Capillary electrophoresis with lamp-based wavelength-resolved fluorescence detection for the probing of protein conformational changes

Native protein fluorescence spectra encompass information on protein conformation. In this study, capillary electrophoresis (CE) combined with lamp-based wavelength-resolved fluorescence detection (wrFlu) is presented as a novel tool for the analysis of protein mixtures and the monitoring of protein unfolding. The CE-wrFlu system provides three-dimensional data (time, emission wavelength, intensity) from which electropherograms and accurate emission spectra of separated proteins can be extracted. For model proteins, linear detector responses (peak height vs concentration) were obtained (R(2) > 0.96) with detection limits (LODs) in the 6-32 nM range. The minimum protein concentration required for precise determination of the maximum emission wavelength by CE-wrFlu was about 15 times the LOD. Unfolding of various model proteins was induced by protein incubation and analysis in background electrolyte (BGE) containing 7.0 M urea. CE-wrFlu of the unfolded species revealed peaks with clear red-shifted spectra, which adequately corresponded to reference spectra obtained on a standard spectrophotometer. Moreover, unfolded proteins showed a significant decrease in effective electrophoretic mobility (after correction for BGE viscosity) due to the increase of their molecular hydrodynamic radii. It is concluded that the CE-wrFlu system provides two independent indicators for changes in protein folding and will allow the simultaneous assessment of protein purity and conformation.     

Monitoring and modeling of protein processes using mass spectrometry, circular dichroism, and multivariate curve resolution methods

Mass spectrometry has recently become one of the major analytical tools to study biomolecular structure and function. Ionization techniques, such as electrospray ionization (ESI), desorb biomolecules from solution to the gas phase keeping practically intact their natural structure. ESI applied to a protein solution produces a mixture of multiply charged ions, the ion charge distribution of which depends on the oligomeric form (mass) and on the protein surface exposed (amount of accommodated charges) of the related protein conformation. ESI-MS provides an efficient way to monitor protein processes; however, the ionic contributions of the different protein conformations involved usually overlap, and the use of chemometric tools is necessary to unravel the information related to the pure conformations that the biomolecule adopts along the process. Multivariate curve resolution-alternating least squares applied to MS-monitored protein processes provides the concentration profiles associated with the different protein conformations occurring during the process and the related pure mass spectra. The concentration profiles, in this context, the ionic contributions, describe the process mechanism and the structural information derived from the pure mass spectra characterizes the involved conformations. Mass spectra can be expressed schematically through percentages of base peak intensity. This chemical transformation compresses significantly the raw spectra and allows for an easier application of natural MS-related constraints, such as the presence of only one maximum, i.e., the base peak of a particular conformation, into the resolution of the pure signals. The combination of mass spectrometry and multivariate curve resolution methods is used to elucidate the mechanism of the pH-induced conformation changes of the bovine beta-lactoglobulin. As a final step, MS data are fused with circular dichroism data and are simultaneously analyzed to ensure and confirm that all the previously detected MS conformations really exist in solution and are an artifact of neither the ionization process nor their chemometric resolution.     

Towards complete descriptions of the free-energy landscapes of proteins

In recent years increasingly detailed information about the structures and dynamics of protein molecules has been obtained by innovative applications of experimental techniques, in particular nuclear magnetic resonance spectroscopy and protein engineering, and theoretical methods, notably molecular dynamics simulations. In this article we discuss how such approaches can be combined by incorporating a wide range of different types of experimental data as restraints in computer simulations to provide unprecedented detail about the ensembles of structures that describe proteins in a wide variety of states from the native structure to highly unfolded species. Knowledge of these ensembles is beginning to enable the complete free-energy landscapes of individual proteins to be defined at atomic resolution. This strategy has provided new insights into the mechanism by which proteins are able to fold into their native states, or by which they fail to do so and give rise to harmful aggregates that are associated with a wide range of debilitating human diseases.     

Application of multivariate curve resolution for analysis of FT-IR microspectroscopic images of in situ plant tissue

The chemometric techniques of multivariate curve resolution (MCR) are aimed at extracting the spectra and concentrations of individual components present in mixtures using a minimum set of initial assumptions. We present results from the application of alternating least squares (ALS) based MCR to the analysis of hyperspectral images of in situ biological material. The spectra of individual pure components were mathematically extracted and then identified by searching the spectra against a commercial library. No prior information about the chemical composition of the material was used in the data analysis. The spectra recovered by ALS-MCR analysis of an FT-IR microspectroscopic image of an 8-micron-cornkernel section matched very well the spectra of the corn storage protein, zein, and starch. Through the application of MCR, we were able to show the presence of a second spectrally different protein, which could not be easily seen using univariate analysis. These results demonstrate the value of multivariate curve resolution techniques for the analysis of biological tissue. The value of principal components analysis (PCA) for hyperspectral image analysis is also discussed.     

Direct determination of unsaturation level of milk fat using Raman spectroscopy

We have demonstrated the potential of visible Raman spectroscopy in combination with chemometric analysis as a fast and simple tool for the determination of the unsaturation level of milk fat. The Raman measurements have been performed directly on liquid milk and on fat extracted from liquid milk. The Raman spectra taken from the extracted fat showed a higher resolution. The spectra directly obtained from the milk samples had some fluorescence background but nevertheless yielded the desired information. For calibration purposes, the iodine value (IV) was determined in all cases in order to evaluate the unsaturation level of the investigated samples. Two separate calibration models have been constructed; one for the milk samples and the second one for the extracted fat. The accuracy of these calibration models was estimated using the root mean square error of calibration and validation (RMSE) and the coefficient of determination (R(2)) between actual and predicted values.     

Introduction and application of secured principal component regression for analysis of uncalibrated spectral features in optical spectroscopy and chemical sensing

In this study, a novel chemometric algorithm for improved evaluation of analytical data is presented and applied to three spectroscopic data sets obtained by different analytical methods. This so-called secured principal component regression (sPCR) was developed for detecting and correcting uncalibrated spectral features newly emerging in spectra after finalizing the PCR calibration, which may result in major concentration errors. Hence, detection and correction of uncalibrated features is essential. Furthermore, detected uncalibrated features provide qualitative information for sensing and process monitoring applications indicating problems in the process flow. After conventional PCR calibration, sPCR analyzes measurement data in two steps: The first step investigates whether the obtained data set is consistent with the calibration model or not. If spectroscopic features are found that cannot be modeled by the principal components, they are extracted from the measurement spectrum. This corrected spectrum is then evaluated by conventional PCR. In the Experimental Section, sPCR was successfully applied to three data sets obtained by different spectroscopic measurements in order to corroborate general applicability of the proposed concept. For each data set, one of several substances was excluded from the calibration acting in the sPCR assessment as uncalibrated absorber. The test sets consisted of disturbed and undisturbed samples. A total of 109 out of 110 test samples were correctly classified as disturbed or undisturbed by an uncalibrated absorber. It was confirmed that the extracted disturbance spectra are in accordance with the spectra of the uncalibrated analytes. The concentration results obtained with sPCR were found to be equivalent to conventional PCR results in the case of undisturbed samples and more precise for disturbed samples.     

Structure and vibrational motion of insulin from Raman optical activity spectra

The Raman optical activity (ROA) spectroscopic technique has been applied in the past to many biologically relevant systems including peptides, proteins, sugars, and even viruses. However, theoretical interpretation of the spectra relies on lengthy quantum-chemical computations, which are difficult to extend to larger molecules. In the present study, ROA and Raman spectra of insulin under a range of various conditions were measured and interpreted with the aid of the Cartesian-coordinate tensor transfer (CCT) method. The CCT methodology yielded spectra of insulin monomer and dimer of nearly ab initio quality, while at the same time reproducing the experimental data very well. The link between the spectra and the protein structure could thus be studied in detail. Spectral contributions from the peptide backbone and the amino acid side chains were calculated. Likewise, specific intensity features originating from the α-helical, coil, β-sheet, and 3(10)-helical parts of the protein could be deciphered. The assignment of the Raman and ROA bands to intrinsic molecular coordinates as based on the harmonic force field calculation revealed their origin and degree of locality. Alternatively, the relation of the structural flexibility of insulin to the inhomogeneous broadening of spectral bands was studied by a combination of CCT and molecular dynamics (MD). The present study confirms the sensitivity of the ROA technique to some subtle static and dynamic changes in molecular geometry, and many previous ad hoc or semiempirical spectral-structure assignments could be verified. On the other hand, a limitation in longer-range tertiary structure sensitivity was revealed. Unlike for smaller molecules with approximately equal contributions of the electric dipole (α), quadrupole (A), and magnetic dipole (G') polarizabilities, only the electric dipolar polarization (α) interactions seem to dominate in the protein ROA signal. The simulations concern the largest molecule for which such spectra were interpreted by a priori procedures and significantly enhance protein folding studies undertaken by this technique.     

Kinetics of lisinopril intramolecular cyclization in solid phase monitored by Fourier transform infrared microscopy

The solid-state intramolecular cyclization of lisinopril to diketopiperazine was investigated by in situ Fourier transform infrared (FT-IR) microscopy. Using a controllable heating cell, the isothermal transformation was monitored in situ at 147.5, 150, 152.5, 155, and 157.5 degrees C. The collected time-dependent FT-IR spectra at each isothermal temperature were preprocessed and analyzed using a multivariate chemometric approach. The pure component spectra of the observable component (lisinopril and diketopiperazine) were resolved and their time-dependent relative contributions were also determined. Model-free and various model fitting methods were implemented in the kinetic analysis to estimate the activation energy of the intramolecular cyclization reaction. Arrhenius plots indicate that the activation energy is circa 327 kJ/mol.     

Signal response of coexisting protein conformers in electrospray mass spectrometry

Electrospray ionization mass spectrometry (ESI-MS) is a commonly used tool for characterizing conformational changes of proteins in solution. Different conformations can be distinguished on the basis of their ESI charge state distributions. ESI-MS studies carried out under semidenaturing conditions result in bi- or multimodal distributions that reflect the presence of coexisting conformers. This study explores whether the concentration ratios of these species in solution are reflected in the measured ion intensities. Experiments on two model proteins, lysozyme and myoglobin, reveal that non-native polypeptide chains tend to result in a much stronger signal response than natively folded species. The measured ion intensity ratios can differ from the actual concentration ratios by as much as 2 orders of magnitude. It is proposed that the higher ionization efficiency of unfolded proteins is due to their partially hydrophobic character, which results in a larger surface activity and facilitates protein transfer into ion-producing progeny droplets. Conversely, natively folded proteins have a lower affinity for the air/liquid interface, such that ionization of these conformers is suppressed. The extent of ion suppression is strongly dependent on the experimental conditions such as flow rate and protein concentration, which determine if ESI occurs in a charge deficient or a charge surplus regime. These aspects should be taken into account for the design of ESI-MS-based protein folding experiments and for studies that use ion intensity ratios for the determination of protein-ligand binding affinities.     

An Adaptation of Kubista's Method for Spectral Curve Deconvolution

A chemometric approach to spectral curve deconvolution is described, evaluated, and applied to micellar systems. The technique is based on the method of principal component analysis of a spectral matrix followed by transformation of the abstract vectors into real spectra and concentrations. The approach reported here is similar to that of Kubista et al. (Anal. Chem. 1993, 65, 994-998). In the present study, however, more spectral information is known about the system of interest. This information is included in the deconvolution, which should, in general, increase the reliability of the method. From this method we obtain very reliable (noise-insensitive) λ(max) values of indicator molecules in the micellar pseudophase free from contributions of the indicator in the aqueous phase. The water-to-micelle partition coefficients are also determined. The effects of noise and the extent of indicator partitioning on the reliability of the method are evaluated using model data. The application of the method to the study of eight indicators in a prototypical micellar system (sodium dodecyl sulfate) is presented. Extension of the method to other types of chemical studies such as the determination of kinetic rate constants and product spectra is briefly discussed.     

On the formation of highly charged gaseous ions from unfolded proteins by electrospray ionization

Electrospray ionization (ESI) of native proteins results in a narrow distribution of low protonation states. ESI for these folded species proceeds via the charged residue mechanism. In contrast, ESI of unfolded proteins yields a wide distribution of much higher charge states. The current work develops a model that can account for this effect. Recent molecular dynamics simulations revealed that ESI for unfolded polypeptide chains involves protein ejection from nanodroplets, representing a type of ion evaporation mechanism (IEM). We point out the analogies between this IEM, and the dissociation of gaseous protein complexes after collisional activation. The latter process commences with unraveling of a single subunit, in concert with Coulombically driven proton transfer. The subunit then separates from the residual complex as a highly charged ion. We propose that similar charge equilibration events accompany the IEM of unfolded proteins, thereby causing the formation of high ESI charge states. A bead chain model is used for examining how charge is partitioned as protein and droplet separate. It is shown that protein ejection from differently sized ESI droplets generates a range of protonation states. The predicted behavior agrees well with experimental data.     

Fluorescence-based transient state monitoring for biomolecular spectroscopy and imaging

To increase read-out speed, sensitivity or specificity, an often applied strategy in fluorescence-based biomolecular spectroscopy and imaging is to simultaneously record two or more of the fluorescence parameters: intensity, lifetime, polarization or wavelength. This review highlights how additional, to-date largely unexploited, information can be extracted by monitoring long-lived, photo-induced transient states of organic dyes and their dynamics. Two major approaches are presented, where the transient state information is obtained either from fluorescence fluctuation analysis or by recording the time-averaged fluorescence response to a time-modulated excitation. The two approaches combine the detection sensitivity of the fluorescence signal with the environmental sensitivity of the long-lived transient states. For both techniques, proof-of-principle experiments are reviewed, and advantages, limitations and possible applications for biomolecular cellular biology studies are discussed.     

Charger: combination of signal processing and statistical learning algorithms for precursor charge-state determination from electron-transfer dissociation spectra

Tandem mass spectrometry in combination with liquid chromatography has emerged as a powerful tool for characterization of complex protein mixtures in a high-throughput manner. One of the bioinformatics challenges posed by the mass spectral data analysis is the determination of precursor charge when unit mass resolution is used for detecting fragment ions. The charge-state information is used to filter database sequences before they are correlated to experimental data. In the absence of the accurate charge state, several charge states are assumed. This dramatically increases database search times. To address this problem, we have developed an approach for charge-state determination of peptides from their tandem mass spectra obtained in fragmentations via electron-transfer dissociation (ETD) reactions. Protein analysis by ETD is thought to enhance the range of amino acid sequences that can be analyzed by mass spectrometry-based proteomics. One example is the improved capability to characterize phosphorylated peptides. Our approach to charge-state determination uses a combination of signal processing and statistical machine learning. The signal processing employs correlation and convolution analyses to determine precursor masses and charge states of peptides. We discuss applicability of these methods to spectra of different charge states. We note that in our applications correlation analysis outperforms the convolution in determining peptide charge states. The correlation analysis is best suited for spectra with prevalence of complementary ions. It is highly specific but is dependent on quality of spectra. The linear discriminant analysis (LDA) approach uses a number of other spectral features to predict charge states. We train LDA classifier on a set of manually curated spectral data from a mixture of proteins of known identity. There are over 5000 spectra in the training set. A number of features, pertinent to spectra of peptides obtained via ETD reactions, have been used in the training. The loading coefficients of LDA indicate the relative importance of different features for charge-state determination. We have applied our model to a test data set generated from a mixture of 49 proteins. We search the spectra with and without use of the charge-state determination. The charge-state determination helps to significantly save the database search times. We discuss the cost associated with the possible misclassification of charge states.     

Characterizing the structures and folding of free proteins using 2-D gas-phase separations: observation of multiple unfolded conformers

Understanding the 3-D structure and dynamics of proteins and other biological macromolecules in various environments is among the central challenges of chemistry. Electrospray ionization can often transfer ions from solution to gas phase with only limited structural distortion, allowing their profiling using mass spectrometry and other gas-phase approaches. Ion mobility spectrometry (IMS) can separate and characterize macroion conformations with high sensitivity and speed. However, IMS separation power is generally insufficient for full resolution of major structural variants of protein ions and elucidation of their interconversion dynamics. Here we report characterization of macromolecular conformations using field asymmetric waveform IMS (FAIMS) coupled to conventional IMS in conjunction with mass spectrometry. The collisional heating of ions in the electrodynamic funnel trap between FAIMS and IMS stages enables investigating the structural evolution of particular isomeric precursors as a function of the intensity and duration of activation that can be varied over large ranges. These new capabilities are demonstrated for ubiquitin and cytochrome c, two common model proteins for structure and folding studies. For nearly all charge states, two-dimensional FAIMS/IMS separations distinguish many more conformations than either FAIMS or IMS alone, including some with very low abundance. For cytochrome c in high charge states, we find several abundant "unfolded" isomer series not distinguishable by IMS, possibly corresponding to different "string of beads" geometries. The unfolding of specific ubiquitin conformers selected by FAIMS has been studied by employing their heating in the FAIMS/IMS interface.     

Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualization of biomarker changes in 1H NMR spectroscopic metabonomic studies

In general, applications of metabonomics using biofluid NMR spectroscopic analysis for probing abnormal biochemical profiles in disease or due to toxicity have all relied on the use of chemometric techniques for sample classification. However, the well-known variability of some chemical shifts in 1H NMR spectra of biofluids due to environmental differences such as pH variation, when coupled with the large number of variables in such spectra, has led to the situation where it is necessary to reduce the size of the spectra or to attempt to align the shifting peaks, to get more robust and interpretable chemometric models. Here, a new approach that avoids this problem is demonstrated and shows that, moreover, inclusion of variable peak position data can be beneficial and can lead to useful biochemical information. The interpretation of chemometric models using combined back-scaled loading plots and variable weights demonstrates that this peak position variation can be handled successfully and also often provides additional information on the physicochemical variations in metabonomic data sets.     

On-line monitoring of the density of linear low-density polyethylene in a real plant by near-infrared spectroscopy and chemometrics

This paper reports on-line monitoring of the density of linear low-density polyethylene (LLDPE) by near-infrared (NIR) spectroscopy and chemometrics. The on-line monitoring was carried out not only in a laboratory but also in a real plant. We composed an on-line monitoring system for molten polymers consisting of a Fourier transform near-infrared (FT-NIR) spectrometer, input/output (I/O) module, a personal computer, and a sampling cell that we developed. We first compared NIR spectra of LLDPE in the solid and melt states and then developed calibration models that predict the density using partial least squares regression (PLS). The sample sets for developing prediction models were collected for three months at the plant, and the density of LLDPE was continuously monitored on-line for another three months using the model. The standard error of prediction (SEP) for the on-line monitoring of the density of LLDPE at the plant was +/-2.1 mg/cm(3) (range: 0.91-0.95 g/cm(3)).     

Quantitation and facilitated de novo sequencing of proteins by isotopic N-terminal labeling of peptides with a fragmentation-directing moiety

We describe a method for comparative quantitation and de novo peptide sequencing of proteins separated either by standard chromatographic methods or by one- and two-dimensional polyacrylamide gel electrophoresis. The approach is based on the use of an isotopically labeled reagent to quantitate (by mass spectrometry) the ratio of peptides from digests of a protein being expressed under different conditions. The method allows quantitation of the changes occurring in spots or bands that contain more than one protein and has a greater dynamic range than most staining methods. Since the reagent carries a fixed positive charge under acidic conditions and labels only the N-terminal of peptides, the interpretation of tandem mass spectra to obtain sequence information is greatly simplified. The sequences can easily be extracted for homology searches instead of using indirect mass spectral-based searches and are independent of posttranslational modifications.     

Gas-phase compaction and unfolding of protein structures

Ion-mobility mass spectrometry is emerging as a powerful tool for studying the structures of less established protein assemblies. The method provides simultaneous measurement of the mass and size of intact protein assemblies, providing information not only on the subunit composition and network of interactions but also on the overall topology and shape of protein complexes. However, how the experimental parameters affect the measured collision cross-sections remains elusive. Here, we present an extensive systematic study on a range of proteins and protein complexes with differing sizes, structures, and oligomerization states. Our results indicate that the experimental parameters, T-wave height and velocity, influence the determined collision cross-section independently and in opposite directions. Increasing the T-wave height leads to compaction of the protein structures, while higher T-wave velocities lead to their expansion. These different effects are attributed to differences in energy transmission and dissipation rates. Moreover, by analyzing proteins in their native and denatured states, we could identify the lower and upper boundaries of the collision cross-section, which reflect the "maximally packed" and "ultimately unfolded" states. Together, our results provide grounds for selecting optimal experimental parameters that will enable preservation of the nativelike conformation, providing structural information on uncharacterized protein assemblies.     

High-sensitivity stark spectroscopy obtained by surface plasmon resonance measurement

The effect (Stark effect) of an applied electric field on the electronic states of molecular adsorbates was studied by measuring surface plasmon resonance (SPR) as a function of the wavelength of the incident light that excites the SPR. Using the Kramers-Kronig relation, Stark spectra comparable to those obtained with conventional methods were extracted from the electric field-induced SPR angular shift for several organic adsorbates. Because this method relies on detecting the SPR angular shift that can be measured precisely, high-sensitivity Stark spectroscopy can be achieved. In addition, the adsorbate coverage information can be determined from the SPR angular shift upon molecular adsorption.     

Dissociation of multiple protein ion charge states following a single gas-phase purification and concentration procedure

The formation of a range of precursor ion charge states from a single concentrated and purified charge state, followed by activation of each charge state, is introduced as a means to obtain more protein structural information than is available from dissociation of a single charge state alone. This approach is illustrated using off-resonance collisional activation of the [M + 8H]8+ to [M + 6H]6+ precursor ions of the bacteriophage MS2 viral coat protein following concentration and purification of the [M + 8H]8+ charge state. This range of charge states was selected on the basis of an ion trap collisional activation study of the effects of precursor ion charge state on the dissociation of the [M + 12H]12+ to [M + 5H]5+ ions. Gas-phase ion/ion proton-transfer reactions and the ion parking technique were applied to purify and concentrate selected precursor ion charge states as well as to simplify the product ion spectra. The high-charge-state ions fragment preferentially at the N-terminal side of proline residues while the product ion spectra of the lowest charge states investigated are dominated by C-terminal aspartic acid cleavages. Maximum structural information is obtained by fragmentation of the intermediate-charge states.