Identification of Salmonella Taxon-Specific Peptide Markers to the Serovar Level by Mass Spectrometry

Python workflow for the selection and identification of marker peptides-proof-of-principle study with heated milk

The analysis of almost holistic food profiles has developed considerably over the last years. This has also led to larger amounts of data and the ability to obtain more information about health-beneficial and adverse constituents in food than ever before. Especially in the field of proteomics, software is used for evaluation, and these do not provide specific approaches for unique monitoring questions. An additional and more comprehensive way of evaluation can be done with the programming language Python. It offers broad possibilities by a large ecosystem for mass spectrometric data analysis, but needs to be tailored for specific sets of features, the research questions behind. It also offers the applicability of various machine-learning approaches. The aim of the present study was to develop an algorithm for selecting and identifying potential marker peptides from mass spectrometric data. The workflow is divided into three steps: (I) feature engineering, (II) chemometric data analysis, and (III) feature identification. The first step is the transformation of the mass spectrometric data into a structure, which enables the application of existing data analysis packages in Python. The second step is the data analysis for selecting single features. These features are further processed in the third step, which is the feature identification. The data used exemplarily in this proof-of-principle approach was from a study on the influence of a heat treatment on the milk proteome/peptidome.

Flos populi (Male Inflorescence of Populus tomentosa Carrière) Aqueous Extract Suppresses Salmonella Pullorum Infection by Affecting T3SS-1

Pullorum disease, caused by Salmonella Pullorum (S. Pullorum), is one of the most serious infectious diseases in the poultry industry. Flos populi is traditionally used in Eastern Asian countries to treat various intestinal diseases. However, the anti-infection mechanism of Flos populi is not very clear. In this study, we evaluated the anti-infective effects on S. Pullorum of Flos populi aqueous extract (FPAE) in chickens. FPAE significantly reduced S. Pullorum growth in vitro. At the cellular level, FPAE reduced S. Pullorum adhesion and invasion on DF-1 cells but did not affect its intracellular survival or replication in macrophages. Further investigation revealed that FPAE inhibited the transcription of T3SS-1 genes, which is the main virulence factor that mediates S. Pullorum adhesion and invasion in host cells. The results suggest that the anti-infective effect of FPAE likely occurs through the inhibition of S. Pullorum T3SS-1, thereby impairing its ability to adhere to and invade cells. Further, we evaluated its therapeutic effect on animal models (Jianghan domestic chickens) and found that FPAE reduced the bacterial loads in organs and decreased the mortality and weight loss of infected chickens. Our findings provide novel insights into the potential development of FPAE against S. Pullorum as an effective anti-virulence therapeutic substitute for antibiotics.

Protective Effects of Cinnamaldehyde on the Oxidative Stress, Inflammatory Response, and Apoptosis in the Hepatocytes of Salmonella Gallinarum-Challenged Young Chicks

The development of novel therapeutics to treat multidrug-resistant pathogenic infections like Salmonella gallinarum is the need of the hour. Salmonella infection causes typhoid fever, jaundice, and Salmonella hepatitis resulting in severe liver injury. Natural compounds have been proved beneficial for the treatment of these bacterial infections. The beneficial roles of cinnamaldehyde due to its antibacterial, anti-inflammatory, and antioxidative properties have been determined by many researchers. However, alleviation of liver damage caused by S. gallinarum infection to young chicks by cinnamaldehyde remains largely unknown. Therefore, this study was performed to identify the effects of cinnamaldehyde on ameliorating liver damage in young chicks. Young chicks were intraperitoneally infected with S. gallinarum and treated with cinnamaldehyde orally. Liver and serum parameters were investigated by qRT-PCR, ELISA kits, biochemistry kits, flow cytometry, JC-1 dye experiment, and transcriptome analysis. We found that ROS, cytochrome c, mitochondrial membrane potential (Ψm), caspase-3 activity, ATP production, hepatic CFU, ALT, and AST, which were initially increased by Salmonella infection, significantly ( $P<0.05$ ) decreased by cinnamaldehyde treatment at 1, 3, and 5 days postinfection (DPI). In addition, S. gallinarum infection significantly increased proinflammatory gene expression (IL-1β, IL-6, IL-12, NF-κB, TNF-α, and MyD-88) and decreased the expression of anti-inflammatory genes (IL-8, IL-10, and iNOS); however, cinnamaldehyde reverted these effects at 1, 3, and 5 DPI. Transcriptome analysis showed that S. gallinarum modulates certain genes of the AMPK-mTOR pathway for its survival and replication, and these pathway modulations were reversed by cinnamaldehyde treatment. We concluded that cinnamaldehyde ameliorates inflammation and apoptosis by suppressing NF-Kβ/caspase-3 pathway and reverts the metabolic changes caused by S. gallinarum infection via modulating the AMPK-mTOR pathway. Furthermore, cinnamaldehyde has antibacterial, anti-inflammatory, antioxidative, and antiapoptotic properties against S. gallinarum-challenged young chicks and can be a candidate novel drug to treat salmonellosis in poultry production.

Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach

Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation shows that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in identifying antibiotic resistance proteins. In addition to having high sensitivity and precision, MiCId's workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 min per MS/MS sample using computing resources that are available in most desktop and laptop computers. We have also demonstrated other use of MiCId's workflow. Using MS/MS data sets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions agree with the published study. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Mass Spectrometry Proteotyping-Based Detection and Identification of Staphylococcus aureus, Escherichia coli, and Candida albicans in Blood

Bloodstream infections (BSIs), the presence of microorganisms in blood, are potentially serious conditions that can quickly develop into sepsis and life-threatening situations. When assessing proper treatment, rapid diagnosis is the key; besides clinical judgement performed by attending physicians, supporting microbiological tests typically are performed, often requiring microbial isolation and culturing steps, which increases the time required for confirming positive cases of BSI. The additional waiting time forces physicians to prescribe broad-spectrum antibiotics and empirically based treatments, before determining the precise cause of the disease. Thus, alternative and more rapid cultivation-independent methods are needed to improve clinical diagnostics, supporting prompt and accurate treatment and reducing the development of antibiotic resistance. In this study, a culture-independent workflow for pathogen detection and identification in blood samples was developed, using peptide biomarkers and applying bottom-up proteomics analyses, i.e., so-called "proteotyping". To demonstrate the feasibility of detection of blood infectious pathogens, using proteotyping, Escherichia coli and Staphylococcus aureus were included in the study, as the most prominent bacterial causes of bacteremia and sepsis, as well as Candida albicans, one of the most prominent causes of fungemia. Model systems including spiked negative blood samples, as well as positive blood cultures, without further culturing steps, were investigated. Furthermore, an experiment designed to determine the incubation time needed for correct identification of the infectious pathogens in blood cultures was performed. The results for the spiked negative blood samples showed that proteotyping was 100- to 1,000-fold more sensitive, in comparison with the MALDI-TOF MS-based approach. Furthermore, in the analyses of ten positive blood cultures each of E. coli and S. aureus, both the MALDI-TOF MS-based and proteotyping approaches were successful in the identification of E. coli, although only proteotyping could identify S. aureus correctly in all samples. Compared with the MALDI-TOF MS-based approaches, shotgun proteotyping demonstrated higher sensitivity and accuracy, and required significantly shorter incubation time before detection and identification of the correct pathogen could be accomplished.

Type 3 secretion system 1 of Salmonella typhimurium and its inhibitors: a novel strategy to combat salmonellosis

Unsuccessful vaccination against Salmonella due to a large number of serovars, and antibiotic resistance, necessitates the development of novel therapeutics to treat salmonellosis. The development of anti-virulence agents against multi-drug-resistant bacteria is a novel strategy because of its non-bacterial feature. Hence, a thorough study of the type three secretion system (T3SS) of Salmonella would help us better understand its role in bacterial pathogenesis and development of anti-virulence agents. However, T3SS can be inhibited by different chemicals at different stages of infection and sequenced delivery of effectors can be blocked to restrict the progression of disease. This review highlights the role of T3SS-1 in the internalization, survival, and replication of Salmonella within the intestinal epithelium and T3SS inhibitors. We concluded that the better we understand the structures and functions of T3SS, the more we have chances to develop anti-virulence agents. Furthermore, greater insights into the T3SS inhibitors of Salmonella would help in the mitigation of the antibiotic resistance problem and would lead us to the era of new therapeutics against salmonellosis.

Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping

Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): Staphylococcus aureus; Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, i.e. proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.

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.