Quantitative online liquid chromatography-surface-enhanced Raman scattering of purine bases.

Raman spectroscopy has been of interest as a detection method for liquid chromatographic separations for a significant period of time, due to the structural information it can provide, allowing the identification and distinction of coeluting analytes. Combined with the rapidly advancing field of enhanced Raman techniques, such as surface-enhanced Raman scattering (SERS), the previous low sensitivity of Raman measurements has also been alleviated. At-line LC-SERS analyses, where SERS measurements are taken of fractions collected during or after HPLC separation have been shown to be sensitive and applicable to a wide variety of analytes; however, quantitative, real-time, online LC-SERS analysis at comparable sensitivity to existing methods, applicable to high-throughput experiments, has not been previously demonstrated. Here we show that by introducing silver colloid, followed by an aggregating agent into the postcolumn flow of an HPLC system, we can quantitatively and reproducibly analyze mixtures of purine bases, with limits of detection in the region of 100-500 pmol. The analysis is performed without the use of a flow cell, thereby eliminating previously detrimental memory effects.

Metabolic fingerprinting as a tool to monitor whole-cell biotransformations.

Fourier transform infrared (FT-IR) spectroscopy was employed as a rapid high-throughput phenotypic typing technique to generate metabolic fingerprints of Escherichia coli MG1655 pDTG601A growing in fed-batch culture, during the dioxygenase-catalysed biotransformation of toluene to toluene cis-glycol. With toluene fed as a vapour, the final toluene cis-glycol concentration was 83 mM, whereas the product concentration was only 22 mM when the culture was supplied with liquid toluene. Multivariate statistical analysis employing cluster analysis was used to analyse the dynamic changes in the data. The analysis revealed distinct trends and trajectories in cluster ordination space, illustrating phenotypic changes related to differences in the growth and product formation of the cultures. In addition, partial least squares regression was used to correlate the FT-IR metabolic fingerprints with the levels of toluene cis-glycol and acetate, the latter being an indicator of metabolic stress. We propose that this high-throughput metabolic fingerprinting approach is an ideal tool to assess temporal biochemical dynamics in complex biological processes, as demonstrated by this redox biotransformation. Moreover, this approach can also give useful information on product yields and fermentation health indicators directly from the fermentation broth without the need for lengthy chromatographic analysis of the products.

Impact of silver(I) on the metabolism of Shewanella oneidensis.

Anaerobic cultures of Shewanella oneidensis MR-1 reduced toxic Ag(I), forming nanoparticles of elemental Ag(0), as confirmed by X-ray diffraction analyses. The addition of 1 to 50 microM Ag(I) had a limited impact on growth, while 100 microM Ag(I) reduced both the doubling time and cell yields. At this higher Ag(I) concentration transmission electron microscopy showed the accumulation of elemental silver particles within the cell, while at lower concentrations the metal was exclusively reduced and precipitated outside the cell wall. Whole organism metabolite fingerprinting, using the method of Fourier transform infrared spectroscopy analysis of cells grown in a range of silver concentrations, confirmed that there were significant physiological changes at 100 microM silver. Principal component-discriminant function analysis scores and loading plots highlighted changes in certain functional groups, notably, lipids, amides I and II, and nucleic acids, as being discriminatory. Molecular analyses confirmed a dramatic drop in cellular yields of both the phospholipid fatty acids and their precursor molecules at high concentrations of silver, suggesting that the structural integrity of the cellular membrane was compromised at high silver concentrations, which was a result of intracellular accumulation of the toxic metal.

Fourier transform infrared spectroscopy as a metabolite fingerprinting tool for monitoring the phenotypic changes in complex bacterial communities capable of degrading phenol.

The coking process produces great volumes of wastewater contaminated with pollutants such as cyanides, sulfides and phenolics. Chemical and physical remediation of this wastewater removes the majority of these pollutants; however, these processes do not remove phenol and thiocyanate. The removal of these compounds has been effected during bioremediation with activated sludge containing a complex microbial community. In this investigation we acquired activated sludge from an industrial bioreactor capable of degrading phenol. The sludge was incubated in our laboratory and monitored for its ability to degrade phenol over a 48 h period. Multiple samples were taken across the time-course and analysed by Fourier transform infrared (FT-IR) spectroscopy. FT-IR was used as a whole-organism fingerprinting approach to monitor biochemical changes in the bacterial cells during the degradation of phenol. We also investigated the ability of the activated sludge to degrade phenol following extended periods (2-131 days) of storage in the absence of phenol. A reduction was observed in the ability of the microbial community to degrade phenol and this was accompanied by a detectable biochemical change in the FT-IR fingerprint related to cellular phenotype of the microbial community. In the absence of phenol a decrease in thiocyanate vibrations was observed, reflecting the ability of these communities to degrade this substrate. Actively degrading communities showed an additional new band in their FT-IR spectra that could be attributed to phenol degradation products from the ortho- and meta-cleavage of the aromatic ring. This study demonstrates that FT-IR spectroscopy when combined with chemometric analysis is a very powerful high throughput screening approach for assessing the metabolic capability of complex microbial communities.

Monitoring the effects of chiral pharmaceuticals on aquatic microorganisms by metabolic fingerprinting.

The effects of the chiral pharmaceuticals atenolol and propranolol on Pseudomonas putida, Pseudomonas aeruginosa, Micrococcus luteus, and Blastomonas natatoria were investigated. The growth dynamics of exposed cultures were monitored using a Bioscreen instrument. In addition, Fourier-transform infrared (FT-IR) spectroscopy with appropriate chemometrics and high-performance liquid chromatography (HPLC) were employed in order to investigate the phenotypic changes and possible degradation of the drugs in exposed cultures. For the majority of the bacteria studied there was not a statistically significant difference in the organism's phenotype when it was exposed to the different enantiomers or mixtures of enantiomers. In contrast, the pseudomonads appeared to respond differently to propranolol, and the two enantiomers had different effects on the cellular phenotype. This implies that there were different metabolic responses in the organisms when they were exposed to the different enantiomers. We suggest that our findings may indicate that there are widespread effects on aquatic communities in which active pharmaceutical ingredients are present.

Phenotypic characterization of Shewanella oneidensis MR-1 under aerobic and anaerobic growth conditions by using fourier transform infrared spectroscopy and high-performance liquid chromatography analyses.

Shewanella oneidensis is able to conserve energy for growth by reducing a wide variety of terminal electron acceptors during anaerobic respiration, including several environmentally hazardous pollutants. This bacterium employs various electron transfer mechanisms for anaerobic respiration, including cell-bound reductases and secreted redox mediators. The aim of this study was to develop rapid tools for profiling the key metabolic changes associated with these different growth regimes and physiological responses. Initial experiments focused on comparing cells grown under aerobic and anaerobic conditions. Fourier transform infrared (FT-IR) spectroscopy with cluster analysis showed that there were significant changes in the metabolic fingerprints of the cells grown under these two culture conditions. FT-IR spectroscopy clearly differentiated cells of S. oneidensis MR-1 cultured at various growth points and cells grown using different electron acceptors, resulting in different phenotypic trajectories in the cluster analysis. This growth-related trajectory analysis is applied successfully for the first time, here with FT-IR spectroscopy, to investigate the phenotypic changes in contrasting S. oneidensis cells. High-performance liquid chromatography (HPLC) was also used to quantify the concentrations of flavin compounds, which have been identified recently as extracellular redox mediators released by a range of Shewanella species. The partial least-squares regression (PLSR) multivariate statistical technique was combined with FT-IR spectroscopy to predict the concentrations of the flavins secreted by cells of S. oneidensis MR-1, suggesting that this combination could be used as a rapid alternative to conventional chromatographic methods for analysis of flavins in cell cultures. Furthermore, coupling of the FT-IR spectroscopy and HPLC techniques appears to offer a potentially useful tool for rapid characterization of the Shewanella cell metabolome in various process environments.

Rapid monitoring of recombinant antibody production by mammalian cell cultures using fourier transform infrared spectroscopy and chemometrics.

Fourier transform infrared (FT-IR) spectroscopy combined with multivariate statistical analyses was investigated as a physicochemical tool for monitoring secreted recombinant antibody production in cultures of Chinese hamster ovary (CHO) and murine myeloma non-secreting 0 (NS0) cell lines. Medium samples were taken during culture of CHO and NS0 cells lines, which included both antibody-producing and non-producing cell lines, and analyzed by FT-IR spectroscopy. Principal components analysis (PCA) alone, and combined with discriminant function analysis (PC-DFA), were applied to normalized FT-IR spectroscopy datasets and showed a linear trend with respect to recombinant protein production. Loadings plots of the most significant spectral components showed a decrease in the C-O stretch from polysaccharides and an increase in the amide I band during culture, respectively, indicating a decrease in sugar concentration and an increase in protein concentration in the medium. Partial least squares regression (PLSR) analysis was used to predict antibody titers, and these regression models were able to predict antibody titers accurately with low error when compared to ELISA data. PLSR was also able to predict glucose and lactate amounts in the medium samples accurately. This work demonstrates that FT-IR spectroscopy has great potential as a tool for monitoring cell cultures for recombinant protein production and offers a starting point for the application of spectroscopic techniques for the on-line measurement of antibody production in industrial scale bioreactors.

Shining light on the microbial world the application of Raman microspectroscopy.

Raman microspectroscopy is a noninvasive, label-free, and single-cell technology for biochemical analysis of individual mammalian cells, organelles, bacteria, viruses, and nanoparticles. Chemical information derived from a Raman spectrum provides comprehensive and intrinsic information (e.g., nucleic acids, protein, carbohydrates, and lipids) of single cells without the need of any external labeling. A Raman spectrum functions as a molecular "fingerprint" of single cells, which enables the differentiation of cell types, physiological states, nutrient condition, and variable phenotypes. Raman microspectroscopy combined with stable isotope probing, fluorescent in situ hybridization, and optical tweezers offers a culture-independent approach to study the functions and physiology of unculturable microorganisms in the ecosystem. Here, we review the application of Raman microspectroscopy to microbiology research with particular emphasis on single bacterial cells.

Combining metabolic fingerprinting and footprinting to understand the phenotypic response of HPV16 E6 expressing cervical carcinoma cells exposed to the HIV anti-viral drug lopinavir.

Recently, it has been reported that the anti-viral drug, lopinavir, which is currently used as a human immunodeficiency virus (HIV) protease inhibitor, could also inhibit E6-mediated proteasomal degradation of mutant p53 in E6-transfected C33A cells. In this study, C33A parent control cells and HPV16 E6-transfected cells were exposed to lopinavir at concentrations ranging from 0 to 30 microM. The phenotypic response was assessed by Fourier transform infrared (FT-IR) spectroscopy directly on cells (the metabolic fingerprint) and on the cell growth medium (the metabolic footprint). Multivariate analysis of the data using both principal components analysis (PCA) and canonical variates analysis (PC-CVA) showed trends in scores plots that were related to the concentration of the drug. Inspection of the PC-CVA loadings vector revealed that the effect was not due to the drug alone and that several IR spectral regions including proteins, nucleotides and carbohydrates contributed to the separation in PC-CVA space. Finally, partial least squares regression (PLSR) could be used to predict the concentration of the drug accurately from the metabolic fingerprints and footprints, indicating a dose related phenotypic response. This study shows that the combination of metabolic fingerprinting and footprinting with appropriate chemometric analysis is a valuable approach for studying cellular responses to anti-viral drugs.

Non-invasive metabolomic analysis of breath using differential mobility spectrometry in patients with chronic obstructive pulmonary disease and healthy smokers.

The rapid, accurate and non-invasive diagnosis of respiratory disease represents a challenge to clinicians, and the development of new treatments can be confounded by insufficient knowledge of lung disease phenotypes. Exhaled breath contains a complex mixture of volatile organic compounds (VOCs), some of which could potentially represent biomarkers for lung diseases. We have developed an adaptive sampling methodology for collecting concentrated samples of exhaled air from participants with impaired respiratory function, against which we employed two-stage thermal desorption gas chromatography-differential mobility spectrometry (GC-DMS) analysis, and showed that it was possible to discriminate between participants with and without chronic obstructive pulmonary disease (COPD). A 2.5 dm(3) volume of end tidal breath was collected onto adsorbent traps (Tenax TA/Carbotrap), from participants with severe COPD and healthy volunteers. Samples were thermally desorbed and analysed by GC-DMS, and the chromatograms analysed by univariate and multivariate analyses. Kruskal-Wallis ANOVA indicated several discriminatory (p < 0.01) signals, with good classification performance (receiver operator characteristic area up to 0.82). Partial least squares discriminant analysis using the full DMS chromatograms also gave excellent discrimination between groups (alpha = 19% and beta = 12.4%).

Multiobjective evolutionary optimisation for surface-enhanced Raman scattering.

In most optimisation experiments, a single parameter is first optimised before a second and then third one are subsequently modified to give the best result. By contrast, we believe that simultaneous multiobjective optimisation is more powerful; therefore, an optimisation of the experimental conditions for the colloidal SERS detection of L-cysteine was carried out. Six aggregating agents and three different colloids (citrate, borohydride and hydroxylamine reduced silver) were tested over a wide range of concentrations for the enhancement and the reproducibility of the spectra produced. The optimisation was carried out using two methods, a full factorial design (FF, a standard method from the experimental design literature) and, for the first time, a multiobjective evolutionary algorithm (MOEA), a method more usually applied to optimisation problems in computer science. Simulation results suggest that the evolutionary approach significantly out-performs random sampling. Real experiments applying the evolutionary method to the SERS optimisation problem led to a 32% improvement in enhancement and reproducibility compared with the FF method, using far fewer evaluations.

Raman chemical mapping reveals site of action of HIV protease inhibitors in HPV16 E6 expressing cervical carcinoma cells.

It has been shown that the HIV protease inhibitors indinavir and lopinavir may have activity against the human papilloma virus (HPV) type 16 inhibiting HPV E6-mediated proteasomal degradation of p53 in cultured cervical carcinoma cells. However, their mode and site of action is unknown. HPV-negative C33A cervical carcinoma cells and the same cells stably transfected with E6 (C33AE6) were exposed to indinavir and lopinavir at concentrations of 1 mM and 30 µM, respectively. The intracellular distribution of metabolites and metabolic changes induced by these treatments were investigated by Raman microspectroscopic imaging combined with the analysis of cell fractionation products by liquid chromatography-mass spectrometry (LC-MS). A uniform cellular distribution of proteins was found in drug-treated cells irrespective of cell type. Indinavir was observed to co-localise with nucleic acid in the nucleus, but only in E6 expressing cells. Principal components analysis (PCA) score maps generated on the full Raman hypercube and the corresponding PCA loadings plots revealed that the majority of metabolic variations influenced by the drug exposure within the cells were associated with changes in nucleic acids. Analysis of cell fractionation products by LC-MS confirmed that the level of indinavir in nuclear extracts was approximately eight-fold greater than in the cytoplasm. These data demonstrate that indinavir undergoes enhanced nuclear accumulation in E6-expressing cells, which suggests that this is the most likely site of action for this compound against HPV.

Explanatory multivariate analysis of ToF-SIMS spectra for the discrimination of bacterial isolates.

Multivariate analysis (PC-CVA and GA-CVA) was carried out on time-of-flight secondary ion mass spectra (ToF-SIMS) derived from 16 bacterial isolates associated with urinary tract infections, with an objective of extracting the spectral information relevant to their species-level discrimination. The use of spectral pre-processing, such as removal of the dominant peaks prior to analysis and analysis of the dominant peaks alone, enabled the identification of 37 peaks contributing to the principal components-canonical variates analysis (PC-CVA) discrimination of the bacterial isolates in the mass range of m/z 1-1000. These included signals at m/z 70, 84, 120, 134, 140, 150, 175 and 200. A univariate statistical analysis (Kruskal-Wallis) of the signal intensities at the identified m/z enabled an understanding of the discriminatory basis, which can be used in the development of robust parsimonious models for predictive purposes. The utility of genetic algorithm (GA)-based feature selection in identifying the discriminatory variables is also demonstrated. A database search of the identified signals enabled the biochemical origins of some these signals to be postulated.

Global metabolic profiling of Escherichia coli cultures: an evaluation of methods for quenching and extraction of intracellular metabolites.

Metabolomics and systems biology require the acquisition of reproducible, robust, reliable, and homogeneous biological data sets. Therefore, we developed and validated standard operating procedures (SOPs) for quenching and efficient extraction of metabolites from Escherichia coli to determine the best methods to approach global analysis of the metabolome. E. coli was grown in chemostat culture so that cellular metabolism could be held in reproducible, steady-state conditions under a range of precisely defined growth conditions, thus enabling sufficient replication of samples. The metabolome profiles were generated using gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS). We employed univariate and multivariate statistical analyses to determine the most suitable method. This investigation indicates that 60% cold (-48 degrees C) methanol solution is the most appropriate method to quench metabolism, and we recommend 100% methanol, also at -48 degrees C, with multiple freeze-thaw cycles for the extraction of metabolites. However, complementary extractions would be necessary for coverage of the entire complement of metabolites as detected by GC/TOF-MS. Finally, the observation that metabolite leakage was significant and measurable whichever quenching method is used indicates that methods should be incorporated into the experiment to facilitate the accurate quantification of intracellular metabolites.

Surface-enhanced Raman scattering from intracellular and extracellular bacterial locations.

While surface-enhanced Raman scattering (SERS) can increase the Raman cross-section by 4-6 orders of magnitude, for SERS to be effective it is necessary for the analyte to be either chemically bonded or within close proximity to the metal surface used. Therefore most studies investigating the biochemical constituents of microorganisms have introduced an external supply of gold or silver nanoparticles. As a consequence, the study of bacteria by SERS has to date been focused almost exclusively on the extracellular analysis of the Gram-negative outer cell membrane. Bacterial cells typically measure as little as 0.5 by 1 mum, and it is difficult to introduce a nanometer sized colloidal metal particle into this tiny environment. However, dissimilatory metal-reducing bacteria, including Shewanella and Geobacter species, can reduce a wide range of high valence metal ions, often within the cell, and for Ag(I) and Au(III) this can result in the formation of colloidal zero-valent particles. Here we report, for the first time, SERS of the bacterium Geobacter sulfurreducens facilitated by colloidal gold particles precipitated within the cell. In addition, we show SERS from the same organism following reduction of ionic silver, which results in colloidal silver depositions on the cell surface.

Multiplexed detection of six labelled oligonucleotides using surface enhanced resonance Raman scattering (SERRS).

The labelling of target biomolecules followed by detection using some form of optical spectroscopy has become common practice to aid in their detection. This approach has allowed the field of bioanalysis to dramatically expand; however, most methods suffer from the lack of the ability to discriminate between the components of a complex mixture. Currently, fluorescence spectroscopy is the method of choice but its ability to multiplex is greatly hampered by the broad overlapping spectra which are obtained. Surface enhanced resonance Raman scattering (SERRS) holds many advantages over fluorescence both in sensitivity and, more importantly here, in its ability to identify components in a mixture without separation due to the sharp fingerprint spectra obtained. Here the first multiplexed simultaneous detection of six different DNA sequences, corresponding to different strains of the Escherichia coli bacterium, each labelled with a different commercially available dye label (ROX, HEX, FAM, TET, Cy3, or TAMRA) is reported. This was achieved with the aid of multivariate analysis, also known as chemometrics, which can involve the application of a wide range of statistical and data analysis methods. In this study, both exploratory discriminant analysis and supervised learning, by partial least squares (PLS) regression, were used and the ability to discriminate whether a particular labelled oligonucleotide was present or absent in a mixture was achieved using PLS with very high sensitivity (0.98-1), specificity (0.98-1), accuracy (range 0.99-1), and precision (0.98-1).

Towards quantitatively reproducible substrates for SERS.

There is a need for a method to facilitate the development of novel, reproducible colloidal surface-enhanced Raman scattering (SERS) substrates to encourage the use of SERS in applied studies. In this study we show for the first time that by using suitably designed SERS experiments in conjunction with multivariate analysis of variance (MANOVA), an objective assessment of colloidal SERS reproducibility can be made. This is demonstrated with the analyte cresyl violet, but could be extended to any analyte of interest for which reproducible SERS data are needed.

PYCHEM: a multivariate analysis package for python.

UNLABELLED: We have implemented a multivariate statistical analysis toolbox, with an optional standalone graphical user interface (GUI), using the Python scripting language. This is a free and open source project that addresses the need for a multivariate analysis toolbox in Python. Although the functionality provided does not cover the full range of multivariate tools that are available, it has a broad complement of methods that are widely used in the biological sciences. In contrast to tools like MATLAB, PyChem 2.0.0 is easily accessible and free, allows for rapid extension using a range of Python modules and is part of the growing amount of complementary and interoperable scientific software in Python based upon SciPy. One of the attractions of PyChem is that it is an open source project and so there is an opportunity, through collaboration, to increase the scope of the software and to continually evolve a user-friendly platform that has applicability across a wide range of analytical and post-genomic disciplines. AVAILABILITY: http://sourceforge.net/projects/pychem

Ultra-violet resonance Raman spectroscopy for the rapid discrimination of urinary tract infection bacteria.

The ability to identify pathogenic organisms rapidly provides significant benefits to clinicians; in particular, with respect to best prescription practices and tracking of recurrent infections. Conventional bioassays require 3-5 days before identification of an organism can be made, thus compromising the effectiveness with which patients can be treated for bacterial infections. We analysed 20 clinical isolates of urinary tract infections (UTI) by ultra-violet resonance Raman (UVRR) spectroscopy, utilising 244 nm excitation delivering approximately 0.1 mW laser power at the sample, with typical spectral collection times of 120 s. UVRR results in resonance-enhanced Raman signals for certain chromophoric segments of macromolecules, intensifying those selected bands above what would otherwise be observed for a normal Raman experiment. Utilising the whole-organism 'fingerprints' obtained by UVRR we were able to discriminate successfully between UTI pathogens using chemometric cluster analyses. This work demonstrates significant improvements in the speed with which spectra can be obtained by Raman spectroscopic techniques for the discrimination of clinical bacterial samples.

Characterisation and identification of bacteria using SERS.

Within microbiology Raman spectroscopy is considered as a very important whole-organism fingerprinting technique, which is used to characterise, discriminate and identify microorganisms and assess how they respond to abiotic or biotic stress. Enhancing the sensitivity of Raman spectroscopy is very beneficial for the rapid analysis of bacteria (and indeed biological systems in general), where the ultimate goal is to achieve this without the need for lengthy cell culture. Bypassing this step would provide significant benefits in many areas such as medical, environmental and industrial microbiology, microbial systems biology, biological warfare countermeasures and bioprocess monitoring. In this tutorial review we will report on the advances made in bacterial studies, a relatively new and exciting application area for SERS.