Time-domain THz spectroscopy reveals coupled protein-hydration dielectric response in solutions of native and fibrils of human lyso-zyme

Here we reveal details of the interaction between human lysozyme proteins, both native and fibrils, and their water environment by intense terahertz time domain spectroscopy. With the aid of a rigorous dielectric model, we determine the amplitude and phase of the oscillating dipole induced by the THz field in the volume containing the protein and its hydration water. At low concentrations, the amplitude of this induced dipolar response decreases with increasing concentration. Beyond a certain threshold, marking the onset of the interactions between the extended hydration shells, the amplitude remains fixed but the phase of the induced dipolar response, which is initially in phase with the applied THz field, begins to change. The changes observed in the THz response reveal protein-protein interactions me-diated by extended hydration layers, which may control fibril formation and may have an important role in chemical recognition phenomena

Land use change alters carbon composition and degree of decomposition of tropical peat soils

Drainage associated with land use change in tropical peatlands has increased the rate of decomposition of peat soils and contributed to CO2 emissions. Increased decomposition may result in changes in the composition of the soil organic carbon (SOC). We examined the carbon functional group composition and degree of decomposition of peat soils under five different land uses to understand the effects of changing management intensity on tropical peatland soils. Samples were collected from seven sites spanning five different land uses (forest, shrubland, fernland, revegetation, smallholder oil palm) at the Pedamaran peatland in South Sumatra, Indonesia. SOC composition, measured by Solid-state 13C Nuclear Magnetic Resonance (NMR) spectroscopy, was dominated by the alkyl carbon (C) functional group in managed peatlands. However, in the forest far from drainage canals, the SOC comprised predominantly O-alkyl C. The contributions of the functional groups ketone C, carbonyl C and O-aryl C were low and tended to occur in stable proportions throughout the soil profiles. Drainage and land use change significantly affected peat carbon chemistry. The effects were greatest under oil palm, where O-alkyl C had been depleted rapidly under aerobic conditions leading to a change in the dominant carbon functional group from O-alkyl C to alkyl C. Furthermore, our results indicate that the alkyl C:O-alkyl C ratio is a more useful and informative indicator of the degree of decomposition of peat soil than the traditionally used C:N ratio. This more nuanced understanding of the different types of carbon that make up tropical peat soils under different land uses can be applied to support peatland restoration. In particular, nutrient cycling and water availability are likely to be influenced by carbon functional group and degree of decomposition. In order to reduce fire risk and support Indonesia’s aspirations to manage the national forest estate as a net carbon sink, further research into the links between peat soil organic carbon chemistry, revegetation performance and new peat accumulation is recommended

Distinguishing epimers through raman optical activity

The Raman optical activity spectra of the epimers β-d-glucose and β-d-galactose, two monosaccharides of biological importance, have been calculated using molecular dynamics combined with a quantum mechanics/molecular mechanics approach. Good agreement between theoretical and experimental spectra is observed for both monosaccharides. Full band assignments have been carried out, which has not previously been possible for carbohydrate epimers. For the regions where the spectral features are opposite in sign, the differences in the vibrational modes have been noted and ascribed to the band sign changes

Secondary Structure and Glycosylation of Mucus Glycoproteins by Raman Spectroscopies

The major structural components of protective mucus hydrogels on mucosal surfaces are the secreted polymeric gel-forming mucins. The very high molecular weight and extensive O-glycosylation of gel-forming mucins, which are key to their viscoelastic properties, create problems when studying mucins using conventional biochemical/structural techniques. Thus, key structural information, such as the secondary structure of the various mucin subdomains, and glycosylation patterns along individual molecules, remains to be elucidated. Here, we utilized Raman spectroscopy, Raman optical activity (ROA), circular dichroism (CD), and tip-enhanced Raman spectroscopy (TERS) to study the structure of the secreted polymeric gel-forming mucin MUC5B. ROA indicated that the protein backbone of MUC5B is dominated by unordered conformation, which was found to originate from the heavily glycosylated central mucin domain by isolation of MUC5B O-glycan-rich regions. In sharp contrast, recombinant proteins of the N-terminal region of MUC5B (D1-D2-D′-D3 domains, NT5B), C-terminal region of MUC5B (D4-B-C-CK domains, CT5B) and the Cys-domain (within the central mucin domain of MUC5B) were found to be dominated by the β-sheet. Using these findings, we employed TERS, which combines the chemical specificity of Raman spectroscopy with the spatial resolution of atomic force microscopy to study the secondary structure along 90 nm of an individual MUC5B molecule. Interestingly, the molecule was found to contain a large amount of α-helix/unordered structures and many signatures of glycosylation, pointing to a highly O-glycosylated region on the mucin

Secondary Structure and Glycosylation of Mucus Glycoproteins by Raman Spectroscopies

The major structural components of protective mucus hydrogels on mucosal surfaces are the secreted polymeric gel-forming mucins. The very high molecular weight and extensive O-glycosylation of gel-forming mucins, which are key to their viscoelastic properties, create problems when studying mucins using conventional biochemical/structural techniques. Thus, key structural information, such as the secondary structure of the various mucin subdomains, and glycosylation patterns along individual molecules, remains to be elucidated. Here, we utilized Raman spectroscopy, Raman optical activity (ROA), circular dichroism (CD), and tip-enhanced Raman spectroscopy (TERS) to study the structure of the secreted polymeric gel-forming mucin MUC5B. ROA indicated that the protein backbone of MUC5B is dominated by unordered conformation, which was found to originate from the heavily glycosylated central mucin domain by isolation of MUC5B O-glycan-rich regions. In sharp contrast, recombinant proteins of the N-terminal region of MUC5B (D1-D2-D′-D3 domains, NT5B), C-terminal region of MUC5B (D4-B-C-CK domains, CT5B) and the Cys-domain (within the central mucin domain of MUC5B) were found to be dominated by the β-sheet. Using these findings, we employed TERS, which combines the chemical specificity of Raman spectroscopy with the spatial resolution of atomic force microscopy to study the secondary structure along 90 nm of an individual MUC5B molecule. Interestingly, the molecule was found to contain a large amount of α-helix/unordered structures and many signatures of glycosylation, pointing to a highly O-glycosylated region on the mucin

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p

Calculation of Raman optical activity spectra for vibrational analysis

By looking back on the history of Raman Optical Activity (ROA), the present article shows that the success of this analytical technique was for a long time hindered, paradoxically, by the deep level of detail and wealth of structural information it can provide. Basic principles of the underlying theory are discussed, to illustrate the technique's sensitivity due to its physical origins in the delicate response of molecular vibrations to electromagnetic properties. Following a short review of significant advances in the application of ROA by UK researchers, we dedicate two extensive sections to the technical and theoretical difficulties that were overcome to eventually provide predictive power to computational simulations in terms of ROA spectral calculation. In the last sections, we focus on a new modelling strategy that has been successful in coping with the dramatic impact of solvent effects on ROA analyses. This work emphasises the role of complementarity between experiment and theory for analysing the conformations and dynamics of biomolecules, so providing new perspectives for methodological improvements and molecular modelling development. For the latter, an example of a next-generation force-field for more accurate simulations and analysis of molecular behaviour is presented. By improving the accuracy of computational modelling, the analytical capabilities of ROA spectroscopy will be further developed so generating new insights into the complex behaviour of molecules

The Raman optical activity of β-D-xylose: where experiment and theory meet

Besides its applications in bioenergy and biosynthesis, β-D-xylose is a very simple monosaccharide that exhibits relatively high rigidity. As such, it provides the best basis to study the impact of different solvation shell radii on the computation of its Raman optical activity (ROA) spectrum. Indeed, this chiroptical spectroscopic technique provides exquisite sensitivity to stereochemistry, and benefits much from theoretical support for interpretation. Our simulation approach combines density functional theory (DFT) and molecular dynamics (MD) in order to efficiently account for the crucial hydration effects in the simulation of carbohydrates and their spectroscopic response predictions. Excellent agreement between the simulated spectrum and the experiment was obtained with a solvation radius of 10 Å. Vibrational bands have been resolved from the computed ROA data, and compared with previous results on different monosaccharides in order to identify specific structure–spectrum relationships and to investigate the effect of the solvation environment on the conformational dynamics of small sugars. From the comparison with ROA analytical results, a shortcoming of the classical force field used for the MD simulations has been identified and overcome, again highlighting the complementary role of experiment and theory in the structural characterisation of complex biomolecules. Indeed, due to unphysical puckering, a spurious ring conformation initially led to erroneous conformer ratios, which are used as weights for the averaging of the spectral average, and only by removing this contribution was near perfect comparison between theory and experiment achieved