Identification of novel molecular targets for Weissella species-specific real-time PCR based on pangenome analysis

Kim, Eiseul; Yang, Seung-Min; Kim, Ik-Seon; Kim, Hae Yeong

doi:10.1007/s00253-022-12003-z

Cited by 6 publications

(7 citation statements)

References 35 publications

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“…cibaria , W . confusa , and non-target Weissella strains were previously designed through pangenome analysis [ 9 ] and used to identify the isolates. Each primer produced an amplification plot for each strain.…”

Section: Resultsmentioning

confidence: 99%

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Differentiation between Weissella cibaria and Weissella confusa Using Machine-Learning-Combined MALDI-TOF MS

Kim

Yang

Park

et al. 2023

IJMS

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Although Weissella cibaria and W. confusa are essential food-fermenting bacteria, they are also opportunistic pathogens. Despite these species being commercially crucial, their taxonomy is still based on inaccurate identification methods. In this study, we present a novel approach for identifying two important Weissella species, W. cibaria and W. confusa, by combining matrix-assisted laser desorption/ionization and time-of-flight mass spectrometer (MALDI-TOF MS) data using machine-learning techniques. After on- and off-plate protein extraction, we observed that the BioTyper database misidentified or could not differentiate Weissella species. Although Weissella species exhibited very similar protein profiles, these species can be differentiated on the basis of the results of a statistical analysis. To classify W. cibaria, W. confusa, and non-target Weissella species, machine learning was used for 167 spectra, which led to the listing of potential species-specific mass-to-charge (m/z) loci. Machine-learning techniques including artificial neural networks, principal component analysis combined with the K-nearest neighbor, support vector machine (SVM), and random forest were used. The model that applied the Radial Basis Function kernel algorithm in SVM achieved classification accuracy of 1.0 for training and test sets. The combination of MALDI-TOF MS and machine learning can efficiently classify closely-related species, enabling accurate microbial identification.

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Section: Resultsmentioning

confidence: 99%

“…Several methods have been developed for Weissella identification, such as polymerase chain reaction (PCR) assays, sequencing, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-TOF MS) [ 9 , 10 , 11 ]. Of these, MALDI-TOF MS has been used in many clinical laboratories for bacterial identification.…”

Section: Introductionmentioning

confidence: 99%

Differentiation between Weissella cibaria and Weissella confusa Using Machine-Learning-Combined MALDI-TOF MS

Kim

Yang

Park

et al. 2023

IJMS

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“…Fusco et al ( 2011 ) developed a species-specific PCR for Weissella confusa from an AFLP (amplified fragment length polymorphism)-derived marker, whereas a conventional PCR and a real-time PCR were developed by Snyder et al ( 2015 ) for the identification and quantification of W. ceti NC36. A real-time PCR assay was developed by Gómez-Rojo et al ( 2015 ) to quantitatively detect W. viridescens in blood sausages, whereas following a pan-genome analysis, Kim et al ( 2022b ) designed species-specific pairs of primers for the real-time PCR detection of 11 Weissella species. Finally, Ma et al ( 2022 ) developed an aptasensor based on fluorescence polarization for the detection of W. viridescens .…”

Section: Detection and Typing Of Weissellamentioning

confidence: 99%

The Weissella and Periweissella genera: up-to-date taxonomy, ecology, safety, biotechnological, and probiotic potential

Fusco,

Chieffi,

Fanelli

et al. 2023

Front. Microbiol.

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Bacteria belonging to the genera Weissella and Periweissella are lactic acid bacteria, which emerged in the last decades for their probiotic and biotechnological potential. In 2015, an article reviewing the scientific literature till that date on the taxonomy, ecology, and biotechnological potential of the Weissella genus was published. Since then, the number of studies on this genus has increased enormously, several novel species have been discovered, the taxonomy of the genus underwent changes and new insights into the safety, and biotechnological and probiotic potential of weissellas and periweissellas could be gained. Here, we provide an updated overview (from 2015 until today) of the taxonomy, ecology, safety, biotechnological, and probiotic potential of these lactic acid bacteria.

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“…Thus, molecular assays targeting genetic markers achieve higher resolution within closely related species. The previous researchers have successfully identified for species, subspecies, or serovar-specific marker genes using the presence/absence matrix with a script built into Roary (Bannantine et al, 2021;Shang et al, 2021;Kim et al, 2022c).…”

Section: Screening Species-specific Genesmentioning

confidence: 99%

Identification of Leuconostoc species based on novel marker genes identified using real-time PCR via computational pangenome analysis

et al. 2022

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Leuconostoc species are important microorganisms in food fermentation but also cause food spoilage. Although these species are commercially important, their taxonomy is still based on inaccurate identification methods. Here, we used computational pangenome analysis to develop a real-time PCR-based method for identifying and differentiating the 12 major Leuconostoc species found in food. Analysis of pan and core-genome phylogenies showed clustering of strains into 12 distinct groups according to the species. Pangenome analysis of 130 Leuconostoc genomes from these 12 species enabled the identification of each species-specific gene. In silico testing of the species-specific genes against 143 publicly available Leuconostoc and 100 other lactic acid bacterial genomes showed that all the assays had 100% inclusivity/exclusivity. We also verified the specificity for each primer pair targeting each specific gene using 23 target and 124 non-target strains and found high specificity (100%). The sensitivity of the real-time PCR method was 102 colony forming units (CFUs)/ml in pure culture and spiked food samples. All standard curves showed good linear correlations, with an R2 value of ≥0.996, suggesting that screened targets have good specificity and strong anti-interference ability from food sample matrices and non-target strains. The real-time PCR method can be potentially used to determine the taxonomic status and identify the Leuconostoc species in foods.

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Identification of novel molecular targets for Weissella species-specific real-time PCR based on pangenome analysis

Cited by 6 publications

References 35 publications

Differentiation between Weissella cibaria and Weissella confusa Using Machine-Learning-Combined MALDI-TOF MS

Differentiation between Weissella cibaria and Weissella confusa Using Machine-Learning-Combined MALDI-TOF MS

The Weissella and Periweissella genera: up-to-date taxonomy, ecology, safety, biotechnological, and probiotic potential

Identification of Leuconostoc species based on novel marker genes identified using real-time PCR via computational pangenome analysis

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