Protein secondary structure content in solution, films and tissues: redundancy and complementarity of the information content in circular dichroism, transmission and ATR FTIR spectra

Structural properties and microbial diversity of the biofilm colonizing plastic substrates in Terra Nova Bay (Antarctica)

Microbial colonization on plastic polymers has been extensively explored, however the temporal dynamics of biofilm community in Antarctic environments are almost unknown. As a contribute to fill this knowledge gap, the structural characteristics and microbial diversity of the biofilm associated with polyvinyl chloride (PVC) and polyethylene (PE) panels submerged at 5 m of depth and collected after 3, 9 and 12 months were investigated in four coastal sites of the Ross Sea. Additional panels placed at 5 and 20 m were retrieved after 12 months. Chemical characterization was performed by FTIR-ATR and Raman (through Surface-Enhanced Raman Scattering, SERS) spectroscopy. Bacterial community composition was quantified at a single cell level by Catalyzed Reporter Deposition Fluorescence In Situ Hybridization (CARD-FISH) and Confocal Laser Scanning Microscopy (CLSM); microbial diversity was assessed by 16S rRNA gene sequencing. This multidisciplinary approach has provided new insights into microbial community dynamics during biofouling process, shedding light on the biofilm diversity and temporal succession on plastic substrates in the Ross Sea. Significant differences between free-living and microbial biofilm communities were found, with a more consolidated and structured community composition on PVC compared to PE. Spectral features ascribable to tyrosine, polysaccharides, nucleic acids and lipids characterized the PVC-associated biofilms. Pseudomonadota (among Gamma-proteobacteria) and Alpha-proteobacteria dominated the microbial biofilm community. Interestingly, in Road Bay, close to the Italian "Mario Zucchelli" research station, the biofilm growth - already observed during summer season, after 3 months of submersion - continued afterwards leading to a massive microbial abundance at the end of winter (after 12 months). After 3 months, higher percentages of Gamma-proteobacteria in Road Bay than in the not-impacted site were found. These observations lead us to hypothesize that in this site microbial fouling developed during the first 3 months could serve as a starter pioneering community stimulating the successive growth during winter.

Artificial Intelligence-based Amide-II Infrared Spectroscopy Simulation for Monitoring Protein Hydrogen Bonding Dynamics

The structurally sensitive amide II infrared (IR) bands of proteins provide valuable information about the hydrogen bonding of protein secondary structures, which is crucial for understanding protein dynamics and associated functions. However, deciphering protein structures from experimental amide II spectra relies on time-consuming quantum chemical calculations on tens of thousands of representative configurations in solvent water. Currently, the accurate simulation of amide II spectra for whole proteins remains a challenge. Here, we present a machine learning (ML)-based protocol designed to efficiently simulate the amide II IR spectra of various proteins with an accuracy comparable to experimental results. This protocol stands out as a cost-effective and efficient alternative for studying protein dynamics, including the identification of secondary structures and monitoring the dynamics of protein hydrogen bonding under different pH conditions and during protein folding process. Our method provides a valuable tool in the field of protein research, focusing on the study of dynamic properties of proteins, especially those related to hydrogen bonding, using amide II IR spectroscopy.

A fluorescent sensing platform based on collagen peptides-protected Au/Ag nanoclusters and WS2 for determining collagen triple helix integrity

The unique triple helix structure of collagen plays an important role in its biological properties, and the triple helix integrity is closely correlated with its molecular behavior and biological functions. Nevertheless, there is still a lack of convenient, accurate and practical methods for quantitatively determining collagen triple helix integrity. Herein, we first prepared bovine skin collagen peptide (BSCP)-protected Au/Ag nanoclusters (Au/AgNCs@BSCP) with excellent optical properties, high stability and good biocompatibility, which could adsorb on WS₂ surface leading to fluorescence quenching. Upon the addition of collagen, the interaction of collagen and Au/AgNCs@BSCP led to the detachment of Au/AgNCs@BSCP from the WS₂ surface, causing an increase in the fluorescence signal. Using the difference in the fluorescence recovery of the different samples, we achieved the quantitative determination of collagen triple helix integrity. This developed strategy exhibited excellent accuracy, selectivity, and practicality, thus showing promising potentials in biomedical applications.

Determination of Secondary Structure of Proteins by Nanoinfrared Spectroscopy

Nanoscale infrared spectroscopy (AFMIR) is becoming an important tool for the analysis of biological sample, in particular protein assemblies, at the nanoscale level. While the amide I band is usually used to determine the secondary structure of proteins in Fourier transform infrared spectroscopy, no tool has been developed so far for AFMIR. The paper introduces a method for the study of secondary structure of protein based on a protein library of 38 well-characterized proteins. Ascending stepwise linear regression (ASLR) and partial least square (PLS) regression were used to correlate spectrum characteristic bands with the major secondary structures (α-helixes and β-sheets). ASLR appears to provide better results than PLS. The secondary structure predictions are characterized by a root mean square standard error in a cross validation of 6.39% for α-helixes and 6.23% for β-sheets.

ATR-FTIR Biosensors for Antibody Detection and Analysis

Quality control of drug products is of paramount importance in the pharmaceutical world. It ensures product safety, efficiency, and consistency. In the case of complex biomolecules such as therapeutic proteins, small variations in bioprocess parameters can induce substantial variations in terms of structure, impacting the drug product quality. Conditions for obtaining highly reproducible grafting of 11-mercaptoundecanoic acid were determined. On that basis, we developed an easy-to-use, cost effective, and timesaving biosensor based on ATR-FTIR spectroscopy able to detect immunoglobulins during their production. A germanium crystal, used as an internal reflection element (IRE) for FTIR spectroscopy, was covalently coated with immunoglobulin-binding proteins. This thereby functionalized surface could bind only immunoglobulins present in complex media such as culture media or biopharmaceutical products. The potential subsequent analysis of their structure by ATR-FTIR spectroscopy makes this biosensor a powerful tool to monitor the production of biotherapeutics and assess important critical quality attributes (CQAs) such as high-order structure and aggregation level.

Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data

MOTIVATION

With continually improved instrumentation, Fourier transform infrared (FTIR) microspectroscopy can now be used to capture thousands of high-resolution spectra for chemical characterization of a sample. The spatially resolved nature of this method lends itself well to histological profiling of complex biological specimens. However, current software can make joint analysis of multiple samples challenging and, for large datasets, computationally infeasible.

RESULTS

To overcome these limitations, we have developed Photizo-an open-source Python library enabling high-throughput spectral data pre-processing, visualization and downstream analysis, including principal component analysis, clustering, macromolecular quantification and mapping. Photizo can be used for analysis of data without a spatial component, as well as spatially resolved data, obtained e.g. by scanning mode IR microspectroscopy and IR imaging by focal plane array detector.

AVAILABILITY AND IMPLEMENTATION

The code underlying this article is available at https://github.com/DendrouLab/Photizo with access to example data available at https://zenodo.org/record/6417982#.Yk2O9TfMI6A.

Structural basis of transposon end recognition explains central features of Tn7 transposition systems

Tn7 is a bacterial transposon with relatives containing element-encoded CRISPR-Cas systems mediating RNA-guided transposon insertion. Here, we present the 2.7 Å cryoelectron microscopy structure of prototypic Tn7 transposase TnsB interacting with the transposon end DNA. When TnsB interacts across repeating binding sites, it adopts a beads-on-a-string architecture, where the DNA-binding and catalytic domains are arranged in a tiled and intertwined fashion. The DNA-binding domains form few base-specific contacts leading to a binding preference that requires multiple weakly conserved sites at the appropriate spacing to achieve DNA sequence specificity. TnsB binding imparts differences in the global structure of the protein-bound DNA ends dictated by the spacing or overlap of binding sites explaining functional differences in the left and right ends of the element. We propose a model of the strand-transfer complex in which the terminal TnsB molecule is rearranged so that its catalytic domain is in a position conducive to transposition.

Progress in infrared spectroscopy as an efficient tool for predicting protein secondary structure

Infrared (IR) spectroscopy is a highly sensitive technique that provides complete information on chemical compositions. The IR spectra of proteins or peptides give rise to nine characteristic IR absorption bands. The amide I bands are the most prominent and sensitive vibrational bands and widely used to predict protein secondary structures. The interference of H₂O absorbance is the greatest challenge for IR protein secondary structure prediction. Much effort has been made to reduce/eliminate the interference of H₂O, simplify operation steps, and increase prediction accuracy. Progress in sampling and equipment has rendered the Fourier transform infrared (FTIR) technique suitable for determining the protein secondary structure in broader concentration ranges, greatly simplifying the operating steps. This review highlights the recent progress in sample preparation, data analysis, and equipment development of FTIR in A/T mode, with a focus on recent applications of FTIR spectroscopy in the prediction of protein secondary structure. This review also provides a brief introduction of the progress in ATR-FTIR for predicting protein secondary structure and discusses some combined IR methods, such as AFM-based IR spectroscopy, that are used to analyze protein structural dynamics and protein aggregation.

Feature selection of infrared spectra analysis with convolutional neural network

Data-driven deep learning analysis, especially for convolution neural network (CNN), has been developed and successfully applied in many domains. CNN is regarded as a black box, and the main drawback is the lack of interpretation. In this study, an interpretable CNN model was presented for infrared data analysis. An ascending stepwise linear regression (ASLR)-based approach was leveraged to extract the informative neurons in the flatten layer from the trained model. The characteristic of CNN network was employed to visualize the active variables according to the extracted neurons. Partial least squares (PLS) model was presented for comparison on the performance of extracted features and model interpretation. The CNN models yielded accuracies with extracted features of 93.27%, 97.50% and 96.65% for Tablet, meat, and juice datasets on the test set, while the PLS-DA models obtained accuracies with latent variables (LVs) of 95.19%, 95.50% and 98.17%. Both the CNN and PLS models demonstrated the stable patterns on active variables. The repeatability of CNN model and proposed strategies were verified by conducting the Monte-Carlo cross-validation.

Diagnostic segregation of human breast tumours using Fourier-transform infrared spectroscopy coupled with multivariate analysis: Classifying cancer subtypes

The present study aimed to investigate whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with multivariate analysis could be applied to discriminate and classify among breast tumour molecular subtypes based on the unique spectral "fingerprints" of their biochemical composition. The different breast cancer tissues and normal breast tissues were collected and identified by pathology and ATR-FTIR spectroscopy respectively. The study indicates that the levels of the lipid-to-protein, nucleic acid-to-lipid, phosphate-to-carbohydrate and their secondary structure ratio, including RNA-to-DNA, Amide I-to-Amide II, and RNA-to-lipid ratios were significantly altered among the molecular subtype of breast tumour compared with normal breast tissues, which helps explain the changes in the biochemical structure of different molecular phenotypes of breast cancer. Tentatively-assigned characteristic peak ratios of infrared (IR) spectra reflect the changes of the macromolecule structure in different issues to a great extent and can be used as a potential biomarker to predict the molecular subtype of breast tumour. The present study acts as the first case study to show the successful application of IR spectroscopy in classifying subtypes of breast cancer with biochemical alterations. Therefore, the present study is likely to help to provide a new diagnostic approach for the accurate diagnosis of breast tumours and differential molecular subtypes and has the potential to be used for further intraoperative management.

Interaction of Squid (Dosidicus giga) Mantle Protein with a Mixtures of Potato and Corn Starch in an Extruded Snack, as Characterized by FTIR and DSC

The majority of snacks expanded by extrusion (SEE) are made with vegetable sources, to improve their nutritional content; it has been proposed to incorporate squid (Dosidicus gigas), due to its high protein content, low price and high availability. However, the interaction of proteins of animal origin with starch during extrusion causes negative effects on the sensory properties of SEE, so it is necessary to know the type of protein-carbohydrate interactions and their effect on these properties. The objective of this research was to study the interaction of proteins and carbohydrates of SEE elaborated with squid mantle, potato and corn. The nutritional composition and protein digestibility were evaluated, Fourier transform infrared (FTIR) and Differential Scanning Calorimetry (DSC) were used to study the formation of protein-starch complexes and the possible regions responsible for their interactions. The SEE had a high protein content (40-85%) and biological value (>93%). The melting temperature (Tm) was found between 145 and 225 °C; the Tm values in extruded samples are directly proportional to the squid content. The extrusion process reduced the amine groups I and II responsible for the protein-protein interaction and increased the O-glucosidic bonds, so these bonds could be responsible for the protein-carbohydrate interactions.

FTIR Imaging of Protein Microarrays for High Throughput Secondary Structure Determination

The paper introduces a new method designed for high-throughput protein structure determination. It is based on spotting proteins as microarrays at a density of ca. 2000-4000 samples per cm² and recording Fourier transform infrared (FTIR) spectra by FTIR imaging. It also introduces a new protein library, called cSP92, which contains 92 well-characterized proteins. It has been designed to cover as well as possible the structural space, both in terms of secondary structures and higher level structures. Ascending stepwise linear regression (ASLR), partial least square (PLS) regression, and support vector machine (SVM) have been used to correlate spectral characteristics to secondary structure features. ASLR generally provides better results than PLS and SVM. The observation that secondary structure prediction is as good for protein microarray spectra as for the reference attenuated total reflection spectra recorded on the same samples validates the high throughput microarray approach. Repeated double cross-validation shows that the approach is suitable for the high accuracy determination of the protein secondary structure with root mean square standard error in the cross-validation of 4.9 ± 1.1% for α-helix, 4.6 ± 0.8% for β-sheet, and 6.3 ± 2.2% for the "other" structures when using ASLR.

Amino acid side chain contribution to protein FTIR spectra: impact on secondary structure evaluation

Prediction of protein secondary structure from FTIR spectra usually relies on the absorbance in the amide I–amide II region of the spectrum. It assumes that the absorbance in this spectral region, i.e., roughly 1700–1500 cm⁻¹ is solely arising from amide contributions. Yet, it is accepted that, on the average, about 20% of the absorbance is due to amino acid side chains. The present paper evaluates the contribution of amino acid side chains in this spectral region and the potential to improve secondary structure prediction after correcting for their contribution. We show that the β-sheet content prediction is improved upon subtraction of amino acid side chain contributions in the amide I–amide II spectral range. Improvement is relatively important, for instance, the error of prediction of β-sheet content decreases from 5.42 to 4.97% when evaluated by ascending stepwise regression. Other methods tested such as partial least square regression and support vector machine have also improved accuracy for β-sheet content evaluation. The other structures such as α-helix do not significantly benefit from side chain contribution subtraction, in some cases prediction is even degraded. We show that co-linearity between secondary structure content and amino acid composition is not a main limitation for improving secondary structure prediction. We also show that, even though based on different criteria, secondary structures defined by DSSP and XTLSSTR both arrive at the same conclusion: only the β-sheet structure clearly benefits from side chain subtraction. It must be concluded that side chain contribution subtraction benefit for the evaluation of other secondary structure contents is limited by the very rough description of side chain absorbance which does not take into account the variations related to their environment. The study was performed on a large protein set. To deal with the large number of proteins present, we worked on protein microarrays deposited on BaF₂ slides and FTIR spectra were acquired with an imaging system.

Evaluation of protein secondary structure from FTIR spectra improved after partial deuteration

FTIR spectroscopy has become a major tool to determine protein secondary structure. One of the identified obstacle for reaching better predictions is the strong overlap of bands assigned to different secondary structures. Yet, while for instance disordered structures and α-helical structures absorb almost at the same wavenumber, the absorbance bands are differentially shifted upon deuteration, in part because exchange is much faster for disordered structures. We recorded the FTIR spectra of 85 proteins at different stages of hydrogen/deuterium exchange process using protein microarrays and infrared imaging for high throughput measurements. Several methods were used to relate spectral shape to secondary structure content. While in absolute terms, β-sheet is always better predicted than α-helix content, results consistently indicate an improvement of secondary structure predictions essentially for the α-helix and the category called “Others” (grouping random, turns, bends, etc.) after 15 min of exchange. On the contrary, the β-sheet fraction is better predicted in non-deuterated conditions. Using partial least square regression, the error of prediction for the α-helix content is reduced after 15-min deuteration. Further deuteration degrades the prediction. Error on the prediction for the “Others” structures also decreases after 15-min deuteration. Cross-validation or a single 25-protein test set result in the same overall conclusions.

Searching for a Better Match between Protein Secondary Structure Definitions and Protein FTIR Spectra

Obtaining protein secondary structure content from high-resolution structures requires definitions and thresholds for the various parameters involved, typically hydrogen bond energy or length/angle and backbone φ/ψ angles. Several definitions are currently used and can have a profound impact on secondary structure content. Fourier transform infrared (FTIR) spectroscopy has its own sensitivity to molecular geometry. It is, therefore, important to select a set of definitions that matches this sensitivity. Here, we used a new protein set consisting of 92 proteins designed for the calibration of spectroscopic methods. Spectra have been obtained from protein microarrays in a high throughput process. The potential for improving secondary structure predictions from FTIR spectra has been tested using 71 structures determined according to different definitions. The paper demonstrates that different secondary structure definitions result in large variations in secondary structure content that are not equivalent in view of the protein FTIR spectra. The prediction quality factor ζ can be improved by ca. 20-50% by selecting an adequate definition set. The results also indicate that the dictionary of secondary structure of proteins (DSSP) algorithm, which is currently widely used to evaluate protein secondary structure content, is a good choice when dealing with FTIR spectra.

Ready-to-Use Germanium Surfaces for the Development of FTIR-Based Biosensors for Proteins

Germanium is particularly suitable for the design of FTIR-based biosensors for proteins. The grafting of stable and thin organic layers on germanium surfaces remains, however, challenging. To tackle this problem, we developed a calix[4]arene-tetradiazonium salt decorated with four oligo(ethylene glycol) chains and a terminal reactive carboxyl group. This versatile molecular platform was covalently grafted on germanium surfaces to yield robust ready-to-use surfaces for biosensing applications. The grafted calixarene monolayer prevents nonspecific adsorption of proteins while allowing bioconjugation with biomolecules such as bovine serum albumin (BSA) or biotin. It is shown that the native form of the investigated proteins was maintained upon immobilization. As a proof of concept, the resulting calix[4]arene-based germanium biosensors were used through a combination of ATR-FTIR spectroscopy and fluorescence microscopy for the selective detection of streptavidin from a complex medium. This study opens real possibilities for the development of sensitive and selective FTIR-based biosensors devoted to the detection of proteins.

A convenient protein library for spectroscopic calibrations

While several Raman, CD or FTIR spectral libraries are available for well-characterized proteins of known structure, proteins themselves are usually very difficult to acquire, preventing a convenient calibration of new instruments and new recording methods. The problem is particularly critical in the field of FTIR spectroscopy where numerous new methods are becoming available on the market.

The present papers reports the construction of a protein library (cSP92) including commercially available products, that are well characterized experimentally for their purity and solubility in conditions compatible with the recording of FTIR spectra and whose high-resolution structure is available.

Overall, 92 proteins were selected. These proteins cover well the CATH space at the level of classes and architectures. In terms of secondary structure content, an analysis of their high-resolution structure by DSSP shows that the mean content in the different secondary structures present in cSP92 is very similar to the mean content found in the PDB.

The 92-protein set is analyzed in details for the distribution of helix length, number of strands in β- sheets, length of β-strands and amino acid content, all features that may be important for the interpretation of FTIR spectra.

On the Secondary Structure of Silk Fibroin Nanoparticles Obtained Using Ionic Liquids: An Infrared Spectroscopy Study

Silk fibroin from Bombyx mori caterpillar is an outstanding biocompatible polymer for the production of biomaterials. Its impressive combination of strength, flexibility, and degradability are related to the protein’s secondary structure, which may be altered during the manufacture of the biomaterial. The present study looks at the silk fibroin secondary structure during nanoparticle production using ionic liquids and high-power ultrasound using novel infrared spectroscopic approaches. The infrared spectrum of silk fibroin fibers shows that they are composed of 58% β-sheet, 9% turns, and 33% irregular and/or turn-like structures. When fibroin was dissolved in ionic liquids, its amide I band resembled that of soluble silk and no β-sheet absorption was detected. Silk fibroin nanoparticles regenerated from the ionic liquid solution exhibited an amide I band that resembled that of the silk fibers but had a reduced β-sheet content and a corresponding higher content of turns, suggesting an incomplete turn-to-sheet transition during the regeneration process. Both the analysis of the experimental infrared spectrum and spectrum calculations suggest a particular type of β-sheet structure that was involved in this deficiency, whereas the two other types of β-sheet structure found in silk fibroin fibers were readily formed.

Rapid Physicochemical Changes in Microplastic Induced by Biofilm Formation

Risk assessment of microplastic (MP) pollution requires understanding biodegradation processes and related changes in polymer properties. In the environment, there are two-way interactions between the MP properties and biofilm communities: (i) microorganisms may prefer some surfaces, and (ii) MP surface properties change during the colonization and weathering. In a 2-week experiment, we studied these interactions using three model plastic beads (polyethylene [PE], polypropylene [PP], and polystyrene [PS]) exposed to ambient bacterioplankton assemblage from the Baltic Sea; the control beads were exposed to bacteria-free water. For each polymer, the physicochemical properties (compression, crystallinity, surface chemistry, hydrophobicity, and surface topography) were compared before and after exposure under controlled laboratory conditions. Furthermore, we characterized the bacterial communities on the MP surfaces using 16S rRNA gene sequencing and correlated community diversity to the physicochemical properties of the MP. Significant changes in PE crystallinity, PP stiffness, and PS maximum compression were observed as a result of exposure to bacteria. Moreover, there were significant correlations between bacterial diversity and some physicochemical characteristics (crystallinity, stiffness, and surface roughness). These changes coincided with variation in the relative abundance of unique OTUs, mostly related to the PE samples having significantly higher contribution of Sphingobium, Novosphingobium, and uncultured Planctomycetaceae compared to the other test materials, whereas PP and PS samples had significantly higher abundance of Sphingobacteriales and Alphaproteobacteria, indicating possible involvement of these taxa in the initial biodegradation steps. Our findings demonstrate measurable signs of MP weathering under short-term exposure to environmentally relevant microbial communities at conditions resembling those in the water column. A systematic approach for the characterization of the biodegrading capacity in different systems will improve the risk assessment of plastic litter in aquatic environments.

Super-Resolution Infrared Imaging of Polymorphic Amyloid Aggregates Directly in Neurons

Loss of memory during Alzheimer's disease (AD), a fatal neurodegenerative disorder, is associated with neuronal loss and the aggregation of amyloid proteins into neurotoxic β-sheet enriched structures. However, the mechanism of amyloid protein aggregation is still not well understood due to many challenges when studying the endogenous amyloid structures in neurons or in brain tissue. Available methods either require chemical processing of the sample or may affect the amyloid protein structure itself. Therefore, new approaches, which allow studying molecular structures directly in neurons, are urgently needed. A novel approach is tested, based on label-free optical photothermal infrared super-resolution microspectroscopy, to study AD-related amyloid protein aggregation directly in the neuron at sub-micrometer resolution. Using this approach, amyloid protein aggregates are detected at the subcellular level, along the neurites and strikingly, in dendritic spines, which has not been possible until now. Here, a polymorphic nature of amyloid structures that exist in AD transgenic neurons is reported. Based on the findings of this work, it is suggested that structural polymorphism of amyloid proteins that occur already in neurons may trigger different mechanisms of AD progression.

Assessment of the denaturation of collagen protein concentrates using different techniques

The use of collagen and gelatin in the field of regenerative medicine is widely extended. However, most of the studies in this topic are focused on the scaffolds' properties, but only a few are related to the properties of the raw material used. The raw material analysis not only consists of a study of the composition, but also of the denaturation degree that can influence the processing and properties of the structure of the scaffold. Thus, the denaturation degree analysis of different collagen proteins was performed and assessed by the comparison of four different methods: differential scanning calorimetry (DSC), Fourier transform Infrared Spectroscopy (FTIR) and circular dichroism (CD) spectra and sulfhydryls content analysis. DSC measurements put forward a glass transition between 88°C and 95°C as well as from the FTIR measurements; the characteristic peaks for proteins are evidenced. However, from the sulfur content, only a small proportion of free sulfhydryls are present with respect to their total amount. In addition, CD spectra allow to estimate the secondary structure of the protein by the analysis of the α-helix and β-strand and also quantify the denaturation degree with the 'positive/negative ratio' (RPN) from the CD profiles, obtaining values in the range between 25% and 100%.

Interactions of Casein and Polypeptides in Multilayer Films Studied by FTIR and Molecular Dynamics

Multilayer films containing α- and β-casein and polypeptides, poly-L-lysine (PLL), and poly-L-arginine (PLArg) were formed by the layer-by-layer technique and Fourier Transform InfraRed spectroscopy with Attenuated Total Reflection (FTIR-ATR) and FTIR/Grazing Angle analyzed their infrared spectra. We investigated the changes of conformations of casein and polypeptides in the complexes formed during the build-up of the films. To elucidate the differences in the mechanism of complex formation leading to various growths of (PLL/casein)_n and (PLArg/casein)_n films, we performed the molecular dynamics simulations of the systems consisting of short PLL and PLArg chains and the representative peptide chains—casein fragments, which consists of several aminoacid sequences. The results of the simulation indicated the preferential formation of hydrogen bonds of poly-L-arginine with phosphoserine and glutamic acid residues of caseins. FTIR spectra confirmed those, which revealed greater conformational changes during the formation of casein complex with poly-L-arginine than with poly-L-lysine resulting from stronger interactions, which was also reflected in the bigger growth of (PLArg/casein)_n films with the number of deposited layers.

HTS-FTIR spectroscopy allows the classification of polyphenols according to their differential effects on the MDA-MB-231 breast cancer cell line

Breast cancer is a major public health issue among women in the world. Meanwhile new anticancer treatments struggle more and more to be accepted in the pharmaceutical market and research costs still increase. There is therefore a need to find new treatments and new screening methods to test them more quickly and efficiently. Among natural compounds, an increasing interest has been given to polyphenols as they can take action at the different stages of carcinogenesis, from tumour initiation to metastasis formation, by disturbing multiple cellular signalling pathways. They constitute one of the largest groups of plant metabolites and more than 8000 compounds have already been identified based on their chemical structure. Traditionally in pharmacology, new anticancer drugs are first evaluated for their potential to inhibit the proliferation of cancer cell lines. Numerous potential drugs are discarded at this stage even though they could show interesting modes of action. In turn, there is an increasing demand for more systemic approaches in order to obtain a global and accurate insight into the biochemical processes mediated by drugs. Recently, FTIR spectroscopy was demonstrated to be an innovative tool to obtain a unique fingerprint of the effects of anticancer drugs on cells in culture. While this spectral technique appears to have a definite potential to sort drugs according to their spectral fingerprints, characteristic of the metabolic modifications induced, the present challenge remains to evaluate the drug-induced spectral changes in cancer cells on a larger scale. This article presents the results obtained for a 24 h-exposure of the breast cancer cell line MDA-MB-231 to 15 compounds belonging to different classes of polyphenols using FTIR spectroscopy connected to a high throughput screening extension. Through unsupervised and supervised statistical analyses (PCA, MANOVA, Student's t-tests and HCA), a distinction between polyphenol treatments and controls could be well established.

3D chemical imaging of the brain using quantitative IR spectro-microscopy

Three-dimensional (3D) histology is the next frontier for modern anatomo-pathology. Characterizing abnormal parameters in a tissue is essential to understand the rationale of pathology development. However, there is no analytical technique, in vivo or histological, that is able to discover such abnormal features and provide a 3D distribution at microscopic resolution. Here, we introduce a unique high-throughput infrared (IR) microscopy method that combines automated image correction and subsequent spectral data analysis for 3D-IR image reconstruction. We performed spectral analysis of a complete organ for a small animal model, a mouse brain with an implanted glioma tumor. The 3D-IR image is reconstructed from 370 consecutive tissue sections and corrected using the X-ray tomogram of the organ for an accurate quantitative analysis of the chemical content. A 3D matrix of 89 × 106 IR spectra is generated, allowing us to separate the tumor mass from healthy brain tissues based on various anatomical, chemical, and metabolic parameters. We demonstrate that quantitative metabolic parameters can be extracted from the IR spectra for the characterization of the brain vs. tumor metabolism (assessing the Warburg effect in tumors). Our method can be further exploited by searching for the whole spectral profile, discriminating tumor vs. healthy tissue in a non-supervised manner, which we call 'spectromics'.

Gene expression data and FTIR spectra provide a similar phenotypic description of breast cancer cell lines in 2D and 3D cultures

Gene expression patterns and FTIR spectral data are strongly correlated. Both identified the genotypes and phenotypes of breast cancer cell lines.

Heterogeneity of the Transmembrane Protein Conformation in Purple Membranes Identified by Infrared Nanospectroscopy

Cell membranes are intrinsically heterogeneous, as the local protein and lipid distribution is critical to physiological processes. Even in template systems embedding a single protein type, like purple membranes, there can be a different local response to external stimuli or environmental factors, resulting in heterogeneous conformational changes. Despite the dramatic advances of microspectroscopy techniques, the identification of the conformation heterogeneity is still a challenging task. Tip-enhanced infrared nanospectroscopy is here used to identify conformational changes connected to the hydration state of the transmembrane proteins contained in a 50 nm diameter cell membrane area, without the need for fluorescent labels. In dried purple membrane monolayers, areas with fully hydrated proteins are found among large numbers of molecules with randomly distributed hydration states. Infrared nanospectroscopy results are compared to the spectra obtained with diffraction-limited infrared techniques based on the use of synchrotron radiation, in which the diffraction limit still prevents the observation of nanoscale heterogeneity.

Formation mechanism of α-lactalabumin/oleic acid complex characterized by 2D correlation analysis

Partially unfolded α-lactalbumin (ALA) forms a complex with oleic acid (OA) that exhibits cytotoxic activity. In this study, for the first time, the pH-induced formation mechanism for ALA/OA complexes with two different molar ratios was investigated at the molecular level. For a deeper understanding of the formation mechanism of the two different ALA/OA complexes with decreasing pH, principal component analysis (PCA) and two-dimensional (2D) correlation spectroscopy were used to examine the pH-dependent IR spectra of ALA/OA complexes. By tracking the secondary structural variations in the ALA/OA complexes with decreasing pH, we successfully elucidated the formation mechanism of the ALA/OA complexes at the molecular level. The results showed that the secondary structures of theses complexes exhibited the greatest change between pH4 and pH3.5 and that the components that mainly contributed to the pH-induced transition from the N-state to the A-state were dissimilar in the two different ALA/OA complexes.

Controlled Functionalization of Gold Nanoparticles with Mixtures of Calix[4]arenes Revealed by Infrared Spectroscopy

Labile ligands such as thiols and carboxylates are commonly used to functionalize AuNPs, though little control over the composition is possible when mixtures of ligands are used. It was shown recently that robustly functionalized AuNPs can be obtained through the reductive grafting of calix[4]arenes bearing diazonium groups on the large rim. Here, we report a calix[4]arene-tetradiazonium decorated by four oligo(ethylene glycol) chains on the small rim, which upon grafting gave AuNPs with excellent stability thanks to the C-Au bonds. Mixtures of this calixarene and one with four carboxylate groups were grafted on AuNPs. The resulting particles were analyzed by infrared spectroscopy, which revealed that the composition of the ligand shell clearly reflected the ratio of calixarenes that was present in solution. This strategy opens the way to robustly protected AuNPs with well-defined numbers of functional or postfunctionalizable groups.

Characterization of intermediate state of myoglobin in the presence of PEG 10 under physiological conditions

The macromolecular crowding progressively has been gaining prominence in recent years as it acts as a sword with double-edge on protein stability and folding, i.e., showing assorted results of having both stabilizing and destabilizing effects. We studied the effects of different concentrations of polyethylene glycol (PEG-10) on structure and stability of myoglobin. The tertiary structure of myoglobin was found to be perturbed in the presence of polyethylene glycol, however there was insignificant change in the secondary structure. It was observed that polyethylene glycol induces molten globule state in myoglobin, where the intermediate state holds hydrophobic patches and larger hydrodynamic volume as compared to the native protein. In addition, isothermal titration calorimetry (ITC) showed strong binding between myoglobin and polyethylene glycol, at the physiological pH. We hypothesize that polyethylene glycol induces molten globule conformation in myoglobin by interacting with heme group of myoglobin. We caution that the binding of protein with crowder and other soft interactions need to be gravely well thought-out when studying macromolecular crowding. In our case, destabilizing protein-crowder interactions could compete and overcome the stabilizing exclusion volume effect.

Fourier-transform infrared spectroscopy as a novel approach to providing effect-based endpoints in duckweed toxicity testing

Traditional duckweed toxicity tests only measure plant growth inhibition as an endpoint, with limited effects-based data. The present study aimed to investigate whether Fourier-transform infrared (FTIR) spectroscopy could enhance the duckweed (Lemna minor L.) toxicity test. Four chemicals (Cu, Cd, atrazine, and acetochlor) and 4 metal-containing industrial wastewater samples were tested. After exposure of duckweed to the chemicals, standard toxicity endpoints (frond number and chlorophyll content) were determined; the fronds were also interrogated using FTIR spectroscopy under optimized test conditions. Biochemical alterations associated with each treatment were assessed and further analyzed by multivariate analysis. The results showed that comparable x% of effective concentration (ECx) values could be achieved based on FTIR spectroscopy in comparison with those based on traditional toxicity endpoints. Biochemical alterations associated with different doses of toxicant were mainly attributed to lipid, protein, nucleic acid, and carbohydrate structural changes, which helped to explain toxic mechanisms. With the help of multivariate analysis, separation of clusters related to different exposure doses could be achieved. The present study is the first to show successful application of FTIR spectroscopy in standard duckweed toxicity tests with biochemical alterations as new endpoints. Environ Toxicol Chem 2017;36:346-353. © 2016 SETAC.

Insights into Biochemical Alteration in Cancer-Associated Fibroblasts by using Novel Correlative Spectroscopy

The microenvironment of a tumor changes chemically and morphologically during cancer progression. Cancer‐stimulated fibroblasts promote tumor growth, however, the mechanism of the transition to a cancer‐stimulated fibroblast remains elusive. Here, the multi‐modal spectroscopic methods Fourier transform infrared imaging (FTIRI), X‐ray absorption spectroscopy (XAS) and X‐ray fluorescence imaging (XFI) are used to characterize molecular and atomic alterations that occur in cancer‐stimulated fibroblasts. In addition to chemical changes in lipids (olefinic and acyl chain) and protein aggregation observed with FTIRI, a new infrared biomarker for oxidative stress in stimulated fibroblasts is reported. Oxidative stress is observed to cause lipid peroxidation, which leads to the appearance of a new band at 1721 cm⁻¹, assigned to 4‐hydroxynonenal. Complementary to FTIRI, XFI is well suited to determining atom concentrations and XAS can reveal the speciation of individual elements. XFI reveals increased concentrations of P, S, K, Ca within stimulated fibroblasts. Furthermore, XAS studies reveal alterations in the speciation of S and Ca in stimulated fibroblasts, which might provide insight into the mechanisms of cancer progression. Using XFI, not only is the concentration change of individual elements observed, but also the subcellular localization. This study demonstrates the wealth of biochemical information provided by a multi‐modal imaging approach and highlights new avenues for future research into the microenvironment of breast tumors.

Secondary Structure Determination by Means of ATR-FTIR Spectroscopy

Specialized infrared spectroscopic techniques have been developed that allow studying the secondary structure of membrane proteins and the influence of crucial parameters like lipid content and detergent. Here, we focus on an ATR-FTIR spectroscopic study of Af-Amt1 and the influence of LDAO/glycerol on its structural integrity. Our results clearly indicate that infrared spectroscopy can be used to identify the adapted sample conditions.

Infrared imaging of high density protein arrays

We propose in this paper that protein microarrays could be analysed by infrared imaging in place of enzymatic or fluorescence labelling.

A-type dimeric epigallocatechin-3-gallate (EGCG) is a more potent inhibitor against the formation of insulin amyloid fibril than EGCG monomer

Because fibrillary protein aggregates is regarded to be closely associated with many diseases such as Alzheimer's disease, diabetes, and Parkinson's disease, growing interest and researches have been focused on finding potential fibrillation inhibitors. In the present study, the inhibitory effects of epigallocatechin-3-gallate (EGCG) and A-type dimeric epigallocatechin-3-gallate (A-type EGCG dimer) on the formation of insulin fibrillation were compared by multi-dimensional approaches including thioflavin-T (ThT) fluorescence assay, 1-anilinonaphthalene-8-sulfonic (ANS) fluorescence assay, dynamic light scattering (DLS), transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy and circular dichroism (CD) spectroscopy. Our results confirmed that A-type EGCG dimer is a more potent inhibitor against the formation of bovine insulin amyloid fibril than EGCG. In addition, A-type EGCG dimer could not only inhibit insulin amyloid fibril formation, but also change the aggregation pathway and induce bovine insulin into amorphous aggregates. The results of the present study may provide a new guide on finding novel anti-amyloidogenic agents.

Identification of melanoma cells and lymphocyte subpopulations in lymph node metastases by FTIR imaging histopathology

While early stages of melanoma are usually cured by surgery, metastatic melanomas are difficult to treat because the widely available options have low response rates. Careful and precise diagnosis and staging are essential to determine patient's risk and to select appropriate treatments. Fortunately, the recent progress in immunotherapy is very encouraging. In this context, it is important to characterize the intratumoral infiltration of immune cells in each patient, which is however not done routinely due to the lack of standardized methods. In this study, we used Fourier transform infrared (FTIR) imaging combined with multivariate statistical analyses to investigate non-metastatic and metastatic lymph nodes from melanoma patients. Our results show that the different cell types have different infrared spectral features allowing automated identification of these cell types. High recognition rates were obtained using a supervised partial least square discriminant analysis (PLS-DA) model. Melanoma cells were recognized with 87.1% sensitivity and 85.7% specificity, showing that FTIR spectroscopy has similar detection power as immunohistochemistry. Besides, FTIR imaging could also distinguish lymphocyte subpopulations (B and T cells). Finally, we investigated the changes in lymphocytes due to the presence of metastases. Interestingly, specific features of spectra of lymphocytes present in metastatic or tumor-free lymph nodes could be evidenced by PCA. A PLS-DA model was capable of predicting whether lymphocytes originated from invaded or non-invaded lymph nodes. These data demonstrate that FTIR imaging is capable to distinguish known and also novel biological features in human tissues, with potential practical relevance for histopathological diagnosis and biomarker assessment.

FTIR imaging of the 3D extracellular matrix used to grow colonies of breast cancer cell lines

Infrared imaging was applied to investigate a reconstituted basement membrane, known as Matrigel, in three-dimensional cell cultures.

Self-assembly of 33-mer gliadin peptide oligomers

The 33-mer gliadin peptide, LQLQPF(PQPQLPY)3PQPQPF, is a highly immunogenic peptide involved in celiac disease and probably in other immunopathologies associated with gliadin. Herein, dynamic light scattering measurements showed that 33-mer, in the micromolar concentration range, forms polydisperse nano- and micrometer range particles in aqueous media. This behaviour is reminiscent of classical association of colloids and we hypothesized that the 33-mer peptide self-assembles into micelles that could be the precursors of 33-mer oligomers in water. Deposition of 33-mer peptide aqueous solution on bare mica generated nano- and microstructures with different morphologies as revealed by atomic force microscopy. At 6 μM, the 33-mer is organised in isolated and clusters of spherical nanostructures. In the 60 to 250 μM concentration range, the spherical oligomers associated mainly in linear and annular arrangements and structures adopting a "sheet" type morphology appeared. At higher concentrations (610 μM), mainly filaments and plaques immersed in a background of nanospherical structures were detected. The occurrence of different morphologies of oligomers and finally the filaments suggests that the unique specific geometry of the 33-mer oligomers has a crucial role in the subsequent condensation and organization of their fractal structures into the final filaments. The self-assembly process on mica is described qualitatively and quantitatively by a fractal diffusion limited aggregation (DLA) behaviour with the fractal dimension in the range of 1.62 ± 0.02 to 1.73 ± 0.03. Secondary structure evaluation of the oligomers by Attenuated Total Reflection FTIR spectroscopy (ATR-FTIR) revealed the existence of a conformational equilibrium of self-assembled structures, from an extended conformation to a more folded parallel beta elongated structures. Altogether, these findings provide structural and morphological information about supramolecular organization of the 33-mer peptide, which might offer new perspectives for the understanding and treatment of gliadin intolerance disorders.

Infrared spectra of primary melanomas can predict response to chemotherapy: The example of dacarbazine

Metastatic melanomas are highly aggressive and median survival is 6-9months for stage IV patients in the absence of treatment with anti-tumor activity. Dacarbazine is an alkylating agent that has been widely used in the treatment of metastatic melanomas and that could be still used in combination with targeted or immune therapies. Indeed, therapeutic benefits of these treatments in monotherapy are poor and one option to improve them is to combine drugs and/or to better anticipate the individual response to a defined treatment. To our best knowledge and to date, there is no test available to predict the response of a patient to dacarbazine. We show here that examination of melanoma histological sections by infrared micro-spectroscopy reveals the sensitivity of the cancer to dacarbazine. Unsupervised analysis of the FTIR spectra evidences spontaneous and significant clustering of infrared spectra into two groups that match the clinical responsiveness of the patients to dacarbazine used as a first-line treatment. A supervised model resulted in 83% of the patient status (responder/non-responder) being correctly identified. The spectra revealed a key modification in the nature and quantity of lipids in the cells of both groups.

Label-free phenotyping of peripheral blood lymphocytes by infrared imaging

It is now widely accepted that the immune microenvironment of tumors and more precisely Tumor Infiltrating Lymphocytes (TIL) play an important role in cancer development and outcome. TILs are considered to be important prognostic and predictive factors based on a growing body of clinical evidence; however, their presence at the tumor site is not currently assessed routinely. FTIR (Fourier transform infrared) imaging has proven it has value in studying a range of tumors, particularly for characterizing tumor cells. Currently, very little is known about the potential for FTIR imaging to characterize TIL. The present proof of concept study investigates the ability of FTIR imaging to identify the principal lymphocyte subpopulations present in human peripheral blood (PB). A negative cell isolation method was employed to select pure, label-free, helper T cells (CD4(+)), cytotoxic T cells (CD8(+)) and B cells (CD19(+)) from six healthy donors PB by Fluorescence Activated Cell Sorting (FACS). Cells were centrifuged onto Barium Fluoride windows and ten infrared images were recorded for each lymphocyte subpopulation from all six donors. After spectral pre-treatment, statistical analyses were performed. Unsupervised Principal Component Analyses (PCA) revealed that in the absence of donor variability, CD4(+) T cells, CD8(+) T cells and B cells each display distinct IR spectral features. Supervised Partial Least Square Discriminant Analyses (PLS-DA) demonstrated that the differences between the three lymphocyte subpopulations are reflected in their IR spectra, permitting their individual identification even when significant donor variability is present. Our results also show that a distinct spectral signature is associated with antibody binding. To our knowledge this is the first study reporting that FTIR imaging can effectively identify T and B lymphocytes and differentiate helper T cells from cytotoxic T cells. This proof of concept study demonstrates that FTIR imaging is a reliable tool for the identification of lymphocyte subpopulations and has the potential for use in characterizing TIL.