UV resonance Raman (UVRR) spectroscopy is used to probe changes in vibrational structure associated with cation–π interactions for the most prevalent amino acid π –donor, tryptophan. The model compound studied here is a diaza crown ether with two indole substituents. In the presence of sodium or potassium sequestered in the crown ether, or a protonated diaza group on the compound, the indole moieties participate in a cation–π interaction in which the pyrrolo group acts as the primary π-donor. Systematic shifts in relative intensity in the 760–780 cm−1 region are observed upon formation of this cation–π interaction; we propose that these modifications reflect shifts of the delocalized, ring-breathing W18 and hydrogen-out-of-plane (HOOP) vibrational modes in this spectral region. The observed changes are attributed to perturbations of the π-electron density as well as of normal modes that involve large displacement of the hydrogen atom on the C2 position of the pyrrole ring. Modest variations in the UVRR spectra for the three complexes studied here are correlated to differences in cation–π strength. Specifically, the UVRR spectrum of the sodium-bound complex differs from those of the potassium-bound or protonated-diaza complexes, and may reflect the observation that the C2 hydrogen atom in the sodium-bound complex exhibits the greatest perturbation relative to the other species. Normal modes sensitive to hydrogen-bonding, such as the tryptophan W10, W9, and W8 modes, also undergo shifts in the presence of the salts. These shifts reflect the strength of interaction of the indole N–H group with the iodide or hexafluorophosphate counteranion. The current observation that the W18 and HOOP normal mode regions of the indole crown ether compound are sensitive to cation–pyrrolo π interactions suggests that this region may provide reliable spectroscopic evidence of these important interactions in proteins.
tryptophan; noncovalent interactions; vibrational spectroscopy
Aromatic interactions are important stabilizing forces in proteins but are difficult to detect in the absence of high-resolution structures. Ultraviolet resonance Raman spectroscopy is used to probe the vibrational signatures of aromatic interactions in TrpZip2, a synthetic β-hairpin peptide that is stabilized by edge-to-face and face-to-face tryptophan π-π interactions. The vibrational markers of isolated edge-to-face π-π interactions are investigated in the related β-hairpin peptide W2W11. The bands that comprise the Fermi doublet exhibit systematic shifts in position and intensity for TrpZip2 and W2W11 relative to the model peptide, W2W9, which does not form aromatic interactions. Additionally, hypochromism of the Bb absorption band of tryptophan in TrpZip2 leads to a decrease in the relative Raman cross-sections of Bb-coupled Raman bands. These results reveal spectral markers for stabilizing tryptophan π-π interactions and indicate that ultraviolet resonance Raman may be an important tool for the characterization of these biological forces.
noncovalent interactions; fluorescence; exciton; Fermi doublet; β-hairpin
The cytochromes P450 (CYPs) are heme proteins responsible for the oxidation of xenobiotics and pharmaceuticals and the biosynthesis of essential steroid products. In all cases, substrate binding initiates the enzymatic cycle, converting ferric low spin (LS) to high-spin (HS), with the efficiency of the conversion varying widely for different substrates, so documentation of this conversion for a given substrate is an important objective. Resonance Raman (rR) spectroscopy can effectively yield distinctive frequencies for the ν3 “spin state marker” bands. Here, employing a reference cytochrome P450 (CYP101), the intensities of the ν3 modes (ILS) and (IHS) relative to an internal standard (sodium sulfate) yield relative populations for the two spin states; i.e., a value of 1.24 was determined for the ratio of the relative cross sections for the ν3 modes. Use of this value was then shown to permit a reliable calculation of relative populations of the two spin states from rR spectra of several other Cytochromes P450. The importance of this work is that, using this information, it is now possible to conveniently document by rR the spin state population without conducting separate experiments requiring different analytical methods, instrumentation and additional sample.
Cytochrome P450; Raman; spin state
Gout is a disease process where the nucleation and growth of crystals in the synovial fluid of joints elicit painful arthritis-like symptoms. Raman spectroscopy is evolving as a potential diagnostic tool in identifying such crystals; however, attainment of sufficient Raman signal while overcoming the background fluorescence remains as a major challenge. The current study focused on assessing whether excitation in 532–700 nm range will provide greater signal intensity than the standard 785 nm while not being impeded by background fluorescence. We characterized the fluorescence spectra, absorption spectra and Raman spectra of synovial fluid from patients who presented “gout-like symptoms” (symptomatic) and controls (asymptomatic). A digestion and filtration method was developed to isolate crystals from synovial fluid while reducing the organic burden. Spectral profile and photobleaching dynamics during Raman spectroscopy were observed under an excitation wavelength range spanning 532 to 785 nm. Absorbance and fluorescence profiles indicated the digestion and filtration worked effectively to extract crystals from symptomatic synovial fluid without introducing additional fluorescence. Raman spectral analyses at 532 nm, 660 nm, 690 nm and 785 nm indicated that both asymptomatic and symptomatic samples had significant levels of fluorescence at excitation wavelengths below 700 nm, which either hindered the collection of Raman signal or necessitated prolonged durations of photobleaching. Raman-based diagnostics were more feasible at the longest excitation wavelength of 785 nm without employing photobleaching. This study further demonstrated that a near-infrared OEM based lower-cost Raman system at 785 nm excitation has sufficient sensitivity to identify crystals isolated from the synovial fluid. In conclusion, while lower excitation wavelengths provide greater signal, the fluorescence necessitates near-infrared wavelengths for Raman analysis of crystal species observed in synovial aspirates.
Raman spectroscopy; fluorescence; absorbance; synovial fluid; monosodium urate monohydrate
Plasmonic gold nanostars offer a new platform for Surface-Enhanced Raman Scattering (SERS). However, due to the presence of organic surfactant on the nanoparticles, SERS characterization and application of nanostar ensembles in solution have been challenging. Here we applied our newly developed surfactant-free nanostars for SERS characterization and application. The SERS enhancement factors (EF) of silver spheres, gold spheres and nanostars of similar sizes and concentration were compared. Under 785 nm excitation, nanostars and silver spheres have similar EF, and both are much stronger than gold spheres. Having plasmon matching the incident energy and multiple “hot spots” on the branches bring forth strong SERS response without the need to aggregate. Intracellular detection of silica-coated SERS-encoded nanostars was also demonstrated in breast cancer cells. The non-aggregated field enhancement makes the gold nanostar ensemble a promising agent for SERS bioapplications.
Gold nanoparticle; nanostars; SERS; in vitro; silica
Raman spectroscopy can differentiate the spectral fingerprints of many molecules, resulting in potentially high multiplexing capabilities of Raman-tagged nanoparticles. However, accurate quantitative unmixing of Raman spectra is challenging because of potential overlaps between Raman peaks from each molecule as well as slight variations in the location, height and width of the very narrow peaks. If not accounted for properly, even minor fluctuations in the spectra may produce significant error which will ultimately result in poor unmixing accuracy. The objective of our study was to develop and validate a mathematical model of the Raman spectra of nanoparticles to unmix the contributions from each nanoparticle allowing simultaneous quantitation of several nanoparticle concentrations during sample characterization.
We developed and evaluated an algorithm for quantitative unmixing of the spectra, called Narrow Peak Spectral Algorithm (NPSA) . Using NPSA, we were able to successfully unmix Raman spectra from up to 7 Raman nanoparticles after correcting for the spectral variations of 30% in intensity and shifts in peak locations of up to 10 cm−1 which is equivalent to 50% of the full width at half maximum (FWHM). We compared the performance of NPSA to the conventional least squares analysis (LS), error in NPSA is approximately 50% lower than LS. The error in estimating the relative contributions of each nanoparticle using NPSA are in the range of 10-16% for equal ratios and 13-19% for unequal ratios for unmixing of 7 composite organic – inorganic nanoparticles (COINs) whereas the errors using the traditional least squares approach were in the range of 25-38% for equal ratios and 45-68% for unequal ratios. Here, we report for the first time, the quantitative unmixing of 7 nanoparticles with maximum RMS % error less than 20%.
Raman Spectroscopy; Quantitative Unmixing; COINs; Variability; Least Squares; Multiplexing
We report an ab-initio simulation study of the ultrafast broad bandwidth ultraviolet (UV) stimulated resonance Raman spectra (SRRS) of L-tyrosine, L-tryptophan and trans-L-tryptophan-L-tyrosine (WY) dipeptide. Two-pulse one-dimensional (1D) SRRS and three-pulse 2D SRRS that reveal inter- and intra-residue vibrational coorelations are simulated using electronically resonant or preresonant pulse configurations that select the Raman signal and discriminate against excited state pathways. Multimode effects are incorporated via the cumulant expansion. The 2D SRRS technique is more sensitive to residue couplings than spontaneous Raman.
4-Hydroxybenzoyl-CoA (4-HB-CoA) thioesterase from Arthrobacter is the final enzyme catalyzing the hydrolysis of 4-HB-CoA to produce coenzyme A and 4-hydroxybenzoic acid in the bacterial 4-chlorobenzoate dehalogenation pathway. Using a mutation E73A that blocks catalysis, stable complexes of the enzyme and its substrate can be analyzed by Raman difference spectroscopy. Here we have used Raman difference spectroscopy, in the non-resonance regime, to characterize 4-HB-CoA bound in the active site of the E73A thioesterase. In addition we have characterized complexes of the wild-type enzyme complexed with the unreactive substrate analog 4-hydroxyphenacyl-CoA (4-HP-CoA). Both sets of complexes show evidence for two forms of the ligand in the active site, one population has the 4-hydroxy group protonated, 4-OH, while the second has the group as the hydroxide, 4-O−. For bound 4-HP-CoA X-ray data show that glutamate 78 is close to the 4-OH in the complex and it is likely that this is the proton acceptor for the 4-OH proton. Although the pKa of the 4-OH group on the free substrate in aqueous solution is 8.6, the relative populations of ionized and neutral 4-HB-CoA bound to E73A remain invariant between pH 7.3 and pH 9.8. The invariance with pH suggests that the 4-OH and the -COO− of E78 constitute a tightly coupled pair where their separate pKas lose their individual qualities. Narrow band profiles are seen in the C=O double bond and C-S regions suggesting that the hydrolyzable thioester group is rigidly bound in the active site in a syn gauche conformation.
Raman difference spectroscopy; thioesterase; ionization; conformation; enzyme-substrate complex
The characterisation of stem cells is of vital importance to regenerative medicine. Failure to separate out all stem cells from differentiated cells before therapies can result in teratomas – tumours of multiple cell types. Typically, characterisation is performed in a destructive manner with fluorescent assays. A truly non-invasive method of characterisation would be a major breakthrough in stem cell-based therapies. Raman spectroscopy has revealed that DNA and RNA levels drop when a stem cell differentiates into other cell types, which we link to a change in the relative sizes of the nucleus and cytoplasm. We also used Raman spectroscopy to investigate the biochemistry within an early embryo, or blastocyst, which differs greatly from colonies of embryonic stem cells. Certain cell types that differentiate from stem cells can be identified by directly imaging the biochemistry with CARS microscopy; examples presented are hydroxyapatite – a precursor to bone, and lipids in adipocytes.
Raman spectroscopy; CARS microscopy; stem cells; live cells; differentiation
Evidence for the widespread occurrence of extraterrestrial halite, particularly on Mars, has led to speculations on the possibility of halophilic microbial forms of life; these ideas have been strengthened by reports of viable haloarchaea from sediments of geological age (millions of years). Raman spectroscopy, being a sensitive detection method for future astrobiological investigations onsite, has been used in the current study for the detection of nine different extremely halophilic archaeal strains which had been embedded in laboratory-made halite crystals in order to simulate evaporitic conditions. The cells accumulated preferentially in tiny fluid inclusions, in simulation of the precipitation of salt in natural brines. FT-Raman spectroscopy using laser excitation at 1064 nm and dispersive micro Raman spectroscopy at 514.5 nm were applied. The spectra showed prominent peaks at 1507, 1152 and 1002 cm−1 which are attributed to haloarchaeal C50 carotenoid compounds (mainly bacterioruberins). Their intensity varied from strain to strain at 1064-nm laser excitation. Other distinguishable features were peaks due to peptide bonds (amide I, amide III) and to nucleic acids. No evidence for fatty acids was detected, consistent with their general absence in all archaea.
These results contribute to a growing database on Raman spectra of terrestrial microorganisms from hypersaline environments and highlight the influence of the different macromolecular composition of diverse strains on these spectra.
Raman spectroscopy; extremely halophilic archaea; halite; astrobiology; fluid inclusions; carotenoids; bacterioruberins; Martian subsurface
Raman spectroscopy has the potential to differentiate among the various stages leading to high-grade cervical cancer such as normal, squamous metaplasia, and low-grade cancer. For Raman spectroscopy to successfully differentiate among the stages, an applicable statistical method must be developed. Algorithms like linear discriminant analysis (LDA) are incapable of differentiating among three or more types of tissues. We developed a novel statistical method combining the method of maximum representation and discrimination feature (MRDF) to extract diagnostic information with sparse multinomial logistic regression (SMLR) to classify spectra based on nonlinear features for multiclass analysis of Raman spectra. We found that high-grade spectra classified correctly 95% of the time; low-grade data classified correctly 74% of the time, improving sensitivity from 92 to 98% and specificity from 81 to 96% suggesting that MRDF with SMLR is a more appropriate technique for categorizing Raman spectra. SMLR also outputs a posterior probability to evaluate the algorithm’s accuracy. This combined method holds promise to diagnose subtle changes leading to cervical cancer.
Raman spectroscopy; optical diagnosis; cervix; dysplasia
The incorporation of unnatural amino acids into proteins that act as spectroscopic probes can be used to study protein structure and function. One such probe is 4-cyanophenylalanine (PheCN), the nitrile group of which has a stretching mode that occurs in a region of the vibrational spectrum that does not contain any modes from the usual components of proteins and the wavenumber is sensitive to the polarity of its environment. In this work we evaluate the potential of UV resonance Raman spectroscopy for monitoring the sensitivity of the νC≡N band of PheCN incorporated into proteins to the protein environment. Measurement of the Raman excitation profile of PheCN showed that considerable resonance enhancement of the Raman signal was obtained using UV excitation and the best signal-to-noise ratios were obtained with excitation wavelengths of 229 and 244 nm. The detection limit for PheCN in proteins was ~10 μM, approximately a hundred-fold lower than the concentrations used in IR studies, which increases the potential applications of PheCN as a vibrational probe. The wavenumber of the PheCN νC≡N band was strongly dependent on the polarity of its environment, when the solvent was changed from H2O to THF it decreased by 8 cm−1. The presence of liposomes caused a similar though smaller decrease in νC≡N for a peptide, mastoparan X, modified to contain PheCN. The selectivity and sensitivity of resonance Raman spectroscopy of PheCN mean that it can be a useful probe of intra- and intermolecular interactions in proteins and opens the door to its application in the study of protein dynamics using time-resolved resonance Raman spectroscopy.
4-cyanophenylalanine; UV Raman spectroscopy; unnatural amino acid; nitrile
A principal component analysis (PCA) based on the sign of the second derivative of the surface enhanced Raman spectroscopy (SERS) spectrum obtained on in-situ grown Au cluster covered SiO2 substrates results in improved reproducibility and enhanced specificity for bacterial diagnostics. The barcode generated clustering results are systematically compared to those obtained from corresponding spectral intensities, first derivatives and second derivatives for the SERS spectra of closely related cereus group Bacillus strains. PCA plots and corresponding hierarchical cluster analysis (HCA) dendrograms illustrate the improved bacterial identification resulting from the barcode spectral data reduction. Supervised DFA plots result in slightly improved group separation but show more susceptibility to false positive classifications than the corresponding PCA contours. In addition, this PCA treatment is used to highlight the enhanced bacterial species specificity observed for SERS as compared to normal bulk (non-SERS) Raman spectra. The identification algorithm described here is critical for the development of SERS microscopy as a rapid, reagentless, portable diagnostic of bacterial pathogens.