A quantitative PCR based method using propidium monoazide for specific and sensitive detection of Pectobacterium carotovorum ssp. carotovorum in kimchi cabbage (Brassica rapa L. subsp. pekinensis)

Quantification of Pectobacterium carotovorum subsp. carotovorum in kimchi cabbage using a surface-enhanced Raman scattering platform with silver nanostructures

Pectobacterium carotovorum subsp. carotovorum (PCC) is a notorious plant pathogen responsible for severe soft rot in kimchi cabbage, which results in significant economic losses. To detect PCC rapidly and accurately in kimchi cabbage, we developed a surface-enhanced Raman scattering (SERS) substrate on which silver nanospheres (AgNSs), nanowires (AgNWs), and nanoseeds are combined on a polydimethylsiloxane (PDMS) platform. The incorporation of Ag nanoseeds creates a higher density of hotspots, which ensures a low detection limit of 1.001 CFU/mL. Electron microscopy and spectroscopic analyses confirmed the successful fabrication of the substrate and its enhanced sensitivity. The SERS substrate exhibits excellent selectivity by effectively distinguishing PCC from other bacteria commonly found in kimchi cabbage. The substrate gives rise to strong Raman signals across PCC concentrations ranging from 101 to 106 CFU/mL. Additionally, a predictive model was developed for accurately detecting PCC in real kimchi cabbage samples, and the results were validated by polymerase chain reaction measurements. A sensitive, selective, and rapid approach for PCC detection in kimchi cabbage that offers a promising improvement over existing methodologies is presented.

Rapid Detection and Quantification of Viable Cells of Pectobacterium brasiliense Using Propidium Monoazide Combined with Real-Time PCR

Pectobacterium brasiliense (Pbr) has caused significant economic losses in major vegetable production areas in Northern China by causing bacterial soft rot in cash crops such as potatoes and cucumbers. This study aimed to establish a PMA-qPCR detection method for Pbr by screening specific and sensitive primers based on the glu gene and the conserved region of the 23S rRNA gene. Based on the optimized PMA pretreatment conditions, a standard curve was designed and constructed for PMA-qPCR detection (y = -3.391x + 36.28; R2 = 0.99). The amplification efficiency reached 97%, and the lowest detection limit of viable cells was approximately 2 × 102 CFU·mL-1. The feasibility of the PMA-qPCR method was confirmed through a manually simulated viable/dead cell assay under various concentrations. The analysis of potato tubers and cucumber seeds revealed that nine naturally collected seed samples contained a range from 102 to 104 CFU·g-1 viable Pbr bacteria. Furthermore, the system effectively identified changes in the number of pathogenic bacteria in cucumber and potato leaves affected by soft rot throughout the disease period. Overall, the detection and prevention of bacterial soft rot caused by Pbr is crucial.

Nondestructive classification of soft rot disease in napa cabbage using hyperspectral imaging analysis

Identification of soft rot disease in napa cabbage, an essential ingredient of kimchi, is challenging at the industrial scale. Therefore, nondestructive imaging techniques are necessary. Here, we investigated the potential of hyperspectral imaging (HSI) processing in the near-infrared region (900–1700 nm) for classifying napa cabbage quality using nondestructive measurements. We determined the microbiological and physicochemical qualitative properties of napa cabbage for intercomparison of HSI information, extracted HSI characteristics from hyperspectral images to predict and classify freshness, and established a novel approach for classifying healthy and rotten napa cabbage. The second derivative Savitzky–Golay method for data preprocessing was implemented, followed by wavelength selection using variable importance in projection scores. For multivariate data of the classification models, partial least square discriminant analysis (PLS-DA), support vector machine (SVM), and random forests were used for predicting cabbage conditions. The SVM model accurately distinguished the cabbage exhibiting soft rot disease symptoms from the healthy cabbage. This study presents the potential of HSI systems for separating soft rot disease-infected napa cabbages from healthy napa cabbages using the SVM model, especially under the most effective wavelengths (970, 980, 1180, 1070, 1120, and 978 nm), prior to processing. These results are applicable to industrial multispectral images.

New PCR-Based Assay for the Identification of Pectobacterium carotovorum Causing Potato Soft Rot

Soft rot on potato tuber is a destructive disease caused by pathogenic bacterial species of the genera Pectobacterium and Dickeya. Accurate identification of the causal agent is necessary to ensure adequate disease management because different species may have distinct levels of aggressiveness and host range. One of the most important potato pathogens is Pectobacterium carotovorum, a highly heterogeneous species capable of infecting multiple hosts. The complexity of this species, until recently divided into several subspecies, has made it difficult to develop precise diagnostic tests. This study proposes a PCR assay based on the new pair of primers Pcar1F/R to facilitate the identification of potato isolates of P. carotovorum according to the most recent taxonomic description of this species. The new primers were designed on a variable segment of the 16S rRNA gene and the intergenic spacer region of available DNA sequences from classical and recently established species in the genus Pectobacterium. The results of the PCR analysis of genomic DNA from 32 Pectobacterium and Dickeya strains confirmed that the Pcar1F/R primers have sufficient nucleotide differences to discriminate between P. carotovorum and other Pectobacterium species associated with damage to potato crops, with the exception of Pectobacterium versatile, which improves the specificity of the currently available primers. The proposed assay was originally developed as a conventional PCR but was later adapted to the real-time PCR format for application in combination with the existing real-time PCR test for the potato-specific pathogen Pectobacterium parmentieri. This should be useful for the routine diagnosis of potato soft rot.

Use of qPCR for the analysis of population heterogeneity and dynamics during Lactobacillus delbrueckii spp. bulgaricus batch fculture

Direct molecular methods such as real-time polymerase chain reaction (qPCR) and propidium monoazide (PMA)-qPCR have been successfully used for quantifying viable microorganisms in the food industry. This study attempted to use qPCR and PMA-qPCR for quantifying Lactobacillus delbrueckii spp. bulgaricus sp1.1 physiological states. The qPCR standards of the 16S rRNA gene were employed to calibrate the qPCR assay, which contributed to an amplification efficiency of 98.42%. The number of copies of the 16S rRNA gene was linearly related to cell density, and this linear relationship was used to construct a quantitative curve (R² =0.9981) with a detection limit of 15.1 colony-forming units mL^-1·reaction^-1. qPCR in combination with an optimal PMA concentration (60 μM) helped in discriminating and quantifying the viable cells, without any interference by heat-killed cells. Compared with the conventional methods, the population heterogeneity of viable, culturable, dormant-like and membrane-permeabilized cells were well identified and quantified using qPCR during L. delbrueckii spp. bulgaricus sp1.1 batch culture. Despite the restriction in the enumeration of lysed cells, qPCR-based methods facilitated reliable identification and quantification of bacterial physiological states and provided additional knowledge on the dynamics of L. delbrueckii spp. bulgaricus sp1.1 physiological states.

Volatile Metabolic Markers for Monitoring Pectobacterium carotovorum subsp. carotovorum Using Headspace Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry

Identifying the extracellular metabolites of microorganisms in fresh vegetables is industrially useful for assessing the quality of processed foods. Pectobacterium carotovorum subsp. carotovorum (PCC) is a plant pathogenic bacterium that causes soft rot disease in cabbages. This microbial species in plant tissues can emit specific volatile molecules with odors that are characteristic of the host cell tissues and PCC species. In this study, we used headspace solid-phase microextraction followed by gas chromatography coupled with mass spectrometry (HS-SPME-GC-MS) to identify volatile compounds (VCs) in PCC-inoculated cabbage at different storage temperatures. HS-SPME-GC-MS allowed for recognition of extracellular metabolites in PCC-infected cabbages by identifying specific volatile metabolic markers. We identified 4-ethyl-5-methylthiazole and 3-butenyl isothiocyanate as markers of fresh cabbages, whereas 2,3-butanediol and ethyl acetate were identified as markers of soft rot in PCC-infected cabbages. These analytical results demonstrate a suitable approach for establishing non-destructive plant pathogen-diagnosis techniques as alternatives to standard methods, within the framework of developing rapid and efficient analytical techniques for monitoring plant-borne bacterial pathogens. Moreover, our techniques could have promising applications in managing the freshness and quality control of cabbages.