Fluorescence spectroscopy of complex aromatic mixtures

The contribution of two- to seven-ring polycyclic aromatic hydrocarbons (PAH) and of larger aromatic structures contained in complex PAH-laden mixtures collected in flames was evaluated by fluorescence spectroscopy. A composition procedure of the fluorescence spectra of individual PAHs, analyzed by gas chromatography/mass spectrometry (GC/MS) was applied for the evaluation of their contribution to the fluorescence spectra of PAH-laden mixtures. In this way, it was possible to put in evidence the contribution to the total fluorescence spectrum of high molecular weight aromatic species present in the PAH-laden mixtures and not detectable by GC/MS. Qualitative and quantitative interpretation of synchronous and conventional fluorescence spectra of PAH-laden mixtures formed in combustion processes was proposed. The composition procedure was showed to be reliable in the UV-visible region for samples dissolved in cyclohexane solutions, but failed in the UV region when the solvent contained heavy atoms, as in the case of dichloromethane. However, the heavy-atom solvent effect was not sufficient to explain the depression of the UV fluorescence signal. Energy transfer interaction between fluorene and other fluorescing PAHs was suggested to be also responsible for this effect on the basis of fluorescence studies performed on single PAHs and their mixtures in cyclohexane, methanol, and dichloromethane.     

Fluorescence multiplexing with time-resolved and spectral discrimination using a near-IR detector

We report on the design and performance of a two-color, time-resolved detector for the acquisition of both steady-state and time-resolved fluorescence data acquired in real time during the capillary gel electrophoresis separation of DNA sequencing fragments. The detector consisted of a pair of pulsed laser diodes operating at 680 and 780 nm. The diode heads were coupled directly to single-mode fibers, which were terminated into a single fiber mounted via a FC/PC connector to the detector body. The detector contained a dichroic filter, which directed the dual-laser beams to an objective. The objective focused the laser light into a capillary gel column and also collected the resulting fluorescence emission. The dual-color emission was transmitted through the dichroic and focused onto a multimode fiber (core diameter 50 microm), which carried the luminescence to a pair of single-photon avalanche diodes (SPADs). The emission was sorted spectrally using a second dichroic onto one of two SPADs and isolated using appropriate interference filters (710- or 810-nm channel). The dual-color detector demonstrated a time response of 450 and 510 ps (fwhm) for the 710- and 810-nm channels, respectively. The mass detection limits for two near-IR dye-labeled sequencing primers electrophoresed in a capillary gel column were found to be 7.1 x 10(-21) and 3.2 x 10(-20) mol (SNR = 3) for the 710- and 810-nm detector channels, respectively. In addition, no leakage of luminescence excited at 680 nm was observed in the 810-nm channel or 780-nm excited luminescence into the 710-nm channel. An M13mp18 template was sequenced in a single capillary gel column using a two-color, two-lifetime format. The read length was found to be 650 base pairs for the test template at a calling accuracy of 95.1% using a linear poly(dimethylacrylamide) (POP6) gel column, with the read length determined primarily by the electrophoretic resolution produced by the sieving gel.     

Indirect spectral hard modeling for the analysis of reactive and interacting mixtures

We present an indirect hard modeling (IHM) approach for the quantitative analysis of reactive multicomponent mixtures with intermolecular interaction. It can be used when it is not possible to obtain calibration data in the composition region of interest. The goal of this work, specifically, is to analyze reactive systems, although the validation of the method is done with nonreactive systems. Compared to conventional hard modeling, the new approach reduces the manual work required for modeling and renders unnecessary the assignment of bands in mixture spectra to individual components. It is based on parametric models of the pure component spectra that are made just flexible enough to fit the spectra of the unknown mixtures, and it only requires small calibration data sets that may lie in different regions of the composition space. The application to infrared (IR) and Raman spectra of multicomponent systems is discussed.     

Quantitative analysis of piroxicam polymorphs pharmaceutical mixtures by hyperspectral imaging and chemometrics

It has been recognized that crystal polymorphism is an important factor related to the physicochemical and biological properties of drug substances and formulations. In this work, the piroxicam polymorphic forms 1 and 2 were studied using near-infrared chemical imaging (NIR-CI) technology to map the distribution of both species in pharmaceutical formulations. In this direction, the partial least squares (PLS) method was used to construct calibration models of concentrations per pixel of the sample. The RMSEP results for both models of the polymorphic forms remained below 4% (w/w). It was also possible to distinguish local and global information of the constituents through this method. These results seem to be a suitable tool for quality process control and final product quality assurance.     

Fluorescence spectral imaging for characterization of tissue based on multivariate statistical analysis

A novel spectral imaging method for the classification of light-induced autofluorescence spectra based on principal component analysis (PCA), a multivariate statistical analysis technique commonly used for studying the statistical characteristics of spectral data, is proposed and investigated. A set of optical spectral filters related to the diagnostically relevant principal components is proposed to process autofluorescence signals optically and generate principal component score images of the examined tissue simultaneously. A diagnostic image is then formed on the basis of an algorithm that relates the principal component scores to tissue pathology. With autofluorescence spectral data collected from nasopharyngeal tissue in vivo, a set of principal component filters was designed to process the autofluorescence signal, and the PCA-based diagnostic algorithms were developed to classify the spectral signal. Simulation results demonstrate that the proposed spectral imaging system can differentiate carcinoma lesions from normal tissue with a sensitivity of 95% and specificity of 93%. The optimal design of principal filters and the optimal selection of PCA-based algorithms were investigated to improve the diagnostic accuracy. The robustness of the spectral imaging method against noise in the autofluorescence signal was studied as well.     

Universal two-dimensional HPLC technique for the chemical analysis of complex surfactant mixtures

Two-dimensional HPLC was applied for the first time to the analysis of complex surfactant mixtures. In the first dimension, ion chromatographic-type separations were performed on a diol column eluted by an acetonitrile-water (0.1% trifluoroacetic acid) gradient. Using this new technique, cationic and amphoteric surfactants were not retained at all, nonionic surfactants exhibited a weak and essentially unspecific retention, and anionic surfactants were retained mainly according to their functional group. Rather than detecting the analytes immediately after this first separation, successive fractions were automatically and quantitatively transferred to parallel C2 (dimethyl) and C4 (butyl) reversed-phase columns using an innovative setup. The second dimension of the separation then took place, by which the analytes were separated according to their hydrophobicity. Surfactants from all four classes, cationic, amphoteric, nonionic, and anionic, were separated simultaneously in single 54-min two-dimensional HPLC runs. The suitability of the method for quantitative measurements was demonstrated.     

The chemometrics approach applied to FTIR spectral data for the analysis of rice bran oil in extra virgin olive oil

Among eleven studied vegetable oils, rice bran oil (RBO) has the close similarity to extra virgin olive oil (EVOO) in terms of FTIR spectra, as shown in the score plot of first and second principal components. The peak intensities at 18 frequency regions were used as matrix variables in principal component analysis (PCA). Consequently, the presence of RBO in EVOO is difficult to detect. This study aimed to use the chemometrics approach, namely discriminant analysis (DA) and multivariate calibrations of partial least square and principle component regression to analyze RBO in EVOO. DA was used for the classification of EVOO and EVOO mixed with RBO. Multivariate calibrations were exploited for the quantification of RBO in EVOO. The combined frequency regions of 1200-900 and 3020-3000 cm^− 1 were used for such analysis. The results showed that no misclassification was reported for the classification of EVOO and EVOO mixed with RBO. Partial least square regression either using normal or first derivative FTIR spectra can be successfully used for the quantification of RBO in EVOO. In addition, analysis of fatty acid composition can complement the results obtained from FTIR spectral data.     

Higher-order mass defect analysis for mass spectra of complex organic mixtures

Higher-order mass defect analysis is introduced as a unique formula assignment and visualization method for the analysis of complex mass spectra. This approach is an extension of the concepts of Kendrick mass transformation widely used for identification of homologous compounds differing only by a number of base units (e.g., CH(2), H(2), O, CH(2)O, etc.) in complex mixtures. We present an iterative renormalization routine for defining higher-order homologous series and multidimensional clustering of mass spectral features. This approach greatly simplifies visualization of complex mass spectra and increases the number of chemical formulas that can be confidently assigned for given mass accuracy. The potential for using higher-order mass defects for data reduction and visualization is shown. Higher-order mass defect analysis is described and demonstrated through third-order analysis of a deisotoped high-resolution mass spectrum of crude oil containing nearly 13,000 peaks.     

Independent components in spectroscopic analysis of complex mixtures

We applied two methods of “blind” spectral decomposition (MILCA and SNICA) to quantitative and qualitative analyses of UV absorption spectra of several non-trivial mixture types. Both methods use the concept of statistical independence and aim at the reconstruction of minimally dependent components from a linear mixture. We examined mixtures of major ecotoxicants (aromatic and polyaromatic hydrocarbons), amino acids and complex mixtures of vitamins in a veterinary drug. Both MICLA and SNICA were able to recover concentrations and individual spectra with minimal errors comparable with instrumental noise. In most cases their performance was similar to or better than that of other chemometric methods such as MCR-ALS, SIMPLISMA, RADICAL, JADE and FastICA. These results suggest that the ICA methods used in this study are suitable for real life applications.     

Application of two-dimensional correlation spectroscopy to chemometrics: self-modeling curve resolution analysis of spectral data sets

This paper demonstrates the use of two-dimensional (2D) correlation spectroscopy in conjunction with alternating least squares (ALS) based self-modeling curve resolution (SMCR) analysis of spectral data sets. This iterative regression technique utilizes the non-negativity constraints for spectral intensity and concentration. ALS-based SMCR analysis assisted with 2D correlation was applied to Fourier transform infrared (FT-IR) spectra of a polystyrene/methyl ethyl ketone/deuterated toluene (PS/MEK/d-toluene) solution mixture during the solvent evaporation process to obtain the pure component spectra and then the time-dependent concentration profiles of these three components during the evaporation process. We focus the use of asynchronous 2D correlation peaks for the identification of pure variables needed for the initial estimates of the ALS process. Choosing the most distinct bands via the positions of asynchronous 2D peaks is a viable starting point for ALS iteration. Once the pure variables are selected, ALS regression can be used to obtain the concentration profiles and pure component spectra. The obtained pure component spectra of MEK, d-toluene, and PS matched well with known spectra. The concentration profiles for components looked reasonable.     

Two-dimensional gas-phase separations coupled to mass spectrometry for analysis of complex mixtures

Ion mobility spectrometry (IMS) has been explored for decades, and its versatility in separation and identification of gas-phase ions is well established. Recently, field asymmetric waveform IMS (FAIMS) has been gaining acceptance in similar applications. Coupled to mass spectrometry (MS), both IMS and FAIMS have shown the potential for broad utility in proteomics and other biological analyses. A major attraction of these separations is extremely high speed, exceeding that of condensed-phase alternatives by orders of magnitude. However, modest separation peak capacities have limited the utility of FAIMS and IMS for analyses of complex mixtures. We report 2-D gas-phase separations that join FAIMS to IMS, in conjunction with high-resolution and accuracy time-of-flight (TOF) MS. Implementation of FAIMS/IMS and IMS/MS interfaces using electrodynamic ion funnels greatly improves sensitivity. Evaluation of FAIMS/IMS/TOF performance for a protein mixture tryptic digest reveals high orthogonality between FAIMS and IMS dimensions and, hence, the benefit of FAIMS filtering prior to IMS/MS. The effective peak capacities in analyses of tryptic peptides are approximately 500 for FAIMS/IMS separations and approximately 10(6) for 3-D FAIMS/IMS/MS, providing a potential platform for ultrahigh-throughput analyses of complex mixtures.     

Processing complex mixtures of intact proteins for direct analysis by mass spectrometry

For analysis of intact proteins by mass spectrometry (MS), a new twist to a two-dimensional approach to proteome fractionation employs an acid-labile detergent instead of sodium dodecyl sulfate during continuous-elution gel electrophoresis. Use of this acid-labile surfactant (ALS) facilitates subsequent reversed-phase liquid chromatography (RPLC) for a net two-dimensional fractionation illustrated by transforming thousands of intact proteins from Saccharomyces cerevisiae to mixtures of 5-20 components (all within approximately 5 kDa of one another) for presentation via electrospray ionization (ESI) to a Fourier transform MS (FTMS). Between 3 and 13 proteins have been detected directly using ESI-FTMS (or MALDI-TOF), and the fractionation showed a peak capacity of approximately 400 between 0 and 70 kDa. A probability-based identification was made automatically from raw MS/MS data (obtained using a quadrupole-FTMS hybrid instrument) for one protein that differed from that predicted in a yeast database of approximately 19,000 protein forms. This ALS-PAGE/RPLC approach to proteome processing ameliorates the "front end" problem that accompanies direct analysis of whole proteins and assists the future realization of protein identification with 100% sequence coverage in a high-throughput format.     

NMR diffusion measurements in complex mixtures using constant-time-HSQC-IDOSY and computer-optimized spectral aliasing for high resolution in the carbon dimension

A new 3D pulse sequence for NMR diffusion measurements in complex mixtures is presented. It is based on the constant-time (CT) HSQC experiment and combines diffusion delay with the carbon evolution time. This combination has great potential to obtain high resolution in the carbon dimension. When using classical sampling of the carbon dimension, maximal resolution would require a large number of time increments, leading to unrealistically long acquisition times. The application of computer-optimized spectral aliasing allows one to reduce the number of time increments and the total acquisition time by 1-2 orders of magnitude by taking advantage of the information content of 1D carbon spectra, HSQC experiments, or both. With the new CT-HSQC-IDOSY experiment, the diffusion rates of the six anomers present in a 0.1 M D2O solution of glucose, maltose, and maltotriose could be obtained at natural abundance in 8 h with standard deviations below 5%.     

Coupling ion mobility separations, collisional activation techniques, and multiple stages of MS for analysis of complex peptide mixtures

An ion trap/ion mobility/quadrupole/collision cell/time-of-flight mass spectrometer that incorporates a differentially pumped orifice-skimmer cone region at the back of the drift tube has been developed for the analysis of peptide mixtures. The combined approach allows a variety of strategies to be employed for collisionally activating ions, and fragments can be monitored by subsequent stages of mass spectrometry in a parallel fashion, as described previously (Anal. Chem. 2000, 72, 2737). Here, we describe the overall experimental approach in detail. Applications involving different aspects of the initial mobility separation and various collisional activation and parallel sequencing strategies are illustrated by examining several simple peptide mixtures and a mixture of tryptic peptides from beta-casein. Detection limits associated with various experimental configurations and the utility for analysis of complex systems are discussed.     

Analysis of ternary mixtures with a single dynamic microbial sensor and chemometrics using a nonlinear multivariate calibration

An amperometric biosensor based on immobilized bacterial cells of Alcaligenes eutrophus KT02 and an oxygen electrode was integrated in a flow-through system. Because microorganisms metabolize various organic analytes in a specific manner, the sensor shows for different pure analytes distinct time-dependent oxygen consumption rates that can be treated as characteristic patterns. This behavior is conserved also when the biosensor is exposed to a mixture of these organic analytes; the sensor with a particular type of microorganisms responds with a total signal. The respiration curves as time-dependent amplitudes were subdivided into several time channels. This procedure creates an additional data dimension and makes the single sensor "dynamic". Using multivariate calibration models with only one single biosensor, simultaneous quantitative analysis of ternary mixtures of acetate, L-lactate, and succinate was realized. A nonlinear algorithm that compensated for conceivable interactions of the analytes was superior to a partial least-squares algorithm. Each analyte was predicted more precisely by the nonlinear approach resulting in root-mean-square errors of prediction of 0.20 mg/L for acetate, 0.43 mg/L for L-lactate, and 0.73 mg/L for succinate.     

Two-layer sample preparation: a method for MALDI-MS analysis of complex peptide and protein mixtures

The analytical performance of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for direct analysis of peptide and protein mixtures is strongly dependent on the sample and matrix preparation. A two-layer sample preparation method is demonstrated to be very effective for analyzing complex mixtures. In this method, the first layer on the MALDI probe is the densely packed matrix microcrystals formed by fast solvent evaporation of a matrix solution. A mixture solution containing both matrix and sample is then deposited onto the first layer to form uniform analyte/matrix micrococrystals. It is found that the addition of matrix to the second-layer sample solution proves to be critical in analyzing mixtures of peptides and proteins covering a broad mass range. The effect of solvent conditions for preparing the second-layer solution is discussed. The application of this method is demonstrated for the analysis of cow's milk where milk proteins as well as peptide fragments produced from proteins by indigenous proteinases are detected. Direct analyses of peptides and proteins from a bacteria extract and crude egg white are also illustrated.     

Phosphoprotein isotope-coded solid-phase tag approach for enrichment and quantitative analysis of phosphopeptides from complex mixtures

Many cellular processes are regulated by reversible protein phosphorylation, and the ability to broadly identify and quantify phosphoproteins from proteomes would provide a basis for gaining a better understanding of these dynamic cellular processes. However, such a sensitive, efficient, and global method capable of addressing the phosphoproteome has yet to be developed. Here we describe an improved stable-isotope labeling method using a phosphoprotein isotope-coded solid-phase tag (PhIST) for isolating and measuring the relative abundances of phosphorylated peptides from complex peptide mixtures resulting from the enzymatic digestion of extracted proteins. The PhIST approach is an extension of the previously reported phosphoprotein isotope-coded affinity tag (PhIAT) approach developed by our laboratory, where phosphoseryl and phosphothreonyl residues were derivatized by hydroxide ion-mediated beta-elimination followed by the Michael addition of 1,2-ethanedithiol (EDT). Instead of using the biotin affinity tag, peptides containing the EDT moiety were captured and labeled in one step using isotope-coded solid-phase reagents containing either light (12C6, 14N) or heavy (13C6, 15N) stable isotopes. The captured peptides labeled with the isotope-coded tags were released from the solid-phase support by UV photocleavage and analyzed by capillary liquid chromatography-tandem mass spectrometry. The efficiency and sensitivity of the PhIST labeling approach for identification of phosphopeptides from mixtures were determined using casein proteins. Its utility for proteomic applications was demonstrated by the labeling of soluble phosphoproteins from a human breast cancer cell line.     

Band-target entropy minimization. A robust algorithm for pure component spectral recovery. Application to complex randomized mixtures of six components

A newly developed self-modeling curve resolution method, band-target entropy minimization (BTEM), is described. This method starts with the data decomposition of a set of spectroscopic mixture data using singular value decomposition. It is followed by the transformation of the orthonormal basis vectors/loading vectors into individual pure component spectra one at a time. The transformation is based in part on some seminal ideas borrowed from information entropy theory with the desire to maximize the simplicity of the recovered pure component spectrum. Thus, the proper estimate is obtained via minimization of the proposed information entropy function or via minimization of derivative and area of the spectral estimate. Nonnegativity constraints are also imposed on the recovered pure component spectral estimate and its corresponding concentrations. As its name suggests, in this method, one targets a spectral feature readily observed in loading vectors to retain, and then combinations of the loading vectors are searched to achieve the global minimum value of an appropriate objective function. The major advantage of this method is its one spectrum at a time approach and its capability of recovering minor components having low spectroscopic signals. To illustrate the application of BTEM, spectral resolution was performed on FT-IR measurements of very highly overlapping mixture spectra containing six organic species with a two-component background interference (air). BTEM estimates were also compared with the estimates obtained using other self-modeling curve resolution techniques, i.e., SIMPLISMA, IPCA, OPA-ALS, and SIMPLISMA-ALS.     

Pressure-assisted capillary electrophoresis coupling with matrix-assisted laser desorption/ionization-mass spectrometric imaging for quantitative analysis of complex Peptide mixtures

Herein, we report a pressure-assisted capillary electrophoresis-mass spectrometric imaging (PACE-MSI) platform for peptide analysis. This new platform has addressed the sample diffusion and peak splitting problems that appeared in our previous groove design, and it enables homogeneous deposition of the CE trace for high-throughput MALDI imaging. In the coupling of CE to MSI, individual peaks (m/z) can be visualized as discrete colored image regions and extracted from the MS imaging data, thus eliminating issues with peak overlapping and reducing reliance on an ultrahigh mass resolution mass spectrometer. Through a PACE separation, 46 tryptic peptides from bovine serum albumin and 150 putative neuropeptides from the pericardial organs of a model organism blue crab Callinectes sapidus were detected from the MALDI MS imaging traces, enabling a 4- to 6-fold increase of peptide coverage as compared with direct MALDI MS analysis. For the first time, quantitation with high accuracy was obtained using PACE-MSI for both digested tryptic peptides and endogenous neuropeptides from complex biological samples in combination with isotopic formaldehyde labeling. Although MSI is typically employed in tissue imaging, we show in this report that it offers a unique tool for quantitative analysis of complex trace-level analytes with CE separation. These results demonstrate a great potential of the PACE-MSI platform for enhanced quantitative proteomics and neuropeptidomics.