Subtyping of Listeria monocytogenes at the haplotype level by Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis

Bacterial discrimination by Fourier transform infrared spectroscopy, MALDI-mass spectrometry and whole-genome sequencing

Aim: Proof-of-concept study, highlighting the clinical diagnostic ability of FT-IR compared with MALDI-TOF MS, combined with WGS. Materials & methods: 104 pathogenic isolates of Neisseria meningitidis, Streptococcus pneumoniae, Streptococcus pyogenes and Staphylococcus aureus were analyzed. Results: Overall prediction accuracy was 99.6% in FT-IR and 95.8% in MALDI-TOF-MS. Analysis of N. meningitidis serogroups was superior in FT-IR compared with MALDI-TOF-MS. Phylogenetic relationship of S. pyogenes was similar by FT-IR and WGS, but not S. aureus or S. pneumoniae. Clinical severity was associated with the zinc ABC transporter and DNA repair genes in S. pneumoniae and cell wall proteins (biofilm formation, antibiotic and complement permeability) in S. aureus via WGS. Conclusion: FT-IR warrants further clinical evaluation as a promising diagnostic tool.

A multi-center validation study on the discrimination of Legionella pneumophila sg.1, Legionella pneumophila sg. 2-15 and Legionella non-pneumophila isolates from water by FT-IR spectroscopy

This study developed and validated a method, based on the coupling of Fourier-transform infrared spectroscopy (FT-IR) and machine learning, for the automated serotyping of Legionella pneumophila serogroup 1, Legionella pneumophila serogroups 2-15 as well as their successful discrimination from Legionella non-pneumophila. As Legionella presents significant intra- and inter-species heterogeneities, careful data validation strategies were applied to minimize late-stage performance variations of the method across a large microbial population. A total of 244 isolates were analyzed. In details, the method was validated with a multi-centric approach with isolates from Italian thermal and drinking water (n = 82) as well as with samples from German, Italian, French, and British collections (n = 162). Specifically, robustness of the method was verified over the time-span of 1 year with multiple operators and two different FT-IR instruments located in Italy and Germany. Moreover, different production procedures for the solid culture medium (in-house or commercial) and different culture conditions (with and without 2.5% CO₂) were tested. The method achieved an overall accuracy of 100, 98.5, and 93.9% on the Italian test set of Legionella, an independent batch of Legionella from multiple European culture collections, and an extra set of rare Legionella non-pneumophila, respectively.

Identification of Listeria species by Fourier-transform infrared spectroscopy

Differentiation of the genus Listeria is significant for food industry, but only few reliable methods are available so far. In the present study, 56 strains isolated from 345 samples of cow raw milk were used. The isolated pure cultures were defined by PCR-based method using specific primers of 16S-23S IGS region of DNA. Bacterial strain samples were submitted to spectroscopic measurements by the trans-mission method at a wavelength of 3000–700 cm–1 using Fourier-transform infrared (FTIR) spectro-photometry. Hierarchical cluster analysis (HCA) was performed based on the identification of the 56 isolated strains. The utilisation of HCA in univariate-FTIR spectral analyses as the most progressive chemometric method was supported by the correct identification of 86.9% bacteria of the genus Listeria at the species level. These results explained the ability of univariate-FTIR spectrum analysis for determination of suspected Listeria species.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.

Typing and Species Identification of Clinical Klebsiella Isolates by Fourier Transform Infrared Spectroscopy and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry

Klebsiella pneumoniae and related species are frequent causes of nosocomial infections and outbreaks. Therefore, quick and reliable strain typing is crucial for the detection of transmission routes in the hospital. The aim of this study was to evaluate Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) as rapid methods for typing clinical Klebsiella isolates in comparison to whole-genome sequencing (WGS), which was considered the gold standard for typing and identification. Here, 68 clinical Klebsiella strains were analyzed by WGS, FTIR, and MALDI-TOF MS. FTIR showed high discriminatory power in comparison to the WGS reference, whereas MALDI-TOF MS exhibited a low ability to type the isolates. MALDI-TOF mass spectra were further analyzed for peaks that showed high specificity for different Klebsiella species. Phylogenetic analysis revealed that the Klebsiella isolates comprised three different species: K. pneumoniae, K. variicola, and K. quasipneumoniae Genome analysis showed that MALDI-TOF MS can be used to distinguish K. pneumoniae from K. variicola due to shifts of certain mass peaks. The peaks were tentatively identified as three ribosomal proteins (S15p, L28p, L31p) and one stress response protein (YjbJ), which exhibit amino acid differences between the two species. Overall, FTIR has high discriminatory power to recognize the clonal relationship of isolates, thus representing a valuable tool for rapid outbreak analysis and for the detection of transmission events due to fast turnaround times and low costs per sample. Furthermore, specific amino acid substitutions allow the discrimination of K. pneumoniae and K. variicola by MALDI-TOF MS.

Rapid characterisation of Klebsiella oxytoca isolates from contaminated liquid hand soap using mass spectrometry, FTIR and Raman spectroscopy

Microbiological monitoring of consumer products and the efficiency of early warning systems and outbreak investigations depend on the rapid identification and strain characterisation of pathogens posing risks to the health and safety of consumers. This study evaluates the potential of three rapid analytical techniques for identification and subtyping of bacterial isolates obtained from a liquid hand soap product, which has been recalled and reported through the EU RAPEX system due to its severe bacterial contamination. Ten isolates recovered from two bottles of the product were identified as Klebsiella oxytoca and subtyped using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI TOF MS), near-infrared Fourier transform (NIR FT) Raman spectroscopy and Fourier transform infrared (FTIR) spectroscopy. Comparison of the classification results obtained by these phenotype-based techniques with outcomes of the DNA-based methods pulsed-field gel electrophoresis (PFGE), multi-locus sequence typing (MLST) and single nucleotide polymorphism (SNP) analysis of whole-genome sequencing (WGS) data revealed a high level of concordance. In conclusion, a set of analytical techniques might be useful for rapid, reliable and cost-effective microbial typing to ensure safe consumer products and allow source tracking.

Listeria monocytogenes in Foods

Listeria monocytogenes causes listeriosis, a rare foodborne disease with a mortality rate of 20%-30%. The elderly and immunocompromised are particularly susceptible to listeriosis. L. monocytogenes is ubiquitous in nature and can contaminate food-processing environments, posing a threat to the food chain. This is particularly important for ready-to-eat foods as there is no heat treatment or other antimicrobial step between production and consumption. Thus, occurrence and control of L. monocytogenes are important for industry and public health. Advances in whole-genome sequence technology are facilitating the investigation of disease outbreaks, linking sporadic cases to outbreaks, and linking outbreaks internationally. Novel control methods, such as bacteriophage and bacteriocins, can contribute to a reduction in the occurrence of L. monocytogenes in the food-processing environment, thereby reducing the risk of food contamination and contributing to a reduction in public health issues.

Rapid Identification and Classification of Listeria spp. and Serotype Assignment of Listeria monocytogenes Using Fourier Transform-Infrared Spectroscopy and Artificial Neural Network Analysis

The use of Fourier Transform-Infrared Spectroscopy (FT-IR) in conjunction with Artificial Neural Network software NeuroDeveloper™ was examined for the rapid identification and classification of Listeria species and serotyping of Listeria monocytogenes. A spectral library was created for 245 strains of Listeria spp. to give a biochemical fingerprint from which identification of unknown samples were made. This technology was able to accurately distinguish the Listeria species with 99.03% accuracy. Eleven serotypes of Listeria monocytogenes including 1/2a, 1/2b, and 4b were identified with 96.58% accuracy. In addition, motile and non-motile forms of Listeria were used to create a more robust model for identification. FT-IR coupled with NeuroDeveloper™ appear to be a more accurate and economic choice for rapid identification of pathogenic Listeria spp. than current methods.

Listeria monocytogenes: Strain Heterogeneity, Methods, and Challenges of Subtyping

Listeria monocytogenes is a food-borne bacterial pathogen that is associated with 20% to 30% case fatality rate. L. monocytogenes is a genetically heterogeneous species, with a small fraction of strains (serotypes 1/2a, 1/2b, 4b) implicated in human listeriosis. Monitoring and source tracking of L. monocytogenes involve the use of subtyping methods, with the performance of genetic-based methods found to be superior to phenotypic-based ones. Various methods have been used to subtype L. monocytogenes isolates, with the pulsed-field gel electrophoresis (PFGE) being the gold standard. Although PFGE has had a massive impact on food safety through the establishment of the PulseNet, there is no doubt that whole genome sequence (WGS) typing is accurate, has a discriminatory power superior to any known method, and allows genome-wide differences between strains to be quantified through the comparison of nucleotide sequences. This review focuses on the different techniques that have been used to type L. monocytogenes strains, their performance challenges, and the tremendous impact WGS typing could have on the food safety landscape.

Differentiation of different mixed Listeria strains and also acid-injured, heat-injured, and repaired cells of Listeria monocytogenes using fourier transform infrared spectroscopy

Fourier transform infrared (FT-IR) spectroscopy was used to differentiate mixed strains of Listeria monocytogenes and mixed strains of L. monocytogenes and Listeria innocua. FT-IR spectroscopy was also applied to investigate the hypothesis that heat-injured and acid-injured cells would return to their original physiological integrity following repair. Thin smears of cells on infrared slides were prepared from cultures for mixed strains of L. monocytogenes, mixed strains of L. monocytogenes and L. innocua, and each individual strain. Heat-injured and acid-injured cells were prepared by exposing harvested cells of L. monocytogenes strain R2-764 to a temperature of 56 ± 0.2°C for 10 min or lactic acid at pH 3 for 60 min, respectively. Cellular repair involved incubating aliquots of acid-injured and heat-injured cells separately in Trypticase soy broth supplemented with 0.6% yeast extract for 22 to 24 h; bacterial thin smears on infrared slides were prepared for each treatment. Spectral collection was done using 250 scans at a resolution of 4 cm(-1) in the mid-infrared wavelength region. Application of multivariate discriminant analysis to the wavelength region from 1,800 to 900 cm(-1) separated the individual L. monocytogenes strains. Mixed strains of L. monocytogenes and L. monocytogenes cocultured with L. innocua were successfully differentiated from the individual strains when the discriminant analysis was applied. Different mixed strains of L. monocytogenes were also successfully separated when the discriminant analysis was applied. A data set for injury and repair analysis resulted in the separation of acid-injured, heat-injured, and intact cells; repaired cells clustered closer to intact cells when the discriminant analysis (1,800 to 600 cm(-1)) was applied. FT-IR spectroscopy can be used for the rapid source tracking of L. monocytogenes strains because it can differentiate between different mixed strains and individual strains of the pathogen.

Nano/micro and spectroscopic approaches to food pathogen detection

Despite continuing research efforts, timely and simple pathogen detection with a high degree of sensitivity and specificity remains an elusive goal. Given the recent explosion of sensor technologies, significant strides have been made in addressing the various nuances of this important global challenge that affects not only the food industry but also human health. In this review, we provide a summary of the various ongoing efforts in pathogen detection and sample preparation in areas related to Fourier transform infrared and Raman spectroscopy, light scattering, phage display, micro/nanodevices, and nanoparticle biosensors. We also discuss the advantages and potential limitations of the detection methods and suggest next steps for further consideration.

Rapid differentiation of Listeria monocytogenes epidemic clones III and IV and their intact compared with heat-killed populations using Fourier transform infrared spectroscopy and chemometrics

The objectives of this study were to determine if Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis (chemometrics) could be used to rapidly differentiate epidemic clones (ECs) of Listeria monocytogenes, as well as their intact compared with heat-killed populations. FT-IR spectra were collected from dried thin smears on infrared slides prepared from aliquots of 10 μL of each L. monocytogenes ECs (ECIII: J1-101 and R2-499; ECIV: J1-129 and J1-220), and also from intact and heat-killed cell populations of each EC strain using 250 scans at a resolution of 4 cm(-1) in the mid-infrared region in a reflectance mode. Chemometric analysis of spectra involved the application of the multivariate discriminant method for canonical variate analysis (CVA) and linear discriminant analysis (LDA). CVA of the spectra in the wavelength region 4000 to 600 cm(-1) separated the EC strains while LDA resulted in a 100% accurate classification of all spectra in the data set. Further, CVA separated intact and heat-killed cells of each EC strain and there was 100% accuracy in the classification of all spectra when LDA was applied. FT-IR spectral wavenumbers 1650 to 1390 cm(-1) were used to separate heat-killed and intact populations of L. monocytogenes. The FT-IR spectroscopy method allowed discrimination between strains that belong to the same EC. FT-IR is a highly discriminatory and reproducible method that can be used for the rapid subtyping of L. monocytogenes, as well as for the detection of live compared with dead populations of the organism.

PRACTICAL APPLICATION

Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis can be used for L. monocytogenes source tracking and for clinical case isolate comparison during epidemiological investigations since the method is capable of differentiating epidemic clones and it uses a library of well-characterized strains. The FT-IR method is potentially less expensive and more rapid compared to genetic subtyping methods, and can be used for L. monocytogenes strain typing by food industries and public health agencies to enable faster response and intervention to listeriosis outbreaks. FT-IR can also be applied for routine monitoring of the pathogen in food processing plants and for investigating postprocessing contamination because it is capable of differentiating heat-killed and viable L. monocytogenes populations.

Zinc oxide microrods and nanorods: different antibacterial activity and their mode of action against Gram-positive bacteria

ZnO micro and nanorods, produced through simple and inexpensive techniques, resulted to be strong antimicrobials against Gram-positive bacteria, in vitro as well as in vivo, by altering cell outer structures like membrane and exopolysaccharides.

Diverse high-risk B2 and D Escherichia coli clones depicted by Fourier Transform Infrared Spectroscopy

We aimed to develop a reliable method based on Fourier transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) to discriminate Escherichia coli clones from B2(n = 9) and D(n = 13) phylogenetic groups. Eighty-eight E. coli isolates belonging to phylogenetic groups B2(n = 39) and D(n = 49), including particularly widespread high risk clones or clonal complexes (HiRCC) ST131, ST69, ST393 and ST405 were studied. Spectra were analysed by unsupervised (hierarchical cluster analysis-HCA) and supervised methods (soft independent modelling of class analogy-SIMCA and partial least square discriminant analysis-PLSDA). B2-ST131 isolates were discriminated from B2 non-ST131 and D phylogroup isolates (ST69, ST393, ST405) by HCA, SIMCA and PLSDA. D-ST69, D-ST393 and D-ST405 isolates were also distinguished from each other and from other STs from phylogroup D by the three methods. We demonstrate that FTIR-ATR coupled with chemometrics is a reliable and alternative method to accurately discriminate particular E. coli clones. Its validation towards an application at a routine basis could revolutionize high-throughput bacterial typing.

Collaborative survey on the colonization of different types of cheese-processing facilities with Listeria monocytogenes

Cross-contamination via equipment and the food-processing environment has been implicated as the main cause of Listeria monocytogenes transmission. The aim of this study, therefore, was to determine the occurrence and potential persistence of L. monocytogenes in 19 European cheese-processing facilities. A sampling approach in 2007-2008 included, respectively, 11 and two industrial cheese producers in Austria and the Czech Republic, as well as six Irish on-farm cheese producers. From some of the producers, isolates were available from sampling before 2007. All isolates from both periods were included in a strain collection consisting of 226 L. monocytogenes isolates, which were then typed by serotyping and pulsed-field gel electrophoresis (PFGE). In addition, metabolic fingerprints from a subset of isolates were obtained by means of Fourier-transform infrared (FTIR) spectroscopy. PFGE typing showed that six processing environments were colonized with seven persistent PFGE types of L. monocytogenes. Multilocus sequence typing undertaken on representatives of the seven persisting PFGE types grouped them into distinct clades on the basis of country and origin; however, two persistent strains from an Austrian and an Irish food processor were shown to be clonal. It was concluded that despite the fact that elaborate Hazard Analysis and Critical Control Point concepts and cleaning programs are applied, persistent occurrence of L. monocytogenes can take place during cheese making. L. monocytogenes sanitation programs could be strengthened by including rapid analytical tools, such as FTIR, which allow prescreening of potentially persistent L. monocytogenes contaminants.

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.