Combining Raman and FT-IR Spectroscopy with Quantitative Isotopic Labeling for Differentiation of E. coli Cells at Community and Single Cell Levels

There is no doubt that the contribution of microbially mediated bioprocesses toward maintenance of life on earth is vital. However, understanding these microbes <i>in situ</i> is currently a bottleneck, as most methods require culturing these microorganisms to suitable biomass levels so that their phenotype can be measured. The development of new culture-independent strategies such as stable isotope probing (SIP) coupled with molecular biology has been a breakthrough toward linking gene to function, while circumventing <i>in vitro</i> culturing. In this study, for the first time we have combined Raman spectroscopy and Fourier transform infrared (FT-IR) spectroscopy, as metabolic fingerprinting approaches, with SIP to demonstrate the quantitative labeling and differentiation of Escherichia coli cells. E. coli cells were grown in minimal medium with fixed final concentrations of carbon and nitrogen supply, but with different ratios and combinations of ¹³C/¹²C glucose and ¹⁵N/¹⁴N ammonium chloride, as the sole carbon and nitrogen sources, respectively. The cells were collected at stationary phase and examined by Raman and FT-IR spectroscopies. The multivariate analysis investigation of FT-IR and Raman data illustrated unique clustering patterns resulting from specific spectral shifts upon the incorporation of different isotopes, which were directly correlated with the ratio of the isotopically labeled content of the medium. Multivariate analysis results of single-cell Raman spectra followed the same trend, exhibiting a separation between E. coli cells labeled with different isotopes and multiple isotope levels of C and N

Quantitative detection of codeine in human plasma using surface enhance Raman scattering via adaptation of the isotopic labelling principle

In this study surface enhanced Raman scattering (SERS) combined with the isotopic labelling (IL) principle has been used for the quantification of codeine spiked into both water and human plasma. Multivariate statistical approaches were employed for the analysis of these SERS spectral data, particularly partial least squares regression (PLSR) which was used to generate models using the full SERS spectral data for quantification of codeine with, and without, an internal isotopic labelled standard. The PLSR models pro-vided accurate codeine quantification in water and human plasma with high prediction accuracy (Q2). In addition, the employment of codeine-d6 as the internal standard further improved the accuracy of the model, by increasing the Q2 from 0.89 to 0.94 and decreasing the low root-mean-square error of predic-tions (RMSEP) from 11.36 to 8.44. Using the peak area at 1281 cm−1 assigned to C–N stretching, C–H wagging and ring breathing, the limit of detection was calculated in both water and human plasma to be 0.7 μM (209.55 ng mL−1) and 1.39 μM (416.12 ng mL−1), respectively. Due to a lack of definitive codeine vibrational assignments, density functional theory (DFT) calculations have also been used to assign the spectral bands with their corresponding vibrational modes, which were in excellent agreement with our experimental Raman and SERS findings. Thus, we have successfully demonstrated the application of SERS with isotope labelling for the absolute quantification of codeine in human plasma for the first time with a high degree of accuracy and reproducibility. The use of the IL principle which employs an isotopolog (that is to say, a molecule which is only different by the substitution of atoms by isotopes) improves quantifi-cation and reproducibility because the competition of the codeine and codeine-d6 for the metal surface used for SERS is equal and this will offset any difference in the number of particles under analysis or any fluctuations in laser fluence. It is our belief that this may open up new exciting opportunities for testing SERS in real-world samples and applications which would be an area of potential future studies

Towards improved quantitative analysis using surface-enhanced Raman scattering incorporating internal isotope labelling

Raman spectroscopy has attracted considerable interest during the past two decades as a vibrational technique used for the molecular characterisation of different molecules. Whilst the Raman effect is known to be generally weak, it is also known that this can be greatly improved using surface-enhanced Raman scattering (SERS). Indeed, in recent years, the power of SERS for rapid identification and quantification of target analytes in a wide range of applications has been repeatedly demonstrated in multiple studies. Moreover, the application of SERS in combination with an isotopically labelled compound (ILC), as an internal standard, has also very recently shown promising results for quantitative SERS measurements, by improving both its accuracy and precision. This is due to the 12 C and 13 C or 1 H and 2 H (D) having similar physicochemical properties. The use of these internal standards results in the reduction of any influences due to the number of nanoparticles within the analysis zone and fluctuations in laser fluence. Thus, in this study we have employed SERS for quantitative detection of tryptophan (Trp) and caffeine. These have been chosen because Trp is readily available as the deuterated form and caffeine is available in both 12 C and 13 C. Quantum chemical calculations based on density functional theory (DFT) have been utilized to determine the vibrational characteristics of the target analytes. For SERS analysis incorporating isotopologues of tryptophan three independent experiments were conducted with three different batches of nanoparticles over a 12 month period; our results show that the use of this internal standard improves quantification of this target molecule. In particular for the independent test sets (i.e., samples not used in quantitative partial least squares regression (PLSR) model construction) we observed improvements in the linearity for test set predictions, as well as lower errors in test set pred

Quantitative On-line Liquid Chromatography-Surface- Enhanced Raman Scattering (LC-SERS) of Methotrexate and its Major Metabolites

The application of Raman spectroscopy as a detection method coupled with liquid chromatography (LC) has recently attracted considerable interest, although this has currently been limited to isocratic elution. The combination of LC with rapidly advancing Raman techniques, such as surface-enhanced Raman scattering (SERS), allows for rapid separation, identification and quantification, leading to quantitative discrimination of closely eluting analytes. This study has demonstrated the utility of SERS in conjunction with reversed-phase liquid chromatography (RP-LC), for the detection and quantification of the therapeutically relevant drug molecule methotrexate (MTX) and its metabolites 7-hydroxy methotrexate (7-OH MTX) and 2,4-diamino-<i>N</i>(10)-methylpteroic acid (DAMPA) in pure solutions and mixtures, including spikes into human urine from a healthy individual and patients under medication. While the RP-LC analysis developed employed gradient elution, where the chemical constituents of the mobile phase were modified stepwise during analysis, this did not overtly interfere with the SERS signals. In addition, the practicability and clinical utility of this approach has also been demonstrated using authentic patients’ urine samples. Here, the identification of MTX, 7-OH MTX and DAMPA are based on their unique SERS spectra, providing limits of detection of 2.36, 1.84, and 3.26 μM respectively. Although these analytes are amenable to LC and LC-MS detection an additional major benefit of the SERS approach is its applicability toward the detection of analytes that do not show UV absorption or are not ionised for mass spectrometry (MS)-based detection. The results of this study clearly demonstrate the potential application of online LC-SERS analysis for real-time high-throughput detection of drugs and their related metabolites in human biofluids

Rapid, accurate, and comparative differentiation of clinically and industrially relevant microorganisms:Via multiple vibrational spectroscopic fingerprinting

Comparison of the applicability and accuracy of FT-IR, Raman and SERS, as physicochemical whole organism fingerprinting approaches, for differentiation of a range of microbial samples.</p

Chicken, beams, and Campylobacter: rapid differentiation of foodborne bacteria via vibrational spectroscopy and MALDI-mass spectrometry.:rapid differentiation of foodborne bacteria via vibrational spectroscopy and MALDI-mass spectrometry

This study is focused on the rapid differentiation of multipleCampylobacterspecies down to sub-species level, which may provide critical information and knowledge of risk factors, virulence, and distribution of these major foodborne pathogens.</p