Species-Level Discrimination of Psychrotrophic Pathogenic and Spoilage Gram-Negative Raw Milk Isolates Using a Combined MALDI-TOF MS Proteomics–Bioinformatics-based Approach

The usefulness of the MALDI-TOF MS technique in the determination of dairy samples' microbial composition: comparison of the new EXS 2600 system with MALDI Biotyper platform

This study compared the EXS 2600 system with the MALDI Biotyper for identifying microorganisms in dairy samples. Of the 196 bacterial isolates from milk, whey, buttermilk, cream, and dairy wastewater, the species and genus consistent identification between two systems showed 74% and 99%, respectively. However, the level of species identification rate exhibited a difference, which was higher in Zybio than in Bruker-76.0% and 66.8%, respectively. Notably, the EXS 2600 system performed better with certain yeast species and H. alvei, while the Biotyper excelled with Pseudomonas bacteria. Unique microbial compositions were found in 85% of dairy samples, with whey and buttermilk having the highest diversity. This research highlights the EXS 2600's potential as a reliable dairy microbial identification tool and underscores the need for a more diverse and comprehensive spectral database, despite the database's focus on clinical applications (as announced).

A Combination of MALDI-TOF MS Proteomics and Species-Unique Biomarkers' Discovery for Rapid Screening of Brucellosis

Brucellosis is considered to be a zoonotic infection with a predominant incidence in most parts of Iran that may even simply involve diagnostic laboratory personnel. In the present study, we apply matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for rapid and reliable discrimination of Brucella abortus and Brucella melitensis, based on proteomic mass patterns from chemically treated whole-cell analyses. Biomarkers of the low molecular weight proteome in the MALDI-TOF MS spectra were assigned to conserved ribosomal and structural protein families that were found in genome assemblies of B. abortus and B. melitensis in the NCBI database. Significant protein mass signals successfully mapped to ribosomal proteins and structural proteins, such as integration host factor subunit alpha, cold-shock proteins, HU family DNA-binding protein, ATP synthase subunit C, and GNAT family N-acetyltransferase, with specific biomarker peaks that have been identified for each virulent and vaccine strain. Web-accessible bioinformatics algorithms, with a robust data analysis workflow, followed by ribosomal and structural protein mapping, significantly enhanced the reliable assignment of key proteins and accurate identification of Brucella species. Furthermore, clinical samples were analyzed to confirm the most dominant protein biomarker candidates and their relevance for the identifications of B. melitensis and B. abortus. With proper optimization, we envision that the presented MALDI-TOF MS proteomics analyses, coupled with special usage of bioinformatics, could be used as a cost-efficient strategy for the diagnostics of brucellosis and introduce a reliable identification protocol for species of dangerous bacteria.

Biological silicon nanoparticles improve Phaseolus vulgaris L. yield and minimize its contaminant contents on a heavy metals-contaminated saline soil

The synthesis of biological silicon nano-particles (Bio-Si-NPs) is an eco-friendly and low-cost method. There is no study focusing on the effect of Bio-Si-NPs on the plants grown on saline soil contaminated with heavy metals. In this study, an attempt was made to synthesis Bio-Si-NPs using potassium silica florid substrate, and the identified Aspergillus tubingensis AM11 isolate that separated from distribution systems of the potable water. A two-year field trial was conducted to compare the protective effects of Bio-Si-NPs (2.5 and 5.0 mmol/L) and potassium silicate (10 mmol/L) as a foliar spray on the antioxidant defense system, physio-biochemical components, and the contaminants contents of Phaseolus vulgaris L. grown on saline soil contaminated with heavy metals. Our findings showed that all treatments of Bio-Si-NPs and potassium silicate significantly improved plant growth and production, chlorophylls, carotenoids, transpiration rate, net photosynthetic rate, stomatal conductance, membrane stability index, relative water content, free proline, total soluble sugars, N, P, K, Ca²⁺, K⁺/Na⁺, and the activities of peroxidase, catalase, ascorbic peroxidase and superoxide oxide dismutase. Application of Bio-Si-NPs and potassium silicate significantly decreased electrolyte leakage, malondialdehyde, H₂O₂, O₂^•-, Na⁺, Pb, Cd, and Ni in leaves and pods of Phaseolus vulgaris L. compared to control. Bio-Si-NPs were more effective compared to potassium silicate. Application of Bio-Si-NPs at the rate of 5 mmol/L was the recommended treatment to enhance the performance and reduce heavy metals content on plants grown on contaminated saline soils.

MALDI-ToF MS: A Rapid Methodology for Identifying and Subtyping Listeria monocytogenes

Listeria monocytogenes is a major food-borne pathogen and causative agent of a fatal disease, listeriosis. Stringent regulatory guidelines and zero tolerance policy toward this bacterium necessitate rapid, accurate, and reliable methods of identification and subtyping. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS) has recently become a method of choice for routine identification of pathogens in clinical settings and has largely replaced biochemical assays. Identification relies on well-curated databases such as SARAMIS. Extensive use of SARAMIS to generate consensus mass spectra, in conjunction with statistical analysis, such as partial least square-discriminant analysis and hierarchical cluster analysis, is useful in subtyping bacteria. While MALDI-ToF MS has been extensively used for pathogen detection, its application in bacterial subtyping has been limited. The protocol describes a MALDI-ToF MS workflow as a single tool for simultaneous identification and subtyping of L. monocytogenes directly from solid culture medium.

Multispecies biofilm formation by the contaminating microbiota in raw milk

Biofilms can be formed on the surfaces of dairy processing equipment and are a potential source of product contamination. This study evaluated the diversity of multispecies biofilms formed on stainless steel (SS) due to the contaminating microbiota in raw milk. Samples of raw milk were used: one was fresh milk and the other maintained in refrigerated bulk tanks for up to 48 h. The mesophilic aerobic contamination was ∼10⁴ CFU ml^-1 in fresh milk and 10⁶ CFU ml^-1 in bulk milk. SS coupons were kept immersed in the milk at 7 ±2 °C for 10 days, and every two days, the raw milk was changed for samples of the same origin collected on the current day. After incubation for 10 days, sessile cells in the biofilm reached 10⁵ CFU cm^-2 in the presence of fresh milk, and 10⁶ CFU cm^-2 in the presence of bulk milk. The genetic diversity analysis showed that Gammaproteobacteria and Bacilli predominated in the biofilms throughout the incubation of both milk samples and these biofilms showed a reduction in diversity over time. The main classes of bacteria found in these biofilms have representatives of great importance since many of them have spoilage potential.

Current and Emerging Technologies for the Detection of Norovirus from Shellfish

Reports of norovirus infections associated with the consumption of contaminated bivalve molluscan shellfish negatively impact both consumers and commercial shellfish operators. Current virus recovery and PCR detection methods can be expensive and time consuming. Due to the lack of rapid, user-friendly and onsite/infield methods, it has been difficult to establish an effective virus monitoring regime that is able to identify contamination points across the production line (i.e., farm-to-plate) to ensure shellfish quality. The focus of this review is to evaluate current norovirus detection methods and discuss emerging approaches. Recent advances in omics-based detection approaches have the potential to identify novel biomarkers that can be incorporated into rapid detection kits for onsite use. Furthermore, some omics techniques have the potential to simultaneously detect multiple enteric viruses that cause human disease. Other emerging technologies discussed include microfluidic, aptamer and biosensor-based detection methods developed to detect norovirus with high sensitivity from a simple matrix. Many of these approaches have the potential to be developed as user-friendly onsite detection kits with minimal costs. However, more collaborative efforts on research and development will be required to commercialize such products. Once developed, these emerging technologies could provide a way forward that minimizes public health risks associated with shellfish consumption.

Detection of Foodborne Pathogens Using Proteomics and Metabolomics-Based Approaches

Considering the short shelf-life of certain food products such as red meat, there is a need for rapid and cost-effective methods for pathogen detection. Routine pathogen testing in food laboratories mostly relies on conventional microbiological methods which involve the use of multiple selective culture media and long incubation periods, often taking up to 7 days for confirmed identifications. The current study investigated the application of omics-based approaches, proteomics using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF MS) and metabolomics using gas chromatography-mass spectrometry (GC-MS), for detection of three red meat pathogens - Listeria monocytogenes, Salmonella enterica and Escherichia coli O157:H7. Species-level identification was achieved within 18 h for S. enterica and E. coli O157:H7 and 30 h for L. monocytogenes using MALDI-ToF MS analysis. For the metabolomics approach, metabolites were extracted directly from selective enrichment broth samples containing spiked meat samples (obviating the need for culturing on solid media) and data obtained using GC-MS were analyzed using chemometric methods. Putative biomarkers relating to L. monocytogenes, S. enterica and E. coli O157:H7 were observed within 24, 18, and 12 h, respectively, of inoculating meat samples. Many of the identified metabolites were sugars, fatty acids, amino acids, nucleosides and organic acids. Secondary metabolites such as cadaverine, hydroxymelatonin and 3,4-dihydroxymadelic acid were also observed. The results obtained in this study will assist in the future development of rapid diagnostic tests for these important foodborne pathogens.