Spectral signatures for the classification of microbial species using Raman spectra

In general, classification-based methods based on confocal Raman microscopy are focused on targeted studies under which the spectral libraries are collected under controlled instrument parameters, which facilitate analyses via standard multivariate data analysis methods and cross-validation. We develop and compare approaches to transform spectra collected at different spectral ranges and varying levels of resolution into a single lower-dimension spectral signature library. This will result in a more robust analysis method able to accommodate spectra accumulated at different times and conditions. We demonstrate these approaches on a relevant test case; the identification of microbial species from a natural environment. The training data were based on samples prepared for three unique species collected at two time points and the test data consisted of blinded unknowns prepared and analyzed at a later date with different instrument parameters. The results indicate that using reduced dimension representations of the spectral signatures improves classification accuracy over basic alignment protocols. In particular, utilizing the microbial species partial least squares discriminant analysis classifier on the blinded samples based on alignment achieved ~78 % accuracy, while both binning and peak selection approaches yielded 100 % accuracy.

Spectral Reproducibility and Quantification of Peptides in MALDI of Samples Prepared by Micro-Spotting

Previously, we reported that MALDI spectra of peptides became reproducible when temperature was kept constant. Linear calibration curves derived from such spectral data could be used for quantification. Homogeneity of samples was one of the requirements. Among the three popular matrices used in peptide MALDI [i.e., α-cyano-4-hydroxycinnamic acid (CHCA), 2,5-dihydroxybenzoic acid (DHB), and sinapinic acid (SA)], homogeneous samples could be prepared by conventional means only for CHCA. In this work, we showed that sample preparation by micro-spotting improved the homogeneity for all three cases.

Efficient Methods to Generate Reproducible Mass Spectra in Matrix-Assisted Laser Desorption Ionization of Peptides

In our previous matrix-assisted laser desorption ionization (MALDI) studies of peptides, we found that their mass spectra were virtually determined by the effective temperature in the early matrix plume, T_early, when samples were rather homogeneous. This empirical rule allowed acquisition of quantitatively reproducible spectra. A difficulty in utilizing this rule was the complicated spectral treatment needed to get T_early. In this work, we found another empirical rule that the total number of particles hitting the detector, or TIC, was a good measure of the spectral temperature and, hence, selection of spectra with the same TIC resulted in reproducible spectra. We also succeeded in obtaining reproducible spectra throughout a measurement by controlling TIC near a preset value through feedback adjustment of laser pulse energy. Both TIC selection and TIC control substantially reduced the shot-to-shot spectral variation in a spot, spot-to-spot variation in a sample, and even sample-to-sample variation in MALDI using α-cyano-4-hydroxycinnamic acid or 2,5-dihydroxybenzoic acid as matrix. Based on the utilization of acquired data, TIC control was more efficient than TIC selection by an order of magnitude. Both techniques produced calibration curves with excellent linearity, suggesting their utility in quantification of peptides.

Absorption-Mode Fourier Transform Mass Spectrometry: The Effects of Apodization and Phasing on Modified Protein Spectra

The method of phasing broadband Fourier transform ion cyclotron resonance (FT-ICR) spectra allows plotting the spectra in the absorption-mode; this new approach significantly improves the quality of the data at no extra cost. Herein, an internal calibration method for calculating the phase function has been developed and successfully applied to the top-down spectra of modified proteins, where the peak intensities vary by 100×. The result shows that the use of absorption-mode spectra allows more peaks to be discerned within the recorded data, and this can reveal much greater information about the protein and modifications under investigation. In addition, noise and harmonic peaks can be assigned immediately in the absorption-mode.

Structural Documentation of Glycan Epitopes: Sequential Mass Spectrometry and Spectral Matching

Documenting mass spectral data is a fundamental aspect of accepted protocols. In this report, we contrast MSⁿ sequential disassembly spectra obtained from natural and synthetic glycan epitopes. The epitopes considered are clusters found on conjugate termini of lipids and N- and O-glycans of proteins. The latter are most frequently pendant through a CID-labile HexNAc glycosidic linkage. The synthetic samples were supplied by collaborating colleagues and commercial sources and usually possessed a readily released reducing-end linker, a by-product of synthesis. All samples were comparably methylated, extracted, and MSⁿ disassembled to compare their linkage and branching spectral details. Both sample types provide B-ion type fragments early in a disassembly pathway and their compositions are a suggestion of structure. Further steps of disassembly are necessary to confirm the details of linkage and branching. Included in this study were various Lewis and H antigens, 3- and 6-linked sialyl-lactosamine, NeuAc-2,8-NeuAc dimer, and Galα1,3Gal. Sample infusion provided high quality spectral data whereas disassembly to small fragments generates reproducible high signal/noise spectra for spectral matching. All samples were analyzed as sodium adducted positive ions. This study includes comparability statistics and evaluations on several mass spectrometers.

Artifacts Induced by Selective Blanking of Time-Domain Data in Fourier Transform Mass Spectrometry

Fourier transform mass spectrometry (FTMS) of the isolated isotopic distribution for a highly charged biomolecule produces time-domain signal containing large amplitude signal “beats” separated by extended periods of much lower signal magnitude. Signal-to-noise ratio for data sampled between beats is low because of destructive interference of the signals induced by members of the isotopic distribution. Selective blanking of the data between beats has been used to increase spectral signal-to-noise ratio. However, blanking also eliminates signal components and, thus, can potentially distort the resulting FT spectrum. Here, we simulate the time-domain signal from a truncated isotopic distribution for a single charge state of an antibody. Comparison of the FT spectra produced with or without blanking and with or without added noise clearly show that blanking does not improve mass accuracy and introduces spurious peaks at both ends of the isotopic distribution (thereby making it more difficult to identify posttranslational modifications and/or adducts). Although the artifacts are reduced by use of multiple Gaussian (rather than square wave) windowing, blanking appears to offer no advantages for identifying true peaks or for mass measurement.

A Comparison of Alternating Current and Direct Current Electrospray Ionization for Mass Spectrometry

A series of studies comparing the performance of alternating current electrospray ionization (AC ESI) mass spectrometry (MS) and direct current electrospray ionization (DC ESI) MS have been conducted, exploring the absolute signal intensity and signal-to-background ratios produced by both methods using caffeine and a model peptide as targets. Because the high-voltage AC signal was more susceptible to generating gas discharges, the operating voltage range of AC ESI was significantly smaller than that for DC ESI, such that the absolute signal intensities produced by DC ESI at peak voltages were one to two orders of magnitude greater than those for AC ESI. Using an electronegative nebulizing gas, sulfur hexafluoride (SF₆), instead of nitrogen (N₂) increased the operating range of AC ESI by ~50 %, but did not appreciably improve signal intensities. While DC ESI generated far greater signal intensities, both ionization methods produced comparable signal-to-background noise, with AC ESI spectra appearing qualitatively cleaner. A quantitative calibration analysis was performed for two analytes, caffeine and the peptide MRFA. AC ESI utilizing SF₆ outperforms all other techniques for the detection of MRFA, producing chromatographic limits of detection nearly one order of magnitude lower than that of DC ESI utilizing N₂, and one-half that of DC ESI utilizing SF₆. However, DC ESI outperforms AC ESI for the analysis of caffeine, indicating that improvements in spectral quality may benefit certain compounds or classes of compounds, on an individual basis.

The effect of different gloss levels on in-line monitoring of the thickness of printed layers by NIR spectroscopy

Near-infrared (NIR) reflection spectroscopy was used for monitoring the thickness or rather the coating weight of thin printed layers of transparent oil-based offset printing varnishes in a range from 0.5 to 5 g?m^?2. Quantitative analysis of the spectral data was carried out with partial least squares regression. Surface properties such as the gloss were found to strongly affect the prediction of the coating weight. This influence was minimized by the development of calibration models, which contained spectra of layers with a broad range of gloss levels. The prediction error of these models was in the order of 0.12 to 0.16 g?m^?2. In-line measurements were carried out at a sheet-fed offset printing press in order to test the performance of the models under real process control conditions. Varnishes were applied to paper at printing speeds of 90 or 180 m?min^?1. A close correlation between the predictions from in-line NIR spectra and the reference data from gravimetry was observed regardless of the specific degree of gloss of the layers (errors between 0.15 and 0.17 g?m^?2). The results clearly prove the efficiency of NIR reflection spectroscopy for quantitative investigations on thin layers in fast processes such as printing and demonstrate its analytical potential for quality and process control.

The effect of optical substrates on micro-FTIR analysis of single mammalian cells

The study of individual cells with infrared (IR) microspectroscopy often requires living cells to be cultured directly onto a suitable substrate. The surface effect of the specific substrates on the cell growth—viability and associated biochemistry—as well as on the IR analysis—spectral interference and optical artifacts—is all too often ignored. Using the IR beamline, MIRIAM (Diamond Light Source, UK), we show the importance of the substrate used for IR absorption spectroscopy by analyzing two different cell lines cultured on a range of seven optical substrates in both transmission and reflection modes. First, cell viability measurements are made to determine the preferable substrates for normal cell growth. Successively, synchrotron radiation IR microspectroscopy is performed on the two cell lines to determine any genuine biochemically induced changes or optical effect in the spectra due to the different substrates. Multivariate analysis of spectral data is applied on each cell line to visualize the spectral changes. The results confirm the advantage of transmission measurements over reflection due to the absence of a strong optical standing wave artifact which amplifies the absorbance spectrum in the high wavenumber regions with respect to low wavenumbers in the mid-IR range. The transmission spectra reveal interference from a more subtle but significant optical artifact related to the reflection losses of the different substrate materials. This means that, for comparative studies of cell biochemistry by IR microspectroscopy, it is crucial that all samples are measured on the same substrate type.

Interpretation and Deconvolution of Nanodisc Native Mass Spectra

Nanodiscs are a promising system for studying gas-phase and solution complexes of membrane proteins and lipids. We previously demonstrated that native electrospray ionization allows mass spectral analysis of intact Nanodisc complexes at single lipid resolution. This report details an improved theoretical framework for interpreting and deconvoluting native mass spectra of Nanodisc lipoprotein complexes. In addition to the intrinsic lipid count and charge distributions, Nanodisc mass spectra are significantly shaped by constructive overlap of adjacent charge states at integer multiples of the lipid mass. We describe the mathematical basis for this effect and develop a probability-based algorithm to deconvolute the underlying mass and charge distributions. The probability-based deconvolution algorithm is applied to a series of dimyristoylphosphatidylcholine Nanodisc native mass spectra and used to provide a quantitative picture of the lipid loss in gas-phase fragmentation.

Least-Squares Fitting of Time-Domain Signals for Fourier Transform Mass Spectrometry

To advance Fourier transform mass spectrometry (FTMS)-based molecular structure analysis, corresponding development of the FTMS signal processing methods and instrumentation is required. Here, we demonstrate utility of a least-squares fitting (LSF) method for analysis of FTMS time-domain (transient) signals. We evaluate the LSF method in the analysis of single- and multiple-component experimental and simulated ion cyclotron resonance (ICR) and Orbitrap FTMS transient signals. Overall, the LSF method allows one to estimate the analytical limits of the conventional instrumentation and signal processing methods in FTMS. Particularly, LSF provides accurate information on initial phases of sinusoidal components in a given transient. For instance, the phase distribution obtained for a statistical set of experimental transients reveals the effect of the first data-point problem in FT-ICR MS. Additionally, LSF might be useful to improve the implementation of the absorption-mode FT spectral representation for FTMS applications. Finally, LSF can find utility in characterization and development of filter-diagonalization method (FDM) MS.

Advantages of Monodisperse and Chemically Robust “SpheriCal” Polyester Dendrimers as a “Universal” MS Calibrant

The utilization of dendrimer calibrants as an alternative to peptides and proteins for high mass calibration is explored. These synthetic macromolecules exhibited a number of attractive advantages, including exceptional shelf-lives, broad compatibility with a wide range of matrices and solvents, and evenly spaced calibration masses across the mass range examined, 700–30,000 u. The exceptional purity of these dendrimers and the technical simplicity of this calibration platform validate their broad relevance for high molecular weight mass spectrometry.

Comparison of methods for the processing of voltammetric electronic tongues data

We are making a numerical comparison of various preprocessing strategies for dealing with data from voltammetric electronic tongues in order to reduce the high dimensionality of the response matrices. Different modelling tools are presented and briefly described. We then compare combinations of four preprocessing strategies (principal component analysis, fast Fourier transform, discrete wavelet transform, voltammogram-windowed slicing integral) with four modelling alternatives (principal component regression, partial least squares regression, multi-way partial least squares regression, artificial neural networks) by employing data from a voltammetric bioelectronic tongue, an array formed by enzyme-modified biosensors and applied to the discrimination and quantification of phenolic compounds.

Characterization and analysis of mycobacteria and Gram-negative bacteria and co-culture mixtures by Raman microspectroscopy, FTIR, and atomic force microscopy

The molecular composition of mycobacteria and Gram-negative bacteria cell walls is structurally different. In this work, Raman microspectroscopy was applied to discriminate mycobacteria and Gram-negative bacteria by assessing specific characteristic spectral features. Analysis of Raman spectra indicated that mycobacteria and Gram-negative bacteria exhibit different spectral patterns under our experimental conditions due to their different biochemical components. Fourier transform infrared (FTIR) spectroscopy, as a supplementary vibrational spectroscopy, was also applied to analyze the biochemical composition of the representative bacterial strains. As for co-cultured bacterial mixtures, the distribution of individual cell types was obtained by quantitative analysis of Raman and FTIR spectral images and the spectral contribution from each cell type was distinguished by direct classical least squares analysis. Coupled atomic force microscopy (AFM) and Raman microspectroscopy realized simultaneous measurements of topography and spectral images for the same sampled surface. This work demonstrated the feasibility of utilizing a combined Raman microspectroscopy, FTIR, and AFM techniques to effectively characterize spectroscopic fingerprints from bacterial Gram types and mixtures.

Spectroscopic analysis of bacterial biological warfare simulants and the effects of environmental conditioning on a bacterial spectrum

The ability to distinguish bacteria from mixed samples is of great interest, especially in the medical and defence arenas. This paper reports a step towards the aim of differentiating pathogenic endospores in situ, to aid any required response for hazard management using infrared spectroscopy combined with multivariate analysis. We describe a proof-of-principle study aimed at discriminating biological warfare simulants from common environmental bacteria. We also report an evaluation of multiple pre-processing techniques and subsequent differences in cross-validation of two pattern recognition models (Support Vector Machines and Principal Component–Linear Discriminant Analysis) for a six-class classification (bacterial classification). These classifications were possible with an average sensitivity of 88.0 and 86.9?%, and an average specificity of 97.6 and 97.5?% for the SVM and the PC-LDA models, respectively. Most spectroscopic models are built upon spectra from bacteria that have been specifically prepared for analysis by a particular method; this paper will comment upon the differences in the bacterial spectrum that occur between specific preparations when the bacteria have spent 30?days in the simulated weather conditions of a hot dry climate.

Determination of amylose content in starch using Raman spectroscopy and multivariate calibration analysis

Fourier transform Raman spectroscopy and chemometric tools have been used for exploratory analysis of pure corn and cassava starch samples and mixtures of both starches, as well as for the quantification of amylose content in corn and cassava starch samples. The exploratory analysis using principal component analysis shows that two natural groups of similar samples can be obtained, according to the amylose content, and consequently the botanical origins. The Raman band at 480 cm^?1, assigned to the ring vibration of starches, has the major contribution to the separation of the corn and cassava starch samples. This region was used as a marker to identify the presence of starch in different samples, as well as to characterize amylose and amylopectin. Two calibration models were developed based on partial least squares regression involving pure corn and cassava, and a third model with both starch samples was also built; the results were compared with the results of the standard colorimetric method. The samples were separated into two groups of calibration and validation by employing the Kennard-Stone algorithm and the optimum number of latent variables was chosen by the root mean square error of cross-validation obtained from the calibration set by internal validation (leave one out). The performance of each model was evaluated by the root mean square errors of calibration and prediction, and the results obtained indicate that Fourier transform Raman spectroscopy can be used for rapid determination of apparent amylose in starch samples with prediction errors similar to those of the standard method.

Factorial Experimental Designs Elucidate Significant Variables Affecting Data Acquisition on a Quadrupole Orbitrap Mass Spectrometer

Instrument parameter values for a quadrupole Orbitrap mass spectrometer were optimized for performing global proteomic analyses. Fourteen factors were evaluated for their influence on data-dependent acquisition with an emphasis on both the rate of sequencing and spectral quality by maximizing two individually tested response variables (unique peptides and protein groups). Of the 14 factors, 12 factors were assigned significant contrast values (P?<?0.05) for both response variables. Fundamentally, when optimizing parameters, a balance between spectral quality and duty cycle needs to be reached in order to maximize proteome coverage. This is especially true when using a data-dependent approach for sequencing complex proteomes. For example, maximum ion injection time, automatic gain control settings, and minimum threshold settings for triggering MS/MS isolation and activation all heavily influence ion signal, the number of spectra collected, and spectral quality. To better assess the effect these parameters have on data acquisition, all MS/MS data were parsed according to ion abundance by calculating the percent of the AGC target reached for each MS/MS event and then compared with successful peptide-spectrum matches. This proved to be an effective approach for understanding the effect of ion abundance on successful peptide-spectrum matches and establishing minimum ion abundance thresholds for triggering MS/MS isolation and activation.

Metabonomics studies of intact hepatic and renal cortical tissues from diabetic db/db mice using high-resolution magic-angle spinning 1H NMR spectroscopy

A metabonomics approach based on high-resolution magic-angle spinning (HRMAS) ¹H NMR spectroscopy was applied to investigate the metabolite composition in intact hepatic tissues and renal cortical tissues from db/db mice of 8 weeks old, an animal model of type 2 diabetes mellitus. Compared to the control group, the hepatic tissues of diabetic mice have elevated levels of triglyceride and bile acid and declined levels of trimethylamine-N-oxide, phosphocholine, glycerophosphocholine, and choline. The biochemical changes are less obvious in renal cortical tissues of diabetic mice. The WET_CPMG pulse sequence was selected for our metabonomics study after the quality and reproducibility of the spectra obtained from the NOEPR, NOEPR_CPMG, and WET_CPMG pulse sequences were analyzed together with principal component analysis. The influence of line-broadening factor of exponential window function for spectral manipulation on class separation was paid attention to for the first time, and an optimal value was obtained under our experimental conditions. These studies show the efficiency of HRMAS ¹H NMR spectroscopy for tissue metabonomics study in combination with multivariate statistical analysis, which may help to explore the etiological factor of diabetes mellitus from a new perspective.

Glassy carbon electrode modified with organic�Cinorganic pillared montmorillonites for voltammetric detection of mercury

A glassy carbon electrode modified with organic?Cinorganic pillared montmorillonite was used for voltammetric detection of mercury(II) in water. High sensitivity is obtained due to the use of the montmorillonites which displays outstanding capability in terms of adsorbing mercury ion due to its high specific surface and the presence of multiple binding sites. The experimental parameters and the effect of a chelating agent were optimized to further enhance sensitivity and selectivity. Linear calibration curves were obtained over the Hg(II) concentration range from 10 to 800???g?L^?1 for 5?min accumulation, with a detection limit of 1???g?L^?1. Simultaneous determination of Hg(II) and Cu(II) was also studied, and no interference was observed.

Enantioselective separation and simultaneous determination of fenarimol and nuarimol in fruits, vegetables, and soil by liquid chromatography–tandem mass spectrometry

A method for simultaneous enantioselective determination of fenarimol and nuarimol in apple, grape, cucumber, tomato, and soil was developed using liquid chromatography–tandem mass spectrometry. The enantioseparation results of the two fungicides through three different cellulose-based chiral columns are discussed. The influence of column temperature on the resolution of the enantiomers of the two fungicides was examined. Complete enantioseparation of the two fungicides’ enantiomers was obtained on a cellulose tris(4-methylbenzoate) column (Lux Cellulose-3) at 25?°C using methanol and 0.1?% formic acid solution (80:20, v/v) as mobile phase. The linearity, matrix effect, recovery, and precision were evaluated. Good linearity was obtained over the concentration range of 1–500?μg?L^?1 for each enantiomer in the standard solution and sample matrix calibration solution. There was no significant matrix effect in apple, grape, cucumber, or tomato samples, but signal suppression was typically observed with the soil extracts. The mean recoveries, repeatability, and reproducibility were 76.5–103?%, 2.1–9.0?%, and 4.2–11.8?%, respectively. The limit of quantification for enantiomers of the two fungicides in fruits, vegetables and soil was 5?μg?kg^?1. Moreover, the absolute configuration of the enantiomers of fenarimol and nuarimol was determined from a combination of experimentally determined and predicted electronic circular dichroism spectra.