The use of analytical techniques for the rapid detection of microbial spoilage and adulteration in milk

Milk is an important nutritious component of our diet consumed by most humans on a daily basis. Microbiological spoilage affects its safe use and consumption, its organoleptic properties and is a major part of its quality control process. European Union legislation and the Hazard Analysis and the Critical Control Point (HACCP) system in the dairy industry are therefore in place to maintain both the safety and the quality of milk production in the dairy industry. A main limitation of currently used methods of milk spoilage detection in the dairy industry is the time-consuming and sometimes laborious turnover of results. Attenuated total reflectance (ATR) and high throughput (HT) Fourier transform infrared (FTIR) spectroscopy metabolic fingerprinting techniques were investigated for their speed and accuracy in the enumeration of viable bacteria in fresh pasteurized cows' milk. Data analysis was performed using principal component-discriminant function analysis (PC-DFA) and partial least squares (PLS) multivariate statistical techniques. Accurate viable microbial loads were rapidly obtained after minimal sample preparation, especially when FTIR was combined with PLS, making it a promising technique for routine use by the dairy industry. FTIR and Raman spectroscopies in combination with multivariate techniques were also explored as rapid detection and enumeration techniques of S. aureus, a common milk pathogen, and Lactococcus lactis subsp cremoris, a common lactic acid bacterium (LAB) and potential antagonist of S. aureus, in ultra-heat treatment milk. In addition, the potential growth interaction between the two organisms was investigated. FTIR spectroscopy in combination with PLS and kernel PLS (KPLS) appeared to have the greatest potential with good discrimination and enumeration attributes for the two bacterial species even when in co-culture without previous separation. Furthermore, it was shown that the metabolic effect of L. cremoris predominates when in co-culture with S. aureus in milk but with minimal converse growth interaction between the two microorganisms and therefore potential implications in the manufacture of dairy products using LAB. The widespread and high consumption of milk make it a target for potential financial gain through adulteration with cheaper products reducing quality, breaking labeling and patent laws and potentially leading to dire health consequences. The time consuming and laborious nature of currently used analytical techniques in milk authentication enabled the study of FTIR spectroscopy and matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-ToF-MS) as rapid analytical techniques in quantification of milk adulteration, using binary and tertiary fresh whole cows', goats' and sheep's milk mixture samples. Chemometric data analysis was performed using PLS and KPLS multivariate analyses. Overall, results indicated that both techniques have excellent enumeration and detection attributes for use in milk adulteration with good prospects for potential use in the dairy industry.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An environmental metabolomics investigation of the effects of chiral pharmaceuticals and environmental pollutants on microorganisms

Active pharmaceutical ingredients (APIs) and their metabolites are ubiquitous in the environment and their occurrence in the aquatic environment is of growing concern. However, despite the fact that these may cause harmful effects in organisms found within this niche, little is currently known about the effects of APIs in the aquatic environment. Chiral pharmaceuticals are of particular concern as the enantiomers may be metabolised differently, with the potential for the production of an array of harmful compounds. There are many racemic APIs for treating human and animal conditions, and even in these target organisms the pharmacodynamic effects of the enantiomers are not always known. Within recent years the importance of the interactions of these compounds within the aquatic environment has been realised and information regarding the fate and biodegradation of such environmental pollutants is of great importance. The advent of post-genomic technologies has proved advantageous in the study of the effects of these environmental pollutants. In this thesis, the effects of a range of chiral APIs, and other environmental pollutants, on environmentally relevant microorganisms were investigated at the metabolome level. The effects of chiral APIs were investigated in a number of prokaryotic and eukaryotic systems in order to provide a comprehensive study of the effects of the APIs in the aquatic environment. FT-IR spectroscopy was employed for metabolic fingerprinting of some environmentally relevant bacteria and GC-MS was subsequently employed for metabolite profiling of two pseudomonads that had shown differential chiral effects with Propranolol. In addition, FT-IR microspectroscopy was employed for the investigation of the phenotypic and localised effects of chiral APIs in a eukaryotic system. Furthermore, the effects of a range of environmental pollutants on a complex bacterial community were investigated with the use of FT-IR spectroscopy and multivariate analysis. Initial results indicated a large phenotypic response in relation to phenol, and this was further explored with a range of ageing experiments and metabolic fingerprinting. An FT-IR peak was found to be characteristic of the phenotypic changes in the actively degrading communities and this was likely to be a degradation product of phenol, and armed with this knowledge the activated sludge community was monitored during the active degradation of phenol with the use of GC-MS.The work presented in this thesis has shown for the first time that metabolomics allows subtle phenotypes in microorganisms to be revealed when they are exposed to chiral forms of APIs which are commonly found in the aquatic environment. Despite these APIs not being designed for any interaction with bacteria and aquatic life in general these are significant findings and may have implications as more and more APIs become detectable and concentrated in the environment due to continued use in man and indeed animals or aquaculture.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Toxicity of ionic liquids and organic solvents towards Escherichia coli and Pseudomonas putida

By turning to biological catalysts such as whole cell microorganisms it is possible to both improve the specificity of a (bio) chemical transformation with the added benefit of reducing the energy demands of a number of synthetic processes which currently use chemical catalysts. The replacement of chemical catalysts with whole cell biological catalysts is often limited by the toxicity of the substrate, side products or end products of a catalytic reaction. The exposure of microorganisms to these products or substrates is usually reflected in phenotypic alterations in membrane of the cell. The techniques of growth data, FT-IR spectroscopy and cluster analysis have been successfully used to establish the phenotypic changes occurring within a microbial culture.The use of microorganisms as replacements for chemical catalysts in synthetic processes may be further increased by the replacement of conventional organic solvents, with a different class of solvents known as ionic liquids.Ionic liquids have been widely reported as 'green' solvents due to their negligible vapour pressure; however reported toxicity testing has demonstrated that many ionic liquid structures have poor toxicity profiles when tested against a range of microorganisms. Due to the large number of ionic liquids which are currently available it is desirable to have a fast and reliable method for initial toxicity screening of many ionic liquids against a wide range of microorganisms. To this end, a simple and cost effective method for ionic liquid toxicity testing using agar diffusion plates and specific growth rates, has been developed and employed to test a wide range of ionic liquid structures against a number of test bacteria.Additionally, the phenotypic changes associated with the exposure of a number of test organisms to a set of both water miscible and water immiscible ionic liquids, have been successfully assessed by FT-IR spectroscopy, cluster analysis, growth data and viable count information, suggesting that this combination of techniques has great potential for future work involving the assessment of phenotypic alterations within microbial cultures.EThOS - Electronic Theses Online ServiceBBSRCGBUnited Kingdo

Investigation of HIV anti-viral drug effect on HPV16 E6 expressing cervical carcinoma cells using advanced metabolomics methods

Metabolomics approaches have recently been used to understand the complex molecular interactions of biological systems. One popular area in which these methods are being developed is to understand the biochemical changes during abiotic and biotic stresses; for example, how a cell may respond to a drug. Since metabolites are the end products of gene expression, these can be used to indicate the result of the activities and interaction of the cell or organism with its environment. The investigation of the level and compositional changes of metabolites against metabolic stresses such as chemotherapeutic treatment (drug exposure) are required to understand more fully abiotic perturbation to biological systems. The aim of this project was to understand the metabolic effect that the anti-viral drugs indinavir and lopinavir (currently used by HIV patients) have on HPV-related cervical cancer cell lines by measuring changes in metabolism using a wide range of analytical techniques; including Fourier transform infrared (FT-IR) and Raman spectroscopies, and gas and liquid chromatography-mass spectrometry (GC and LC-MS). The analyses and interpretation of the large volumes of complex multidimensional data generated by metabolomics approaches were performed with a combination of multivariate data analysis techniques such as principal components analysis (PCA) and canonical variates analysis (CVA), as well as univariate approaches such as N-Way analysis of variance (ANOVA). By combining biochemical imaging, metabolite fingerprinting and footprinting, and metabolite profiling, with multi- and uni-variate analyses, the actions and effects of the anti-viral drugs were investigated. FT-IR spectroscopy was initially used to generate global biochemical finger- and foot-prints, and Raman spectroscopy was employed to investigate intracellular distribution of metabolites, and other cellular species, as well as the localisation of drug molecules within cells. FT-IR spectroscopy ascertained that the intra- and extra-cellular metabolomes were being directly influenced in a fashion that correlated with increasing anti-viral dosing; these effects were phenotypic rather than measurements of the drug level. Raman imaging spectroscopy indicated that the indinavir but not lopinavir was being compartmentalised within the cell nucleus, but only in HPV early protein 6 (E6) expressing cells. This observation was further confirmed by fractionation of cell samples into nuclear and cytoplasmic fractions and assessing the indinavir concentrations via LC-MS. Finally, LC-MS and GC-MS metabolite profiling were employed to investigate changes in the intracellular metabolome in response to the anti-viral compounds across a range of physiologically relevant concentrations and in the presence and absence of the E6 oncoprotein. General effects of both anti-viral compounds included the regulation of metabolites such as glutathione, octenedionoic and octadecenoic acids, which may be involved in stress related responses, reduced levels of sugars and sugar-phosphates indicating a potential arrest of glycolysis, and reduced levels of malic acid indicating potential decreased flux into the TCA cycle; all indicating that central metabolism was being reduced. Finally, LC-MS based quantification indicated that in the presence of E6, lopinavir was actively removed from the cell, whereas the indinavir intracellular concentration increased concomitantly with the level of dosing. These investigations have revealed that metabolomics approaches are an apt tool for the study of anti-viral effects within cell cultures, but improvements need to be made with respect to the major limitation of metabolite identification.EThOS - Electronic Theses Online ServiceORSSchool award from School of ChemistryGBUnited Kingdo

Metabolic profiling of volatile organic compounds and enhanced vibrational spectroscopy

Metabolomics is a post genomic field of research concerned with the study of low molecular weight compounds within a biological system permitting the investigation of the metabolite differences between natural and perturbed systems (such as cells, organs and tissues). Rapid identification and discrimination of biological samples based upon metabolic differences and physiological status in microbiology, mammalian systems (particularly for disease diagnosis), plants and food science is highly desirable. Volatile organic compound (VOC) profiling is a novel area of research where the composition of the VOCs emitted by the biological samples can be correlated to its origin and physiological status. The aim of this project was to investigate the applicability of VOC profiling as a potential complementary tool within metabolomics.In this project the discrimination of bacteria using a novel gas phase separation method was investigated and the development of VOC-based profiling tools for the collections of VOCs emitted from biological samples was also studied. The optimisation and validation of a high throughput method for VOC analysis was achieved and this was used to assess wound healing.VOC metabolite profiling was further extended to the discrimination of S. typhimurium contaminated meat; the study was conducted in parallel with metabolite profiling analysis for the analysis of non-volatile small molecules. Finally, enhanced vibrational spectroscopic techniques were applied to the characterisation and screening of dye molecules in contaminated foodstuffs using Raman spectroscopy. This thesis clearly demonstrates that VOC metabolic profiling is a complementary tool within the metabolomics toolbox, one of its great attractions is that it permits the characterisation of biological samples in a rapid and non-invasive manner. The technique provides detailed chemical information regarding the VOC composition present above the headspace of the sample and can be used to understand its physiological status and biological origin. VOCs metabolite profiling will become a valuable tool for non-invasive analysis of many biological systems. Raman spectroscopy is a sensitive and non-destructive technique which can generate detailed chemical and structural information regarding the analyte under investigation with little or no sample preparation needed. The effect of the weak Raman signal can be significantly amplified by coupling the analyte molecule to surfaces of nanoparticles and demonstrated that it is ideal for analysing aqueous dye solutions in a quantitative manner.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Multivariate data analysis for embedded sensor networks within the perishable goods supply chain

This study was aimed at exploring data analysis techniques for generating accurate estimates of the loss in quality of fresh fruits, vegetables and cut flowers in chilled supply chains based on data from advanced sensors. It was motivated by the recent interest in the application of advanced sensors, by emerging concepts in quality controlled logistics, and by the desire to minimise quality losses during transport and storage of the produce. Cut roses were used in this work although the findings will also be applicable to other produce. The literature has reported that whilst temperature was considered to be the most critical post-harvest factor, others such as growing conditions could also be important in the senescence of cut roses. Kinetic modelling was the most commonly used modelling approach for shelf life predictions of foods and perishable produce, but not for estimating vase life (VL) of cut flowers, and so this was explored in this work along with multiple linear regression (MLR) and partial least squares (PLS). As the senescence of cut roses is not fully understood, kinetic modelling could not be implemented directly. Consequently, a novel technique, called Kinetic Linear System (KLS), was developed based on kinetic modelling principles. Simulation studies of shelf life predictions for tomatoes, mushrooms, seasoned soybean sprouts, cooked shrimps and other seafood products showed that the KLS models could effectively replace the kinetic ones. With respect to VL predictions KLS, PLS and MLR were investigated for data analysis from an in-house experiment with cut roses from Cookes Rose Farm (Jersey). The analysis concluded that when the initial and final VLs were available for model calibration, effective estimates of the post-harvest loss in VL of cut roses could be obtained using the post-harvest temperature. Otherwise, when the initial VLs were not available, such effective estimates could not be obtained. Moreover, pre-harvest conditions were shown to correlate with the VL loss but the correlation was too weak to produce or improve an effective estimate of the loss. The results showed that KLS performance was the best while PLS one could be acceptable; but MLR performance was not adequate. In another experiment, boxes of cut roses were transported from a Kenyan farm to a UK distribution centre. Using KLS and PLS techniques, the analysis showed that the growing temperature could be used to obtain effective estimates of the VLs at the farm, at the distribution centre and also the in-transit loss. Further, using post-harvest temperature would lead to a smaller error for the VL at the distribution centre and the VL loss. Nevertheless, the estimates of the VL loss may not be useful practically due to the excessive relative prediction error. Overall, although PLS had a slightly smaller prediction error, KLS worked effectively in many cases where PLS failed, it could handle constraints while PLS could not.In conclusion, KLS and PLS can be used to generate effective estimates of the post-harvest VL loss of cut roses based on post-harvest temperature stresses recorded by advanced sensors. However, the estimates may not be useful practically due to significant relative errors. Alternatively, pre-harvest temperature could be used although it may lead to slightly higher errors. Although PLS had slightly smaller errors KLS was more robust and flexible. Further work is recommended in the objective evaluations of product quality, alternative non-linear techniques and dynamic decision support system.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Metabolomics reveals the physiological response of Pseudomonas putida KT2440 (UWC1) after pharmaceutical exposure

Human pharmaceuticals have been detected in wastewater treatment plants, rivers, and estuaries throughout Europe and the United States. It is widely acknowledged that there is insufficient information available to determine whether prolonged exposure to low levels of these substances is having an impact on the microbial ecology in such environments. In this study we attempt to measure the effects of exposing cultures of Pseudomonas putida KT2440 (UWC1) to six pharmaceuticals by looking at differences in metabolite levels. Initially, we used Fourier transform infrared (FT-IR) spectroscopy coupled with multivariate analysis to discriminate between cell cultures exposed to different pharmaceuticals. This suggested that on exposure to propranolol there were significant changes in the lipid complement of P. putida. Metabolic profiling with gas chromatography-mass spectrometry (GC-MS), coupled with univariate statistical analyses, was used to identify endogenous metabolites contributing to discrimination between cells exposed to the six drugs. This approach suggested that the energy reserves of exposed cells were being expended and was particularly evident on exposure to propranolol. Adenosine triphosphate (ATP) concentrations were raised in P. putida exposed to propranolol. Increased energy requirements may be due to energy dependent efflux pumps being used to remove propranolol from the cell. © The Royal Society of Chemistry 2016

A systems approach to understanding Dupuytren's disease

Introduction: Dupuytren's disease (DD) is an ill-defined fibroproliferative disorder affecting the palms of the hands of certain patient groups. Whether changes in DD fibroblasts are due to genetic alterations alone or related to metabolic dysregulation has not yet been investigated. Hypotheses: 1. DD is a disease of several networks rather than of a single gene. 2. DD may be investigated more effectively by employing systems biology. 3. Strict definition of cell passage number is important for the revelation of any DD phenotype. 4. Some of the differences between DD and healthy tissues reside in a difference in their respiratory metabolism. 5. Any such differences are akin the Warburg effect noted for tumour cells in the literature. Methods: We induced hypoxia in healthy and disease cells to test whether the difference in disease cell types and healthy is the same as the difference in control fibroblasts cultured in normoxia and hypoxia. We investigated both at the metabolic level (intracellular and extracellular) and at the transcript level. This study also employed Fourier transform infrared spectroscopy to permit profiling of cells: (1) DD cords and nodules against the unaffected transverse palmar fascia (internal control), (2) those (1) with carpal ligamentous fascia (external controls) (3) those in (1) against DD fat surrounding the nodule, and skin overlying the nodule. We then compared metabolic profiles of the above to determine the effect of serial passaging by assessment of reproducibility. Subsequently, a novel protocol was employed in carefully controlled culture conditions for the parallel extraction of the metabolome and transcriptome of DD-derived fibroblasts and control at normoxic and hypoxic conditions to investigate this hypothesis. Gas chromatography-mass spectrometry combined with microarrays was employed to identify metabolites and transcript characteristic for DD tissue phenotypes. The extracellular metabolome was also studied for a selected subset. The metabolic and transcriptional changes were then integrated employing a network approach. Results: Carefully controlled culture conditions combined with multivariate statistical analyses demonstrated metabolic differences in DD and unaffected transverse palmar fascia, in addition to the external control. Differences between profiles of the four DD tissue phenotypes were also demonstrated. In addition early passage (0-3) metabolic differences were observed where a clear separation pattern in clusters was observed. Subsequent passages (4-6) displayed asynchrony, losing distinction between diseased and non-diseased sample phenotypes. A substantial number of dysregulated metabolites involved in amino acid metabolism, carbohydrate metabolism and also metabolism of cofactors and vitamins including downregulated cysteine and aspartic acid have been identified from the integrative analyses. Metabolic and transcriptional differences were revealed between fibroblast cell samples (passage number 3) cultured in 1% and 21% oxygen. The hypothesis that the difference in disease and healthy cells maybe akin to the differences in healthy cells in normoxia and hypoxia was rejected as only a very small number of significant molecules from these studies coincided in perturbed fascia and disease samples. No lactic acid was observed and little difference in the pyruvate concentrations. Yet, upon perturbation several of these transcripts and metabolites involved in the afore-mentioned pathways were significantly dysregulated. Conclusion: Early, but not late, passage numbers of primary cells provide representative metabolic and transcript fingerprinting for investigating DD. A unique parallel analysis of transcript and metabolic profiles of DD fibroblasts and control, enabled a robust characterization of DD and correlation of parameters across the various levels of systemic description. The tools that should facilitate our understanding of these complex systems are immature, but the pleiotropy of the difference between healthy and DD tissue suggest the aetiology of a network-based disease.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Assessing the impact of nitrogen supplementation in oats across multiple growth locations and years with targeted phenotyping and high-resolution metabolite profiling approaches

Oats (Avena sativa L.) are a healthy food, being high in dietary fibre (e.g. β-glucans), antioxidants, minerals, and vitamins. Understanding the effect of variety and crop management on nutritional quality is important. The response of four oat varieties to increased nitrogen levels was investigated across multiple locations and years with respect to yield, grain quality and metabolites (assessed via GC- and LC- MS). A novel high-resolution UHPLC-PDA-MS/MS method was developed, providing improved metabolite enrichment, resolution, and identification. The combined phenotyping approach revealed that, amino acid levels were increased by nitrogen supplementation, as were total protein and nitrogen containing lipid levels, whereas health-beneficial avenanthramides were decreased. Although nitrogen addition significantly increased grain yield and β-glucan content, supporting increasing the total nitrogen levels recommended within agricultural guidelines, oat varietal choice as well as negative impacts upon health beneficial secondary metabolites and the environmental burdens associated with nitrogen fertilisation, require further consideration

Optical photothermal infrared spectroscopy can differentiate equine osteoarthritic plasma extracellular vesicles from healthy controls

Background Equine osteoarthritis is a chronic degenerative disease of the articular joint, characterised by cartilage degradation resulting in pain and reduced mobility and thus is a prominent equine welfare concern. Diagnosis is usually at a late stage through radiographic examination, whilst treatment is symptomatic not curative. Extracellular vesicles are small nanoparticles that are involved in intercellular communication. The objective of this study was to investigate the feasibility of Raman and optical photothermal infrared spectroscopy to detect osteoarthritis using plasma-derived extracellular vesicles. Methods Plasma samples were derived from thoroughbred racehorses. A total of 14 samples were selected (control; n= 6 and diseased; n=8). Extracellular vesicles were isolated using differential ultracentrifugation and characterised using nanoparticle tracking analysis, transmission electron microscopy, and human tetraspanin chips. Samples were then analysed using Raman and optical photothermal infrared spectroscopy. Results Infrared spectra were analysed between 950-1800 cm -1 . Raman spectra had bands between the wavelengths of 900-1800 cm -1 analysed. Bands below 900 cm -1 . Spectral data for both Raman and optical photothermal infrared spectroscopy was used to obtain a classification model and confusion matrices, characterising the techniques ability to distinguish diseased samples. Optical photothermal infrared spectroscopy could differentiate osteoarthritic extracellular vesicles from healthy with good classification (93.4%) whereas Raman displayed poor classification (64.3%). Plasma-derived extracellular vesicles from osteoarthritic horses contained increased signal for proteins, lipids and nucleic acids. Discussion/ conclusion For the first time we demonstrated the ability to use optical photothermal infrared spectroscopy to interrogate extracellular vesicles and osteoarthritis-related samples. Optical photothermal infrared spectroscopy was superior to Raman in this study, and could distinguish osteoarthritis samples, suggestive of its potential use diagnostically to identify osteoarthritis in equine patients. This study demonstrates the potential of Raman and optical photothermal infrared spectroscopy to be used as a diagnostic tool in clinical practice, with the capacity to detect changes in extracellular vesicles from clinically derived samples