Vibrational two-dimensional correlation spectroscopy (2DCOS) study of proteins

Pyrite from acid mine drainage promotes the removal of antibiotic resistance genes and mobile genetic elements in karst watershed with abundant calcium carbonate

More information is needed to fully comprehend how acid mine drainage (AMD) affects the phototransformation of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in karst water and sewage-irrigated farmland soil with abundant carbonate rocks (CaCO3) due to increasing pollution of AMD formed from pyrite (FeS2). The results showed FeS2 accelerated the inactivation of ARB with an inactivation of 8.7 log. Notably, extracellular and intracellular ARGs and mobile genetic elements (MGEs) also experienced rapid degradation. Additionally, the pH of the solution buffered by CaCO3 significantly influenced the photo-inactivation of ARB. The Fe2+ in neutral solution was present in Fe(II) coordination with strong reducing potential and played a crucial role in generating •OH (7.0 μM), which caused severe damage to ARB, ARGs, and MGEs. The •OH induced by photo-Fenton of FeS2 posed pressure to ARB, promoting oxidative stress response and increasing generation of reactive oxygen species (ROS), ultimately damaging cell membranes, proteins and DNA. Moreover, FeS2 contributed to a decrease in MIC of ARB from 24 mg/L to 4 mg/L. These findings highlight the importance of AMD in influencing karst water and sewage-irrigated farmland soil ecosystems. They are also critical in advancing the utilization of FeS2 to inactivate pathogenic bacteria.

Composition and structure analysis of different depths in the stratum corneum using confocal Raman microscopy combined with two-dimensional correlation spectroscopy

The chemical composition and structure of the stratum corneum (SC) play a crucial role in the skin barrier function. Therefore, accurately determining the SC thickness and studying the changes in lipid and keratin structure and distribution within it are key aspects of skin barrier research. Currently, there are limited analytical tools and data analysis methods available for real-time and online studies of SC composition and structural changes. In this study, we focus on depth as a perturbation and employ confocal Raman microscopy combined with moving-window two-dimensional correlation spectroscopy (MW2D) technique to investigate the SC thickness. Additionally, we employ confocal Raman microscopy combined with perturbation-correlation moving-window two-dimensional correlation spectroscopy (PCMW2D) to precisely characterize the stratification of the SC. Furthermore, the two-dimensional correlation spectroscopy (2DCOS) method is utilized to examine the content of various conformations in the keratin secondary structure within the SC, as well as the subtle interrelationships between lipid and keratin structures.

Streamlined Multi-Attribute Assessment of an Array of Clinical-Stage Antibodies: Relationship Between Degradation and Stability

Clinical antibodies are an important class of drugs for the treatment of both chronic and acute diseases. Their manufacturability is subject to evaluation to ensure product quality and efficacy. One critical quality attribute is deamidation, a non-enzymatic process that is observed to occur during thermal stress, at low or high pH, or a combination thereof. Deamidation may induce antibody instability and lead to aggregation, which may pose immunogenicity concerns. The introduction of a negative charge via deamidation may impact the desired therapeutic function (i) within the complementarity-determining region, potentially causing loss of efficacy; or (ii) within the fragment crystallizable region, limiting the effector function involving antibody-dependent cellular cytotoxicity. Here we describe a transformative solution that allows for a comparative assessment of deamidation and its impact on stability and aggregation. The innovative streamlined method evaluates the intact protein in its formulation conditions. This breakthrough platform technology is comprised of a quantum cascade laser microscope, a slide cell array that allows for flexibility in the design of experiments, and dedicated software. The enhanced spectral resolution is achieved using two-dimensional correlation, co-distribution, and two-trace two-dimensional correlation spectroscopies that reveal the molecular impact of deamidation. Eight re-engineered immunoglobulin G4 scaffold clinical antibodies under control and forced degradation conditions were evaluated for deamidation and aggregation. We determined the site of deamidation, the overall extent of deamidation, and where applicable, whether the deamidation event led to self-association or aggregation of the clinical antibody and the molecular events that led to the instability. The results were confirmed using orthogonal techniques for four of the samples.

Two-Dimensional Correlation Spectroscopy (2D-COS) Analysis of Evolving Hyperspectral Images

The evolutionary behavior is examined for heterogeneously distributed hyperspectral images of a simulated biological tissue sample comprising lipid-like and protein-like components during the aging process. Taking a simple planar average of a spectral image loses useful information about the spatially resolved nature of the data. In contrast, multivariate curve resolution (MCR) analysis of a spectral image at a given stage of aging produces a set of loadings of major component groups. Each loading represents the combined spectral contributions of a mixture of similar but not identical constituents (i.e., lipid-like and protein-like components). Temporal analysis of individual component groups using two-dimensional correlation spectroscopy (2D-COS) and MCR provides much-streamlined results without interferences from the overlapped contributions. Grouping of data into separate components also allows for the effective comparison of the parallel processes of lipid oxidation and protein denaturation involving a number of constituents using the heterocomponent 2D-COS analysis. The complex interplays of lipid constituents and protein secondary structures during the tissue aging process are unambiguously highlighted. The possibility of extending this approach to a much more general form of applications using a moving window analysis is also discussed.

Characterizing dissolved organic matter and bacterial community interactions in a river network under anthropogenic landcover

Anthropogenic landcover could rise nutrient concentrations and impact the characteristics and bioavailability of dissolved organic matter (DOM) in a river network. Exploring the interactions between DOM and microbials might be conducive to revealing biogeochemistry behaviors of organic matter. In this study, synchronous fluorescence spectra (SFS) with Gaussian band fitting and two-dimensional correlation spectroscopy (2D-COS) were employed to identify DOM fractions and reveal their interactions with bacterial communities. DOM was extracted from a river network under eco-agricultural rural (RUR), eco-residential urban (URB), eco-economical town (TOW), and eco-industrial park (IND) regions in Jiashan Plain of eastern China. The overlapping peaks observed in the SFS were successfully separated into four fractions using Gaussian band fitting, i.e., tyrosine-like fluorescence (TYLF), tryptophan-like fluorescence (TRLF), microbial humic-like fluorescence (MHLF), and fulvic-like fluorescence (FLF) materials. Across all four regions, TRLF (44.79% ± 7.74%) and TYLF (48.09% ± 8.85%) were the dominant components. Based on 2D-COS, variations of TYLF and TRLF were extremely larger than those of FLF in RUR-TOW. However, in URB-IND, the former exhibited lower variations compared to the latter. These suggested that FLF be likely derived continuously from lignin and other residue of terrestrial plant origin along the river network, and TYLF and TRLF be originated discontinuously from domestic wastewater in RUR-TOW. By high-throughput sequenced OTUs, the number of organisms in RUR-TOW could be higher than those in URB-IND, while genes associated with carbohydrate metabolism were lower in former than those in the latter. According to co-occurrence networks, microbes could promote the production of TYLF and TRLF in RUR-TOW. In contrast, microbial communities in URB-IND might contribute to decompose FLF. The obtained results could not only reveal interactions between DOM fractions and bacterial communities in the river network, but this methodology may be applied to other water bodies from different landscapes.

Rapid authentication of variants of Gastrodia elata Blume using near-infrared spectroscopy combined with chemometric methods

The variety is one of the most important factors to generate difference of chemical compositions, which unavoidably influences the quality of natural medicine. Thus, simple and rapid authentication of different variants has great academic and practical significance. In this study, the goal was achieved with the help of near infrared spectroscopy (NIR) and chemometrics by using Gastrodia elata Blume as an example. A total of 540 samples including two classes of variants and their forms were investigated as a whole. The mean spectra of samples of each class and their 2-D synchronous correlation spectra were simultaneously applied to discover the difference of chemical characteristics. After hybrid pre-processing of the first and second derivative combined with Savitzky-Golay and Norris filtering, partial least squares discrimination analysis (PLS-DA) on the basis of latent variable projection was used to assess the feasibility for classification. The results show higher prediction accuracy in both internal test set and external prediction set. In order to further improve the robustness for modeling, three methods for wavelength selection were comprehensively compared to optimize PLS-DA models, including variable importance in the projection (VIP), random frog (RF), and Monte Carlo uninformative variable elimination (MC-UVE). The prediction accuracy of combination of the 2nd derivative, Norris, MC-UVE and PLS-DA achieved to 99.11% and 98.89% corresponding to the internal test set and external prediction set, respectively. The strategies proposed in this work perform effectiveness for rapid and accurate authentication of variants of plants with high chemical complexity.

Study on depolymerization kinetics of formic acid dimers in binary mixture

In this study, polarization Raman spectra were collected for binary mixtures of formic acid/methanol and formic acid/acetonitrile with different volume fractions. The broad band of formic acid in the CO vibration region was divided into four vibration peaks, corresponding to CO symmetric and anti-symmetric stretching vibration from cyclic dimer, CO stretching from open dimer, and CO stretching from the free monomer. The experiments showed that as the volume fraction of formic acid in the binary mixture decreased, the cyclic dimer gradually converted to the open dimer, and at a volume fraction of 0.1, fully depolymerized into monomer form (free monomer, solvated monomer, and hydrogen bonding monomer clusters with solvent). The contribution percentage of the total CO stretching intensity of each structure at different concentrations was quantitatively calculated using high resolution infrared spectroscopy, and the results were consistent with the conclusions predicted by polarization Raman spectroscopy. Concentration-triggered 2D-COS synchronous and asynchronous spectra also confirmed the kinetics of formic acid diluted in acetonitrile. This work provides a spectroscopic method for studying the structure of organic compounds in solution and concentration-triggering kinetics in mixtures.

The intermolecular polar bond interaction and coupling induced spectral splitting phenomenon for a binary mixture

To explain the polarization Raman noncoincidence effect of specific polar bonds and the noncoincidence phenomenon between FT-Raman and FT-IR spectra, aggregation-induced spectral splitting theory was proposed. In this paper, the vibration splitting theory was demonstrated using two strategies: improving the spectral resolution with cryogenic matrix isolation techniques and identifying cases where the coupling splitting is large enough to be distinguishable. The monomer and dimer splitting bands of acetone were detected when cryogenically isolated by the Ar matrix. Additionally, the polarization Raman and two-dimensional infrared spectra of a β-propiolactone (PIL)/CCl₄ binary mixture were collected at room temperature, and the spectral splitting phenomenon was clearly observed. The dynamic transformation between the monomer and dimer could be achieved and detected by adjusting the PIL concentration. The observed splitting phenomenon was further confirmed by theoretical DFT calculations based on the monomer and dimer of PIL, as well as the FT-IR and FT-Raman spectra of PIL. Concentration-triggered 2D-COS synchronous and asynchronous spectra also confirmed the splitting phenomenon and the dilution kinetics of PIL/CCl₄.

Probing the interactions between amyloidogenic proteins and bio-membranes

Protein misfolding diseases (PMDs) in humans are characterized by the deposition of protein aggregates in tissues, including Alzheimer's disease, Parkinson's disease, type 2 diabetes, and amyotrophic lateral sclerosis. Misfolding and aggregation of amyloidogenic proteins play a central role in the onset and progression of PMDs, and these processes are regulated by multiple factors, especially the interaction between proteins and bio-membranes. Bio-membranes induce conformational changes in amyloidogenic proteins and affect their aggregation; on the other hand, the aggregates of amyloidogenic proteins may cause membrane damage or dysfunction leading to cytotoxicity. In this review, we summarize the factors that affect the binding of amyloidogenic proteins and membranes, the effects of bio-membranes on the aggregation of amyloidogenic proteins, mechanisms of membrane disruption by amyloidogenic aggregates, technical approaches for detecting these interactions, and finally therapeutic strategies targeting membrane damage caused by amyloidogenic proteins.

Identification of gallbladder cancer by direct near-infrared measurement of raw bile combined with two-trace two-dimensional correlation analysis

We demonstrated the utility of direct near-infrared (NIR) bile analysis for the identification of gallbladder (GB) cancer by employing two-trace two-dimensional (2T2D) correlation analysis to recognize dissimilar spectral features among diverse bile samples for potential improvement of discrimination accuracy. To represent more diverse clinical cases for reliable assessment, bile samples obtained from five normal, 44 gallstone, 25 GB polyp, six hepatocellular cancer (HCC), and eight GB cancer subjects were analyzed. Due to the altered metabolic pathways by carcinogenesis, the NIR spectral features of GB cancer samples, including intensity ratios of main peaks, were different from those of other sample groups. The differentiation of GB cancer in the principal component (PC) score domain was mediocre and subsequent discrimination accuracy based on linear discriminant analysis (LDA) was 88.5%. When 2T2D slice spectra were obtained using a reference spectrum constructed by the linear combination of the spectra of five pure representative bile metabolites and employed, the accuracy was improved to 95.6%. The sensitive recognition of dissimilar spectral features in GB cancer by 2T2D correlation analysis was responsible for the enhanced discrimination.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS), part I. Yesterday and today

This comprehensive survey review, as the first of three parts, compiles past developments and early concepts of two-dimensional correlation spectroscopy (2D-COS) and subsequent evolution, as well as its early applications in various fields for the last 35 years. It covers past review articles, books, proceedings, and numerous research papers published on 2D-COS. 2D-COS continues to evolve and grow with new significant developments and versatile applications in diverse scientific fields. The healthy, vigorous, and diverse progress of 2D-COS studies in many fields confirms that it is well accepted as a powerful analytical technique to provide the in-depth understanding of systems of interest.

Towards the identification of humic ligands associated with iron transport through a salinity gradient

Humic ligands from boreal rivers have been identified as important sources of iron-binding ligands to the coastal marine environment but remain poorly characterized. A novel method using Fourier transformed infrared spectroscopy (FTIR) was used to identify and quantify iron-binding ligands present in a boreal river in Newfoundland, Canada. 20 to 35% of the total iron load was carried through an artificial salinity gradient, and remained in solution at 35 salinity. Using FTIR combined with linear regression and 2D correlation analysis, we identified two pools of organic ligands, with different behaviour with regards to iron across the salinity gradient. The weaker ligand pool consisted of alkenes, ethers, and esters, and was found to release iron to flocculation at low salinities, and not contribute to iron transport into the marine environment. The stronger ligand group contained carboxylic acids and aliphatic functional groups. This group appears to contain two subgroups, one which was able to retain iron in the dissolved phase at 35 salinity, and another that flocculated out with iron across the salinity gradient. The strong ligands that retain iron in solution through the salinity gradient provide a much-needed source of the micronutrient to the coastal and marine environment, while the other subgroup sequesters iron and carbon in estuarine sediments. The balance between these two subgroups appears to be controlled by the hydrographic and weather conditions at the time of sampling, suggesting a dynamic ligand-iron relationship throughout the year, impacting the biogeochemical cycles of both iron and carbon in contrasting ways.

Investigations of pH-dependent dynamic properties of OmpG-16SL, an outer membrane protein G mutant by ATR-FTIR spectroscopy

In this paper, the dynamic properties of outer membrane protein G mutant (OmpG-16SL) are investigated with ATR-FTIR spectroscopy. While OmpG-WT has 14 β-strands in its structure, the mutant is designed to have 16 β-strands with the intention of creating an enlarged pore. Loop L6 is elongated by introducing six residues, two of which are negatively charged. The solvent accessibility of the OmpG-16SL mutant is compared with WT and a previously reported mutant OmpG-16S by tracking the ¹H/²H exchange kinetics in acidic and neutral buffer conditions. The exchange kinetics and dynamics in the fast and slow exchange phases are separately investigated using the 2DCOS technique, which enables the tracking of the structural changes at each phase of the exchange process. The results suggest that the mutant OmpG-16SL is equally exposed to buffer in both acidic and neutral pH conditions. Additionally, the time range in the fast phase is very short - one-tenth of that for WT - and most of the exchange is completed in this phase. This fast exchange within minutes is also indicative of the presence of highly flexible and/or unstructured regions. In all, the fast exchange rates independent of the buffer pH justify the assumption that there is an altered interaction among the charged residues, which leads to a steadily-open pore. The role of the side-chain interactions within the pore and between the loops involving the loop L6 is also discussed.

Investigation into the impact of aged microplastics on oil behavior in shoreline environments

Understanding the interactions between oil and other particles in shoreline can help determine the environmental risk and cleanup strategy after oil spill. Nevertheless, far less has been known regarding the impact of aged MPs on oil behavior in the shoreline environment. In this study, the aging course of polyethylene (PE) in shaking seawater and ultraviolet (UV) radiation conditions was investigated. The seawater aging mainly affected the physical properties of MPs, increasing its surface pores and hydrophilicity. UV aging significantly affected both the physical and chemical properties of MPs, which increased its hydrophilicity and crystallinity, decreased its mean particle size and introduced oxygen-containing functional groups onto MPs. The two-dimensional correlation spectroscopy (2D COS) analysis confirmed the evolution of oxygen-containing functional groups from C-O to CO. The effects of aged MPs on oil behavior in water-sand system were further explored. The oil remaining percentages were non-linearly changed with the increasing aging degree of MPs. The particle size of the aqueous phase after washing was inversely related to the oil remaining percentage. Further FTIR analysis revealed that C-O and C-H functional groups played an important role in the process of oil adsorbed on MPs.

Distinguishing Resonant from Non-Resonant Nonlinear Optical Processes Using Intensity-Intensity Correlation Analyses

Three-color coherent anti-Stokes Raman scattering (CARS) represents non-degenerate four wave mixing that includes both non-resonant and resonant processes, the contributions of which depend upon how the molecular vibrational modes are being excited by the input laser pulses. The scattering signal due to resonant processes builds up progressively. An advanced analytical tool to reveal this deferred resonant signal buildup phenomenon is in need. In this work, we adapt a quantitative analytical tool by introducing one-dimensional and two-dimensional intensity-intensity correlation functions in terms of a new variable (probe pulse delay) and a new perturbation parameter (probe pulse linewidth). In particular, discrete diagonal directional sums are defined here as a tool to reduce both synchronous and asynchronous two-dimensional correlation spectroscopy (2D-COS) maps down to one-dimensional plots while maintaining the valuable analytical information. Detailed analyses using the all-Gaussian coherent Raman scattering closed-form solutions and the representative experimental data for resonant and non-resonant processes are presented and compared. The present work holds a promising potential for industrial application, e.g., by extractive industries to distinguish hydrocarbons (chemically resonant substance) from water (non-resonant contaminant) by utilizing the one- and two-dimensional correlation analyses.

Multivariate curve resolution combined with estimation by cosine similarity mapping of analytical data

We developed a multivariate curve resolution (MCR) calculation combined with the mapping of cosine similarity (cos-s) for estimating multiple mixture spectra of chemicals. The cos-s map was obtained by calculating the similarities of the variation of the signal intensities at each scanning parameter, such as the wavelength. The cos-s map was utilized for the initial estimation of the spectra of pure chemicals and also for the restriction of the iterative least-squares calculation of the MCR. These calculations were performed without arbitrary parameters by introducing soft clustering to the cos-s map. The chemically meaningful initial estimation could prevent the convergence at an incorrect local minimum, which frequently happens for the wrong initial estimation of spectra far away from the real answer. Herein, we demonstrated the robustness of this calculation method by applying it for UV/Vis spectra and XRD patterns of multiple unknown chemical mixtures, whose shapes were totally different (broad overlapped peaks and multiple complicated peaks). Pure spectra/patterns were recovered as >84% consistency with the reference spectra, and <6% accuracy of the concentration ratios was demonstrated.

Diffuse reflectance infrared Fourier transform spectroscopy for a qualitative evaluation of plant leaf pigment extraction

The extraction and quantification of leaf pigments are easy, fast, and cheap procedures; on the other hand, diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy associated with chemometrics tools could offer new insights into leaf biochemical composition. We aimed to boost the classic leaf pigment quantification, adding leaf biochemical information derived from DRIFT spectroscopy + principal component analysis, using the same leaf pigment extract produced by the classical quantification method. We performed a dose-response experiment using P as the limiting nutrient, and maize (Zea mays L.) as a plant-test. After 45 d of growth, we evaluated the effects of P fertilization in total maize shoot biomass, P shoot accumulation, leaf pigment quantification by UV-Vis, and the evaluation of biochemical variations by DRIFT spectroscopy analysis associated with a chemometric approach in the same leaf extract used for pigment quantification. P fertilization raised biomass accumulation (∼7.4×), P uptake (∼2.3×), and total chlorophyll a and b contents (∼2.1×). DRIFT spectroscopy analysis of extracted pigments revealed an elevated content of proteins and polysaccharides at high P availability. At low P availability, we found a low efficiency of N metabolism suggested by the accumulation of inorganic N forms. DRIFT spectroscopy applied together with the classic leaf pigment extraction and quantification method is a novel and promising tool for plant nutrition studies as a DRIFT spectroscopy metabolic profile protocol.

Compensation of Strong Water Absorption in Infrared Spectroscopy Reveals the Secondary Structure of Proteins in Dilute Solutions

Infrared (IR) absorption spectroscopy is a powerful tool that can quantify complex biomolecules and their structural conformations. However, conventional approaches to protein analysis in aqueous solutions have been significantly challenged because the strong IR absorption of water overwhelms the limited dynamic range of the detection system and thus allows only a very short path length and a limited concentration sensitivity. Here, we demonstrate a solvent absorption compensation (SAC) approach that can improve the concentration sensitivity and extend the available path length by distinguishing the analyte signal over the full dynamic range at each wavelength. Absorption spectra without any postprocessing show good linearity from 100 to 0.1 mg/mL protein concentration, allowing a >100 times enhanced signal-to-noise ratio in the amide I band compared to the non-SAC results. We apply this method to in situ investigate the isothermal kinetics of insulin fibrillation at two clinical concentrations at 74 °C for 18 h. Simultaneous monitoring of both reactants (native forms) and products (fibrils) allows quantitative discussion of the detailed fibrillation mechanisms, which are not accessible with other single modality measurements. This simple optical technique can be applied to other absorption spectroscopies of analytes in strongly absorbing solvents, allowing for enhanced sensitivity without changing the detection system.

Developability Assessment of an Isolated CH2 Immunoglobulin Domain

The IgG C_H2 domain continues to hold promise for the development of new therapeutic entities because of its bifunctional role as a biomarker and effector protein. The need for further understanding of molecular stability and aggregation in therapeutic proteins has led to the development of a breakthrough quantum cascade laser microscope to allow for real-time comparability assessment of an array of related proteins in solution upon thermal perturbation. Our objective was to perform a comprehensive developability assessment of three similar monoclonal antibody (mAb) fragments: C_H2, C_H2s, and m01s. The C_H2 construct consists of residues Pro238 to Lys340 of the IgG1 heavy chain sequence. C_H2s has a 7-residue deletion at the N-terminus and a 16-residue C-terminal extension containing a histidine tag. The m01s construct is identical to C_H2s, except for two cysteines introduced at positions 242 and 334. A series of hyperspectral images was acquired during thermal perturbation from 28 to 60 °C for all three proteins in an array. Co-distribution and two-dimensional infrared correlation spectroscopies yielded the mechanism of aggregation and stability for these three proteins. The level of detail is unprecedented, identifying the regions within C_H2 and C_H2s that are prone to self-association and establishing the differences in stability. Furthermore, C_H2 helical segments, β-sheets, β-turns, and random coil regions were less stable than in C_H2s and m01s because of the presence of the N-terminal 3₁₀-helix and β-turn type III. The engineered disulfide bridge in m01s eliminated the self-association process and rendered this mAb fragment the most stable.

Nucleotide Adsorption on Iron(III) Oxide Nanoparticle Surfaces: Insights into Nano-Geo-Bio Interactions Through Vibrational Spectroscopy

Molecular processes at geochemical interfaces impact many environmental processes that are critical to the fate and transport of contaminants in water systems. Often these interfaces are coated with natural organic matter, oxyanions, or biological components, yet little is understood about these coatings. Herein, we are interested in better understanding the interaction of biological components with nanoscale iron oxide minerals. In particular, we use attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy to investigate the adsorption behavior of deoxyadenosine monophosphate (dAMP) on hematite nanoparticle surfaces as a function of pH and in the presence and absence of adsorbed phosphate. These results show that fewer nucleotides adsorb at higher pH. Additionally, when phosphate anions are preadsorbed, nucleotide adsorption is significantly limited due to site-blocking by adsorbed inorganic phosphate. The pH dependence provides insights into the adsorption process and the importance of electrostatic interactions. Preadsorbed phosphate affects the binding mode of dAMP, suggesting synergistic interactions between the coadsorbates. Two-dimensional correlation spectroscopy was used to further analyze the infrared spectra. Based on this analysis, a dAMP adsorption pathway onto a preadsorbed phosphate-hematite surface was proposed, suggesting the displacement of adsorbed phosphate by dAMP. Overall, this study provides some insights into geochemical-biological interactions on nanoscale iron oxide surfaces using vibrational spectroscopy.

Cellulase modified waste biomass to remove sulfamethazine from aqueous solutions

The objective of this work is to find a simple and environmentally friendly way to prepare high efficiency adsorbent from maize stover by cellulase. The characteristics of the original maize cob (MC), maize husk (MH), maize straw (MS), and its cellulase modified form (MMC, MMH and MMS) were detected by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Batch adsorption experiments indicated that the adsorption followed the pseudo-second-order kinetic model, and the adsorption capacity of sulfamethazine (SMT) to adsorbents was in order of MMC > MMS > MMH > MC > MS > MH. The adsorption isotherm data of SMT on original materials were consistent with Freundlich models, while Henry models were more suitable for the modified materials. The adsorption was affected by pH and ionic strength which demonstrated the interaction between π-π EDA and H bonds might be an important factor in the adsorption of SMT on maize stover. The results of FTIR and two-dimensional correlation spectroscopy (2D-COS) analysis further demonstrated that oxhydryl and aromatic structures in the modified maize stover could interact with SMT via H bonds and π-π EDA interaction, respectively. This work provides a green way to remove SMT from aqueous solution, and new insights into the mechanisms of adsorption of SMT on stover materials.

The molecular insights into protein adsorption on hematite surface disclosed by in-situ ATR-FTIR/2D-COS study

Proteins are of ubiquitous interest in the Life Sciences but are of interest in the Geosciences as well because of the significant role these compounds play in the biogeochemical cycling of trace and nutrient elements. Structural changes resulting from the adsorption of proteins onto mineral surfaces may alter protein biological function and other environmental interactions. Iron oxides are major sinks of a range of environmental elements including organic compounds. In this study, the adsorption of the broadly studied model protein BSA onto the hematite mineral surface was characterized as a function of pH, ionic strength, and BSA concentration using in-situ Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy. BSA lost the α-helix and gain β-sheets in the secondary structure during adsorption on hematite. BSA adsorption was maximum at pH 5, a value close to the BSA isoelectric point (~ pH 5), and lower at pH 4 and pH 7. Increasing ionic strength decreased to total BSA adsorption. Two-dimensional correlation spectroscopy analysis of the ATR-FTIR spectra revealed that higher initial BSA concentration and the consequent higher BSA surface loading enhanced BSA adsorption by protein–protein interaction, which less ordered structures changes into more compact forms decrease, hence compacting the structural arrangement and could promoting multilayers/aggregation formation on the mineral surface. The activity of enzymes following adsorption on mineral surfaces requires further study.

Glycerol's generalized two-dimensional correlation IR/NIR spectroscopy and its principal component analysis

In this manuscript, the fundamental vibration, the combination vibration and the first overtone vibration of the glycerol hydroxyl were studied by near-infrared and infrared spectroscopy. The composition and variation of hydrogen bond were analyzed by two-dimensional correlation spectroscopy and principal component analysis. The analysis revealed five types of hydroxyl and verified the existence of independent, intramolecular, as well as intermolecular, hydrogen bond hydroxyl. The principal component analysis showed that there were three main forms of glycerol association: the first and second principal components explained the majority of the spectral features, and the third was mainly the independent hydroxyl. The results provided insight into the structure of glycerol and illustrated the potential for using these tools in analyzing bonding in even more complex systems.

Kinetics and Mechanisms of Protein Adsorption and Conformational Change on Hematite Particles

Adsorption kinetics and conformational changes of a model protein, bovine serum albumin (BSA, 0.1, 0.5, or 1.0 g/L), on the surface of hematite (α-Fe₂O₃) particles in 39 ± 9, 68 ± 9, and 103 ± 8 nm, respectively, were measured using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. As the particle size increases, the amount of adsorbed BSA decreases, but the loss in the helical structure of adsorbed BSA increases due to the stronger interaction forces between adsorbed BSA and the larger particles. On 39 or 68 nm hematite particles, refolding of adsorbed BSA can be induced by protein-protein interactions, when the protein surface coverage exceeds certain critical values. Two-dimensional correlation spectroscopy (2D-COS) analysis of time-dependent ATR-FTIR spectra indicate that the increase in the amount of adsorbed BSA occurs prior to the loss in the BSA helical structure in the initial stage of adsorption processes, whereas an opposite sequence of the changes to BSA conformation and surface coverage is observed during the subsequent refolding processes. Desorption experiments show that replacing the protein solution with water can quench the refolding, but not the unfolding, of adsorbed BSA. A kinetic model was proposed to quantitatively describe the interplay of adsorption kinetics and conformational change, as well as the effects of particle size and initial protein concentration on the rate constants of elementary steps in protein adsorption onto a mineral surface.

Coherent Anti-Stokes-Stokes Raman Cross-Correlation Spectroscopy: Asymmetric Frequency Shifts in Hydrogen-Bonded Pyridine-Water Complexes

Hydrogen bonding is a vital molecular interaction for bio-molecular systems, yet deep understanding of its ways of creating various complexes requires extensive empirical testing. A hybrid femtosecond/picosecond coherent Raman spectroscopic technique is applied to study pyridine-water complexes. Both the coherent Stokes and anti-Stokes Raman spectra are recorded simultaneously as the concentration of water in pyridine varied. A 3 ps and 10 cm^-1 narrowband probe pulse enables us to observe well-resolved Raman spectra. The hydrogen bonding between pyridine and water forms the complexes that have altered vibrational frequencies. These red and blue shifts were observed to be uneven. This asymmetry was result of the generated background nonlinear optical processes of pyridine-water complexes. This asymmetry tends to disappear as probe pulse further delayed attaining background-free coherent Raman spectra. For better visualization, spectral analyses both traditional two-dimensional correlation spectroscopy and recent second-order correlation functions defined in frequency domain are employed. Recognized as a label-free and background-free technique, the coherent Raman spectroscopy, complemented with a known high-resolution spectroscopic correlation analysis, has potential in studying the hydrogen-bonded pyridine-water complexes. These complexes are of great biological importance both due to the ubiquitous nature of hydrogen bonds and due to the close resemblance to chemical bases in macro-biomolecules.

Mapping the amide-I vibrations of model dipeptides with secondary structure sensitivity and amino acid residue specificity, and its application to amyloid β-peptide in aqueous solution

Vibrational spectroscopy has been known as particularly well-suited for deciphering the polypeptide's structure. To decode structural information encoded in IR spectra, we developed amide-I frequency maps on the basis of model dipeptides to correlate the amide-I frequency of interest to the combination of the calculated secondary structure dependent amide-I frequency by using DFT method and the electrostatic potentials that projected onto the amide unit from the micro-environment within molecular mechanics force field. The constructed maps were applied to model dipeptides and amyloid β-peptide fragment (Aβ_25-35). The dipeptide specified map (DS map) and the hybrid map (HYB map) predicted amide-I bands of Aβ_25-35 in solution satisfactorily reproduce experimental observation, and indicate the preference of forming β-sheet and random coil structure for Aβ_25-35 in D₂O just as the results of cluster analysis suggested. These maps with secondary structural sensitivity and amino acid residue specificity open up a way for the interpretation of amide-I vibrations and show their potentials in the understanding of molecular structure of polypeptides in solution.

Optimal Hyperspectral Characteristics Determination for Winter Wheat Yield Prediction

Crop growth in different periods influences the final yield. This study started from the agronomic mechanism of yield formation and aimed to extract useful spectral characteristics in different phenological phases, which could directly describe the final yield and dynamic contributions of different phases to the yield formation. Hyperspectral information of the winter wheat canopy was acquired during three important phases (jointing stage, heading stage, and grain-filling stage). An enhanced 2D correlation spectral analysis method modified by mutual information was proposed to identify the sensitive wavebands. The selected wavebands performed well with good mechanism interpretation and close correlation with important crop growth parameters and main physiological activities related to yield formation. The quantitative contribution proportions of plant growth in three phases to the final yield were estimated by determining the coefficients of partial least square models based on full spectral information. They were then used as single-phase weight factors to merge the selected wavebands. The support vector machine model based on the weighted spectral dataset performed well in yield prediction with satisfactory accuracy and robustness. This result would provide rapid and accurate guidance for agricultural production and would be valuable for the processing of hyperspectral remote sensing data.