Dataset Information

Molecular Recognition via Hydrogen Bonding in Supramolecular Complexes: A Fourier Transform Infrared Spectroscopy Study.

ABSTRACT: We assess the assembly of supramolecular complexes by hydrogen bonding between azocompounds and a diacylaminopyridine monomer by temperature-dependent Fourier transform infrared spectroscopy (FT-IR) and density functional theory (DFT) calculations. The electronic delocalisation in the supramolecular rings formed by multiple hydrogen bonds stabilises the complexes, which coexist with dimeric species in temperature-dependent equilibria. We show how the application of readily available molecular modelling and spectroscopic techniques can predict the stability of new supramolecular entities coexisting in equilibria, ultimately assessing the success of molecular recognition.

SUBMITTER: Martinez-Felipe A

PROVIDER: S-EPMC6225378 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Molecular Recognition via Hydrogen Bonding in Supramolecular Complexes: A Fourier Transform Infrared Spectroscopy Study.

Martinez-Felipe Alfonso A Brebner Fraser F Zaton Daniel D Concellon Alberto A Ahmadi Sara S Piñol Milagros M Oriol Luis L

Molecules (Basel, Switzerland) 20180906 9

We assess the assembly of supramolecular complexes by hydrogen bonding between azocompounds and a diacylaminopyridine monomer by temperature-dependent Fourier transform infrared spectroscopy (FT-IR) and density functional theory (DFT) calculations. The electronic delocalisation in the supramolecular rings formed by multiple hydrogen bonds stabilises the complexes, which coexist with dimeric species in temperature-dependent equilibria. We show how the application of readily available molecular mo ...[more]

PMID: 30200584

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Project description:Fourier transform infrared (FTIR) spectroscopy, a technology traditionally used in chemistry to determine the molecular composition of a wide range of sample types, has gained growing interest in microbial typing. It is based on the different vibrational modes of the covalent bonds between atoms of a given sample, as bacterial cells, induced by the absorption of infrared radiation. This technique has been largely used for the study of pathogenic species, especially in the clinical field, and has been proposed also for the typing at different subspecies levels. The high throughput, speed, low cost, and simplicity make FTIR spectroscopy an attractive technique also for industrial applications, in particular, for probiotics. The aim of this study was to compare FTIR spectroscopy with established genotyping methods, pulsed-field gel electrophoresis (PFGE), whole-genome sequencing (WGS), and multilocus sequence typing (MLST), in order to highlight the FTIR spectroscopy potential discriminatory power at strain level. Our study focused on bifidobacteria, an important group of intestinal commensals generally recognized as probiotics. For their properties in promoting and maintaining health, bifidobacteria are largely marketed by the pharmaceutical, food, and dairy industries. Strains belonging to Bifidobacterium longum subsp. longum and Bifidobacterium animalis subsp. lactis were taken into consideration together with some additional type strains. For B. longum subsp. longum, it was possible to discriminate the strains with all the methods used. Although two isolates were shown to be strictly phylogenetically related, constituting a unique cluster, based on PFGE, WGS, and MLST, no clustering was observed with FTIR. For B. animalis subsp. lactis group, PFGE, WGS, and MLST were non-discriminatory, and only one strain was easily distinguished. On the other hand, FTIR discriminated all the isolates one by one, and no clustering was observed. According to these results, FTIR analysis is not only equivalent to PFGE, WGS, and MLST, but also for some strains, in particular, for B. animalis subsp. lactis group, more informative, being able to differentiate strains not discernible with the other two methods based on phenotypic variations likely deriving from certain genetic changes. Fourier transform infrared spectroscopy has highlighted the possibility of using the cell surface as a kind of barcode making tracing strains possible, representing an important aspect in probiotic applications. Furthermore, this work constitutes the first investigation on bifidobacterial strain typing using FTIR spectroscopy.

Project description:Hyaline cartilage and mechanically inferior fibrocartilage consisting of mixed collagen types are frequently found together in repairing articular cartilage. The present study seeks to develop methodology to identify collagen type and other tissue components using Fourier transform infrared (FTIR) spectral evaluation of matrix composition in combination with multivariate analyses. FTIR spectra of the primary molecular components of repair cartilage, types I and II collagen, and aggrecan, were used to develop multivariate spectral models for discrimination of the matrix components of the tissues of interest. Infrared imaging data were collected from bovine bone, tendon, normal cartilage, meniscus and human repair cartilage tissues, and composition predicted using partial least squares analyses. Histology and immunohistochemistry results were used as standards for validation. Infrared fiber optic probe spectral data were also obtained from meniscus (a tissue with mixed collagen types) to evaluate the potential of this method for identification of collagen type in a minimally-invasive clinical application. Concentration profiles of the tissue components obtained from multivariate analysis were in excellent agreement with histology and immunohistochemistry results. Bone and tendon showed a uniform distribution of predominantly type I collagen through the tissue. Normal cartilage showed a distribution of type II collagen and proteoglycan similar to the known composition, while in repair cartilage, the spectral distribution of both types I and II collagen were similar to that observed via immunohistochemistry. Using the probe, the outer and inner regions of the meniscus were shown to be primarily composed of type I and II collagen, respectively, in accordance with immunohistochemistry data. In summary, multivariate analysis of infrared spectra can indeed be used to differentiate collagen type I and type II, even in the presence of proteoglycan, in connective tissues, using both imaging and fiber optic methodology. This has great potential for clinical in situ applications for monitoring tissue repair.

Dataset Information

Molecular Recognition via Hydrogen Bonding in Supramolecular Complexes: A Fourier Transform Infrared Spectroscopy Study.

Publications

Molecular Recognition via Hydrogen Bonding in Supramolecular Complexes: A Fourier Transform Infrared Spectroscopy Study.

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