronic nose) for early detection and diagnosis of diseases such as dermatophytosis, ventilator associated pneumonia and upper gastrointestinal cancer. The investigations included in vitro analysis of various dermatophyte species and strains, antifungal screening, bacterial cultures and associated clinical specimens and oesophageal cell lines. Mass spectrometric analyses were attempted to identify possible markers. The studies that involved e-nose comparisons indicated that the conducting polymer system was unable to differentiate between any of the treatments over the experimental period (120 hours). Metal oxide-based sensor arrays were better suited and differentiated between four dermatophyte species within 96 hours of growth using principal component analysis and cluster analysis (Euclidean distance and Ward’s linkage) based on their volatile profile patterns. Studies on the sensitivity of detection showed that for Trichophyton mentagrophytes and T. rubrum it was possible to differentiate between log3, log5 and log7 inoculum levels within 96 hours. The probabilistic neural network model had a high prediction accuracy of 88 to 96% depending on the number of sensors used. Temporal volatile production patterns studied at a species level for a Microsporum species, two Trichophyton species and at a strain level for the two Trichophyton species; showed possible discrimination between the species from controls after 120 hours. The predictive neural network model misclassified only one sample. Data analysis also indicated probable differentiation between the strains of T. rubrum while strains of T. mentagrophytes clustered together showing good similarity between them. Antifungal treatments with itraconazole on T. mentagrophytes and T. rubrum showed that the e-nose could differentiate between untreated fungal species from the treated fungal species at both temperatures (25 and 30°C). However, the different antifungal concentrations of 50% fungal inhibition and 2 ppm could not be separated from each other or the controls based on their volatiles. Headspace analysis of bacterial cultures in vitro indicated that the e-nose could differentiate between the microbial species and controls in 83% of samples (n=98) based on a four group model (gram-positive, gram-negative, fungi and no growth). Volatile fingerprint analysis of the bronchoalveolar lavage fluid accurately separated growth and no growth in 81% of samples (n=52); however only 63% classification accuracy was achieved with a four group model. 12/31 samples were classified as infected by the e-nose but had no microbiological growth, further analysis suggested that the traditional clinical pulmonary infection score (CPIS) system correlated with the e-nose prediction of infection in 68% of samples (n=31). No clear distinction was observed between various human cell lines (oesophageal and colorectal) based on volatile fingerprints within one to four hours of incubation, although they were clearly separate from the blank media. However, after 24 hours one of the cell lines could be clearly differentiated from the others and the controls. The different gastrointestinal pathologies (forming the clinical samples) did not show any specific pattern and thus could not be distinguished. Mass spectrometric analysis did not detect distinct markers within the fungal and cell line samples, but potential identifiers in the fungal species such as 3-Octanone, 1-Octen-3-ol and methoxybenzene including high concentration of ammonia, the latter mostly in T. mentagrophytes, followed by T. rubrum and Microsporum canis, were found. These detailed studies suggest that the approach of qualitative volatile fingerprinting shows promise for use in clinical settings, enabling rapid detection/diagnoses of diseases thus eventually reducing the time to treatment significantly

Use of volatile fingerprints for rapid screening of antifungal agents for efficacy against dermatophyte Trichophyton species

The potential of using an electronic nose (E-nose) as a rapid technique for screening the responses of dermatophytes to antifungal agents was studied. In vitro, the 50% and 90% effective concentration (EC) values of five antifungal agents including fungicides and antioxidant mixtures against Trichophyton rubrum and Trichophyton mentagrophytes were obtained by mycelial growth assays. The qualitative volatile production patterns of the growth responses of these fungi to the EC values incorporated into solid media were analysed after 96-120h incubation at 25°C using headspace analyses using five replicates per treatment. Overall, results, using principal components analysis and cluster analysis, demonstrated that it was possible to differentiate between various treatments within 96-120h of growth. The EC50 values were discriminated from the controls while the EC90 concentration treatments were often grouped with the agar blanks because of very slow growth. This study showed that potential exists for using qualitative volatile patterns as a rapid screening method for antifungal agents against micro-organisms. This approach could significantly improve and facilitate the monitoring of antimicrobial drug activities and infection control programmes and perhaps also for monitoring of drug resistance buildup in microbial population