Adding dynamics to structure/function studies in microbiology two-dimensional infrared spectroscopy

Microbiology is a pioneering discipline. Many of the fundamental processes of biology were first elucidated in microbial systems - deciphering the genetic code, the one gene-one enzyme hypothesis, the mRNA hypothesis, the first genome sequences, and many more key biological breakthroughs were all the result of microbiologists! In an age where interdisciplinary projects are encouraged it is easy to be cynical. However, true collaborations between biologists and physicists can lead to fascinating insight into biological systems, especially when exciting new techniques can be applied to biology

Understanding 2D-IR Spectra of Hydrogenases: A Descriptive and Predictive Computational Study

[NiFe] hydrogenases are metalloenzymes that catalyze the reversible cleavage of dihydrogen (H2), a clean future fuel. Understanding the mechanism of these biocatalysts requires spectroscopic techniques that yield insights into the structure and dynamics of the [NiFe] active site. Due to the presence of CO and CN− ligands at this cofactor, infrared (IR) spectroscopy represents an ideal technique for studying these aspects, but molecular information from linear IR absorption experiments is limited. More detailed insights can be obtained from ultrafast nonlinear IR techniques like IRpump-IRprobe and two-dimensional (2D-)IR spectroscopy. However, fully exploiting these advanced techniques requires an in-depth understanding of experimental observables and the encoded molecular information. To address this challenge, we present a descriptive and predictive computational approach for the simulation and analysis of static 2D-IR spectra of [NiFe] hydrogenases and similar organometallic systems. Accurate reproduction of experimental spectra from a first-coordination-sphere model suggests a decisive role of the [NiFe] core in shaping the enzymatic potential energy surface. We also reveal spectrally encoded molecular information that is not accessible by experiments, thereby helping to understand the catalytic role of the diatomic ligands, structural differences between [NiFe] intermediates, and possible energy transfer mechanisms. Our studies demonstrate the feasibility and benefits of computational spectroscopy in the 2D-IR investigation of hydrogenases, thereby further strengthening the potential of this nonlinear IR technique as a powerful research tool for the investigation of complex bioinorganic molecules

Using experimental and computational energy equilibration to understand hierarchical self-assembly of Fmoc-dipeptide amphiphiles

Despite progress, a fundamental understanding of the relationships between the molecular structure and self-assembly configuration of Fmoc-dipeptides is still in its infancy. In this work, we provide a combined experimental and computational approach that makes use of free energy equilibration of a number of related Fmoc-dipeptides to arrive at an atomistic model of Fmoc-threonine-phenylalanine-amide (Fmoc-TF-NH2) which forms twisted fibres. By using dynamic peptide libraries where closely related dipeptide sequences are dynamically exchanged to eventually favour the formation of the thermodynamically most stable configuration, the relative importance of C-terminus modifications (amide versus methyl ester) and contributions of aliphatic versus aromatic amino acids (phenylalanine F vs. leucine L) is determined (F > L and NH2 > OMe). The approach enables a comparative interpretation of spectroscopic data, which can then be used to aid the construction of the atomistic model of the most stable structure (Fmoc-TF-NH2). The comparison of the relative stabilities of the models using molecular dynamic simulations and the correlation with experimental data using dynamic peptide libraries and a range of spectroscopy methods (FTIR, CD, fluorescence) allow for the determination of the nanostructure with atomistic resolution. The final model obtained through this process is able to reproduce the experimentally observed formation of intertwining fibres for Fmoc-TF-NH2, providing information of the interactions involved in the hierarchical supramolecular self-assembly. The developed methodology and approach should be of general use for the characterization of supramolecular structures

2D-IR spectroscopy of proteins in H2O – a perspective

The form of the amide I infrared absorption band provides a sensitive probe of the secondary structure and dynamics of proteins in the solution phase. However, the frequency coincidence of the amide I band with the bending vibrational mode of H2O has necessitated the widespread use of deuterated solvents. Recently, it has been demonstrated that ultrafast 2D-IR spectroscopy allows the detection of the protein amide I band in H2O-based fluids, meaning that IR methods can now be applied to study proteins in physiologically relevant solvents. In this perspective, we describe the basis of the 2D-IR method for observing the protein amide I band in H2O and show how this development has the potential to impact on areas ranging from our fundamental appreciation of protein structural dynamics to new applications for 2D-IR spectroscopy in the analytical and biomedical sciences. In addition, we discuss how the spectral response of water, rather than being a hindrance, now provides a basis for new approaches to data pre-processing, standardisation of 2D-IR data collection and signal quantification. Ultimately, we visualise a direction of travel towards the creation of 2D-IR spectral libraries that can be linked to advanced computational methods for use in high-throughput protein screening and disease diagnosis

Shining a light on clinical spectroscopy : translation of diagnostic IR, 2D-IR and Raman spectroscopy towards the clinic

In recent years, the application of vibrational spectroscopy in biomedical research has rapidly expanded; covering aspects of pharmaceutical development, to point-of-care technologies. Vibrational spectroscopy techniques such as Fourier-transform IR (FTIR), and Raman spectroscopy have been at the forefront of this movement, with their complementary information able to shine light onto a range of medical applications. As a relative newcomer to biomedical applications, two-dimensional (2D)-IR is also gaining traction in the field. Here we describe the recent development of these techniques as analytical tools in medical science, and their relative advancements towards the clinic

2D-infrared spectroscopy of proteins in water : using the solvent thermal response as an internal standard

Ultrafast two-dimensional infrared (2D-IR) spectra can now be obtained in a matter of seconds, opening up the possibility of high-throughput screening applications of relevance to the biomedical and pharmaceutical sectors. Determining quantitative information from 2D-IR spectra recorded on different samples and different instruments is however made difficult by variations in beam alignment, laser intensity, and sample conditions. Recently, we demonstrated that 2D-IR spectroscopy of the protein amide I band can be performed in aqueous (H2O) rather than deuterated (D2O) solvents, and we now report a method that uses the magnitude of the associated thermal response of H2O as an internal normalization standard for 2D-IR spectra. Using the water response, which is temporally separated from the protein signal, to normalize the spectra allows significant reduction of the impact of measurement-to-measurement fluctuations on the data. We demonstrate that this normalization method enables creation of calibration curves for measurement of absolute protein concentrations and facilitates reproducible difference spectroscopy methodologies. These advances make significant progress toward the robust data handling strategies that will be essential for the realization of automated spectral analysis tools for large scale 2D-IR screening studies of protein-containing solutions and biofluids

Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology

Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical tech- nique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy carries a degree of morbidity and mortality and on occasion may even be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm−1. To begin development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random Forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spec- tral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Fur- thermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is import to allow future clinical translation and enables IR to achieve its potential

Long-range vibrational dynamics are directed by Watson-Crick base-pairing in duplex DNA

Ultrafast two-dimensional infrared (2D-IR) spectroscopy of a 15-mer A-T DNA duplex in solution has revealed structure-dependent vibrational coupling and energy transfer processes linking bases with the sugar-phosphate backbone. Duplex melting induces significant changes in the positions of off-diagonal peaks linking carbonyl and ring-stretching vibrational modes of the adenine and thymine bases with vibrations of the phosphate group and phosphodiester linkage. These indicate that Watson-Crick hydrogen bonding and helix formation leads to a unique vibrational coupling arrangement of base vibrational modes with those of the phosphate unit. Based on observations from time-resolved 2D-IR data, we conclude that rapid energy transfer processes occur between base and backbone, mediated by additional modes located on the deoxyribose moiety within the same nucleotide. These relaxation dynamics are insensitive to duplex melting, showing that efficient intramo-lecular energy relaxation to the solvent via the phosphate groups is the key to excess energy dissipation in both single and double-stranded DNA

Measuring proteins in H2O using 2D-IR spectroscopy; pre-processing steps and applications towards a protein library

The ability of two-dimensional infrared (2D-IR) spectroscopy to measure the amide I band of proteins in H2O rather than D2O-based solvents by evading the interfering water signals has enabled in-vivo studies of proteins under physiological conditions and in biofluids. Future exploitation of 2D-IR in analytical settings, from diagnostics to protein screening, will however require comparisons between multiple datasets, necessitating control of data collection protocols to minimise measurement-to-measurement inconsistencies. Inspired by analytical spectroscopy applications in other disciplines, we describe a workflow for pre-processing 2D-IR data that aims to simplify spectral cross-comparisons. Our approach exploits the thermal water signal that is collected simultaneously with, but is temporally separated from the amide I response to guide custom baseline correction and spectral normalisation strategies before combining them with Principal Component noise reduction tools. Case studies show that application of elements of the pre-processing workflow to previously-published data enables improvements in quantification accuracy and detection limits. We subsequently apply the complete workflow in a new pilot study, testing the ability of a prototype library of 2D-IR spectra to quantify the four major protein constituents of blood serum in a single, label-free measurement.  These advances show progress towards the robust data handling strategies that will be necessary for future applications of 2D-IR for pharmaceutical or biomedical applications

Effect of oligomer length on vibrational coupling and energy relaxation in double-stranded DNA

The effect of oligomer length on the vibrational mode coupling and energy relaxation mechanisms of AT-rich DNA oligomers in double- and single-stranded conformations has been investigated using two-dimensional infrared spectroscopy. Vibrational coupling of modes of the DNA bases to the symmetric stretching vibration of the backb one phosphate group was observed for oligomers long enough to form duplex-DNA structures. The coupling was lost upon melting of the duplex. No significant effect of oligomer length or DNA secondary structure was found on either the timescale for vibrational relaxation of the base modes or the mechanism, which was consistent with a cascade process from base modes to intermediate modes, some of which are located on the deoxyribose group, and subsequently to the phosphate backbone. The study shows that vibrational coupling between base and backbone requires formation of the double-helix structure while vibrational energy management is an inherent property of the nucleotide