FT-IR microspectroscopy for early identification of some clinically relevant pathogens

Identification and classification of proteins by FTIR microspectroscopy. A proof of concept

FTIR spectroscopy is well known for its molecule fingerprinting capability but is also able to differentiate classes in complex biological systems. This includes strain typing and species level identification of bacterial, yeast or fungal cells, as well as distinguishing between cell layers in eukaryotic tissues. However, its use for the identification of macromolecules such as proteins remains underexplored and rarely used in practice. Here we demonstrate the efficacy of FTIR microspectroscopy coupled with machine learning methods for rapid and accurate identification of proteins in their dry state within minutes, from very small quantities of material, if they are obtained in a pure aqueous solution. FTIR microspectroscopy can provide additional information beside identification: it can detect small differences among different purification batches potentially originating from post-translational modifications or distinct folding states. Moreover, it distinguishes glycoproteins and evaluate glycosylation while detecting contaminants. This methodology presents itself as a valuable quality control tool in protein purification processes or any process requiring the utilization of precisely identified, pure proteins.

Formation of filamentous fungal biofilms in water and the transformation of resistance to chlor(am)ine disinfection

Biofilms are composed of complex multi-species in nature, potentially threatening drinking water safety. In this work, the formation of single- and multi-species fungal biofilms formed by Aspergillus niger (A. niger) and Aspergillus flavus (A. flavus), and the inactivation of mature biofilms using chlor(am)ine were firstly investigated. Results revealed that the antagonistic interaction occurred between A. niger and A. flavus. Chloramination at 20 mg/L for 30 min achieved 74.74 % and 76.04 % inactivation of A. flavus and multi-species biofilm, which were 1.69- and 1.84-fold higher than that of chlorine at the same condition. However, no significant difference was observed in the inactivation of A. niger biofilm between chlorine and monochloramine disinfection due to the lower amount of extracellular polymeric substance produced by it (p > 0.05). The inactivation of biofilm by monochloramine fitted the Weibull model well. According to the Weibull model, the monochloramine resistance of biofilm were as follows: A. flavus > multi-species > A. niger biofilm. Besides, an increase in reactive oxygen levels, damage of cell membrane, and leakage of intracellular substances in biofilms were observed after chlor(am)ination. More intracellular polysaccharides and proteins were leaked in chloramination inactivation (p < 0.05). This study provides important implications for controlling fungal biofilm.

Significant reduction of the culturing time required for bacterial identification and antibiotic susceptibility determination by infrared spectroscopy

Rapid testing of bacteria for antibiotic susceptibility is essential for effective treatment and curbing the emergence of multidrug-resistant bacteria. The misuse of antibiotics, coupled with the time-consuming classical testing methods, intensifies the threat of antibiotic resistance, a major global health concern. In this study, employing infrared spectroscopy-based machine learning techniques, we significantly shortened the time required for susceptibility testing to 10 hours, a significant improvement from the 24 hours in our previous studies as well as the conventional methods that typically take at least 48 hours. This remarkable reduction in turnaround time (from 48 hours to 10 hours), achieved by minimizing the culturing period, offers a game-changing advantage for clinical applications. Our study involves a dataset comprising 400 bacterial samples (200 E. coli, 100 Klebsiella pneumoniae, and 100 Pseudomonas aeruginosa) with an impressive 96% accuracy in the taxonomic classification at the species level and up to 82% accuracy in bacterial susceptibility to various antibiotics.

Evaluation of Chemical Changes in Laboratory-Induced Colistin-Resistant Klebsiella pneumoniae

This study evaluates the electrical potential and chemical alterations in laboratory-induced colistin-resistant Klebsiella pneumoniae, as compared to the susceptible strain using spectroscopic analyses. The minimal inhibitory concentration (MIC) of colistin, ζ-potential and chemical composition analysis of K. pneumoniae strains are determined. The results obtained for the K. pneumoniae^Col-R with induced high-level colistin resistance (MIC = 16.0 ± 0.0 mg/L) are compared with the K. pneumoniae^Col-S strain susceptible to colistin (MIC = 0.25 ± 0.0 mg/L). Fourier transform infrared (FTIR) and Raman spectroscopic studies revealed differences in bacterial cell wall structures and lipopolysaccharide (LPS) of K. pneumoniae^Col-R and K. pneumoniae^Col-S strains. In the beginning, we assumed that the obtained results could relate to a negative charge of the bacterial surface and different electrostatic interactions with cationic antibiotic molecules, reducing the affinity of colistin and leading to its lower penetration into K. pneumoniae^Col-R cell. However, no significant differences in the ζ-potential between the K. pneumoniae^Col-R and K. pneumoniae^Col-S strains are noticed. In conclusion, this mechanism is most probably associated with recognisable changes in the chemical composition of the K. pneumoniae^Col-R cell wall (especially in LPS) when compared to the susceptible strain.

Vibrational spectroscopic analysis of blood for diagnosis of infections and sepsis: a review of requirements for a rapid diagnostic test

Infections and sepsis represent a growing global burden. There is a widespread clinical need for a rapid, high-throughput and sensitive technique for the diagnosis of infections and detection of invading pathogens and the presence of sepsis. Current diagnostic methods primarily consist of laboratory-based haematology, biochemistry and microbiology that are time consuming, labour- and resource-intensive, and prone to both false positive and false negative results. Current methods are insufficient for the increasing demands on healthcare systems, causing delays in diagnosis and initiation of treatment, due to the intrinsic time delay in sample preparation, measurement, and analysis. Vibrational spectroscopic techniques can overcome these limitations by providing a rapid, label-free and low-cost method for blood analysis, with limited sample preparation required, potentially revolutionising clinical diagnostics by producing actionable results that enable early diagnosis, leading to improved patient outcomes. This review will discuss the challenges associated with the diagnosis of infections and sepsis, primarily within the UK healthcare system. We will consider the clinical potential of spectroscopic point-of-care technologies to enable blood analysis in the primary-care setting.

Isolation of intact bacteria from blood by selective cell lysis in a microfluidic porous silica monolith

Rapid and efficient isolation of bacteria from complex biological matrices is necessary for effective pathogen identification in emerging single-cell diagnostics. Here, we demonstrate the isolation of intact and viable bacteria from whole blood through the selective lysis of blood cells during flow through a porous silica monolith. Efficient mechanical hemolysis is achieved while providing passage of intact and viable bacteria through the monoliths, allowing size-based isolation of bacteria to be performed following selective lysis. A process for synthesizing large quantities of discrete capillary-bound monolith elements and millimeter-scale monolith bricks is described, together with the seamless integration of individual monoliths into microfluidic chips. The impact of monolith morphology, geometry, and flow conditions on cell lysis is explored, and flow regimes are identified wherein robust selective blood cell lysis and intact bacteria passage are achieved for multiple gram-negative and gram-positive bacteria. The technique is shown to enable rapid sample preparation and bacteria analysis by single-cell Raman spectrometry. The selective lysis technique presents a unique sample preparation step supporting rapid and culture-free analysis of bacteria for the point of care.

Reagent-Free Identification of Clinical Yeasts by Use of Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy

Invasive fungal infections by opportunistic yeasts have increased concomitantly with the growth of an immunocompromised patient population. Misidentification of yeasts can lead to inappropriate antifungal treatment and complications. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy is a promising method for rapid and accurate identification of microorganisms. ATR-FTIR spectroscopy is a standalone, inexpensive, reagent-free technique that provides results within minutes after initial culture. In this study, a comprehensive spectral reference database of 65 clinically relevant yeast species was constructed and tested prospectively on spectra recorded (from colonies taken from culture plates) for 318 routine yeasts isolated from various body fluids and specimens received from 38 microbiology laboratories over a 4-month period in our clinical laboratory. ATR-FTIR spectroscopy attained comparable identification performance with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In a preliminary validation of the ATR-FTIR method, correct identification rates of 100% and 95.6% at the genus and species levels, respectively, were achieved, with 3.5% unidentified and 0.9% misidentified. By expanding the number of spectra in the spectral reference database for species for which isolates could not be identified or had been misidentified, we were able to improve identification at the species level to 99.7%. Thus, ATR-FTIR spectroscopy provides a new standalone method that can rival MALDI-TOF MS for the accurate identification of a broad range of medically important yeasts. The simplicity of the ATR-FTIR spectroscopy workflow favors its use in clinical laboratories for timely and low-cost identification of life-threatening yeast strains for appropriate treatment.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows adaptation of grass pollen composition

MALDI time-of-flight mass spectrometry (MALDI-TOF MS) has become a widely used tool for the classification of biological samples. The complex chemical composition of pollen grains leads to highly specific, fingerprint-like mass spectra, with respect to the pollen species. Beyond the species-specific composition, the variances in pollen chemistry can be hierarchically structured, including the level of different populations, of environmental conditions or different genotypes. We demonstrate here the sensitivity of MALDI-TOF MS regarding the adaption of the chemical composition of three Poaceae (grass) pollen for different populations of parent plants by analyzing the mass spectra with partial least squares discriminant analysis (PLS-DA) and principal component analysis (PCA). Thereby, variances in species, population and specific growth conditions of the plants were observed simultaneously. In particular, the chemical pattern revealed by the MALDI spectra enabled discrimination of the different populations of one species. Specifically, the role of environmental changes and their effect on the pollen chemistry of three different grass species is discussed. Analysis of the group formation within the respective populations showed a varying influence of plant genotype on the classification, depending on the species, and permits conclusions regarding the respective rigidity or plasticity towards environmental changes.

Using FT-IR spectroscopy for the identification of the T. cruzi, T. rangeli, and the L. chagasi species

The cross-reaction in the diagnosis results is a serious problem, leading to an incorrect treatment and several injuries to patients. The Trypanosoma rangeli and Trypanosoma cruzi belong to the genus Trypanosoma, but the Trypanosoma rangeli is a non-pathogenic parasite to humans. While Trypanosoma cruzi is the etiological agent of Chagas' disease, which affects circa 2-3 million people and more than 6000 deaths annually in Brazil. The Leishmania chagasi causes infectious disease known as visceral leishmaniasis. This diseases have in common the crossed antigenic reaction promoted by serological tests and its differentiation is relevant for epidemiological studies and clinical practice. In this study the Fourier Transform Infrared (FT-IR) Spectroscopy was used to differentiate these microorganisms, which were cultivated and the spectra analyzed. Data analysis were performed by Gaussian curve fitting and multivariate statistical analysis. The cluster analysis have shown four specific regions to identify the microorganisms. The first three PCs of principal component analysis associated to linear discriminant were able to classify 95.6% of the parasites using cross-validation. The curve fitting method showed the quantitative differentiation among L. chagasi, T. cruzi, and T. rangeli species in the vibrational regions of polysaccharides, amide III, lipid esters, and fatty acid.

Hierarchical classification of microorganisms based on high-dimensional phenotypic data

The classification of microorganisms by high-dimensional phenotyping methods such as FTIR spectroscopy is often a complicated process due to the complexity of microbial phylogenetic taxonomy. A hierarchical structure developed for such data can often facilitate the classification analysis. The hierarchical tree structure can either be imposed to a given set of phenotypic data by integrating the phylogenetic taxonomic structure or set up by revealing the inherent clusters in the phenotypic data. In this study, we wanted to compare different approaches to hierarchical classification of microorganisms based on high-dimensional phenotypic data. A set of 19 different species of molds (filamentous fungi) obtained from the mycological strain collection of the Norwegian Veterinary Institute (Oslo, Norway) is used for the study. Hierarchical cluster analysis is performed for setting up the classification trees. Classification algorithms such as artificial neural networks (ANN), partial least-squared discriminant analysis and random forest (RF) are used and compared. The 2 methods ANN and RF outperformed all the other approaches even though they did not utilize predefined hierarchical structure. To our knowledge, the RF approach is used here for the first time to classify microorganisms by FTIR spectroscopy.

A pilot study on fingerprinting Leishmania species from the Old World using Fourier transform infrared spectroscopy

Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains’ hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens.

Graphical abstract

Chemometric analysis of attenuated total reflectance infrared spectra of Proteus mirabilis strains with defined structures of LPS

Proteus spp. strains are some of the most important pathogens associated with complicated urinary tract infections and bacteremia affecting patients with immunodeficiency and long-term urinary catheterization. For epidemiological purposes, various molecular typing methods have been developed for this pathogen. However, these methods are labor intensive and time consuming. We evaluated a new method of differentiation between strains. A collection of Proteus spp. strains was analyzed by attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy in the mid-infrared region. ATR FT-IR spectroscopy used in conjunction with a diamond ATR accessory directly produced the biochemical profile of the surface chemistry of bacteria. We conclude that a combination of ATR FT-IR spectroscopy and mathematical modeling provides a fast and reliable alternative for discrimination between Proteus isolates, contributing to epidemiological research.

Microbial mediated synthesis, characterization, antibacterial and synergistic effect of gold nanoparticles using Klebsiella pneumoniae (MTCC-4030)

Herein, the microbial mediated synthesis of gold nanoparticles (GNPs) was achievedviaan easy biological protocol usingKlebsiella pneumoniae(MTCC-4030).

Differentiation of Leishmania species by FT-IR spectroscopy

Leishmaniasis is a parasitic infectious disease caused by protozoa that belong to the genus Leishmania. It is transmitted by the bite of an infected female Sand fly. The disease is endemic in 88 countries Desjeux (2001) [1] (16 developed countries and 72 developing countries) on four continents. In Brazil, epidemiological data show the disease is present in all Brazilian regions, with the highest incidences in the North and Northeast. There are several methods used to diagnose leishmaniasis, but these procedures have many limitations, are time consuming, have low sensitivity, and are expensive. In this context, Fourier Transform Infrared Spectroscopy (FT-IR) analysis has the potential to provide rapid results and may be adapted for a clinical test with high sensitivity and specificity. In this work, FT-IR was used as a tool to investigate the promastigotes of Leishmaniaamazonensis, Leishmaniachagasi, and Leishmaniamajor species. The spectra were analyzed by cluster analysis and deconvolution procedure base on spectra second derivatives.

RESULTS

cluster analysis found four specific regions that are able to identify the Leishmania species. The dendrogram representation clearly indicates the heterogeneity among Leishmania species. The band deconvolution done by the curve fitting in these regions quantitatively differentiated the polysaccharides, amide III, phospholipids, proteins, and nucleic acids. L. chagasi and L. major showed a greater biochemistry similarity and have three bands that were not registered in L. amazonensis. The L. amazonensis presented three specific bands that were not recorded in the other two species. It is evident that the FT-IR method is an indispensable tool to discriminate these parasites. The high sensitivity and specificity of this technique opens up the possibilities for further studies about characterization of other microorganisms.

Diversity of yeast strains of the genus Hanseniaspora in the winery environment: What is their involvement in grape must fermentation?

Isolated yeast populations of Chardonnay grape must during spontaneous fermentation were compared to those isolated on grape berries and in a winery environment before the arrival of the harvest (air, floor, winery equipment) and in the air through time. Two genera of yeast, Hanseniaspora and Saccharomyces, were isolated in grape must and in the winery environment before the arrival of the harvest but not on grape berries. The genus Hanseniaspora represented 27% of isolates in the must and 35% of isolates in the winery environment. The isolates of these two species were discriminated at the strain level by Fourier transform infrared spectroscopy. The diversity of these strains observed in the winery environment (26 strains) and in must (12 strains) was considerable. 58% of the yeasts of the genus Hanseniaspora isolated in the must corresponded to strains present in the winery before the arrival of the harvest. Although the proportion and number of strains of the genus Hanseniaspora decreased during fermentation, some strains, all from the winery environment, subsisted up to 5% ethanol content. This is the first time that the implantation in grape must of populations present in the winery environment has been demonstrated for a non-Saccharomyces genus.

Identification of microorganisms by FTIR spectroscopy: perspectives and limitations of the method

Fourier transform infrared (FTIR) spectroscopy was introduced in 1991 as a technique to identify and classify microbes. Since then, it has gained growing interest and has undergone a remarkable evolution. Highly sophisticated spectrometers have been developed, enabling a high sample throughput. Today, the generation of high-quality data in a short time and the application of the technique for rapid and reliable identification of microbes to the species level are well documented. What makes FTIR spectroscopy even more attractive is the fact that spectral information can also be exploited for strain typing purposes, which is particularly important for epidemiological analyses and some technological applications. Accordingly, in recent years, FTIR spectroscopy has been increasingly used for typing and classifying microorganisms below the species level. The intention of this review is to give an overview over current knowledge and strategies of using FTIR spectroscopy for species identification and to describe different approaches for strain typing.

Fourier transform infrared microspectroscopy of endocarditis vegetation

The objectives of this work were to compare the infrared spectra of bacterial endocarditis vegetation with those of native valvular tissue and the infrared spectra of vegetation bacterial masses with those of surrounding vegetation tissue. Streptococcal aortic endocarditis was induced in three rabbits. Vegetation slices were cryo-sectioned for study by Fourier transform infrared (FT-IR) microspectroscopy. Valvular apparatus, vegetation, and bacterial masses within the vegetation were localized on hematoxylin and eosin (H&E) stained contiguous slices. Infrared images of whole vegetations and images of bacterial masses were acquired with apertures set to 80 x 80 and 20 x 20 microm, respectively. Valvular apparatus and vegetation showed different infrared spectra, mainly in the amide I and amide II bands (1674-1518 cm(-1)), and at about 1450, 1400, 1340, 1280, 1240, 1200, 1080, and 1030 cm(-1). Valvular collagen, elastin, and proteoglycans may explain these differences. Bacterial masses and surrounding vegetation showed different infrared patterns, mainly in the amide I and amide II bands and in the 1142-991 cm(-1) carbohydrate spectral range. Bacterial nucleic acids and polysaccharides may partly explain these differences. Study of experimental endocarditis vegetation using FT-IR microspectroscopy distinguishes (1) the vegetation from the valvular tissue, and (2) the bacterial masses from the surrounding tissue. This study demonstrates for the first time that FT-IR microspectroscopy is able to detect bacterial growth in infected tissue. FT-IR microspectroscopy appears to be a useful tool for investigation of the biochemical structure of endocarditis vegetation.

Factors influencing the discrimination and classification of prostate cancer cell lines by FTIR microspectroscopy

In this study we obtained Fourier transform infrared (FTIR) spectra of fixed prostate cell lines of differing types as well as the primary epithelial cells from benign prostatic hyperplasia (BPH). Results showed that by using multivariate chemometric analysis it was possible to discriminate and classify these cell lines, which gave rise to sensitivity and specificity values of >94% and >98%, respectively. Following on from these results the possible influences of different factors on the discrimination and classification of the prostate cell lines were examined. Firstly, the effect of using different growth media during cell culturing was investigated, with results indicating that this did not influence chemometric discrimination. Secondly, differences in the nucleus-to-cytoplasm (N/C) ratio were examined, and it was concluded that this factor was not the main reason for the discrimination and classification of the prostate cancer (CaP) cell lines. In conclusion, given the fact that neither growth media nor N/C ratio could totally explain the classification it is likely that actual biochemical differences between the cell lines is the major contributing factor.

Investigation of spermatozoa and seminal plasma by fourier transform infrared spectroscopy

Fourier transform infrared (FT-IR) spectra of human spermatozoa and seminal plasma were recorded and analyzed. The procedure that was established for sample preparation enabled acquisition of reproducible spectra. The parameter I(1087)/I(966) for controlling spectra reproducibility was defined. The assignment of bands was carried out using an empirical approach and the origin of the "sperm specific doublet", the bands at 968 cm(-1) and 981 cm(-1), was determined. The principal component regression (PCR) algorithm was used to define the specific spectral regions correlating to characteristics of spermatozoa, such as concentration, straight-line velocity (VSL), and beat cross frequency (BCF). Then, simple spectral parameters, such as band intensities and band ratios, were tested to determine which one best correlates to characteristics of spermatozoa. The region of the amide I band, between 1700 cm(-1) and 1590 cm(-1), was defined as a specific spectral region that correlates to the concentration of spermatozoa. The parameter that gave the linear dependence to the concentration of spermatozoa was the intensity of the amide I band. For VSL, the bands between 1119 cm(-1) and 943 cm(-1) were defined as the specific spectral region. The relative amount of nucleic acids with respect to proteins showed linear dependence on the straight-line velocity of spermatozoa. BCF showed the best correlation to the bands between 3678 cm(-1) and 2749 cm(-1), which largely represent lipids and proteins. These results suggest that FT-IR spectroscopy can serve as an adjunct to conventional histopathology studies.