Investigation of the effect of different environmental conditions on biofilm structure of Salmonella enterica serotype Virchow via FTIR spectroscopy

Comparative analysis of biofilm structures in Salmonella Typhimurium DMC4 strain and its dam and seqA gene mutants using Fourier transform infrared spectroscopy (FT-IR) and Raman spectroscopy methods

It is well-established that the dam and seqA genes act in the biofilm production in Salmonella. However, the molecular basis underlying this activity remains unexplored. This study aims to address this gap in the literature. In this study, comparative Fourier Transform Infrared (FT-IR) Spectroscopy and Raman spectral analyses were conducted to investigate the molecular basis of decreases in swimming, swarming motility, and biofilm characteristics observed in the dam and seqA gene mutants of S. Typhimurium DMC4 wild-type strain. The comparative analysis revealed a pronounced reduction in proteins, lipids, carbohydrates, and nucleic acids within the biofilm structures of mutant strains. These findings confirm that these macromolecules are crucial for the integrity and functionality of biofilm structures. FT-IR analysis showed that while amide-I bands decreased in the biofilm structures of mutant strains, amide-II bands increased compared to the wild-type strain. Similarly, Raman analyses indicated an increase in amide-IV bonds and a decrease in amide-V bonds. The parallelism between FT-IR and Raman spectral analysis results, particularly regarding amide I, amide V, amide II, and amide IV bands, is noteworthy. Additionally, these findings may lead to the development of markers for rapidly diagnosing transitions from planktonic to biofilm form in Salmonella. The substantial decrease in β-glucans and lipids, including cellulose, within the biofilm matrix of mutant strains highlights the critical role these polymers play in swimming and swarming motility. Given the clinical and industrial importance of Salmonella biofilms, it is crucial to develop strategies to prevent biofilm formation and identify target molecules that can inhibit biofilm formation. The results of our study suggest that β-glucans and amides are essential targets in the effort to combat Salmonella biofilms.

Artificial Intelligence-Driven Analysis of Antimicrobial-Resistant and Biofilm-Forming Pathogens on Biotic and Abiotic Surfaces

The growing threat of antimicrobial-resistant (AMR) pathogens to human health worldwide emphasizes the need for more effective infection control strategies. Bacterial and fungal biofilms pose a major challenge in treating AMR pathogen infections. Biofilms are formed by pathogenic microbes encased in extracellular polymeric substances to confer protection from antimicrobials and the host immune system. Biofilms also promote the growth of antibiotic-resistant mutants and latent persister cells and thus complicate therapeutic approaches. Biofilms are ubiquitous and cause serious health risks due to their ability to colonize various surfaces, including human tissues, medical devices, and food-processing equipment. Detection and characterization of biofilms are crucial for prompt intervention and infection control. To this end, traditional approaches are often effective, yet they fail to identify the microbial species inside biofilms. Recent advances in artificial intelligence (AI) have provided new avenues to improve biofilm identification. Machine-learning algorithms and image-processing techniques have shown promise for the accurate and efficient detection of biofilm-forming microorganisms on biotic and abiotic surfaces. These advancements have the potential to transform biofilm research and clinical practice by allowing faster diagnosis and more tailored therapy. This comprehensive review focuses on the application of AI techniques for the identification of biofilm-forming pathogens in various industries, including healthcare, food safety, and agriculture. The review discusses the existing approaches, challenges, and potential applications of AI in biofilm research, with a particular focus on the role of AI in improving diagnostic capacities and guiding preventative actions. The synthesis of the current knowledge and future directions, as described in this review, will guide future research and development efforts in combating biofilm-associated infections.

High Salmonella load with serovar virchow dominance pose major public safety risk in postchill broiler carcasses

The objective of this study was to determine Salmonella contamination levels, presence and serovar distribution in broiler carcasses before and after chilling, as well as to evaluate the effectiveness of chilling process. A total of 96 pooled neck skin samples (PNSS) of 48 prechill (PreC) and 48 postchill (PosC) carcasses, representing 480 broilers collected in 6 mo' period were analyzed using ISO 6579-2:2012 Miniaturized Most Probable Number (ISO-mMPN) technique. Species confirmation and serovar identification was performed by Salmonella-specific real-time PCR (Salm-PCR) and conventional serotyping, respectively. Mean Salmonella count was 1.84 log10 MPN/g in PreC, and 1.48 log10 MPN/g in PosC samples, indicating a statistically significant reduction of 0.36 log10 MPN/g (p < 0.05) in the counts by plant's air chill system. Salmonella positivity reduced from 97.9% (47/48) in PreC to 85.42% (41/48) in PosC samples, confirmed by Salm-PCR with identified serovars as S. Virchow (89.77 %) followed by S. Schwarzengrund (9.09%) and S. Bredeney (1.14%). Persistence of high load and prevalence of Salmonella with serovar Virchow dominance (other than the ones mandated in current guidelines) in the final product contributes significant and up to date data to relevant literature, and provides unbiased epidemiological reference to legal authorities for future relevant revisions.

Investigating the chemical pathway to the formation of a single biofilm using infrared spectroscopy

Diagnosing biofilm infections has remained a constant challenge for the last 50 years. Existing diagnostic methods struggle to identify the biofilm phenotype. Moreover, most methods of biofilm analysis destroy the biofilm making the resultant data interpretation difficult. In this study we introduce Fourier Transform Infra-Red (FTIR) spectroscopy as a label-free, non-destructive approach to monitoring biofilm progression. We have utilised FTIR in a novel application to evaluate the chemical composition of bacterial biofilms without disrupting the biofilm architecture. S. epidermidis (RP62A) was grown onto calcium fluoride slides for periods of 30 min-96 h, before semi-drying samples for analysis. We report the discovery of a chemical marker to distinguish between planktonic and biofilm samples. The appearance of new proteins in biofilm samples of varying maturity is exemplified in the spectroscopic data, highlighting the potential of FTIR for identifying the presence and developmental stage of a single biofilm.

A Technological Understanding of Biofilm Detection Techniques: A Review

Biofouling is a persistent problem in almost any water-based application in several industries. To eradicate biofouling-related problems in bioreactors, the detection of biofilms is necessary. The current literature does not provide clear supportive information on selecting biofilm detection techniques that can be applied to detect biofouling within bioreactors. Therefore, this research aims to review all available biofilm detection techniques and analyze their characteristic properties to provide a comparative assessment that researchers can use to find a suitable biofilm detection technique to investigate their biofilms. In addition, it discusses the confluence of common bioreactor fabrication materials in biofilm formation.