Assessing the performance of novel software Strain Solution on automated discrimination of Escherichia coli serotypes and their mixtures using matrix-assisted laser desorption ionization-time of flight mass spectrometry

Bacterial Pesticides: Mechanism of Action, Possibility of Food Contamination, and Residue Analysis Using MS

As Sustainable Development Goals (SDGs) and the realities of climate change become widely accepted around the world, the next-generation of integrated pest management will become even more important for establishing a sustainable food production system. To meet the current challenge of food security and climate change, biological control has been developed as one sustainable crop protection technology. However, most registered bacteria are ubiquitous soil-borne bacteria that are closely related to food poisoning and spoilage bacteria. Therefore, this review outlined (1) the mechanism of action of bacterial pesticides, (2) potential concerns about secondary contamination sources associated with past food contamination, and, as a prospective solution, focused on (3) principles and methods of bacterial identification, and (4) the possibility of identifying residual bacteria based on mass spectrometry.

Proteotyping of Campylobacter jejuni by MALDI-TOF MS and Strain Solution Version 2 Software

Identification of microorganisms by MALDI-TOF MS has become a popular method in the past 20 years. Strain Solution ver. 2 software appended with MALDI-TOF MS enables accurate discrimination of serotypes and strains beyond the genus and species level by creating a theoretical mass-based database. In this study, we constructed a theoretical mass database with the validated biomarkers to proteotype Campylobacter jejuni. Using 10 strains belonging to Campylobacter spp. available from culture collections and 41 Campylobacter jejuni strains isolated from humans and foods, the ribosomal protein subunits L36, L32, S14, L24, L23, L7/L12, and S11 could be selected as the effective biomarkers for the proteotyping of C. jejuni at MALDI-TOF MS. An accurate database of their theoretical mass-based values was constructed by matching these gene DNA sequences and the observed mass peaks. We attempted to automatically classify 41 strains isolated from nature using this database and Strain Solution ver. 2 software, and 38 strains (93%) were correctly classified into the intended group based on the theoretical mass-based values. Thus, the seven biomarkers found in this study and Strain Solution ver. 2 are promising for the proteotyping of C. jejuni by MALDI-TOF MS.

Improved MALDI-MS method for the highly sensitive and reproducible detection of biomarker peaks for the proteotyping of Salmonella serotypes

The rapid identification and classification of pathogenic microorganisms, including Salmonella enterica, is important for the surveillance and prevention of foodborne diseases. Matrix-assisted laser desorption\ionization time-of-flight mass spectrometry (MALDI-TOFMS) has been shown to be an effective tool for the rapid identification of microorganisms. In a previous report, a mass database consisting of 12 biomarker proteins, S8, L15, L17, L21, L25, S7, superoxide dismutase (SodA), peptidylprolyl cis-trans isomerase C, Gns, YibT, YaiA, and YciF, was introduced for the serotyping of S. enterica via MALDI-MS (Applied Microbiology and Biotechnology, 2017, 101, 8557-8569). However, the reproducibility of peak detection of biomarkers such as SodA at m\z 23 000 was poor. We report here an optimized MALDI-MS method for detecting these biomarkers with high sensitivity and reproducibility. The issue was solved by controlling the bacterial concentration at 1 × 10 to 1 × 10² MFU (3 × 10⁶ to 3 × 10⁷ CFU\μL, as calculated from the MFU), using the colony suspension supernatant obtained by centrifugation, and using matrix additives such as methylenediphosphonic acid and N-decyl-β-D-maltopyranoside. We propose that the method including the above steps is one of the best for detecting biomarkers with high sensitivity and reproducibility.

Characterization of microbial mixtures by mass spectrometry

MS applications in microbiology have increased significantly in the past 10 years, due in part to the proliferation of regulator-approved commercial MALDI MS platforms for rapid identification of clinical infections. In parallel, with the expansion of MS technologies in the "omics" fields, novel MS-based research efforts to characterize organismal as well as environmental microbiomes have emerged. Successful characterization of microorganisms found in complex mixtures of other organisms remains a major challenge for researchers and clinicians alike. Here, we review recent MS advances toward addressing that challenge. These include sample preparation methods and protocols, and established, for example, MALDI, as well as newer, for example, atmospheric pressure ionization (API) techniques. MALDI mass spectra of intact cells contain predominantly information on the highly expressed house-keeping proteins used as biomarkers. The API methods are applicable for small biomolecule analysis, for example, phospholipids and lipopeptides, and facilitate species differentiation. MS hardware and techniques, for example, tandem MS, including diverse ion source/mass analyzer combinations are discussed. Relevant examples for microbial mixture characterization utilizing these combinations are provided. Chemometrics and bioinformatics methods and algorithms, including those applied to large scale MS data acquisition in microbial metaproteomics and MS imaging of biofilms, are highlighted. Select MS applications for polymicrobial culture analysis in environmental and clinical microbiology are reviewed as well.

Application of proteotyping Strain Solution™ ver. 2 software and theoretically calculated mass database in MALDI-TOF MS typing of Salmonella serotype

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based microbial identification is a popular analytical method. Strain Solution proteotyping software available for MALDI-TOF MS has great potential for the precise and detailed discrimination of microorganisms at serotype- or strain-level, beyond the conventional mass fingerprinting approaches. Here, we constructed a theoretically calculated mass database of Salmonella enterica subspecies enterica consisting of 12 biomarker proteins: ribosomal proteins S8, L15, L17, L21, L25, and S7, Mn-cofactor-containing superoxide dismutase (SodA), peptidyl-prolyl cis-trans isomerase C (PPIase C), and protein Gns, and uncharacterized proteins YibT, YaiA, and YciF, that can allow serotyping of Salmonella. Strain Solution ver. 2 software with the novel database constructed in this study demonstrated that 109 strains (94%), including the major outbreak-associated serotypes, Enteritidis, Typhimurium, and Infantis, could be correctly identified from others by colony-directed MALDI-TOF MS using 116 strains belonging to 23 kinds of typed and untyped serotypes of S. enterica from culture collections, patients, and foods. We conclude that Strain Solution ver. 2 software integrated with the accurate mass database will be useful for the bacterial proteotyping by MALDI-TOF MS-based microbial classification in the clinical and food safety fields.

Matrix-assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Can Precisely Discriminate the Lineages of Listeria monocytogenes and Species of Listeria

The genetic lineages of Listeria monocytogenes and other species of the genus Listeria are correlated with pathogenesis in humans. Although matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has become a prevailing tool for rapid and reliable microbial identification, the precise discrimination of Listeria species and lineages remains a crucial issue in clinical settings and for food safety. In this study, we constructed an accurate and reliable MS database to discriminate the lineages of L. monocytogenes and the species of Listeria (L. monocytogenes, L. innocua, L. welshimeri, L. seeligeri, L. ivanovii, L. grayi, and L. rocourtiae) based on the S10-spc-alpha operon gene encoded ribosomal protein mass spectrum (S10-GERMS) proteotyping method, which relies on both genetic information (genomics) and observed MS peaks in MALDI-TOF MS (proteomics). The specific set of eight biomarkers (ribosomal proteins L24, L6, L18, L15, S11, S9, L31 type B, and S16) yielded characteristic MS patterns for the lineages of L. monocytogenes and the different species of Listeria, and led to the construction of a MS database that was successful in discriminating between these organisms in MALDI-TOF MS fingerprinting analysis followed by advanced proteotyping software Strain Solution analysis. We also confirmed the constructed database on the proteotyping software Strain Solution by using 23 Listeria strains collected from natural sources.