Discrimination of non-typhoid Salmonella serogroups and serotypes by Fourier Transform Infrared Spectroscopy: A comprehensive analysis

Macro-micro exploration on dynamic interaction between aflatoxigenic Aspergillus flavus and maize kernels using Vis/NIR hyperspectral imaging and SEM technology

Aspergillus flavus and its toxic metabolites-aflatoxins infect and contaminate maize kernels, posing a threat to grain safety and human health. Due to the complexity of microbial growth and metabolic processes, dynamic mechanisms among fungal growth, nutrient depletion of maize kernels and aflatoxin production is still unclear. In this study, visible/near infrared (Vis/NIR) hyperspectral imaging (HSI) combined with the scanning electron microscope (SEM) was used to elucidate the critical organismal interaction at kernel (macro-) and microscopic levels. As kernel damage is the main entrance for fungal invasion, maize kernels with gradually aggravated damages from intact to pierced to halved kernels with A. flavus were cultured for 0-120 h. The spectral fingerprints of the A. flavus-maize kernel complex over time were analyzed with principal components analysis (PCA) of hyperspectral images, where the pseudo-color score maps and the loading plots of the first three PCs were used to investigate the dynamic process of fungal infection and to capture the subtle changes in the complex with different hardness of the maize matrix. The dynamic growth process of A. flavus and the interactions of fungus-maize complexes were explained on a microscopic level using SEM. Specifically, fungus morphology, e.g., hyphae, conidia, and conidiophore (stipe) was accurately captured on the microscopic level, and the interaction process between A. flavus and nutrient loss from the maize kernel tissues (i.e., embryo, and endosperm) was described. Furthermore, the growth stage discrimination models based on PLSDA with the results of CCRC = 100 %, CCRV = 97 %, CCRIV = 93 %, and the prediction models of AFB1 based on PLSR with satisfactory performance (R2C = 0.96, R2V = 0.95, R2IV = 0.93 and RPD = 3.58) were both achieved. In conclusion, the results from both macro-level (Vis/NIR-HSI) and micro-level (SEM) assessments revealed the dynamic organismal interactions in A. flavus-maize kernel complex, and the detailed data could be used for modeling, and quantitative prediction of aflatoxin, which would establish a theoretical foundation for the early detection of fungal or toxin contaminated grains to ensure food security.

Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing

The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.

Evaluation of Fourier transform-infrared spectroscopy (FT-IR) as a control measure for nosocomial outbreak investigations

Whole-genome sequencing (WGS) provides greater resolution than other molecular epidemiology strategies and is emerging as a new gold standard approach for microbial strain typing. The Bruker IR Biotyper is designed as a screening tool to identify bacterial isolates that require WGS to establish accurate relationships, but its performance and utility in nosocomial outbreak investigations have not been thoroughly investigated. Here, we evaluated the IR Biotyper by retrospectively examining isolates tested by WGS during investigations of potential nosocomial transmission events or outbreaks. Ninety-eight clinical isolates from 14 different outbreak investigations were examined: three collections of Acinetobacter baumannii (n = 2, n = 9, n = 5 isolates in each collection), one of Escherichia coli (n = 16), two of Pseudomonas aeruginosa (n = 2 and n = 5), two of Serratia marcescens (n = 9 and n = 7), five of Staphylococcus aureus (n = 8, n = 4, n = 3, n = 3, n = 17), and one of Stenotrophomonas maltophilia (n = 8). Linear regression demonstrated a weak, positive correlation between the number of pairwise genome-wide single-nucleotide polymorphisms (SNPs) and IR Biotyper spectral distance values for Gram-positive (r = 0.43, P ≤ 0.0001), Gram-negative (r = 0.1554, P = 0.0639), and all organisms combined (r = 0.342, P ≤ 0.0001). Overall, the IR Biotyper had a positive predictive value (PPV) of 55.81% for identifying strains that were closely related by genomic identity, but a negative predictive value (NPV) of 86.79% for identifying unrelated isolates. When experimentally adjusted cut-offs were applied to A. baumannii, P. aeruginosa, and E. coli, the PPV was 62% for identifying strains that were closely related and the NPV was 100% for identifying unrelated isolates. Implementation of the IR Biotyper as a screening tool in this cohort would have reduced the number of Gram-negative isolates requiring further WGS analysis by 50% and would reduce the number of S. aureus isolates needing WGS resolution by 48%.

Inactivation efficacy and mechanisms of atmospheric cold plasma on Alicyclobacillus acidoterrestris: Insight into the influence of growth temperature on survival

The bactericidal effect of dielectric barrier discharge-atmospheric cold plasma (DBD-ACP, 20, and 30 kV) against Alicyclobacillus acidoterrestris on the saline solution and apple juice was investigated. Results show that DBD-ACP is effective for the inactivation of A. acidoterrestris by causing significant changes in cell membrane permeability and bacterial morphology. The effect of culture temperatures on the resistance of A. acidoterrestris to DBD-ACP was also studied. A. acidoterrestris cells grown at 25°C had the lowest resistance but it was gradually increased as the culture temperature was increased (25–45°C) (p < 0.05). Moreover, results from Fourier transform infrared spectroscopy (FT-IR) and Gas Chromatography-Mass Spectrometer (GC-MS) analysis showed that the increase in the culture temperature can gradually cause the decreased level of cyclohexaneundecanoic acid in the cell membrane of A. acidoterrestris (p < 0.05). In contrast, cyclopentaneundecanoic acid, palmitic acid, and stearic acid showed an increasing trend in which the fluidity of the bacterial cell membrane decreased. This study shows a specific correlation between the resistance of A. acidoterrestris and the fatty acid composition of the cell membrane to DBD-ACP.

Machine learning-based typing of Salmonella enterica O-serogroups by the Fourier-Transform Infrared (FTIR) Spectroscopy-based IR Biotyper system

BACKGROUND

Salmonella enterica is among the major burdens for public health at global level. Typing of salmonellae below the species level is fundamental for different purposes, but traditional methods are expensive, technically demanding, and time-consuming, and therefore limited to reference centers. Fourier transform infrared (FTIR) spectroscopy is an alternative method for bacterial typing, successfully applied for classification at different infra-species levels.

AIM

This study aimed to address the challenge of subtyping Salmonella enterica at O-serogroup level by using FTIR spectroscopy. We applied machine learning to develop a novel approach for S. enterica typing, using the FTIR-based IR Biotyper® system (IRBT; Bruker Daltonics GmbH & Co. KG, Germany). We investigated a multicentric collection of isolates, and we compared the novel approach with classical serotyping-based and molecular methods.

METHODS

A total of 958 well characterized Salmonella isolates (25 serogroups, 138 serovars), collected in 11 different centers (in Europe and Japan), from clinical, environmental and food samples were included in this study and analyzed by IRBT. Infrared absorption spectra were acquired from water-ethanol bacterial suspensions, from culture isolates grown on seven different agar media. In the first part of the study, the discriminatory potential of the IRBT system was evaluated by comparison with reference typing method/s. In the second part of the study, the artificial intelligence capabilities of the IRBT software were applied to develop a classifier for Salmonella isolates at serogroup level. Different machine learning algorithms were investigated (artificial neural networks and support vector machine). A subset of 88 pre-characterized isolates (corresponding to 25 serogroups and 53 serovars) were included in the training set. The remaining 870 samples were used as validation set. The classifiers were evaluated in terms of accuracy, error rate and failed classification rate.

RESULTS

The classifier that provided the highest accuracy in the cross-validation was selected to be tested with four external testing sets. Considering all the testing sites, accuracy ranged from 97.0% to 99.2% for non-selective media, and from 94.7% to 96.4% for selective media.

CONCLUSIONS

The IRBT system proved to be a very promising, user-friendly, and cost-effective tool for Salmonella typing at serogroup level. The application of machine learning algorithms proved to enable a novel approach for typing, which relies on automated analysis and result interpretation, and it is therefore free of potential human biases. The system demonstrated a high robustness and adaptability to routine workflows, without the need of highly trained personnel, and proving to be suitable to be applied with isolates grown on different agar media, both selective and unselective. Further tests with currently circulating clinical, food and environmental isolates would be necessary before implementing it as a potentially stand-alone standard method for routine use.

Validation of Fourier Transform Infrared Spectroscopy for Serotyping of Streptococcus pneumoniae

Fourier transform infrared (FT-IR) spectroscopy (IR Biotyper; Bruker) allows highly discriminatory fingerprinting of closely related bacterial strains. In this study, FT-IR spectroscopy-based capsular typing of Streptococcus pneumoniae was validated as a rapid, cost-effective, and medium-throughput alternative to the classical phenotypic techniques. A training set of 233 strains was defined, comprising 34 different serotypes and including all 24 vaccine types (VTs) and 10 non-vaccine types (NVTs). The acquired spectra were used to (i) create a dendrogram where strains clustered together according to their serotypes and (ii) train an artificial neural network (ANN) model to predict unknown pneumococcal serotypes. During validation using 153 additional strains, we reached 98.0% accuracy for determining serotypes represented in the training set. Next, the performance of the IR Biotyper was assessed using 124 strains representing 59 non-training set serotypes. In this setting, 42 of 59 serotypes (71.1%) could be accurately categorized as being non-training set serotypes. Furthermore, it was observed that comparability of spectra was affected by the source of the Columbia medium used to grow the pneumococci and that this complicated the robustness and standardization potential of FT-IR spectroscopy. A rigorous laboratory workflow in combination with specific ANN models that account for environmental noise parameters can be applied to overcome this issue in the near future. The IR Biotyper has the potential to be used as a fast, cost-effective, and accurate phenotypic serotyping tool for S. pneumoniae.

Application of Fourier transform infrared spectroscopy for real-time typing of Acinetobacter baumannii outbreak in intensive care unit

Aim: Acinetobacter baumannii is a pathogen of serious concern, often exhibiting multiple antibiotic resistance, frequently associated with hospital outbreaks in intensive care units. A prompt detection and tracking of these isolates is crucial. Reference methods for typing (pulsed-field gel electrophoresis, whole-genome sequencing) are accurate, but expensive and time-consuming, therefore limited to retrospective analysis. Materials & methods: In this study, the application of the FTIR-based IR Biotyper^® (IRBT) to track and monitor in real-time the spread of a multidrug-resistant A. baumannii outbreak was investigated. The index case and the multidrug-resistant A. baumannii isolates collected in the following 3 weeks were investigated. Results: IR Biotyper^® clustering results were fully confirmed by pulsed-field gel electrophoresis results. Conclusions: IR Biotyper represent a promising tool for real-time hospital hygiene, enabling a prompt and reliable typing.

Investigation and Rapid Discrimination of Food-Related Bacteria under Stress Treatments Using IR Microspectroscopy

Because the robust and rapid determination of spoilage microorganisms is becoming increasingly important in industry, the use of IR microspectroscopy, and the establishment of robust and versatile chemometric models for data processing and classification, is gaining importance. To further improve the chemometric models, bacterial stress responses were induced, to study the effect on the IR spectra and to improve the chemometric model. Thus, in this work, nine important food-relevant microorganisms were subjected to eight stress conditions, besides the regular culturing as a reference. Spectral changes compared to normal growth conditions without stressors were found in the spectral regions of 900-1500 cm^-1 and 1500-1700 cm^-1. These differences might stem from changes in the protein secondary structure, exopolymer production, and concentration of nucleic acids, lipids, and polysaccharides. As a result, a model for the discrimination of the studied microorganisms at the genus, species and strain level was established, with an accuracy of 96.6%. This was achieved despite the inclusion of various stress conditions and times after incubation of the bacteria. In addition, a model was developed for each individual microorganism, to separate each stress condition or regular treatment with 100% accuracy.

From farm to fork: Colistin voluntary withdrawal in Portuguese farms reflected in decreasing occurrence of mcr-1-carrying Enterobacteriaceae from chicken meat

Expansion of mcr-carrying Enterobacteriaceae (MCR-E) is a well-recognized problem affecting animals, humans and the environment. Ongoing global control actions involve colistin restrictions among food-animal production, but their impact on poultry-derived products is largely unknown, justifying comprehensive farm-to-fork studies. Occurrence of MCR-E among 53 chicken-meat batches supplied from 29 Portuguese farms shortly after colistin withdrawal was evaluated. Strains (FT-IR/MLST/WGS), mcr plasmids and their adaptive features were characterized by cultural, molecular and genomic approaches. We found high rates of chicken-meat batches (80%-100% - 4 months; 12% - the last month) with multiple MDR + mcr-1-carrying Escherichia coli (Ec-including ST117 and ST648-Cplx) and Klebsiella pneumoniae (Kp-ST147-O5:K35) clones, some of them persisting over time. The mcr-1 was located in the chromosome (Ec-ST297/16-farms) or dispersed IncX4 (Ec-ST602/ST6469/5-farms), IncHI2-ST2/ST4 (Ec-ST533/ST6469/5 farms and Kp-ST147/6-farms) or IncI2 (Ec-ST117/1-farm) plasmids. WGS revealed high load and diversity in virulence, antibiotic resistance and metal tolerance genes. This study supports colistin withdrawal potential efficacy in poultry production and highlights both poultry-production chain as a source of mcr-1 and the risk of foodborne transmission to poultry-meat consumers. Finally, in the antibiotic reduction/replacement context, other potential co-selective pressures (e.g., metals-Cu as feed additives) need to be further understood to guide concerted, effective and durable actions under 'One Health' perspective.

Evaluation of the IR Biotyper for Klebsiella pneumoniae typing and its potentials in hospital hygiene management

Klebsiella pneumoniae has emerged as one of the most important pathogens that frequently encounter in community-acquired or hospital-acquired infections. Timely epidemiological surveillance could greatly facilitate infection control of K. pneumoniae and many deadly pathogens alike. In this study, we evaluated the performance of the IR Biotyper, a Fourier transform infrared (FTIR) spectroscopy system for K. pneumoniae isolates typing through (i) optimizing the culture scheme and defining the cutoff value (COV) range and (ii) comparing with commonly used typing tools such as multi-locus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing (WGS). We found that a non-selective and non-chromogenic medium with 24 ± 2 h incubation gives the best discriminatory power for the IR Biotyper (IRBT). COV evaluation indicated that the IRBT is a robust typing method with good reproducibility. Besides, we observed that the modified H2 O-EtOH suspensions preparation method could enhance the quality of the spectrum, especially for those hypermucoviscous strains. For the method comparison study, our data demonstrated that FTIR spectroscopy could accurately cluster K. pneumoniae strains. The typing results of the IRBT were almost entirely in concordance with those from PFGE and WGS. Together with the advantages such as low costs and short turnaround time (less than 3h), the IRBT is a promising tool for strain typing that could make real-time outbreak investigation a reality.

Classification of Salmonella enterica of the (Para-)Typhoid Fever Group by Fourier-Transform Infrared (FTIR) Spectroscopy

Typhoidal and para-typhoidal Salmonella are major causes of bacteraemia in resource-limited countries. Diagnostic alternatives to laborious and resource-demanding serotyping are essential. Fourier transform infrared spectroscopy (FTIRS) is a rapidly developing and simple bacterial typing technology. In this study, we assessed the discriminatory power of the FTIRS-based IR Biotyper (Bruker Daltonik GmbH, Bremen, Germany), for the rapid and reliable identification of biochemically confirmed typhoid and paratyphoid fever-associated Salmonella isolates. In total, 359 isolates, comprising 30 S. Typhi, 23 S. Paratyphi A, 23 S. Paratyphi B, and 7 S. Paratyphi C, respectively and other phylogenetically closely related Salmonella serovars belonging to the serogroups O:2, O:4, O:7 and O:9 were tested. The strains were derived from clinical, environmental and food samples collected at different European sites. Applying artificial neural networks, specific automated classifiers were built to discriminate typhoidal serovars from non-typhoidal serovars within each of the four serogroups. The accuracy of the classifiers was 99.9%, 87.0%, 99.5% and 99.0% for Salmonella Typhi, Salmonella Paratyphi A, B and Salmonella Paratyphi C, respectively. The IR Biotyper is a promising tool for fast and reliable detection of typhoidal Salmonella. Hence, IR biotyping may serve as a suitable alternative to conventional approaches for surveillance and diagnostic purposes.

Rapid detection and discrimination of food-related bacteria using IR-microspectroscopy in combination with multivariate statistical analysis

Spoilage microorganisms are of great concern for the food industry. While traditional culturing methods for spoilage microorganism detection are laborious and time-consuming, the development of early detection methods has gained a lot of interest in the last decades. In this work a rapid and non-destructive detection and discrimination method of eight important food-related microorganisms (Bacillus subtilis DSM 10, Bacillus coagulans DSM 1, Escherichia coli K12 DSM 498, Escherichia coli TOP10, Micrococcus luteus DSM 20030, Pseudomonas fluorescens DSM 4358, Pseudomonas fluorescens DSM 50090 and Bacillus thuringiensis israelensis DSM 5724) based on IR-microspectroscopy and chemometric evaluation was developed. Sampling was carried out directly from the surface to be tested, without the need for sample preparation such as purification, singulation, centrifugation and washing steps, as an efficient and inexpensive blotting technique using the sample carrier. IR spectra were recorded directly after the blotting from the surface of the sample carrier without any further pretreatments. A combination of data preprocessing, principal component analysis and canonical discriminant analysis was found to be suitable. The spectral range from 400 to 1750 cm^-1 of the IR-microspectrosopic data was determined to be highly sensitive to the time after incubation and sample thickness, resulting in a high standard deviation. Therefore, this area was excluded from the evaluation in favor of the meaningfulness of the chemometric model and, thus, only the spectral range of specific -CH/-NH/-OH excitations (2815-3680 cm^-1) was used for model development. This study showed that the differentiation of food-related microorganisms on genera, species and strain level is feasible. A leave-one-out cross-validation of the training data set showed 100% accuracy. The classification of the ungrouped test data showed with an accuracy of 94.5% that, despite the large biological variance of the analytes such as different times after incubation and the presented sampling (including its variance), a robust and meaningful model for the differentiation of food-related bacteria could be developed by data preprocessing and subsequent chemometric evaluation.

Toxicity mechanism of Cu2+ ion individually and in combination with Zn2+ ion in characterizing the molecular changes of Staphylococcus aureus studied using FTIR coupled with chemometric analysis

Copper and zinc have a high binding affinity with a Staphylococcus aureus bacterial community. This causes a change in the biomolecular composition of S. aureus. Our study aims at understanding the resistance mechanism of Cu and Zn either or in various combinations using FTIR and chemometric techniques. Zn toxicity resulted in a significant change in lipid content (3100-2800 cm^-1) compared to Cu. A significant decrease in protein content is observed for Cu treatment in the amide region. The bio-concentration factor shows a higher value for Cu compared to Zn. The increase in band area of carbohydrates moieties 1059 cm^-1 shows the secretion of EPS due to Cu toxicity. A significant change in nucleic acid compositions was noted in the region1200-900 cm^-1 due to Zn treatment. Secondary structural change in protein shows β sheet formation. The result of the finding shows Cu has greater toxicity than Zn. Further toxicity effects were greatly enhanced for metal mixtures ratio (Cu:2Zn). This shows Zn exhibits synergism effect with Cu. The obtained ROC (receiver operating characteristic) curve area gives good reliability of the experiments. The study attempts to understand the mechanism of toxicity removal of Cu and Zn metal mixtures by bacterial population using FTIR coupled with chemometric techniques. Graphical abstract.

Artificial neural network-assisted Fourier transform infrared spectroscopy for differentiation of Salmonella serogroups and its application on epidemiological tracing of Salmonella Bovismorbificans outbreak isolates from fresh sprouts

Salmonellae represent one of the most common bacterial infection reagents in both humans and animals. For detection and epidemiological elucidation of Salmonella infections, determination of Salmonella serotypes and differentiation between different Salmonella isolates is crucial. In the first part of this study, Artificial Neural Network (ANN)-assisted Fourier transform infrared (FTIR) spectroscopy was used to establish a method for subtyping Salmonella isolates according to their serogroups. For this, 290 Salmonella strains from 35 different serogroups were used to establish an ANN for differentiation between infrared spectra of 10 different Salmonella serogroups (B, C1, C2-C3, D1/D2, E1, E4, F, G, H, O:55) vs. the remaining serogroups. In the final ANN, sensitivity values ranged between 90 and 100% for most of the 10 serogroups under investigation. In the second part of this study, ANN-assisted FTIR spectroscopy was applied for epidemiological distinction of Salmonella Bovismorbificans outbreak isolates from fresh sprouts vs. isolates from other sources. Four Salmonella Bovismorbificans isolates from human and food origin in the context of a Southern German outbreak were successfully discriminated from other S. Bovismorbificans isolates from various sources. ANN-assisted FTIR spectroscopy is thus an effective tool for discrimination of Salmonella isolates at or even below serogroup level.

Prevalence and Characteristics of Bacillus cereus Group Isolated from Raw and Pasteurised Milk

The elimination of spore-forming bacteria is not guaranteed by current pasteurisation processes and is a challenging problem for the dairy industry. Given that Bacillus cereus sensu lato (B. cereus group) is an important foodborne pathogen and spoiler in the dairy industry, this study aimed at evaluating the prevalence and characteristics of B. cereus group in raw and pasteurised milk samples collected in Victoria, Australia. Isolated B. cereus group were tested for antimicrobial susceptibility, biofilm formation and virulence properties. Genetic diversity was assessed using ERIC-PCR. Proteomic profiling using MALDI-TOF MS and chemical profiling using Fourier-transform infrared (FTIR) spectroscopy were also applied for clustering of the isolates. Results showed 42.3% of milk samples contained B. cereus group, with a higher contamination level for pasteurised milk. Virulence studies identified genes nheA, nheB, hblA and nheC in most isolates and cyk gene in 46% of all isolates. Antimicrobial susceptibility testing showed a high prevalence of resistance towards ampicillin, ceftriaxone and penicillin. The biofilm-forming capacity of our isolates showed that most (53.7%) had the ability to form a biofilm. Genetic profiling using ERIC-PCR placed most B. cereus group isolates from pasteurised milk in the same cluster, indicating that they probably originated from a similar source. Raw milk isolates showed greater diversity indicating various sources. FTIR spectroscopy showed high agreement with genetic profiling. In contrast, low agreement between proteomic (MALDI-TOF MS) and genetic typing was observed. The present study showed that the FTIR spectroscopy could be adopted as a rapid tool for the typing of B. cereus group. Overall, the virulence and antimicrobial resistance characteristics, together with the ability of isolates to produce biofilm, indicate the importance of B. cereus group in the Australian dairy industry.

A Front Line on Klebsiella pneumoniae Capsular Polysaccharide Knowledge: Fourier Transform Infrared Spectroscopy as an Accurate and Fast Typing Tool

Klebsiella pneumoniae is nowadays recognized as one of the most defiant human pathogens, whose infections are increasingly more challenging to treat and control. Whole-genome sequencing (WGS) has been key for clarifying the population structure of K. pneumoniae, and it is still instrumental to provide insights into potential pathogenicity and evolutionary markers, such as the capsular locus. However, this information and WGS are still far from being accessible and translated into routine clinical microbiology laboratories as quick and cost-efficient strain diagnostic tools. Here, we propose a biochemical fingerprinting approach based on Fourier transform infrared spectroscopy (FT-IR) and multivariate data analysis tools for K. pneumoniae capsular typing that, because of its high resolution, speed, and low cost, can be an asset to provide enough information to support real-time epidemiology and infection control decisions. Besides, it provides a simple framework for phenotypic/biochemical validation of K. pneumoniae capsular diversity.

Genomics-based population analysis of multidrug-resistant (MDR) Klebsiella pneumoniae motivated a renewed interest on the capsule as an evolutionary and virulence marker of clinically relevant strains. Whole-genome sequencing (WGS)-based approaches have provided great insights into the genetic variability of the capsular locus, but genotypic-biochemical capsular (K)-type correlations are lacking, hindering the establishment of a reliable framework for K-type characterization and typing. To fill this gap, we combined molecular, comparative genomics, and multivariate data analysis tools with biochemical data on the capsular locus to support the usefulness of Fourier transform infrared (FT-IR) spectroscopy as a reliable K typing tool. To validate our approach, we used a representative collection of well-defined MDR K. pneumoniae lineages involved in local or nationwide epidemics in multiple countries. With this, we demonstrate a high accuracy and resolution of our FT-IR-based spectroscopy approach for K-type discrimination that is even higher than that provided by WGS. Moreover, the specific associations established between certain K types and specific K. pneumoniae lineages with high clinical relevance, together with the accuracy, simplicity, short time to result, and inexpensive features of the method, support the value of the developed FT-IR-based approach for an easy, fast, and cost-effective strain typing. This fulfills a still unmet need for tools to support real-time monitoring and control of K. pneumoniae infections. In addition, the genotypic-biochemical correlations established provide insights on sugar composition/structure of newly defined K. pneumoniae capsular types.

IMPORTANCEKlebsiella pneumoniae is nowadays recognized as one of the most defiant human pathogens, whose infections are increasingly more challenging to treat and control. Whole-genome sequencing (WGS) has been key for clarifying the population structure of K. pneumoniae, and it is still instrumental to provide insights into potential pathogenicity and evolutionary markers, such as the capsular locus. However, this information and WGS are still far from being accessible and translated into routine clinical microbiology laboratories as quick and cost-efficient strain diagnostic tools. Here, we propose a biochemical fingerprinting approach based on Fourier transform infrared spectroscopy (FT-IR) and multivariate data analysis tools for K. pneumoniae capsular typing that, because of its high resolution, speed, and low cost, can be an asset to provide enough information to support real-time epidemiology and infection control decisions. Besides, it provides a simple framework for phenotypic/biochemical validation of K. pneumoniae capsular diversity.

Escherichia coli and Salmonella Enteritidis dual-species biofilms: interspecies interactions and antibiofilm efficacy of phages

Escherichia coli and Salmonella Enteritidis are foodborne pathogens forming challenging biofilms that contribute to their virulence, antimicrobial resistance, and survival on surfaces. Interspecies interactions occur between species in mixed biofilms promoting different outcomes to each species. Here we describe the interactions between E. coli and S. Enteritidis strains, and their control using specific phages. Single-species biofilms presented more cells compared to dual-species biofilms. The spatial organization of strains, observed by confocal microscopy, revealed similar arrangements in both single- and dual-species biofilms. The EPS matrix composition, assessed by Fourier-transform infrared spectroscopy, disclosed that the spectra extracted from the different dual-species biofilms can either be a combination of both species EPS matrix components or that the EPS matrix of one species predominates. Phages damaged more the single-species biofilms than the mixed biofilms, showing also that the killing efficacy was greatly dependent on the phage growth characteristics, bacterial growth parameters, and bacterial spatial distribution in biofilms. This combination of methodologies provides new knowledge of species-species and phage-host interactions in biofilms of these two major foodborne pathogens.

Fourier-Transform Infrared (FTIR) Spectroscopy for Typing of Clinical Enterobacter cloacae Complex Isolates

Members of the Enterobacter (E.) cloacae complex have emerged as important pathogens frequently encountered in nosocomial infections. Several outbreaks with E. cloacae complex have been reported in recent years, especially in neonatal units. Fast and reliable strain typing methods are crucial for real-time surveillance and outbreak analysis to detect pathogen reservoirs and transmission routes. The aim of this study was to evaluate the performance of Fourier-transform infrared (FTIR) spectroscopy as a fast method for typing of clinical E. cloacae complex isolates, when whole genome sequencing (WGS) analysis was used as reference. First, the technique was used retrospectively on 24 first isolates of E. cloacae complex strains from neonatal patients and showed good concordance with SNP-based clustering [adjusted rand index (ARI) = 0.818] and with the sequence type (ST) (ARI = 0.801). 29 consecutive isolates from the same patients were shown by WGS analysis to almost always belong to the same SNP cluster as the first isolates, which was only inconsistently recognized by FTIR spectroscopy. Training of an artificial neural network (ANN) with all FTIR spectra from sequenced strains markedly improved the recognition of related and unrelated isolate spectra. In a second step, FTIR spectroscopy was applied on 14 strains during an outbreak with E. cloacae complex and provided fast typing results that were confirmed by WGS analysis. In conclusion, FTIR spectroscopy is a promising tool for strain typing of clinical E. cloacae complex strains. Discriminatory power can be improved by implementing an ANN for spectrum analysis. Due to its low costs and fast turnaround times, the method presents a valuable tool for real-time surveillance as well as outbreak analysis.