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Article

A Novel LAMP-Based Lateral Flow Dipstick Technique for Rapid and Visual Detection of Burkholderia gladioli pv. cocovenenans

by
Baoqing Zhou
1,2,3,4,†,
Xiang Nie
1,3,4,†,
Hongwei Fan
1,3,4,
Xudong Mao
1,
Zhongxu Zhan
1,3,4,
Cheng Zhou
1,3,4,
Jingwen Xiong
1,3,4,
Jiatian Gao
5,
Mengxiang Zhang
5,
Li Li
5,
Bei Gan
1,3,4,* and
Xin Wu
1,3,4,*
1
Office of Science and Technology, Jiangxi General Institute of Testing and Certification, Nanchang 330052, China
2
School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
3
National Quality Inspection and Testing Center for Fruit and Vegetable Products and Processed Foods, Jiangxi General Institute of Testing and Certification, Nanchang 330052, China
4
Nanchang Key Laboratory of Food Rapid Testing, Jiangxi General Institute of Testing and Certification, Nanchang 330052, China
5
State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Molecules 2026, 31(15), 2664; https://doi.org/10.3390/molecules31152664
Submission received: 4 June 2026 / Revised: 18 July 2026 / Accepted: 27 July 2026 / Published: 30 July 2026
(This article belongs to the Special Issue Recent Advances in Food Analysis, 2nd Edition)
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Abstract

Burkholderia gladioli pv. cocovenenans (B. gladioli pv. cocovenenans), the most representative pathovar of B. gladioli, is capable of producing thermostable and highly virulent bongkrekic acid, which can result in multiple organ failure and an extremely high case fatality rate in humans. This research aims to mine specific targets for B. gladioli pv. cocovenenans and develop a rapid and accurate assay for the detection of B. gladioli pv. cocovenenans in food. Two novel specific target genes (group_0918 and group_0110) were successfully screened through pan-genome analysis, and the excellent specificity and sensitivity of both targets were verified in comparison to PCR assays. Based on these targets, a loop-mediated isothermal amplification (LAMP) method was developed to specifically identify B. gladioli pv. cocovenenans. In pure culture and spiked fresh black fungus samples, the LAMP assay achieved a limit of detection (LOD) of 4.1 × 101 CFU/mL and 4.1 × 102 CFU/g for the detection of B. gladioli pv. cocovenenans, respectively. To enable point of care testing, a LAMP-based lateral flow dipstick(LFD) assay was established with a detection sensitivity of 4.1 × 103 CFU/g in fresh black fungus. Tests on naturally infected food samples demonstrated that the developed LAMP and LAMP-assisted visual detection assays can serve as an effective alternative for the accurate identification of B. gladioli pv. cocovenenans. The novel molecular detection technology established in this study offers an efficient and reliable detection method for the prevention and control of B. gladioli pv. cocovenenans contamination in food, which holds significant application value and promotion prospects.

1. Introduction

Burkholderia gladioli (B. gladioli) is a Gram-negative bacterium widely found in air, soil, and aquatic environments [1,2]. According to host specificity, this species is divided into four distinct pathovars: B. gladioli pv. alliicola, B. gladioli pv. agaricicola, B. gladioli pv. Cocovenenans, and B. gladioli pv. gladioli [3,4]. Among them, B. gladioli pv. cocovenenans, formerly classified as Pseudomonas cocovenenans subsp. farinofermentans in China, is a highly virulent pathovar that causes severe foodborne infections and intoxications in humans [5]. The mortality rate of this pathogen surpasses 40%, which is significantly higher than that of prevalent food-borne pathogens such as Listeria monocytogenes, Salmonella, and Staphylococcus aureus [6,7]. B. gladioli pv. cocovenenans secretes two harmful toxins, bongkrekic acid (BA) and toxoflavin (TF), which target key human organs such as the liver, brain, and kidneys [8]. Individuals infected with this pathovar typically present with hepatic coma and neurological dysfunction, with eventual death caused by respiratory failure [9,10]. Foodborne poisoning caused by B. gladioli pv. cocovenenans has long been endemic in Indonesia and Asia [11]. In 2015, a severe food poisoning outbreak induced by this pathogen occurred in Mozambique, Africa, causing 75 deaths [12]. In 2024, the first fatal case of bongkrekic acid poisoning was reported in North America [13]. Statistics from the national public health emergency surveillance system indicated that a total of 30 foodborne poisoning incidents triggered by B. gladioli pv. cocovenenans occurred in China during 2005–2020, causing 188 illnesses and 85 deaths [14]. Foodborne diseases attributed to this pathovar are commonly identified in black fungus, Tremella fuciformis, fermented rice and flour products, and various starchy foods [9]. Hence, rapid, accurate, and sensitive identification of this pathovar has become an urgent demand, which plays a key role in mitigating relevant food safety hazards and reducing the risk of food poisoning.
Currently, traditional culture methods serve as the gold standard for the detection of B. gladioli pv. cocovenenans. As stipulated in the Chinese national standard GB 4789.29-2020 [15], the detection procedure, which involves pre-enrichment culture, bacterial isolation and purification, biochemical identification, and toxigenic analysis, is cumbersome to operate and time-consuming. Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) technology is available for the rapid identification of B. gladioli pv. cocovenenans [16]. Nevertheless, this approach depends on specialized apparatus and costly databases. Moreover, pre-enrichment culturing must be carried out before detection to obtain purified single colonies. With the development of molecular biology, molecular detection methods represented by polymerase chain reaction (PCR) [17], loop-mediated isothermal amplification (LAMP) [18], and rolling circle amplification (RCA) [19] have gradually become mainstream due to their advantages of low cost, rapidity, and sensitivity. However, traditional PCR methods rely on professional thermal cyclers, making them unable to meet the needs of primary-level testing. LAMP is a nucleic acid amplification method characterized by low reliance on professional equipment and high sensitivity. It can achieve 109–1010 fold amplification under isothermal conditions in a short time [20]. The traditional LAMP method typically involves direct analysis of amplification products via gel electrophoresis, which can easily lead to aerosol contamination in the experimental environment [21]. To mitigate the risk of cross-contamination during experiments, Kim et al. (2023) [22] developed a fluorescence visualization method based on LAMP technology for the rapid detection of Salmonella Thompson. By incorporating a fluorescent probe, this approach significantly reduces the probability of cross-contamination in the analysis process; furthermore, it achieves a limit of detection (LOD) of 3 CFU/mL without the need for enrichment treatment. Zheng et al. (2025) [23]. designed biotin and FITC-labeled primers and successfully established a LAMP lateral flow dipstick (LFD) platform for rapid, sensitive detection of B. gladioli pv. cocovenenans. The detection sensitivity reached 2.5 pg/μL for purified pathogen DNA and 6.68 × 102 CFU/25 g for artificially contaminated rice noodle samples, which is 10 times more sensitive than conventional PCR. Yao et al. (2025) [24] developed a dual-readout lateral flow biosensor for B. gladioli pv. cocovenenans detection based on the combined colorimetric and magnetic properties of polydopamine-coated Fe3O4 magnetic nanospheres (Fe3O4@PDA MNSs). The method allowed for a quantitative LOD of 2.32 × 103 CFU/mL and a visual LOD of 1.0 × 104 CFU/mL. Compared with the gold-nanoparticle-based lateral flow dipstick (AuNPs-based LFD) platform, this method achieved an approximately ninefold increase in detection sensitivity. Therefore, molecular detection methods based on LAMP and LFD platforms have demonstrated significant application potential in the rapid and accurate identification of pathogenic bacteria.
Specific molecular targets are critical for guaranteeing the specificity and sensitivity of molecular detection assays. Molecular targets and supporting primers for one-step PCR of B. gladioli pv. cocovenenans remain limited, with routine markers confined to 16S rRNA, 23S rRNA, and the 16S-23S rRNA spacer region [25,26]. These conserved sequences share high homology across pathovar subtypes and other Burkholderia species, thereby hindering accurate interspecific discrimination. A qPCR method was developed, targeting the bonM gene within the bongkrekic acid biosynthetic gene cluster, for the rapid screening of B. gladioli pv. cocovenenans in food samples [27]. Nevertheless, as a virulence gene, bonM harbors widespread sequence variation and substantial genetic divergence. Over-reliance on this single target impedes accurate identification and fails to meet practical detection requirements. Driven by the rapid development of high-throughput sequencing and bioinformatics, pangenomic analysis techniques with superior capabilities in global genetic profiling have been extensively utilized for dissecting bacterial genetic variation, gene function enrichment, and species evolutionary traceability [28]. Our previous research successfully mined specific molecular targets for Staphylococcus spp. [29], Salmonella spp. [30], and Listeria spp. [31] based on pan-genome analyses, enabling accurate and rapid identification of target bacteria in complex food matrices. Therefore, based on the public genomic data from the National Center for Biotechnology Information (NCBI, https://www.ncbi.nlm.nih.gov/) and our group’s previously obtained whole-genome sequencing data of B. gladioli pv. cocovenenans, pan-genome analysis can be employed to precisely mine specific molecular detection targets. We will further develop user-friendly, rapid, cost-effective, and highly sensitive LAMP assays and LFD colorimetric methods that will meet the practical demands for the accurate identification and quantitative detection of B. gladioli pv. cocovenenans (Figure 1).

2. Results

2.1. Screening of Novel Specific Targets for B. gladioli pv. cocovenenans

As listed in Table S1, 501 genome sequences were collected to screen novel specific target genes, consisting of 489 from Burkholderia strains and 12 from other common pathogenic bacteria. According to the selection criteria, two of the evaluated genes were successfully identified as candidate targets (Table S2). Functional prediction showed that both group_0918 and group_0110 encode hypothetical proteins, and identifying their specific coding regions may facilitate gene structure–function analyses to elucidate the unique metabolic characteristics of B. gladioli pv. cocovenenans [32]. A local BLASTN program was used to verify the specificity of these genes for the detection of B. gladioli pv. cocovenenans. As shown in Table S3, the two candidate targets displayed 100% detection rate in B. gladioli pv. cocovenenans strains and 100% specificity against non-target strains. By comparison, the reported target BonM showed 100% presence in target strains but only 98.3% specificity in non-target strains in local BLASTN analysis [27]. Overall, our candidate targets exhibited superior performance in both specificity and positive coverage relative to the previously reported marker.
To select an optimal specific target for the detection of B. gladioli pv. cocovenenans, the primer’s specificity and sensitivity for each target were determined. As illustrated in Table 1 and Figure S1, both primer pairs successfully amplified the target amplicon across all tested strains of B. gladioli pv. cocovenenans, while no amplification products were observed in all non-target strains, indicating high primer specificity. The qPCR detection method based on two molecular targets exhibited a limit of detection (LOD) of 4.1 × 102 CFU/g for B. gladioli pv. cocovenenans in artificially contaminated samples (Figure S2). Based on amplification efficiency and LAMP primer design performance, group_0918 was selected for subsequent reactions.

2.2. Verification of LAMP-Based Visual Assay

To achieve novel LAMP-based visual detection of B. gladioli pv. cocovenenans, LAMP primers were designed based on the specific molecular target group_0918 (Table 2), and Figure S3 illustrates the main steps of LAMP and the positioning of the LAMP-modified primers on the target DNA sequence.
The optimal LAMP reaction conditions were determined as follows: The total reaction volume of 25 μL contained 2.5 μL of 10× isothermal amplification buffer, 1 μL of Bst 2.0 WarmStart DNA polymerase (8000 U/mL), primer mixtures of F3/B3:LB/LF:FIP/BIP = 1:4:8 (1 = 0.2 µmol/L), 1 μL of Mg2+ (125 mmol/L), 5 μL of dNTPs (5 mmol/L), 1 μL of target DNA, and ultrapure water to complete the final volume. The LAMP optimal reaction was performed at 65 °C (Figure S4), followed by inactivation at 85 °C for 10 min. Subsequently, 80 μL of 10-fold-diluted LAMP products was thoroughly mixed with 2 μL of anti-digoxigenin (DIG) antibody-modified Au@PDA probes for subsequent LFD visual detection. In the presence of target DNA, LAMP amplicons dual-labeled at both ends with digoxin (DIG) and biotin were generated, which specifically bound to Au@PDA probes in the reaction system. During lateral flow, the biotin-labeled amplicons were specifically captured by immobilized anti-biotin antibodies on the T line, while free Au@PDA probes were recognized and bound by goat anti-mouse secondary antibodies on the C line, thereby forming two distinct visible bands. In contrast, no LAMP was triggered without target DNA. Only free Au@PDA probes were captured by antibodies on the C line, yielding a single distinct control line band. To prevent the non-specific adsorption of large LAMP amplicons onto the membrane matrix and to ensure capillary flow efficiency, we optimized the running buffer with surfactants.

2.3. Sensitivity of LAMP-Based Visual Method

The sensitivity of LAMP-based visual assay was determined using concentration gradients ranging from 100 to 107 of B. gladioli pv. cocovenenans. The plate counting result on LB agar indicated that the concentration of fresh bacterial liquid of B. gladioli pv. cocovenenans was 4.1 × 108 CFU/mL. All genomic DNA was extracted for traditional LAMP and LAMP visual analysis. As shown in Figure 2A, typical ladder-like bands were observed in lanes 1 to 7, while no specific amplicons were detected in lane 8. The LOD of the conventional LAMP assay was calculated to be 4.1 × 101 CFU/mL for pure culture samples. For the LFD method, two bands were observed at the concentration of 4.1 × 102 CFU/mL, while only a single quality control band was present in the 4.1 × 101 CFU/mL group and the blank control. And the absorbance ratio of the T line (ABT) to the C line (ABc) at the concentration of 102 CFU/mL was significantly higher than those obtained at lower concentrations of 102 CFU/mL and the blank control group. Therefore, the LOD of this LFD method was determined to be 4.1 × 102 CFU/mL, with a linear range covering 4.1 × 102–4.1 × 106 CFU/mL in pure culture samples (Figure 2B,C).
For LOD evaluation in artificially spiked samples, fresh spiked black fungus samples with concentration gradients of 101 to 108 CFU/g were obtained. In Figure 3A, the LOD of the conventional LAMP assay was calculated to be 4.1 × 102 CFU/g in a spiked black fungus sample (Figure 3A). The LOD of the LFD method was determined to be 4.1 × 103 CFU/g, with a linear range covering 4.1 × 103–4.1 × 107 CFU/g (Figure 3B,C) and a coefficient of determination (R2) of 0.95 (Figure 3C). It should be noted that although the LFD method exhibited a linear detection range of 4.1 × 103–4.1 × 107 CFU/g with an R2 of 0.95 (Figure 3C), residual analysis revealed an uneven distribution along the concentration gradient, with substantially larger absolute residuals at low bacterial loads, indicating poor linearity within this low-concentration interval. Specifically, the nonlinear deviation was most pronounced at concentrations below 104 CFU/g, whereas acceptable linearity was observed across the higher concentration range (105–107 CFU/g). This nonlinear deviation was likely attributable to the complex food matrix effect: DNA extraction by the boiling lysis approach failed to sufficiently remove endogenous inhibitory components, including polysaccharides and proteins, and these residual impurities suppress LAMP more severely when template DNA is limited, thus accounting for the compromised linearity at low concentrations. Despite this limitation in quantitative linearity at low concentrations, the LFD biosensor achieved an LOD comparable to that of the conventional LAMP method (only one order of magnitude higher). The modest loss of analytical sensitivity is an inherent feature of lateral flow platforms, primarily resulting from partial signal attenuation during chromatographic migration and specific capture of amplicons on the test strip. Nevertheless, the instrument-free format and simple operational workflow of this LFD-based detection system still satisfy the requirements of POCT. The application of commercial DNA extraction kits could further improve genomic DNA recovery and reduce co-extracted inhibitors, thereby alleviating matrix suppression and enhancing linear fitting performance in complex sample testing in future applications.

2.4. Specificity of LAMP-Based Visual Method

To determine the specificity of the LAMP visual assay, genomic DNA from six target B. gladioli pv. cocovenenans strains and 14 non-target B. gladioli pv. cocovenenans strains was extracted (Table S4). As shown in Figure 4, positive results were obtained for all target B. gladioli pv. cocovenenans strains, while negative signals were obtained for non-target bacterial strains, indicating excellent specificity for the identification of B. gladioli pv. cocovenenans.

2.5. Application of the LAMP Visual Method in Natural Samples

To assess the application of LAMP visual detection, a total of 22 samples were prepared for DNA extraction. All results are shown in Figure 5; only two positive control samples exhibited positive test results for B. gladioli pv. cocovenenans, whereas the remaining 20 food samples produced negative results using this established assay. Although the sensitivity, specificity, and efficiency were all 100% in the 22 tested samples (Table 3), the small number of positive samples (n = 2) resulted in a relatively wide 95% confidence interval for sensitivity (34.2–100%), while the specificity (83.9–100%) and efficiency (85.1–100%) showed narrower intervals, reflecting the limited sample size and the high consistency with the standard method.

3. Discussion

B. gladioli pv. cocovenenans mainly contaminates coconuts, edible fungi, cereal crops, and tuber plants, and it readily colonizes humid, organic-rich habitats and synthesizes lethal toxins, thereby resulting in severe economic losses and serious threats to public health [33,34]. At present, the gold standard for the detection of B. gladioli pv. cocovenenans involves a series of procedures, including pre-enrichment, biochemical identification, serotyping, and liquid chromatography analysis. These conventional approaches are time-consuming, laborious, and costly, and they fail to meet the demand for large-scale sample screening. PCR-based molecular detection provides an alternative strategy for the identification of B. gladioli pv. cocovenenans [29]. Previous studies have demonstrated that genes sequencing, such as recA, hisA, gyrB, and 16S rRNA, can be used to differentiate B. gladioli strains [16]. Nevertheless, phylogenetic analysis based on these single gene demonstrates a complex evolutionary relationship within the genus Burkholderia, resulting in inaccurate strain identification. Moreover, reported targets for the specific identification of B. gladioli pv. cocovenenans, such as the 16S-23S rRNA internal transcribed spacer (ITS) [26] and virulence gene BonM [27], were mined based on small-scale genomic datasets, gene fragments, or single virulence genes. High sequence homology of these targets among closely related Burkholderia species, coupled with frequent genetic variations during natural evolution, substantially reduces their specificity and accuracy in practical detection [35]. Therefore, mining of novel conserved molecular targets is essential to establish a reliable approach for accurate detection of B. gladioli pv. cocovenenans.
In contrast to conventional strategies that rely on coding sequences or individual virulence genes, this study employed pan-genome analysis for target mining based on whole-genome sequence alignment. This robust approach has been widely adopted to identify molecular markers associated with bacterial virulence, serotyping, molecular subtyping, and antibiotic resistance [32]. In this study, a total of 501 genomic sequences, including 489 from Burkholderia strains and 12 from other common pathogenic bacteria, were retrieved from the NCBI database and in-house sequencing data. Two novel, specific molecular targets were identified in this study. These targets predominantly derive from genes acquired via interspecific horizontal gene transfer and exhibit stable conservation in strains displaying the associated phenotypic traits [36]. The newly identified targets provide an efficient and convenient alternative for the accurate detection of B. gladioli pv. cocovenenans. It is noteworthy that both target genes characterized in this study correspond to hypothetical proteins of unknown function. Characterization of these protein-coding regions is crucial for unraveling their gene architecture and biological functions, which will significantly enhance our comprehension of the metabolic and phylogenetic features of B. gladioli pv. cocovenenans [37].
With the continuous expansion of genomic databases, some previously reported species-specific nucleotide targets have been confirmed to exhibit cross-reactivity with non-target genomes [16]. It is essential to combine bioinformatics analysis and large-scale strain PCR validation to evaluate the specificity and sensitivity of molecular targets. As shown in Table S3, alignment against the local genomic database revealed that the specific targets identified in our study achieved 100% positive coverage and specificity, whereas previously reported targets displayed slight sequence overlap with other species [27]. PCR validation conducted with 13 target strains and 27 non-target strains indicated that the novel targets achieved positive amplification across all target strains and demonstrated high specificity towards non-target isolates. To achieve rapid and accurate identification of B. gladioli pv. cocovenenans, a qPCR system was established based on the newly screened specific targets. In artificially contaminated fresh black fungus samples, the LOD of the qPCR assay was 4.1 × 102 CFU/g for B. gladioli pv. cocovenenans. Compared with previously reported methods, the established qPCR assay presents a simpler workflow while maintaining high accuracy [38]. To further reduce reliance on sophisticated instruments, a LAMP method was developed using these molecular targets. Under optimal reaction conditions, the detection sensitivities for pure cultures and artificially contaminated fresh black fungus samples were 3.8 × 101 CFU/mL and 3.8 × 102 CFU/g, respectively. The specificity results exhibited no cross-reactivity toward related strains, verifying the favorable stability and reliability of this assay. However, conventional molecular detection techniques rely on agarose gel electrophoresis and fluorescent dye analysis, which fail to meet the requirements of on-site rapid detection. Furthermore, aerosol contamination is easily generated during nucleic acid amplification, leading to false-positive results [21].
To realize low-cost point-of-care testing (POCT), we designed matched linker probes and colorimetric probes and constructed a LAMP-based visualized nucleic acid strip platform (market survey: ¥132 for culture method, ¥50 for commercial qPCR assay, ¥20 for this LAMP-strip assay per test). Sensitivity evaluation showed that the LAMP visualized assay achieved LODs of 3.8 × 102 CFU/mL and 3.8 × 103 CFU/g in pure bacterial cultures and artificially contaminated black fungus samples, respectively. The assay displayed excellent specificity against 14 non-target strains. Its analytical performance, including specificity, LOD, and field applicability, was systematically compared with previously reported LAMP methods from Zheng et al. (2025) and Yao et al. (2025), with full details provided in Table S5 [23,24]. The testing results of 22 natural food samples demonstrated that the established visual LAMP method exhibited high consistency with the standard culture assay, suggesting promising prospects for practical applications. In this study, the performance verification of the LAMP assay was conducted at a pilot scale, with only 22 samples from two food matrices (fresh black fungus and wet rice noodles) included. The validation results cannot fully represent the assay performance across all food matrices potentially contaminated by B. gladioli pv. cocovenenans. Subsequent studies will expand the sample size and cover more food categories to further confirm the universality and stability of the established method.
Undeniably, the detection method established in this study still involves pre-enrichment and nucleic acid amplification procedures, which impose certain limitations on detection efficiency. Existing studies have integrated the CRISPR/Cas system with microfluidic chips for B. gladioli pv. cocovenenans detection. This approach enables discrimination of multiple subtypes of B. gladioli pv. cocovenenans without pre-amplification, and it remarkably improves detection efficiency and practical applicability [39,40]. In subsequent research, we will employ innovative specific molecular targets, integrate the CRISPR/Cas system with microfluidic chips and intelligent analytical technologies, and develop a high-throughput detection system for B. gladioli pv. cocovenenans to promote the prevention and control of food safety risks.

4. Materials and Methods

4.1. Mining of Novel Specific Targets for B. gladioli pv. cocovenenans

To identify specific targets of B. gladioli pv. cocovenenans, a total of 501 genome sequences were retrieved for pan-genome analysis (Table S1). The dataset comprises 489 taxonomically validated Burkholderia genomes (all publicly available strains from the NCBI database plus our in-house sequencing data, collected exhaustively to capture intra-genus genetic diversity) and 12 common foodborne pathogenic strains serving as negative controls for specificity validation. The pan-genome analysis based on a local script written in the Perl programming language was used to achieve rapid and effective screening [32]. Briefly, all genome sequences were annotated to establish an analysis library using the Prokka v1.11, an open-source prokaryotic genome annotation tool developed by Torsten Seemann (Monash University, Australia). Then, Roary v3.11.2, an open-source prokaryotic pan-genome analysis tool primarily developed by Andrew J. Page (The Wellcome Trust Sanger Institute, Hinxton, UK), was used to perform gene sequence alignment with a BLASTP identity cut-off of 85% [36]. The obtained gene coverage data were used to analyze the presence or absence of genes. Based on the principle of 100% gene coverage in the respective target strains and 0% in the nontarget strains, candidate targets of B. gladioli pv. cocovenenans were initially identified. An in-house whole-genome database of foodborne pathogenic bacteria (https://www.mbiosh.com/data-analysis/database/, accessed on 18 July 2025) and the NCBI online BLASTN program (against the non-redundant nucleotide (nt) database) were used to further validate the specificity of the target genes.

4.2. Bacterial Strains and Genomic DNA Extraction

The strains used in this study are listed in Table 1, including 13 target B. gladioli strains and 27 non-target strains. All strains were stored in 30% glycerin broth (v/v) at −80 °C before use. All test bacteria were grown in Luria–Bertani (LB) medium (Guangdong Huankai Co., Ltd., Guangzhou, China) at 37 °C with 180 rpm/min. Bacterial genomic DNA was extracted from each strain using the conventional boiling lysis method and stored at −20 °C prior to use [41].

4.3. Specificity and Sensitivity Verification of Candidate Targets

To evaluate the specificity of targets, the genomic DNA of 40 strains of experimental bacteria was extracted as templates for ordinary PCR reactions (Table 1). The reactions contained 5 µL of 2× Premix Taq (Takara Biomedical Technology Co., Ltd., Beijing, China), 0.5 µL of each forward and reverse primer (10 μM), 1 µL of each genomic DNA, and 3 µL of ultrapure water to a final volume of 10 µL. A T100™ Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA) was used to perform PCR amplification as follows: predenaturation for 3 min at 95 °C; 35 cycles of denaturation for 30 s at 95 °C; annealing for 30 s at 58 °C; and extension for 1 min at 72 °C; and a final extension at 72 °C for 5 min. Agarose gel electrophoresis (2.5%) and the Gel Doc™ XR+ Gel Documentation System (Bio-Rad Laboratories, Hercules, CA, USA) were used to analyze the PCR products. The criteria for great specificity targets were as follows: A single target band was amplified from the DNA of the target bacteria, while no amplification bands were observed from the DNA of non-target bacteria [42]. To evaluate the sensitivity of the molecular targets, a qPCR assay was established using the designed specific primer pairs. A serial 10-fold dilution of B. gladioli pv. cocovenenans from artificially contaminated samples, with concentrations ranging from 108 CFU/mL to 102 CFU/mL, was prepared for qPCR analysis. The total 20 μL reaction system contained 10 μL of TB Green™ Premix Ex Taq™ II (TaKaRa Biotech, Dalian, China), 0.5 μM of each primer, and 1 μL of template DNA, with ultrapure water added to make up the final volume. Amplification was carried out on a LightCycler® 96 real-time PCR instrument (Roche, Basel, Switzerland) with the following thermal profile: initial denaturation at 95 °C for 3 min, followed by 40 cycles of 95 °C for 10 s and 60 °C for 45 s. The acquired fluorescence data were analyzed using LightCycler® 96 Software v1.1.0.1320 (Roche, Basel, Switzerland). All experiments were performed in three replicates, with genomic DNA of the B. gladioli pv. cocovenenans standard strain as the positive control and nuclease-free water as the no-template negative control per amplification run.

4.4. Development of a LAMP Assay for B. gladioli pv. cocovenenans Visualization Detection

4.4.1. LAMP System

The LAMP primer pairs for B. gladioli pv. cocovenenans specific targets were designed through online software (http://primerexplorer.jp/e/, accessed on 25 August 2025) and synthesized by Sangon Biotech Co. Ltd., Shanghai, China (Table 2). The LAMP reaction system was prepared with minor modifications according to a previous study [43]. A temperature gradient ranging from 58 °C to 68 °C was set to screen the optimal amplification condition of the LAMP assay, and the temperature producing the clearest and brightest ladder-like bands was determined as the optimal reaction temperature. The total LAMP reaction volume of 25 µL contained a 10× isothermal amplification buffer, MgSO4 (Sangon Biotech Co., Ltd., Shanghai, China), dNTPs (5 mmol/L, Sangon Biotech Co., Ltd., Shanghai, China), Bst 2.0 WarmStart DNA polymerase (New England Biolabs, Ipswich, MA, USA), outer primers F3/B3, inner primers FIP/BIP, loop primers LB/LF, template DNA (genomic DNA from 105 CFU/mL target strains), and ultrapure water. All amplification reactions were set with genomic DNA of the B. gladioli pv. cocovenenans standard strain as the positive control and nuclease-free water as the no-template negative control. The reactions were amplified at a constant temperature of 58–68 °C and inactivated at 85 °C for 10 min. All amplified products (template: genomic DNA from 105 CFU/mL target strains) were identified via 2% agarose gel electrophoresis.
To mitigate aerosol contamination and prevent false positives in the LAMP system, reagent preparation, sample processing, and amplification/detection were performed in physically separated rooms with unidirectional workflow. During the preparation of the reaction system, aerosol-resistant filter tips were used exclusively, and each reaction mixture was overlaid with mineral oil to prevent contamination. Workbenches and pipettes were regularly treated with DNA decontamination solution before and after experiments.

4.4.2. Development of a LAMP-Based Visual Method

As shown in Figure 1, the LFD platform was independently developed in our laboratory, consisting of three core components: a sample pad, an absorbent pad, and a nitrocellulose (NC) membrane. With the use of an XYZ3060 dispensing system (BioDot, Irvine, CA, USA), 0.8 mg/mL of anti-biotin antibodies and 1.2 mg/mL of goat anti-mouse secondary antibodies were separately coated on the NC membrane to prepare the test (T) line and control (C) line, with the dispensing rate set at 30 μL/s. The treated NC membrane was dried at 37 °C for 12 h. All test strips were hermetically preserved in a desiccator before use.
For visual detection, the LAMP products were diluted 10-fold with sterile water after amplification. Briefly, 80 μL of the diluted solution was thoroughly mixed with 2 μL of 1 mg/mL anti-digoxigenin (DIG) antibody-modified Au@PDA probes. The mixture was loaded onto the pre-prepared sample pad, incubated at room temperature for 15 min, and bands of the T and C lines were judged by the naked eye. For quantitative detection, a strip reader (FIC-S1, Fenghang Technology Co., Ltd., Hangzhou, China) was used to detect and analyze the absorbance intensity. The ratio of the ABT to ABC was utilized to eliminate background interference. All samples were tested in triplicate under consistent experimental conditions (including standardized LAMP product dilution, fixed probe dosage, consistent loading volume, and 15 min room-temperature incubation) to guarantee result repeatability.

4.5. Sensitivity Validation of the LAMP Visual Method

To determine the pure culture sensitivity of the LAMP assay, 10-fold serial dilutions of B. gladioli suspensions ranging from 100 to 108 CFU/mL were prepared. All genomic DNA was extracted for the traditional LAMP assay and LAMP visual analysis.
For LOD evaluation in artificially spiked samples, a total of 25 g of black fungus determined to be negative for B. gladioli by standard culture methods was homogenized in 225 mL of sterile saline solution. Fresh cultures of B. gladioli CICC25108 suspensions were mixed with the homogenate to prepare varied substrate concentrations of 100~107 CFU/g, and all genomic DNA was extracted for the traditional LAMP assay and LAMP visual analysis.

4.6. Specificity Validation of the LAMP Visual Method

The specificity of the developed assay was determined using 6 target B. gladioli strains and 14 non-target strains (Table S4). All genomic DNA for the traditional LAMP assay and LAMP visual analysis was extracted using the conventional boiling lysis method.

4.7. Natural Sample Analysis

For natural sample visual detection, a total of 22 food samples, including 11 fresh black fungus (10 unknown real samples and 1 positive control sample) and 11 wet rice noodles (10 unknown real samples and 1 positive control sample), were purchased from a local agricultural market (Nanchang, China). Subsequently, 25 g of each sample was added to sterile Erlenmeyer flasks containing 225 mL of GVC enrichment broth, thoroughly mixed, and cultured at 37 °C for 4–6 h. Each 1 mL of resuspension containing B. gladioli pv. cocovenenans was collected for DNA extraction and then for LAMP visual analysis. For comparison, the above 22 samples were detected using the Chinese national standard method (GB 4789.29-2020) [15].

5. Conclusions

In summary, specific molecular targets for B. gladioli pv. cocovenenans were successfully mined based on pan-genome analysis, and a novel LAMP-visual detection method was established for the on-site detection of B. gladioli pv. cocovenenans in food. Compared with the traditional culture method, the developed molecular assay is cost-effective and easy to operate, enabling specific and accurate identification of B. gladioli pv. cocovenenans in samples. In artificially contaminated fresh black fungus samples, the LAMP assay exhibited an LOD of 4.1 × 102 CFU/g for B. gladioli pv. cocovenenans, while the visual detection combined with the LFD platform achieved a sensitivity of 4.1 × 103 CFU/g. This developed LAMP visual strategy presents a credible alternative to the conventional culture method, and it provides valuable technical support for exploring the virulence profiles and epidemiological distribution of B. gladioli pv. cocovenenans in food matrices.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/molecules31152664/s1.

Author Contributions

B.Z.: Conceptualization, methodology, data curation, and writing—original draft; X.N.: investigation and methodology; H.F.: validation; X.M.: supervision and data curation; Z.Z.: resources and validation; C.Z.: visualization; J.X.: investigation and data curation; J.G.: visualization; M.Z.: formal analysis and software; L.L.: methodology and conceptualization; B.G.: supervision, funding acquisition, and project administration; X.W.: supervision, project administration, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This project is supported by the Jiangxi Provincial Natural Science Foundation (20242BAB20333, 20252BAC240614), the Science and Technology Project of Jiangxi Provincial Administration for Market Regulation (GSJK202401), and the Research Project of Jiangxi General Institute of Testing and Certification (ZYK202403).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding authors.

Acknowledgments

We thank the State Key Laboratory of Applied Microbiology, Southern China; Key Laboratory of Agricultural Microbiomics and Precision Application; Ministry of Agriculture and Rural Affairs; and faculty members at the Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, P.R. China.

Conflicts of Interest

The authors declare no conflicts of interest.

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Molecules 31 02664 g001
Figure 1. Schematic illustration of experimental workflow. (A) The workflow of special target screening for B. gladioli pv. cocovenenans; (B) establishment of a molecular method based on LAMP and lateral flow dipstick.
Figure 1. Schematic illustration of experimental workflow. (A) The workflow of special target screening for B. gladioli pv. cocovenenans; (B) establishment of a molecular method based on LAMP and lateral flow dipstick.
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Molecules 31 02664 g002
Figure 2. Sensitivity evaluation of conventional LAMP and LAMP-based visual assay in pure culture. (A) The results of the conventional LAMP assay, lanes 1–8: genomic DNA of target bacteria from 107 to 100 CFU/mL, lanes M: DL2000 DNA marker. (B) The results of the LAMP-based visual assay, No. 1–8: genomic DNA of target bacteria from 107 to 100 CFU/mL, NC: negative control. (C) Establishment of standard curves using the ratio values of ABT/ABC in relation to the logarithmic numbers of Burkholderia gladioli pv. cocovenenans cells within a range of 102~106 CFU/mL; ABT: the absorbance intensity of the T line; ABC: the absorbance intensity of the C line. All results were collected in triplicate, with error bars representing the standard deviation of three independent replicates.
Figure 2. Sensitivity evaluation of conventional LAMP and LAMP-based visual assay in pure culture. (A) The results of the conventional LAMP assay, lanes 1–8: genomic DNA of target bacteria from 107 to 100 CFU/mL, lanes M: DL2000 DNA marker. (B) The results of the LAMP-based visual assay, No. 1–8: genomic DNA of target bacteria from 107 to 100 CFU/mL, NC: negative control. (C) Establishment of standard curves using the ratio values of ABT/ABC in relation to the logarithmic numbers of Burkholderia gladioli pv. cocovenenans cells within a range of 102~106 CFU/mL; ABT: the absorbance intensity of the T line; ABC: the absorbance intensity of the C line. All results were collected in triplicate, with error bars representing the standard deviation of three independent replicates.
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Molecules 31 02664 g003
Figure 3. Sensitivity evaluation of conventional LAMP and LAMP-based visual assay in artificially spiked black fungus. (A) The results of the conventional LAMP assay, lanes 1–8: genomic DNA of target bacteria from 108 to 101 CFU/g, lanes M: DL2000 DNA marker. (B) The results of the LAMP-based visual assay, No. 1–8: genomic DNA of target bacteria from 108 to 101 CFU/g; NC: negative control. (C) Establishment of standard curves using the ratio values of ABT/ABC in relation to the logarithmic numbers of Burkholderia gladioli pv. cocovenenans cells within a range of 103~107 CFU/g; ABT: the absorbance intensity of the T line; ABC: the absorbance intensity of the C line. All results were collected in triplicate, with error bars representing the standard deviation of three independent replicates.
Figure 3. Sensitivity evaluation of conventional LAMP and LAMP-based visual assay in artificially spiked black fungus. (A) The results of the conventional LAMP assay, lanes 1–8: genomic DNA of target bacteria from 108 to 101 CFU/g, lanes M: DL2000 DNA marker. (B) The results of the LAMP-based visual assay, No. 1–8: genomic DNA of target bacteria from 108 to 101 CFU/g; NC: negative control. (C) Establishment of standard curves using the ratio values of ABT/ABC in relation to the logarithmic numbers of Burkholderia gladioli pv. cocovenenans cells within a range of 103~107 CFU/g; ABT: the absorbance intensity of the T line; ABC: the absorbance intensity of the C line. All results were collected in triplicate, with error bars representing the standard deviation of three independent replicates.
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Molecules 31 02664 g004
Figure 4. Specificity validation of conventional LAMP and LAMP-based visual assay. (A) The specificity results of the conventional LAMP assay, lanes 1–6: target B. gladioli strains, lanes M: DL2000 DNA marker. (B) Lanes 1–14: non-target strains, lanes M: DL5000 DNA marker. (C) The specificity results of the LAMP-based visual assay: No. 1–6: target B. gladioli strains; No. 7–20: non-target strains.
Figure 4. Specificity validation of conventional LAMP and LAMP-based visual assay. (A) The specificity results of the conventional LAMP assay, lanes 1–6: target B. gladioli strains, lanes M: DL2000 DNA marker. (B) Lanes 1–14: non-target strains, lanes M: DL5000 DNA marker. (C) The specificity results of the LAMP-based visual assay: No. 1–6: target B. gladioli strains; No. 7–20: non-target strains.
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Figure 5. Natural sample analysis. No 1–10: unknown fresh black fungus; No 11: spiked fresh black fungus; No 12–21: unknown wet rice noodles; No 22: spiked wet rice noodles.
Figure 5. Natural sample analysis. No 1–10: unknown fresh black fungus; No 11: spiked fresh black fungus; No 12–21: unknown wet rice noodles; No 22: spiked wet rice noodles.
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Table 1. Strain information for the specific target analysis of B. gladioli pv. cocovenenans in this study.
Table 1. Strain information for the specific target analysis of B. gladioli pv. cocovenenans in this study.
OrganismNo.Bacterial SpeciesStrainSourceSpecial Target for PCR
Group_0918Group_0110
Burkholderia spp.1–4Burkholderia gladioli pv. cocovenenansCICC25108, CICC25126, CICC25131, CICC25131a++
5–13Burkholderia gladioli pv. cocovenenansBGC_0110, BGC_0111, BGC_0112, BGC_0113, BGC_0114, BGC_0115, BGC_0116, BGC_0117, BGC_0118b++
14Burkholderia gladioliBG_0119b−−
15Burkholderia cepaciaCICC10857a−−
16Burkholderia contaminansCICC23882a−−
17Burkholderia aenigmaticaCICC24958a−−
18Burkholderia multivoransCICC25193a−−
19Burkholderia metalliresistensCICC10561a−−
20Burkholderia cenocepaciaCICC25294a−−
21Burkholderia cenocepaciaCICC25262a−−
Non-target strains22Pseudomonas aeruginosaATCC 10104c−−
23Pseudomonas aeruginosaATCC 15442c−−
24Escherichia coliCMCC 44103d−−
25Cronobacter sakazakiiATCC 29544c−−
26Bacillus cereusATCC 14579c−−
27Campylobacter jejuniATCC 6633c−−
28Vibrio parahemolyticusATCC 33847c−−
29Listeria monocytogenesATCC 19114c−−
30Listeria monocytogenesATCC 19113c−−
31Staphylococcus aureusATCC 29213c−−
32Staphylococcus epidermidisSE-1b−−
33StaphylococcushaemolyticusSH-1b−−
34Proteus mirabilisCMCC 49005d−−
35Salmonella enteritidisCMCC 50335d−−
36Proteus vulgarisCMCC 49027d−−
37Flavobacterium columnareATCC 23463c−−
38Flavobacterium aquatileATCC 11947c−−
39FlavobacteriumjohnsoniaeATCC 17061c−−
40Flavobacterium hydatisATCC 29551c−−
a: CICC, China Center of Industrial Culture Collection, China; b: laboratory isolate; c: ATCC, American Type Culture Collection, USA; d: CMCC, China Medical Culture Collection, China; +/−: positive and negative signals.
Table 2. Sequences involved in this study.
Table 2. Sequences involved in this study.
NameSequence (5′-3′)
G0918-PCR-122FAAACCACCCGCAACCTGAT
G0918-PCR-122RGAAACGCAACACCTCCTCCA
G0110-PCR-258FGACCGCCTTCTTCTCCCTGC
G0110-PCR-258RTGGATGATCGCGTGATTCGT
G0918-LAMP-F3CTGGCCGCGTATTTCCG
G0918-LAMP-B3CGCAGCAGCGTATAGACAC
G0918-LAMP-FIPBiotin-CTCGTCGTCGTCGGCGATGT-GAAGACGACGGCGAGGAGA
G0918-LAMP-BIPDig-ATGAGCGAGGAGGAATTGCTCG-CAGGTTGCGGGTGGTTTC
G0918-LAMP-LBGCAGCAGGTTCAGCAGGT
G0918-LAMP-LFGCAATGCGTGATGCTGTTGTT
Table 3. Statistical analysis between conventional LAMP, LAMP visual assay, and the standard method in actual sample detection.
Table 3. Statistical analysis between conventional LAMP, LAMP visual assay, and the standard method in actual sample detection.
Sample TypesSample NameNumber of SamplesStandard MethodConventional LAMP AssayLAMP Visual AssaySensitivity (%)
(95% CI)		Specificity (%)
(95% CI)		Efficiency
(%)
(95% CI)
+−+−+−
Natural negative samples (total n = 20)Fresh black fungus10010010010100
(34.24–100)		100
(83.89–100)		100 (85.14–100)
Wet rice noodles10010010010
Spiked samples (total n = 2)Spiked fresh black fungus1101010
Spiked wet rice noodles1101010
Note: Values in parentheses represent 95% Wilson score confidence intervals for sensitivity and specificity.
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Zhou, B.; Nie, X.; Fan, H.; Mao, X.; Zhan, Z.; Zhou, C.; Xiong, J.; Gao, J.; Zhang, M.; Li, L.; et al. A Novel LAMP-Based Lateral Flow Dipstick Technique for Rapid and Visual Detection of Burkholderia gladioli pv. cocovenenans. Molecules 2026, 31, 2664. https://doi.org/10.3390/molecules31152664

AMA Style

Zhou B, Nie X, Fan H, Mao X, Zhan Z, Zhou C, Xiong J, Gao J, Zhang M, Li L, et al. A Novel LAMP-Based Lateral Flow Dipstick Technique for Rapid and Visual Detection of Burkholderia gladioli pv. cocovenenans. Molecules. 2026; 31(15):2664. https://doi.org/10.3390/molecules31152664

Chicago/Turabian Style

Zhou, Baoqing, Xiang Nie, Hongwei Fan, Xudong Mao, Zhongxu Zhan, Cheng Zhou, Jingwen Xiong, Jiatian Gao, Mengxiang Zhang, Li Li, and et al. 2026. "A Novel LAMP-Based Lateral Flow Dipstick Technique for Rapid and Visual Detection of Burkholderia gladioli pv. cocovenenans" Molecules 31, no. 15: 2664. https://doi.org/10.3390/molecules31152664

APA Style

Zhou, B., Nie, X., Fan, H., Mao, X., Zhan, Z., Zhou, C., Xiong, J., Gao, J., Zhang, M., Li, L., Gan, B., & Wu, X. (2026). A Novel LAMP-Based Lateral Flow Dipstick Technique for Rapid and Visual Detection of Burkholderia gladioli pv. cocovenenans. Molecules, 31(15), 2664. https://doi.org/10.3390/molecules31152664

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