Quantitative determination of the biodegradable polymer Poly(beta-hydroxybutyrate) in a recombinant Escherichia coli strain by use of mid-infrared spectroscopy and multivariative statistics

Fourier transform infrared (FTIR) spectroscopy in combination with the partial least squares (PLS) multivariative statistical technique was used for quantitative analysis of the poly(beta-hydroxybutyrate) (PHB) contents of bacterial cells. A total of 237 replicate spectra from 34 samples were obtained together with gas chromatography-determined reference PHB contents. Using the PLS regression, we were able to relate the infrared spectra to the reference PHB contents, and the correlation coefficient between the measured and predicted values for the optimal model with a standard error of prediction of 1.49% PHB was 0.988. With this technique, there are no solvent requirements, sample preparation is minimal and simple, and analysis time is greatly reduced; our results demonstrate the potential of FTIR spectroscopy as an alternative to the conventional methods used for analysis of PHB in bacterial cells.     

Screening of poly-β-hydroxybutyrate-producing microorganisms using Fourier transform infrared spectroscopy

An alternative method for the analysis of poly--hydroxybutyrate (PHB) in microbial biomass based on FTIR spectroscopy was developed in which a semi-transparent, thin pellet of biomass was made with KBr and scanned by IR spectroscopy, from 400 cm^–1to 2000 cm^–1. The IR spectra of the target biomass showed a distinct absorbance band of the carboxylic ester group at 1724.03 cm^–1. The technique can be used to screen large numbers of microorganisms for PHB production.     

Multivariate Analysis of Phenol in Freeze-Dried and Spray-Dried Insulin Formulations by NIR and FTIR

Dehydration is a commonly used method to stabilise protein formulations. Upon dehydration, there is a significant risk the composition of the formulation will change especially if the protein formulation contains volatile compounds. Phenol is often used as excipient in insulin formulations, stabilising the insulin hexamer by changing the secondary structure. We have previously shown that it is possible to maintain this structural change after drying. The aim of this study was to evaluate the residual phenol content in spray-dried and freeze-dried insulin formulations by Fourier transform infrared (FTIR) spectroscopy and near infrared (NIR) spectroscopy using multivariate data analysis. A principal component analysis (PCA) and partial least squares (PLS) projections were used to analyse spectral data. After drying, there was a difference between the two drying methods in the phenol/insulin ratio and the water content of the dried samples. The spray-dried samples contained more water and less phenol compared with the freeze-dried samples. For the FTIR spectra, the best model used one PLS component to describe the phenol/insulin ratio in the powders, and was based on the second derivative pre-treated spectra in the 850–650 cm⁻¹ region. The best PLS model based on the NIR spectra utilised three PLS components to describe the phenol/insulin ratio and was based on the standard normal variate transformed spectra in the 6,200–5,800 cm⁻¹ region. The root mean square error of cross validation was 0.69% and 0.60% (w/w) for the models based on the FTIR and NIR spectra, respectively. In general, both methods were suitable for phenol quantification in dried phenol/insulin samples.     

Novel spectral method for the study of viral carcinogenesis in vitro

Fourier transform infrared (FTIR) spectroscopy is a unique technique for the laboratory diagnosis of cellular variations based on the characteristic molecular vibrational spectra of the cells. Microscopic FTIR was used to investigate spectral differences between normal and malignant fibroblasts transformed by retrovirus infection. A detailed analysis showed significant differences between cancerous and normal cells. The contents of vital cellular metabolites were significantly lower in the transformed cells than in the normal cells. In an attempt to identify the cellular components responsible for the observed spectral differences between normal and cancerous cells, we found significant differences between DNA of normal and cancerous cells.     

FTIR-spectral analysis of two photosynthetic H2-producing strains and their extracellular polymeric substances

The Fourier transform infrared (FTIR) spectra of the cells of two photosynthetic H₂-producing strains, Rhodoblastus acidophilus and Rhodobacter capsulatus, as well as their extracellular polymeric substances (EPS), were evaluated. The FTIR spectra of R. capsulatus and its EPS during its cultivation were also recorded. The main peaks in the spectra, including 1,080 cm⁻¹ (carbohydrates), 1,250 cm⁻¹ (nucleic acids), 2,830–2,930 cm⁻¹ (lipids), 1,660–1,535 cm⁻¹ (Amide I and II of proteins), were observed. The relative heights of these peaks in the spectra of the two strains were different, showing the difference in contents of various components in the cells or EPS. The ratios among the main components in the EPS obtained from the FTIR spectra were in good agreement with those from a conventional quantitative chemical analysis. As an easy, rapid, and direct technique, the FTIR spectroscopy could be used to characterize the components and their relative contents of EPS of photosynthetic bacteria.An erratum to this article can be found at     

Differentiation of probiotic and environmental Saccharomyces cerevisiae strains in animal feed

Aims: To establish an identification system for probiotic Saccharomyces cerevisiae strains based on artificial neural network (ANN)–assisted Fourier‐transform infrared (FTIR) spectroscopy to improve quality control of animal feed. Methods and Results: The ANN‐based system for differentiating environmental from probiotic S. cerevisiae strains comprises five authorized feed additive strains plus environmental strains isolated from different habitats. A total of 108 isolates were used as reference strains to create the ANN. DHPLC analysis and δ‐PCR were used as reference methods to type probiotic yeast isolates. The performance of the FTIR‐ANN was tested in an internal validation using unknown spectra of each reference strain. This validation step yielded a classification rate of 99·1 %. For an external validation, a test data set comprising 965 spectra of 63 probiotic and environmental S. cerevisiae isolates unknown to the ANN was used, resulting in a classification rate of 98·2 %. Conclusions: Our results demonstrate that probiotic S. cerevisiae strains in feed can be differentiated successfully from environmental isolates using both genotypic approaches and ANN‐based FTIR spectroscopy. Significance and Impact of the Study: FTIR‐based artificial neural network analysis provides a rapid and inexpensive technique for yeast identification both at the species and at the strain level in routine diagnostic laboratories, using a single sample preparation.     

Compositional mapping of mixed gels using FTIR microspectroscopy

We have developed a technique to produce compositional maps of phase-separated protein/polysaccharide mixed gels using Fourier transform infrared (FTIR) microspectroscopy. The maps plot out the composition of either the protein, the polysaccharide or the water as a function of position in the sample and are presented in the form of two-dimensional contour plots. Our technique is completely general in nature, since it simply relies on there being some measurable spectral difference between the two biopolymers. However, in this paper we use our technique to study the particular case of aqueous gelatin/ amylopectin gels.

Semi-quantitative compositional maps were generated in the first instance by simply plotting the area of the infrared amide II absorption band from the gelatin. Fully quantitative compositional maps, in terms of actual weight percentage concentration of gelatin, amylopectin and water, were also produced by analysing a particular region of the spectra with the method of partial least-squares (PLS).

We recently showed how PLS analysis can be used in conjunction with FTIR spectroscopy to plot the phase diagram of bulk phase-separated solutions which are held above the gel temperature of both components. Thus, our mapping technique allows the concentrations in a gel to be directly compared with those reached at equilibrium in the bulk phase-separated solution, using the same molecular probe, namely, infrared radiation.     

Production and characterization of bacterial polyhydroxyalkanoate copolymers and evaluation of their blends by fourier transform infrared spectroscopy and scanning electron microscopy

Rhizobium meliloti produced a copolymer of short chain length polyhydroxyalkanoate (scl-PHA) on sucrose and rice bran oil as carbon substrates. Recombinant Escherichia coli (JC7623ABC1J4), bearing PHA synthesis genes, was used to synthesize short chain length-co-medium chain length PHA (scl-co-mcl-PHA) on glucose and decanoic acid. Fourier transform infrared spectroscopy (FTIR) spectra of the PHAs indicated strong characteristic bands at 1282, 1723, and 2934 cm⁻¹ for scl-PHA and at 2933 and 2976 cm⁻¹ for scl-co-mcl-PHA polymer. Differentiation of polyhydroxybutyrate (PHB) and polyhydroxybutyrate-co-hydroxyvalerate-P(HB-co-HV) copolymer was obseverd using FTIR, with absorption bands at 1723 and 1281 for PHB, and at 1738, 1134, 1215 cm⁻¹ for HV-copolymer. The copolymers were analyzed by GC and ¹H NMR spectroscopy. Films of polymer blends of PHA produced by R. meliloti and recombinant E. coli were prepared using glycerol, polyethylene glycol, polyvinyl acetate, individually (1:1 ratio), to modify the mechanical properties of the films and these films were evaluated by FTIR and scanning electron microscopy.     

Application of multivariate curve resolution-alternating least squares (MCR-ALS) for secondary structure resolving of proteins

Fourier transform infrared (FTIR) spectroscopy is the most common spectroscopic technique used for study of protein structure. Initially, band deconvolution techniques were applied to determine the secondary structure of proteins. Recently, several multivariate regression methods have been used to predict the secondary structure of proteins as an alternative to the previous methods. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied on the FTIR spectra of proteins to resolve the fraction and spectral profiles of different structural motifs. Initial estimates of spectral profiles of different protein motifs were built using orthogonal projection approach (OPA). Predicted fractions of α-helix and β-sheet obtained by MCR-ALS technique were compared with those from partial least squares (PLS) modeling which revealed superiority of the former. If we consider the possibility of pure spectra prediction in addition to the prediction of secondary structure from the data set, MCR-ALS can be proposed as a very valuable alternative for qualitative and quantitative study of protein structures.     

Overestimated accuracy of circular dichroism in determining protein secondary structure

Circular dichroism (CD) is a spectroscopic technique widely used for estimating protein secondary structures in aqueous solution, but its accuracy has been doubted in recent work. In the present paper, the contents of nine globular proteins with known secondary structures were determined by CD spectroscopy and Fourier transform infrared spectroscopy (FTIR) in aqueous solution. A large deviation was found between the CD spectra and X-ray data, even when the experimental conditions were optimized. The content determined by FTIR was in good agreement with the X-ray crystallography data. Therefore, CD spectra are not recommended for directly calculating the content of a protein’s secondary structure.     

Lipid quantification method using FTIR spectroscopy applied on cancer cell extracts

Reprogramming energy metabolism constitutes one of the hallmarks of cancer. Changes in lipid composition of cell membranes also appear early in carcinogenesis. Quantification of various molecules such as lipids evidences the modifications in the metabolism of tumour cells and can serve as potential markers for cancer diagnosis and treatment. Fourier Transform Infrared (FTIR) spectroscopy is a powerful tool used for the detection and characterization of various types of molecules. This technique remains an attractive approach as it is cheap (equipment and reagents), does not require high grade solvents or expensive internal standards, equipment is widely available in standard laboratories and the method is robust and suitable for routine analyses. In this work we established partial least square (PLS) models based on FTIR spectra able to quantify lipids in complex mixtures such as cell extracts. In the first part, we attempted to build PLS models with FTIR spectra of 53 mixtures of 8 well-characterized pure lipids. Second, the PLS models were verified using FTIR spectra of mixtures that did not contribute to the calibration. The third step was the validation of the models on lipid cell extracts. In order to obtain reference values for cell extracts, high performance liquid chromatography was carried out by AVANTI. The lipid distribution were globally similar with both techniques, PLS models and chromatography. Finally, the models were applied to determine the lipid composition of cells exposed to four treatments. We could not evidence significant changes in the lipid composition of cell extracts after treatment, in terms of polar head groups. However, the models established in this study appear reliable and could be applied for high throughput measurements. This article is part of a Special Issue entitled Tools to study lipid functions.     

Taxonomic discrimination of flowering plants by multivariate analysis of Fourier transform infrared spectroscopy data

Fourier transform infrared spectroscopy (FTIR) provides biochemical profiles containing overlapping signals from a majority of the compounds that are present when whole cells are analyzed. Leaf samples of seven higher plant species and varieties were subjected to FTIR to determine whether plants can be discriminated phylogenetically on the basis of biochemical profiles. A hierarchical dendrogram based on principal component analysis (PCA) of FTIR data showed relationships between plants that were in agreement with known plant taxonomy. Genetic programming (GP) analysis determined the top three to five biomarkers from FTIR data that discriminated plants at each hierarchical level of the dendrogram. Most biomarkers determined by GP analysis at each hierarchical level were specific to the carbohydrate fingerprint region (1,200–800 cm^–1) of the FTIR spectrum. Our results indicate that differences in cell-wall composition and structure can provide the basis for chemotaxonomy of flowering plants.Abbreviations FTIR Fourier transform infrared spectroscopy - GP Genetic programming - PCA Principal component analysis - PyMS Pyrolysis mass spectrometry     

Monitoring the in situ crystallization of native biopolyester granules in Ralstonia eutropha via infrared spectroscopy

Poly(3-hydroxybutyrate) (PHB), a representative polyhydroxyalkanoate (PHA), is a naturally occurring biopolyester stored as tiny, intracellular granules in microbial cells. In vivo, native PHB granules are amorphous, stabilized by a monolayer membrane and intra-granule water. When subjected to varying environmental conditions, the native granules may become partially crystalline. The in situ crystallinity of native PHB granules in Ralstonia eutropha cells suspended in aqueous solution was monitored with attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). No sample preparation was required for measurement. A major measurement error could be caused by the evaporation of water. Therefore, the infrared absorption spectra should be taken after the initial settlement of cells, but before excessive dehydration. Background interference caused by water and non-PHB biomass was constant throughout the time course of measurement, regardless of granule crystallinity. The wavenumber 1184 cm⁻¹ was found to be most sensitive to the in situ crystallinity of native PHB granules.     

Discrimination of single‐porin Escherichia (E.) coli mutants by ATR and transmission mode FTIR spectroscopy

Vibrational spectroscopy has long been used in bacterial identification with different levels of taxonomic discrimination but its true potential for intra‐species differentiation remains poorly explored. Herein, both transmission Fourier‐transform infrared (FTIR) and attenuated total reflectance (ATR)‐FTIR spectroscopy are used to analyse E. coli strains that differ solely in their porin expression profile. In this previously unreported approach, the applicability of both FTIR‐spectroscopy techniques is compared with the same collection of unique strains. ATR‐FTIR spectroscopy proved to reliably distinguish between several E. coli porin mutants with an accuracy not replicated by FTIR in transmission mode (using previously optimized procedures). Further studies should allow the identification of the individual contribution of the single porin channel to the overall bacterial infrared spectrum and of molecular predictive patterns of porin alterations. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Reliable and rapid identification of Listeria monocytogenes and Listeria species by artificial neural network-based Fourier transform infrared spectroscopy

Differentiation of the species within the genus Listeria is important for the food industry but only a few reliable methods are available so far. While a number of studies have used Fourier transform infrared (FTIR) spectroscopy to identify bacteria, the extraction of complex pattern information from the infrared spectra remains difficult. Here, we apply artificial neural network technology (ANN), which is an advanced multivariate data-processing method of pattern analysis, to identify Listeria infrared spectra at the species level. A hierarchical classification system based on ANN analysis for Listeria FTIR spectra was created, based on a comprehensive reference spectral database including 243 well-defined reference strains of Listeria monocytogenes, L. innocua, L. ivanovii, L. seeligeri, and L. welshimeri. In parallel, a univariate FTIR identification model was developed. To evaluate the potentials of these models, a set of 277 isolates of diverse geographical origins, but not included in the reference database, were assembled and used as an independent external validation for species discrimination. Univariate FTIR analysis allowed the correct identification of 85.2% of all strains and of 93% of the L. monocytogenes strains. ANN-based analysis enhanced differentiation success to 96% for all Listeria species, including a success rate of 99.2% for correct L. monocytogenes identification. The identity of the 277-strain test set was also determined with the standard phenotypical API Listeria system. This kit was able to identify 88% of the test isolates and 93% of L. monocytogenes strains. These results demonstrate the high reliability and strong potential of ANN-based FTIR spectrum analysis for identification of the five Listeria species under investigation. Starting from a pure culture, this technique allows the cost-efficient and rapid identification of Listeria species within 25 h and is suitable for use in a routine food microbiological laboratory.     

Towards developing a protein infrared spectra databank (PISD) for proteomics research

Fourier transform infrared (FTIR) spectroscopy is an attractive tool for proteomics research as it can be used to rapidly characterize protein secondary structure in aqueous solution. Recently, a number of secondary structure prediction methods based on reference sets of FTIR spectra from proteins with known structure from X-ray crystallography have been suggested. These prediction methods, often referred to as pattern recognition based approaches, demonstrated good prediction accuracy using some error measure, e.g., the standard error of prediction (SEP). However, to avoid possible adverse effects from differences in recording, the analysis has been mostly based on reference sets of FTIR spectra from proteins recorded in one laboratory only. As a result, these studies were based on reference sets of FTIR spectra from a limited number of proteins. Pattern recognition based approaches, however, rely on reference sets of FTIR spectra from as many proteins as possible representing all possible band shape variation to be related to the diversity of protein structural classes. Hence, if we want to build reliable pattern recognition based systems to support proteomics research, which are capable of making good predictions from spectral data of any unknown protein, one common goal should be to build a comprehensive protein infrared spectra databank (PISD) containing FTIR spectra of proteins of known structure. We have started the process of developing a comprehensive PISD composed of spectra recorded in different laboratories. As part of this work, here we investigate possible effects on prediction accuracy achieved by a neural network analysis when using reference sets composed of FTIR spectra from different laboratories. Surprisingly low magnitude of difference in SEPs throughout all our experiments suggests that FTIR spectra recorded in different laboratories may be safely combined into one reference set with only minor deterioration of prediction accuracy in the worst case.     

Classification and identification of bacteria by Fourier-transform infrared spectroscopy.

This study describes a computer-based technique for classifying and identifying bacterial samples using Fourier-transform infrared spectroscopy (FT-IR) patterns. Classification schemes were tested for selected series of bacterial strains and species from a variety of different genera. Dissimilarities between bacterial IR spectra were calculated using modified correlation coefficients. Dissimilarity matrices were used for cluster analysis, which yielded dendrograms broadly equated with conventional taxonomic classification schemes. Analyses were performed with selected strains of the taxa Staphylococcus, Streptococcus, Clostridium, Legionella and Escherichia coli in particular, and with a database containing 139 bacterial reference spectra. The latter covered a wide range of Gram-negative and Gram-positive bacteria. Unknown specimens could be identified when included in an established cluster analysis. Thirty-six clinical isolates of Staphylococcus aureus and 24 of Streptococcus faecalis were tested and all were assigned to the correct species cluster. It is concluded that: (1) FT-IR patterns can be used to type bacteria; (2) FT-IR provides data which can be treated such that classifications are similar and/or complementary to conventional classification schemes; and (3) FT-IR can be used as an easy and safe method for the rapid identification of clinical isolates.     

A Fourier-transform infrared spectroscopic analysis of organic matter degradation in a bench-scale solid substrate fermentation (composting) system

The degradation of organic matter was evaluated by a quantitative Fourier transform infrared spectroscopy (FTIR) analysis technique. The degradation process was conducted in a bench-scale reactor under controlled operational conditions of 50 degrees C, with 50-60% moisture content, and subjected to uniform aeration for 325 h. During the composting process, ATP concentration increased from 0.1 to 8 mug/g and the maximum CO(2) evolution and O(2) consumption rates reached 0.04 and 0.085 mmol/g-h, respectively. Polysaccharide content decreased approximately 50% while lignin content remained unchanged. Three regions of the FTIR spectra were used for quantification: 1070-974, 1705-1614, and 2995-2887 cm(-1), which correspond to polysaccharides and aromatic and aliphatic compounds, respectively. The actual spectra quantification consisted of peak identification using a second derivative and curve fitting technique, followed by normalization using the internal standard CaCO(3). The results obtained with the spectra quantification technique was then compared to commonly used wet chemistry extraction procedures. Reasonable correlation between the two techniques was obtained. (c) 1996 John Wiley & Sons, Inc.     

Nanofibers from blends of polyvinyl alcohol and polyhydroxy butyrate as potential scaffold material for tissue engineering of skin

Nanofibers were prepared by electrospinning from pure polyvinyl alcohol (PVA), polyhydroxybutyrate (PHB), and their blends. Miscibility and morphology of both polymers in the nanofiber blends were studied by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and differential scanning calorimetry (DSC), revealing that PVA and PHB were miscible with good compatibility. DSC also revealed suppression of crystallinity of PHB in the blend nanofibers with increasing proportion of PVA. The hydrolytic degradation of PHB was accelerated with increasing PVA fraction. Cell culture experiments with a human keratinocyte cell line (HaCaT) and dermal fibroblast on the electrospun PHB and PVA/PHB blend nanofibers showed maximum adhesion and proliferation on pure PHB. However, the addition of 5 wt % PVA to PHB inhibited growth of HaCaT cells but not of fibroblasts. On the contrary, adhesion and proliferation of HaCaT cells were promoted on PVA/PHB (50/50) fibers, which inhibited growth of fibroblasts.     

Fourier transform infrared microspectroscopy identifies early lineage commitment in differentiating human embryonic stem cells

Human ESCs (hESCs) are a valuable tool for the study of early human development and represent a source of normal differentiated cells for pharmaceutical and biotechnology applications and ultimately for cell replacement therapies. For all applications, it will be necessary to develop assays to validate the efficacy of hESC differentiation. We explored the capacity for FTIR spectroscopy, a technique that rapidly characterises cellular macromolecular composition, to discriminate mesendoderm or ectoderm committed cells from undifferentiated hESCs. Distinct infrared spectroscopic “signatures” readily distinguished hESCs from these early differentiated progeny, with bioinformatic models able to correctly classify over 97% of spectra. These data identify a role for FTIR spectroscopy as a new modality to complement conventional analyses of hESCs and their derivatives. FTIR spectroscopy has the potential to provide low-cost, automatable measurements for the quality control of stem and differentiated cells to be used in industry and regenerative medicine.