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Portable combination of Fourier transform infrared spectroscopy and differential mobility spectrometry for advanced vapor phase analysis.

ABSTRACT: Designing mobile devices for the analysis of complex sample mixtures containing a variety of analytes at different concentrations across a large dynamic range remains a challenging task in many analytical scenarios. To meet this challenge, a compact hybrid analytical platform has been developed combining Fourier transform infrared spectroscopy based on substrate-integrated hollow waveguides (iHWG-FTIR) with gas chromatography coupled differential mobility spectrometry (GC-DMS). Due to the complementarity of these techniques regarding analyte type and concentration, their combination provides a promising tool for the detection of complex samples containing a broad range of molecules at different concentrations. To date, the combination of infrared spectroscopy and ion mobility techniques remains expensive and bound to a laboratory utilizing e.g. IMS as prefilter or IR as ionization source. In the present study, a cost-efficient and portable solution has been developed and characterized representing the first truly hyphenated IR-DMS system. As a model analyte mixture, 5 ppm isopropylmercaptan (IPM) in methane (CH4) were diluted, and the concentration-dependent DMS signal of IPM along with the concentration-dependent IR signal of CH4 were recorded for all three hybrid IR-DMS systems. While guiding the sample through the iHWG-FTIR or the GC-DMS first did not affect the obtained signals, optimizing the IR data acquisition parameters did benefit the analytical results.

SUBMITTER: Hagemann LT

PROVIDER: S-EPMC6242753 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Portable combination of Fourier transform infrared spectroscopy and differential mobility spectrometry for advanced vapor phase analysis.

Hagemann L Tamina LT McCartney Mitchell M MM Fung Alexander G AG Peirano Daniel J DJ Davis Cristina E CE Mizaikoff Boris B

The Analyst 20181101 23

Designing mobile devices for the analysis of complex sample mixtures containing a variety of analytes at different concentrations across a large dynamic range remains a challenging task in many analytical scenarios. To meet this challenge, a compact hybrid analytical platform has been developed combining Fourier transform infrared spectroscopy based on substrate-integrated hollow waveguides (iHWG-FTIR) with gas chromatography coupled differential mobility spectrometry (GC-DMS). Due to the comple ...[more]

PMID: 30232480

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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

Portable combination of Fourier transform infrared spectroscopy and differential mobility spectrometry for advanced vapor phase analysis.

Publications

Portable combination of Fourier transform infrared spectroscopy and differential mobility spectrometry for advanced vapor phase analysis.

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