Next Article in Journal
Quantifying Soybean Defects: A Computational Approach to Seed Classification Using Deep Learning Techniques
Previous Article in Journal
Application of Urea and Ammonium Nitrate Solution with Potassium Thiosulfate as a Factor Determining Macroelement Contents in Plants
Previous Article in Special Issue
Rapid Automatic Cacao Pod Borer Detection Using Edge Computing on Low-End Mobile Devices
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Development and Evaluation of a Loop-Mediated Isothermal Amplifcation (LAMP) Assay for Specific and Sensitive Detection of Puccinia melanocephala Causing Brown Rust in Sugarcane

1
Hainan Key Laboratory for Monitoring and Control of Tropical Agricultural Pests, Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
2
School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
3
College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China
4
Guangxi Subtropical Crops Research Institute, Nanning 530001, China
5
Sanya Research Institute, Chinese Academy of Tropical Agricultural Sciences, Sanya 572025, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Agronomy 2024, 14(6), 1096; https://doi.org/10.3390/agronomy14061096
Submission received: 3 April 2024 / Revised: 15 May 2024 / Accepted: 18 May 2024 / Published: 22 May 2024

Abstract

:
Sugarcane brown rust (SCBR), caused by Puccinia melanocephala, is a destructive fungal disease that has extensively spread in the sugarcane-cultivating regions across the world. Early monitoring plays an important role in predicting the P. melanocephala epidemic and managing SCBR. However, accurately identifying SCBR based on symptoms and urediniospore morphology at the initial stage is a challenge. Further, it is tedious, time-consuming, labor-intensive, and requires expensive equipment to detect P. melanocephala using PCR-based methods. Loop-mediated isothermal amplification (LAMP) technology is renowned for its speed, simplicity, and low equipment requirements for specifically and sensitively identifying many pathogens. Therefore, in this study, a novel and highly sensitive LAMP assay was developed for the specific detection of P. melanocephala in sugarcane. Here, the internal transcribed spacer (ITS) sequence of P. melanocephala was selected as the target gene for LAMP primer design. Based on the color change of SYBR Green I and gel electrophoresis, specific LAMP primers were screened. Further, the optimal reaction conditions for the LAMP assay were determined at 63 °C for 60 min. The LAMP assay showed a high degree of specificity for the detection of P. melanocephala in sugarcane, with no cross-reactivity with other fungal pathogens. The established LAMP protocol was highly sensitive and can be used to detect as low as 1 pg/μL of P. melanocephala plasmid DNA, which is comparable to that of nested PCR and ~100 times more sensitive than conventional PCR. Finally, the detection rate of the LAMP method was higher than that of conventional and nested PCR in field samples.

1. Introduction

Sugarcane (Saccharum spp.) is an important tropical and subtropical cash crop grown worldwide [1]. Unfortunately, it is affected by various diseases such as red rot, smut, wilt, rust, leaf scald, and yellow leaf [2,3,4]. Sugarcane brown rust (SCBR), caused by the fungal pathogen Puccinia melanocephala, is a devastating disease limiting the sustainable production of sugarcane globally [5]. Typical foliar symptoms initially include yellowish, tiny, elongated spots appearing on both leaf surfaces. The yellow spots expand and turn reddish brown, ultimately resulting in leaf necrosis and premature senescence of even young leaves [6,7]. SCBR was first reported in Java in 1890 [8] and has gradually increased in its geographical distribution [9]. Since the 1970s, this disease has been particularly pervasive, with outbreaks occurring in almost all sugarcane-growing regions in the world, accompanied by serious yield reduction and sucrose losses [9,10]. China is an important producer of sugarcane in the world, comprising 1.32 million hectares of cultivation area and producing about 106 million tons of sugarcane in Guangxi (71.16%), Yunan (15.30%), Guangdong (12.62%), and Hainan (0.09%) provinces (National Bureau of Statistics of China, 2021). However, the occurrence of SCBR generally results in a loss of 15–30% in sugarcane production. Serious disease outbreaks have been reported to cause nearly 40% of loss in sugarcane production, resulting in a serious threat to the stability and sustainability of the sugar industry in China [9,10].
Selecting and breeding disease-resistant cultivars is the most cost-effective measure to control SCBR [9,11]. However, long-term resistance to SCBR is hindered by the constant evolution of the pathogen [12]. Further, breeding and selecting for resistance is challenging due to its complex genome. Sugarcane breeding is a long-drawn-out process, normally taking ten or more years. In addition, the process of replacing susceptible cultivars is slow, owing to the following reasons: firstly, sugarcane is a perennial crop, replanting in China approximately every two to three years; secondly, only a few new varieties were generally released for commercial production each year; thirdly, sugarcane, being a vegetatively propagated crop, requires a longer period to produce adequate planting material for extensive cultivated areas [12]. Therefore, chemical control of SCBR emerges as the obvious choice without a rapid replacement of susceptible cultivars with resistant ones [13].
Early monitoring is crucial for P. melanocephala epidemic forecasting and making informed decisions on fungicide application to effectively control SCBR, particularly when the disease symptoms are masked, or the suspected symptoms appear in the sugarcane leaves [12,13]. However, the accurate identification of SCBR at the early stage of the disease development is hampered by several difficulties. Firstly, it is a challenge to diagnose SCBR when the disease symptoms are masked in the absence of additional tools or techniques. Secondly, it is difficult to distinguish co-existing brown and orange rusts (caused by P. kuehnii) in sugarcane based on early symptoms of infection. Thirdly, relying solely on personal experience and visual observation to discriminate urediniospore morphology of P. melanocephala and P. kuehnii by microscopic inspection can sometimes lead to misdiagnosis, especially when the urediniospore morphology is not distinct enough [14]. It is effective and accurate in diagnosing plant diseases by molecular assays to detect plant pathogens at the early stage [15,16]. Currently, several PCR-based methods are available for the detection of P. melanocephala in sugarcane, such as PCR using universal primers [17] or specific primers [18], nested PCR [19], and single-tube PCR [20]. Nevertheless, these methods are complex, time-consuming, and require expensive instrumentation [21]. Poor sensitivity is another limitation [15,16]. Therefore, a simple, fast, and low equipment requirement method for specifically and sensitively detecting P. melanocephala in sugarcane is needed.
Loop-mediated isothermal amplification (LAMP)-based assay, originally developed by Notomi et al. (2000) [22], is an alternative method for rapid detection of various pathogens, including oomycetes, fungi, bacteria, viruses, and nematodes from plant or animal [23,24,25,26,27]. Under isothermal conditions, DNA can be amplified with higher specificity and sensitivity [28]. Further, visual analysis of changes in turbidity or color in the LAMP-based assay facilitates detection, obviating the need for further postamplification techniques such as electrophoresis or ultra-violet (UV) imaging [29,30]. To date, a series of LAMP assays have been established to detect sugarcane pathogens [14,31,32]. However, the detection of P. melanocephala in SCBR-infected sugarcane has yet to be reported.
Therefore, in this study, our objective is to develop a rapid, simple, and effective LAMP-based assay for the detection of P. melanocephala in sugarcane. For this purpose, we designed and screened several specific primers for LAMP by targeting the internal transcribed spacer (ITS) sequences of P. melanocephala. Then, we optimized several parameters of the LAMP protocol and validated the specificity and sensitivity of the method. Furthermore, we compared the detection rates using LAMP-based assays in field samples with those of conventional and nested PCR assays. This method accelerated the diagnosis of early infection with P. melanocephala in sugarcane.

2. Materials and Methods

2.1. Isolates and Extraction of DNA

Field strains of P. melanocephala were respectively obtained from diseased leaves in four provinces representing several main sugarcane-growing regions in the south of China, including Guangxi (Heping Village in Longzhou and Shanxu Farm in Chongzuo), Yunnan (Guiling Lake in Mangshi), Guangdong (Huoju Farm in Leizhou and Dongfanghong Farm in Xuwen, and Hainan (Bayi Farm in Danzhou) (Figure 1). Six samples of P. melanocephala pustules were carefully scraped from the leaf surface using a sterile needle (Figure 2D; Table S1), and they were used as positive samples for the development of the LAMP assay. Samples without DNA templates were used as negative controls. Forty sugarcane leaves exhibiting suspected symptoms of SCBR at the early stage were evaluated via LAMP and stored at −80 °C until needed (Figure 2B,C; Table 1).
In addition, other fungal pathogens (Table S2), including P. kuehnii (causing sugarcane orange rust), Hemileia vastatrix (causing coffee leaf rust), Phakopsora ampelopsidis (causing grapevine leaf rust), and Coleosporium plumierae (causing Plumeria spp. rust) were obtained from typical diseased leaves, which were identified by morphological observation and molecular identification for plant pathogens. Ustilago scitaminea (causing sugarcane smut), Colletotrichum falcatum (causing sugarcane red rot), Leptosphaeria sacchari (causing sugarcane ring spot), Pytophthora nicotianae (causing sisal zebra disease), and Aspergillus niger (causing sisal stem rot) were collected from pure cultures in our laboratory. These pathogens were used to determine the specificity of the developed LAMP assay. A modified hexadecyltrimethylammonium bromide (CTAB) method was used to extract the genomic DNAs of plant leaves [33]. According to the manufacturer’s protocol, other fungal isolates from pure cultures were extracted using a fungal DNA kit (E.Z.N.A.TM Fungal DNA Kit, Omega, Norcross, GA, USA). The DNA quality and concentration of each sample were determined using a NanoDrop 2000c Spectrophotometer (Thermo Scientific, Waltham, MA, USA), and the obtained DNAs were stored at −20 °C.

2.2. LAMP Primer Design and Screening

In this study, the target gene of the LAMP assay is the ITS sequence of P. melanocephala. The DNAs of six field strains of P. melanocephala (Table S1) were amplified by PCR using fungal universal primer Pm1F/PM2R [18,19]. The target fragments of PCR products were purified using Wizard® SV Gel and a PCR Clean-up System (Promega, Madison, WI, USA). The purified DNA fragments were cloned to pMD18-T simple vector (Takaka Bio Inc., Kusatsu, Japan) and sequenced bidirectionally (Sangon Biotech, Shanghai, China). To obtain the specific portion of ITS sequence for P. melanocephala, several P. melanocephala strains and some other fungal species of Uredinales were aligned using the online software Multalin (http://multalin.toulouse.inra.fr/multalin/multalin.html) (2000 version) (accessed on 18 March 2024). In the specific screened region, several sets of LAMP primers, including outer primers F3/B3 and inner primers FIP (consisting of F1c and F2)/BIP (consisting of B1c and B2), were designed using Primer Explorer 4.0 (https://primerexplorer.jp/e/) (Eiken Chemical Co., Ltd., Tokyo, Japan) (accessed on 18 March 2024). Default primer parameters were set, and the primers were synthesized by Invitrogen Trading (Shanghai) Co., Ltd., Shanghai, China.
A set of specific and sensitive LAMP primers were screened (Figure 3; Table S3). The LAMP reaction protocol is presented in Table 2. The amplification was performed at 60 °C for 60 min and was terminated by heating at 85 °C for 8 min. The LAMP reaction protocol and reaction program were based on previous studies [34,35,36]. After the LAMP products were cooled for 5–10 min at room temperature, they were instantly visualized by adding SYBR Green I (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China). It was considered to be P. melanocephala-positive when the samples turned green, while it was considered to be P. melanocephala-negative when they remained orange. The LAMP tubes were photographed with a Canon digital camera (Model: EOS 200D2 II)(Canon Inc., Tokyo, Japan). The amplified LAMP products were further observed on 2% agarose gel by staining with GoldviewTM (Beijing Solarbio Science & Technology, Beijing, China). In the negative controls, an equivalent volume of nuclease-free water was used instead of DNA in each reaction. Every treatment was replicated three times, and the experiment was repeated twice. In order to avoid cross-contamination, the LAMP amplification and colorimetric assays were carried out in different areas.

2.3. Optimization of LAMP Assays

According to the LAMP primers screened using the LAMP reaction system described above, different ratios of inner-to-outer primers, reaction temperature and time, concentrations of inner and outer primers, Mg2+, dNTP, and betaine were used to optimize the LAMP reaction. Specifically, the inner-to-outer primer concentration ratios were set to 2:1, 4:1, 6:1, and 8:1. The concentrations of Mg2+ were set to 2, 3, 4, 6, 8, 10, and 12 mM. The concentrations of dNTP were set to 0, 0.4, 0.8, 1.0, 1.2, 1.4, and 1.8 mM. The reaction temperatures were set to 57, 60, 63, and 65 °C. The reaction times were 15, 30, 45, 60, 75, and 90 min. The concentrations of betaine were 0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, and 1.6 mM. The products of the LAMP assay were detected using the described method above.

2.4. Validation of Specificity and Sensitivity

To investigate the specificity of the LAMP assay, the DNA extracts derived from the four samples of P. melanocephala from Guangdong Province and 12 other fungal species were tested (Table S2). To compare the differences in sensitivity between the optimized LAMP assay, conventional PCR, and nested PCR, the ITS gene recombinant plasmid DNAs of P. melanocephala were tested using 7 independent 10-fold dilutions ranging from 100 ng/μL to 10−4 ng/μL. The conventional PCR primers were Pm1F (5′-AATTG TGGCTCGAACCATCTTC-3′)/Pm1R (5′-TTGCTACTTTCCTTGATGCTC-3′) [18]. The nested PCR primers were PM2F (5′-GGCTTCATTGCCACATTACC3′)/PM2R (5′-TTTG AGGTCTTAAATGTTAGGGG-3′), followed by PM3F (5′-CATAAACACTATATTAAAG ATTTTGAAG-3′)/PM3R (5′-GTATTGC TACTTTCCTTGATGCTC-3′) [19]. The LAMP reaction protocol was performed as described above. The conventional PCR reaction was carried out in 20 μL containing 10× PCR buffer, 1 µM of each primer, 0.2 mM dNTP, 1 U rTaq DNA polymerase (TakaRa, Dalian, China), and 1 μL template DNA. The amplification conditions were: 94 °C for 3 min, 35 cycles of 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 45 s at, followed by 72 °C for 5 min. For the nested PCR amplification, the products of the first PCR were diluted 1:100 with nuclease-free water, and 1 μL was used as a template. The annealing temperature of the first and second PCRs were 58 °C and 61 °C, respectively. The remaining steps were similar to those of conventional PCR. The PCR-amplified products were analyzed via 1.2% agarose gel electrophoresis.

2.5. Field Application of the LAMP Assay

To assess the feasibility of the developed LAMP assay for the diagnosis of P. melanocephala in the diseased sugarcane samples, 40 sugarcane leaves exhibiting suspected symptoms of SCBR at the early stage were randomly collected from four provinces, including Guangxi (Heping Village in Longzhou County and Shanxu Farm in Chongzuo), Yunnan (Guiling Lake in Mangshi), Guangdong (Huoju Farm in Leizhou City and Dongfanghong Farm in Xuwen), and Hainan (Bayi Farm in Danzhou) (Table 1). Ten asymptomatic leaves obtained from healthy sugarcane plants growing in the same areas were used as negative controls, and the DNA of P. melanocephala was used as a positive control. The DNAs of these field samples were amplified using the optimized LAMP, conventional PCR, and nested PCR as described above, and the detection rates of P. melanocephala were compared.

3. Results

3.1. LAMP Primer Design and Screening

A total of six representative ITS sequences of P. melanocephala collected from different regions were obtained by PCR amplification using fungal universal Pm1F/PM2R [18,19]. The obtained ITS sequences of P. melanocephala shared more than 99.00% sequence similarity with each other (Table S4) and 99.12% to 99.65% similarity with P. melanocephala (accession nos. KP744149.1). Based on the sequence alignment of ITS sequences amplified from a single P. melanocephala strain in this study, eight P. melanocephala strains and twenty-five fungal species of Uredinales from Genebank, a specific region of 259 bp within ITS for P. melanocephala, were selected for primer design (Figures S1 and S2). Finally, five sets of LAMP primers (primers 1–5) were obtained (Table S3), and the corresponding locations and sequences of the LAMP primers are shown in Figure 3. Further, LAMP assays were used to detect P. melanocephala using the five sets of LAMP primers. The results are exhibited in Figure 4. Among the tested five sets of LAMP primers, the samples turned green with primer sets 2–5. However, the LAMP assay yielded the brightest products in agarose gel electrophoresis when the primer set was primer 4 (Figure 4). Thus, primer 4 was the best for detecting P. melanocephala (Figure 4). Specifically, the two outer sets of primer 4 were F3–4 (5′-CACCTGTTTGAGTGTCA TG-3′) and B3–4 (5′-TTAGGAGCCCTTACCCAA-3′), respectively. The two inner primer sets were FIP-4 (consisting of F1c-4 and F2–4, 5′-GTA ATTACAGCAACACTCATCATC-AAACCTCTCACTAAAACAACTTTG-3′) and BIP-4 (consisting of B1c-4 and B2–4, 5′-TGAATAAGTTGGATTGACTTGGTGT-AGATGGCAG TATTGCTACTTTC-3′).

3.2. Optimization of LAMP

To determine the optimal LAMP reaction system for the detection of P. melanocephala in sugarcane, different ratios of inner and outer primers, concentrations of Mg2+, dNTPs, betaine, and reaction temperatures and time were screened. It can be found that all the samples turned green when the inner-to-outer primer ratios ranged from 2:1 to 8:1. However, the ratio of 6:1 yielded the brightest amplification products, which were separated via agarose gel electrophoresis (Figure 5A). Thus, 6:1 was chosen as the optimal inner-to-outer primer ratio. Further, the samples turned green at Mg2+ concentrations of 2 to 4 mM. The LAMP assay yielded the brightest products at a Mg2+ concentration of 4 mM in agarose gel electrophoresis (Figure 5B). Thus, 4 mM was considered as the optimal Mg2+ concentration. In subsequent experiments, all the samples turned green at the tested dNTP concentrations of 0.4 mM to 1.8 mM, but the dNTP concentration of 1.0 mM had the highest amplification efficiency (Figure 5C). Therefore, we selected 1.0 mM as the optimal dNTP concentration. Based on color intensity and agarose gel electrophoresis, the reaction temperatures of 60 °C, 63 °C, and 65 °C were observed to have high amplification efficiency. Finally, 63 °C was selected as the optimal reaction temperature for subsequent experiments (Figure 5D). During the reaction time ranging from 15 min to 90 min, high color intensity and bright DNA bands were detected via agarose gel electrophoresis between 45 min and 90 min. Finally, 60 min was considered as the optimal reaction time (Figure 5E). Different betaine concentrations ranging from 0 to 1.6 mM resulted in a positive reaction, without obvious changes in color intensity of SYBR Green I or brightness of the DNA band in agarose gel electrophoresis (Figure 5F). Thus, no betaine was determined in the optimal LAMP system. Finally, the optimal LAMP reaction system is presented in Table 3. The mixture was incubated at 63 °C for 60 min, followed by another incubation at 85 °C for 8 min to terminate the reaction.

3.3. Specificity and Sensitivity of the LAMP Assay

To evaluate the specificity of the LAMP assay for P. melanocephala, the DNAs of four strains of P. melanocephala and twelve species of other fungal pathogens (Table S2) were analyzed. The results revealed that LAMP specifically detected P. melanocephala in sugarcane without a positive reaction with the 12 DNA isolates from other fungi (Figure 6). Therefore, this method is specific to P. melanocephala diagnosis. Further, the sensitivity evaluation showed that the detection limits of the optimized LAMP assay, conventional PCR, and nested PCR were 1 pg/μL, 100 pg/μL, and 1 pg/μL, respectively (Figure 7). This indicates that the sensitivity of the LAMP assay is comparable to that of nested PCR and ~100-fold higher than that of conventional PCR.

3.4. Evaluation of LAMP Using Field Samples

There are 40 DNA samples obtained from sugarcane leaves showing suspected symptoms of early SCBR. Three methods, including the LAMP assay, conventional PCR, and nested PCR, were used to test them. The results showed that 85% of P. melanocephala samples tested positive with LAMP, 80% with nested PCR, and 55% using conventional PCR (Table 1). By contrast, it yielded negative results in asymptomatic leaves collected from the field using the three types of PCRs. Thus, it was effective for the LAMP assay to detect P. melanocephala in sugarcane leaves exhibiting early symptoms of SCBR. According to the differences in detection rates, it is considered that LAMP is superior to conventional and nested PCRs for the detection of P. melanocephala in the suspected symptoms of early SCBR samples.

4. Discussion

SCBR is a devastating worldwide disease that severely decreases the sugarcane yield, resulting in economic loss. Early monitoring plays a crucial role in forecasting the P. melanocephala epidemic and managing SCBR. However, accurately identifying SCBR based on symptoms and urediniospore morphology at the early stage is difficult. PCR-based methods are considered to be the gold standard for the detection of P. melanocephala due to higher accuracy, including PCR using universal primers [18] or specific primers [18], nested PCR [19], and single-tube PCR [20]. However, they are time-consuming, labor-intensive, and require high-cost reagents and sophisticated equipment [21]. LAMP is a simple, time-saving, and low-cost nucleic acid-based technique [28]. It relies on color changes induced by pathogens for easy interpretation of the results. Therefore, in this study, a LAMP assay for specific and sensitive detection of P. melanocephala in sugarcane was developed.
Primer specificity is a key factor in LAMP. To date, a series of target genes have been selected to design LAMP primers for specifically detecting various fungal pathogens, such as ITS sequence [32,37,38,39], translation elongation factor 1α (TEF-1α), elongation factor (EF-1α) region, β-tubulin (β-tub2) gene, glyceraldehyde 3-phosphate dehydrogenase gene (GAPDH) [40,41], and Pep1 and bE genes [42]. The ITS sequence is frequently chosen as the target gene for detecting plant fungal pathogens due to its variability among closely related species and its high copy number in genomes. For example, ITS sequence has been used as a target to diagnose smut disease caused by Sporisorium scitamineum in sugarcane [32], downy mildew caused by Plasmopara viticola in grape [37], black spot caused by Marssonina brunnea in poplar [38], and round leaf spot caused by Mycocentrospora acerina in Panax notoginseng [39]. In this study, a specific ITS region of 259 bp for P. melanocephala was selected through multiple sequence alignment with a single P. melanocephala strain from our study, eight P. melanocephala strains, and twenty-five fungal species from ten families and fourteen genera of Uredinales. Then, five sets of LAMP primers were designed based on the specific region and its flanking regions (Figure 3). Furthermore, the specificity of these LAMP primers for the detection of P. melanocephala in sugarcane was verified but not of the other rust pathogens like P. kuehnii, H. vastatrix, P. ampelopsidis, and C. plumierae or other common sugarcane pathogens (U. scitaminea, C. falcatum, L. sacchari) (Figure 6). Thus, this developed LAMP assay can be considered to be specific for the detection of P. melanocephala in sugarcane.
Sensitivity is another crucial factor in molecular detection, as higher sensitivity facilitates the detection of target pathogens in samples. Generally, the sensitivity of LAMP is higher than that of PCR-based methods. For example, Guo et al. reported that the detection limit of the LAMP assay was 10-fold higher than that of conventional PCR for detecting Mycoplasma hyopneumoinae [43]. Su et al. reported that the sensitivity of LAMP was 100-fold higher than that of conventional PCR for detecting S. scitamineum [42]. However, some studies suggest that the sensitivity of LAMP is similar to that of PCR [43,44,45,46,47]. The copy number or size of various target genes and various parameters of the LAMP protocol play an important role in determining the sensitivity of the assay. In this study, based on the screened LAMP primers targeting the ITS sequence, we optimized the inner-to-outer primer ratio, concentrations of Mg2+, dNTPs, betaine, and reaction temperatures and time. Finally, the LAMP assay targeting the ITS gene is comparable to nested PCR and ~100-fold more sensitive than conventional PCR. Specifically, the detection limit of LAMP and nested PCR was 1 pg/µL, while that of conventional PCR was 100 pg/µL. This means that when the pathogen level of P. melanocephala is extremely low, LAMP and nested PCRs have the potential ability to detect it, whereas conventional PCR may not. Although the detection limit of LAMP is similar to that of nested PCR in this study, LAMP is simpler and faster than nested PCR. Thus, the LAMP-based assay described in this study is a better alternative to PCR-based techniques due to its simplicity and rapid and sensitive detection of P. melanocephala in sugarcane.
In this study, the newly established LAMP protocol is more rapid, specific, and sensitive than other methods described before, representing a reliable method for the diagnosis of P. melanocephala infection. It will be helpful for predicting the P. melanocephala epidemic and managing SCBR, demonstrating profound implications for increasing sugarcane yield and improving the economic income-earning of sugarcane producers. However, the pathogen P. melanocephala was still undetectable in some suspected SCBR samples, possibly due to low pathogen titer, insufficient sensitivity of the LAMP assay, or the presence of other plant pathogens. In this case, the plants analyzed could be marked, then followed up with a look for the presence or absence of the pathogen after the typical symptoms had appeared. Furthermore, this method has solely been employed to test the suspected SCBR samples. The applicability of this method for symptomless leaves sourced from laboratory-inoculated sugarcane plants or from diseased fields has not been explored, and its detection efficiency remains unknown. In addition, the development of an inoculum-based forecasting system requires further testing for the detection of airborne pathogen inoculum P. melanocephala at the early stage in environmental air samples. Of course, it will be more interesting if the colorimetric LAMP is developed for the detection of SCBR disease by using crude DNA extracted from sugarcane leaves in order to prove the strong point of the LAMP technique for in-field detection. It is worth noting that LAMP products can pose a significant risk of contamination [48], which can persist despite common mitigation measures. Thus, dried sucrose with the fluorescent dye on tube caps would be a safer solution, allowing for the analysis to be performed in a fully closed format. Nonetheless, the LAMP method developed here represents a promising approach for simple, rapid, specific, and sensitive identification of P. melanocephala for the early monitoring of SCBR in sugarcane leaves.

5. Conclusions

In this study, we designed and screened a set of specific LAMP primers by targeting the specific rDNA-ITS sequence, optimized the reaction condition under different parameters, and evaluated the specificity, sensitivity, and application of the developed LAMP assay. This is the first report on developing a simple, rapid, and low-equipment method for specifically and sensitively identifying P. melanocephala in sugarcane. It can be applied in the early monitoring of SCBR and will be helpful for predicting the P. melanocephala epidemic and managing SCBR.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy14061096/s1, Figure S1: Schematic diagram showing multiple sequence alignments between single representative ITS sequences of Puccinia melanocephala in this study, eight P. melanocephala strains, and twenty-five species from ten families in fourteen genera of Uredinales using the online software Multalin (2000 version) (http://multalin.toulouse.inra.fr/multalin/multalin.html)(accessed on 18 March 2024); Figure S2: Specific region (gray shadow) and its flanking region (yellow shadow) selected for primer design in the LAMP assay within ITS of Puccinia melanocephala; Table S1. Six isolates of P. melanocephala used to develop the LAMP assay; Table S2: Isolates used to test the specificity of LAMP for P. melanocephala; Table S3: Sequence information of LAMP primers used for amplification of the target sequence in the ITS gene of P. melanocephala; Table S4. The sequences of Puccinia melanocephala collected from six different sampling locations in this study.

Author Contributions

W.W.: Methodology, Formal analysis, Data curation, Writing—original draft preparation, Writing—review and editing; G.W.: Formal analysis, Data curation, Visualization, Writing—original draft preparation, Writing—review and editing, Funding acquisition; H.W.: Investigation, Validation, Visualization, Formal analysis, Data curation; L.Z.: Methodology, Validation, Data curation, Formal analysis; Y.L. (Yanqiong Liang): Methodology, Investigation, Data curation, Writing—review and editing; T.G.J.: Methodology, Investigation, Data curation, Writing—review and editing; Y.L. (Ying Lu): Investigation, Formal analysis, Writing—review and editing; X.H.: Investigation, Project administration, Formal analysis, Writing—review and editing; C.H.: Investigation, Project administration, Formal analysis, Writing—review and editing; J.Q.: Investigation, resources, Formal analysis, Writing—review and editing; K.Y.: Conceptualization, Supervision, resources, Formal analysis, Writing—review and editing, Funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Innovational Fund for Scientific and Technological Personnel of Hainan Province, grant number KJRC2023B18; the Hainan Provincial Natural Science Foundation of China, grant number 324RC458.

Data Availability Statement

Sequence data from this article can be found in GenBank at https://www.ncbi.nlm.nih.gov/genbank/ (accessed on 17 March 2024) with the accession numbers listed in the Results. All other relevant data are within the paper.

Conflicts of Interest

All the authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Formann, S.; Hahn, A.; Janke, L.; Stinner, W.; Strauber, H.; Logroño, W.; Nikolausz, M. Beyond sugar and ethanol production: Value generation opportunities through sugarcane residues. Front. Energy Res. 2020, 8, 579577. [Google Scholar] [CrossRef]
  2. Viswanathan, R.; Rao, G.P. Disease scenario and management of major sugarcane diseases in India. Sugar Tech 2011, 13, 336–353. [Google Scholar] [CrossRef]
  3. Li, Y.R.; Yang, L.T. Research and development priorities for sugar industry of China: Recent research highlights. Sugar Tech 2015, 17, 9–12. [Google Scholar] [CrossRef]
  4. Ovalle, W.; Viswanathan, R. Sustaining sugarcane production in Guatemala and Nicaragua through efficient disease management approaches. Sugar Tech 2020, 22, 361–366. [Google Scholar] [CrossRef]
  5. Li, X.; Xu, C.; Mao, J.; Liu, H.; Li, C.; Liu, X.; Lin, X.; Kong, C.; Lu, X. Detection of key brown rust resistance gene, Bru1, in 200 sugarcane (Saccharum L.) ancestral species and landraces using a four-primer molecular marker. Sugar Tech 2021, 23, 838–842. [Google Scholar] [CrossRef]
  6. Wang, X.Y.; Li, W.F.; Huang, Y.K.; Lu, X.; Luo, Z.M.; Yin, J.; Shan, H.L.; Zhang, R.Y. Evaluation of sugarcane introgression lines for resistance to brown rust disease caused by Puccinia melanocephala. Trop. Plant Pathol. 2013, 38, 97–101. [Google Scholar] [CrossRef]
  7. Avellaneda, M.C.; Hoy, J.W.; Pontif, M.J. Screening for resistance to sugarcane brown rust with controlled conditions inoculation. Plant Dis. 2015, 99, 1633–1639. [Google Scholar] [CrossRef]
  8. Chen, Q.L. Sugarcane Disease in the World; Agriculture Press: Beijing, China, 1982; pp. 34–40. [Google Scholar]
  9. Li, W.F.; Shan, H.L.; Zhang, R.Y.; Pu, H.C.; Wang, X.Y.; Cang, X.Y.; Yin, J.; Luo, Z.M.; Huang, Y.K. Identification of field resistance and molecular detection of the brown rust resistance gene Bru 1 in new elite sugarcane varieties in China. Crop Prot. 2018, 103, 46–50. [Google Scholar] [CrossRef]
  10. Wang, X.Y.; Li, W.F.; Huang, Y.K.; Shan, H.L.; Jiong, Y. Developing genetically segregating populations for localization of novel sugarcane brown rust resistance genes. Euphytica 2019, 215, 159. [Google Scholar] [CrossRef]
  11. Wang, H.B.; Chen, P.H.; Yang, Y.Q.; D’Hont, A.; Lu, Y.H. Molecular insights into the origin of the brown rust resistance gene Bru1 among Saccharum species. Theor. Appl. Genet. 2017, 130, 2131–2443. [Google Scholar] [CrossRef]
  12. Chaulagain, B.; Raid, R.N.; Rott, P. Timing and frequency of fungicide applications for the management of sugarcane brown rust. Crop Prot. 2019, 124, 104826. [Google Scholar] [CrossRef]
  13. Koch, G.; Ruaro, L.; Calegario, R.F.; Bespalhok, J.C.; Daros, E.; Oliveira, R.A.d.; Duarte, H.D.S. Control of orange rust and brown rust of sugarcane with systemic fungicides. Sugar Tech 2021, 23, 606–614. [Google Scholar] [CrossRef]
  14. Chandra, A.; Keizerweerd, A.T.; Grisham, M.P. Detection of Puccinia kuehnii causing sugarcane orange rust with a loop-mediated isothermal amplification-based assay. Mol. Biotechnol. 2016, 58, 188–196. [Google Scholar] [CrossRef]
  15. Salcedo, A.F.; Purayannur, S.; Standish, J.R.; Miles, T.; Thiessen, L.; Quesada-Ocampo, L.M. Fantastic downy mildew patho- gens and how to find them: Advances in detection and diagnostics. Plants 2021, 10, 435. [Google Scholar] [CrossRef] [PubMed]
  16. Patel, R.; Mitra, B.; Vinchurkar, M.; Adami, A.; Patkar, R.; Giacomozzi, F.; Lorenzelli, L.; Baghini, M.S. Review of recent advances in plant-pathogen detection systems. Heliyon 2022, 8, e11855. [Google Scholar] [CrossRef]
  17. White, T.J.; Bruns, T.; Lee, S.; Taylor, J. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In PCR Protocols: A Guide to Methods and Applications; Academic Press Inc.: New York, NY, USA, 1990; pp. 315–322. [Google Scholar]
  18. Glynn, N.C.; Dixon, L.J.; Castlebury, L.A.; Szabo, L.J.; Comstock, J.C. PCR assays for the sugarcane rust pathogens Puccinia kuehnii and P. melanocephala and detection of a SNP associated with geographical distribution in P. kuehnii. Plant Pathol. 2010, 59, 703–711. [Google Scholar] [CrossRef]
  19. Wang, H.; Wu, W.H.; Yang, X.G.; Yang, X.F.; Li, R.; Zheng, J.L.; Huang, X.; Liang, Y.Q.; He, C.P.; Yi, K.X. Establishment of a nested PCR detection system of Puccinia melanocephala sydow causing sugarcane brown rust disease. Chin. J. Trop. Crops 2017, 38, 2334–2339. [Google Scholar]
  20. Wu, W.H.; Liu, B.H.; Lu, P.P.; Liang, Y.Q.; He, C.P.; Li, R.; Zheng, J.L.; Huang, X.; Liang, Y.Q.; He, C.P.; et al. Establishment of single tube nested PCR detection system for Puccinia melanocephala. Sugar Crops China 2022, 44, 1–7. [Google Scholar]
  21. Shen, L.; Huang, M.; Fang, A.; Yang, Y.; Yu, Y.; Bi, C. Loop-mediated isothermal amplification for the rapid detection of the mutation of carbendazim-resistant isolates in Didymella bryoniae. Agronomy 2022, 12, 2057. [Google Scholar] [CrossRef]
  22. Notomi, T.; Okayama, H.; Masubuchi, H.; Yonekawa, T.; Watanabe, K.; Amino, N.; Hase, T. Loop-mediated isothermal amplification of DNA. Nucleic Acids Res. 2000, 28, E63. [Google Scholar] [CrossRef]
  23. Ortega, S.F.; Tomlinson, J.; Hodgetts, J.; Spadaro, D.; Gullino, M.L.; Boonham, N. Development of loop-mediated isothermal amplification assays for the detection of seedborne fungal pathogens Fusarium fujikuroi and Magnaporthe oryzae in rice seed. Plant Dis. 2018, 102, 1549–1558. [Google Scholar] [CrossRef] [PubMed]
  24. Wang, T.; Ji, H.; Wang, X.; Cheng, Y.; Guo, L.; Xu, J.; Gao, C. Development of a loop-mediated isothermal amplification method for the rapid detection of Phytopythium vexans. Front. Microbiol. 2021, 12, 720485. [Google Scholar] [CrossRef] [PubMed]
  25. Shu, R.; Yin, X.; Long, Y.; Yuan, J.; Zhou, H. Detection and control of Pantoea agglomerans causing plum bacterial shot-hole disease by loop-mediated isothermal amplification technique. Front. Microbiol. 2022, 13, 896567. [Google Scholar] [CrossRef] [PubMed]
  26. Bertacca, S.; Caruso, A.G.; Trippa, D.; Marchese, A.; Giovino, A.; Matic, S.; Noris, E.; Ambrosio, M.I.F.S.; Alfaro, A.; Panno, S.; et al. Development of a real-time loop-mediated isothermal amplification assay for the rapid detection of Olea Europaea geminivirus. Plants 2022, 11, 660. [Google Scholar] [CrossRef] [PubMed]
  27. He, Q.; Wang, D.; Tang, B.; Wang, J.; Zhang, D.; Liu, Y.; Cheng, F. Rapid and sensitive detection of Meloidogyne gram-inicola in soil using conventional PCR, Loop-Mediated Isothermal Amplification, and Real-Time PCR methods. Plant Dis. 2021, 105, 456–463. [Google Scholar] [CrossRef] [PubMed]
  28. Khan, M.; Li, B.; Jiang, Y.; Weng, Q.; Chen, Q. Evaluation of different PCR-based assays and LAMP method for rapid detection of Phytophthora infestans by targeting the Ypt1 gene. Front. Microbiol. 2017, 8, 1920. [Google Scholar] [CrossRef] [PubMed]
  29. Frisch, L.M.; Mann, M.A.; Marwk, D.N.; Niessen, L. Development and optimization of a loop-mediated isothermal amplifi- cation (LAMP) assay for the species-specific detection of Penicillium expansum. Food Microbiol. 2021, 95, 103681. [Google Scholar] [CrossRef] [PubMed]
  30. Verma, G.; Sharma, S.; Raigond, B.; Pathania, S.; Naga, K.; Chakrabarti, S.K. Development and application of fluorescent Loop mediated isothermal amplification technique to detect Phytophthora infestans from potato tubers targeting ITS-1 region. 3 Biotech 2019, 9, 345. [Google Scholar] [CrossRef] [PubMed]
  31. Chandra, A.; Keizerweerd, A.T.; Que, Y.X.; Grisham, M.P. Loop-mediated isothermal amplification (LAMP) based detection of Colletotrichum falcatum causing red rot in sugarcane. Mol. Biol. Rep. 2015, 42, 1309–1316. [Google Scholar] [CrossRef]
  32. Shen, W.; Xu, G.; Sun, L.; Zhang, L.; Jiang, Z. Development of a loop-mediated isothermal amplification assay for rapid and sensitive detection of Sporisorium scitamineum in sugarcane. Ann. Appl. Biol. 2016, 168, 321–327. [Google Scholar] [CrossRef]
  33. Choudhary, P.; Goswami, S.K.; Chakdar, H.; Verma, S.; Thapa, S.; Srivastava, A.K.; Saxena, A.K. Colorimetric loop-mediated isothermal amplification assay for detection and ecological monitoring of Sarocladium oryzae, an important seed-borne pathogen of rice. Front. Plant Sci. 2022, 13, 936766. [Google Scholar] [CrossRef] [PubMed]
  34. Zatti, M.D.S.; Arantes, T.D.; Fernandes, J.A.L.; Bay, M.B.; Milan, E.P.; Naliato, G.F.S.; Theodoro, R.C. Loop-mediated isother- mal amplification and nested PCR of the internal transcribed spacer (ITS) for Histoplasma capsulatum detection. PLoS Negl. Trop. Dis. 2019, 13, e0007692. [Google Scholar] [CrossRef]
  35. Zhang, X.; Harrington, T.C.; Batzer, J.C.; Kubota, R.; Peres, N.A.; Gleason, M.L. Detection of Colletotrichum acutatum Sensu Lato on strawberry by loop-mediated isothermal amplification. Plant Dis. 2016, 100, 1804–1812. [Google Scholar] [CrossRef]
  36. Yang, X.; Qi, Y.J.; Al-Attala, M.N.; Gao, Z.H.; Yi, X.K.; Zhang, A.F.; Zang, H.Y.; Gu, C.Y.; Gao, T.C.; Chen, Y. Rapid detection of alternaria species involved in pear black spot using Loop-mediated isothermal amplification. Plant Dis. 2019, 103, 3002–3008. [Google Scholar] [CrossRef]
  37. Kong, X.J.; Qin, W.T.; Huang, X.Q.; Kong, F.F.; Schoen, C.D.; Feng, J.; Wang, Z.Y.; Zhang, H. Development and application of loop-mediated isothermal amplification (LAMP) for detection of Plasmopara viticola. Sci. Rep. 2016, 6, 28935. [Google Scholar] [CrossRef]
  38. Xiong, Q.; Zhang, L.L.; Zheng, X.Y.; Qian, Y.L.; Zhang, Y.X.; Zhao, L.J.; Cheng, Q. Rapid and specific detection of the poplar black spot disease caused by Marssonina brunnea using loop-mediated isothermal amplification assay. Plants 2021, 10, 253. [Google Scholar] [CrossRef] [PubMed]
  39. Lan, C.; Gan, L.; Dai, Y.; Liu, X.; Yang, X. Development of loop-mediated isothermal amplification (LAMP) assay for specific and sensitive detection of Mycocentrospora acerina (Hart.) causing round leaf spot disease in sanqi (Panax notoginseng). Horticulturae 2022, 8, 1060. [Google Scholar] [CrossRef]
  40. Gupta, S.; Aggarwal, R.; Sharma, S.; Gurjar, M.S.; Bashyal, B.M.; Saharan, M.S.; Agarwal, S. Multiple sequence alignment and phylogenetic analysis of wheat pathogens using conserved genes for identification and development of diagnostic markers. Cereal Res. Commun. 2021, 50, 63–472. [Google Scholar] [CrossRef]
  41. Aglietti, C.; Meinecke, C.D.; Ghelardini, L.; Barnes, I.; van der Nest, A.; Villari, C. Rapid detection of pine pathogens Lecanosticta acicola, Dothistroma pini and D. septosporum on needles by probe-based LAMP assays. Forests 2021, 12, 479. [Google Scholar] [CrossRef]
  42. Su, Y.; Yang, Y.; Peng, Q.; Zhou, D.; Chen, Y.; Wang, Z.; Xu, L.P.; Que, Y.X. Development and application of a rapid and visual loop-mediated isothermal amplification for the detection of Sporisorium scitamineum in sugarcane. Sci. Rep. 2016, 6, 23994. [Google Scholar] [CrossRef]
  43. Guo, P.P.; Huang, S.L.; Zhang, Y.W.; Fu, P.; Li, X.N.; Li, J.H.; Wu, W.X. Loop mediated isothermal amplification for sensitive and rapid detection of Mycoplasma hyopneumoniae. J. Agric. Biotechnol. 2013, 29, 607–616. [Google Scholar]
  44. Fukuta, S.; Takahashi, R.; Kuroyanagi, S.; Ishiguro, Y.; Miyake, N.; Nagai, H.; Suzuki, H.; Tsuji, T.; Hashizume, F.; Watanabe, H.; et al. Development of loop-mediated isothermal amplification assay for the detection of Pythium myriotylum. Lett. Appl. Microbiol. 2014, 59, 49–57. [Google Scholar] [CrossRef] [PubMed]
  45. Feng, W.; Ishiguro, Y.; Hotta, K.; Watanabe, H.; Suga, H.; Kageyama, K. Simple detection of Pythium irregulare using loop-mediated isothermal amplification assay. Fems Microbiol. Lett. 2015, 362, 174. [Google Scholar] [CrossRef] [PubMed]
  46. Rizzo, D.; Moricca, S.; Bracalini, M.; Benigno, A.; Bernardo, U.; Luchi, N.; Da Lio, D.; Nugnes, F.; Cappellini, G.; Salemi, C.; et al. Rapid detection of Pityophthorus juglandis (Blackman) (Coleoptera, Curculionidae) with the loop-mediated isothermal amplification (LAMP) method. Plants 2021, 10, 1048. [Google Scholar] [CrossRef] [PubMed]
  47. Katoh, H.; Yamazaki, S.; Fukuda, T.; Sonoda, S.; Nishigawa, H.; Natsuaki, T. Detection of Fusarium oxysporum f. sp. fragariae by using loop-mediated isothermal amplificaton. Plant Dis. 2021, 105, 1072–1079. [Google Scholar]
  48. Robinson-McCarthy, L.R.; Mijalis, A.J.; Filsinger, G.T.; De Puig, H.; Donghia, N.M.; Schaus, T.E.; Rasmussen, R.A.; Ferreira, R.; Lunshof, J.E.; Chao, G.; et al. Laboratory-generated DNA can cause anomalous pathogen diagnostic test results. Microbiol. Spectr. 2021, 9, e00313-21. [Google Scholar] [CrossRef]
Figure 1. Sampling locations of sugarcane brown rust (SCBR) and some other fungal diseases in south China. Other fungal diseases, including sugarcane orange rust (caused by P. kuehnii), coffee leaf rust (caused by Hemileia vastatrix), grapevine leaf rust (caused by Phakopsora ampelopsidis), and Plumeria spp. rust (caused by Coleosporium plumierae), were obtained from typical diseased leaves.
Figure 1. Sampling locations of sugarcane brown rust (SCBR) and some other fungal diseases in south China. Other fungal diseases, including sugarcane orange rust (caused by P. kuehnii), coffee leaf rust (caused by Hemileia vastatrix), grapevine leaf rust (caused by Phakopsora ampelopsidis), and Plumeria spp. rust (caused by Coleosporium plumierae), were obtained from typical diseased leaves.
Agronomy 14 01096 g001
Figure 2. Typical foliar symptoms of sugarcane brown rust (SCBR) caused by Puccinia melanocephala. (A) Asymptomatic leaf. (B) Early symptoms of SCBR in adaxial leaves. (C) Early symptoms of SCBR in adaxial leaves. (D) Sugarcane plants infected with SCBR with masses of urediniospores in abaxial leaves.
Figure 2. Typical foliar symptoms of sugarcane brown rust (SCBR) caused by Puccinia melanocephala. (A) Asymptomatic leaf. (B) Early symptoms of SCBR in adaxial leaves. (C) Early symptoms of SCBR in adaxial leaves. (D) Sugarcane plants infected with SCBR with masses of urediniospores in abaxial leaves.
Agronomy 14 01096 g002
Figure 3. Design of five LAMP primer sets in a specific ITS region for the detection of Puccinia melanocephala. (A) Schematic illustration of the LAMP primers used in this study. It was constructed by the drawing module of the WPS office PPT (2021) (Beijing Jinshan Office Software Co., Ltd., Beijing, China). (B) The target ITS DNA fragment (299 bp–557 bp) of P. melanocephala for LAMP primer design. Two outer primers (F3, B3), two inner primers FIP (consisting of F1c and F2), and BIP (Consisting of B1c and B2) for LAMP. The sequences in gray are the LAMP primers. The orientation of the primers is shown using the arrows. The primers with reverse arrows represent the reverse complementary sequence of the corresponding regions.
Figure 3. Design of five LAMP primer sets in a specific ITS region for the detection of Puccinia melanocephala. (A) Schematic illustration of the LAMP primers used in this study. It was constructed by the drawing module of the WPS office PPT (2021) (Beijing Jinshan Office Software Co., Ltd., Beijing, China). (B) The target ITS DNA fragment (299 bp–557 bp) of P. melanocephala for LAMP primer design. Two outer primers (F3, B3), two inner primers FIP (consisting of F1c and F2), and BIP (Consisting of B1c and B2) for LAMP. The sequences in gray are the LAMP primers. The orientation of the primers is shown using the arrows. The primers with reverse arrows represent the reverse complementary sequence of the corresponding regions.
Agronomy 14 01096 g003
Figure 4. Screening of five LAMP primer sets (1–6) of P. melanocephala DNA. Lane M denotes 2000 bp DNA ladder; lane 1 denotes negative control (nuclease-free water); and lanes 2–6 denote five different LAMP primer sets. (I) LAMP reaction inducing color change. (II) Electrophoresis results of LAMP products on 2% agarose gel.
Figure 4. Screening of five LAMP primer sets (1–6) of P. melanocephala DNA. Lane M denotes 2000 bp DNA ladder; lane 1 denotes negative control (nuclease-free water); and lanes 2–6 denote five different LAMP primer sets. (I) LAMP reaction inducing color change. (II) Electrophoresis results of LAMP products on 2% agarose gel.
Agronomy 14 01096 g004
Figure 5. LAMP with different (A) ratios of inner and outer primers, (B) Mg2+ concentrations, (C) dNTPs concentrations, (D) annealing temperatures, (E) reaction times, and (F) betaine concentrations. Lane M denotes DL2000 DNA ladder. Lane1 denotes negative control. (A) Lanes 2–5 denote the ratios of inner and outer primers (2:1, 4:1, 6:1, and 8:1); (B) lanes 2–8 denote Mg2+ concentrations (0 mM, 2 mM, 3 mM, 4 mM, 8 mM, 10 mM, and 12 mM); (C) lanes 2–8 denote dNTP concentrations (0 mM, 0.4 mM, 0.8 mM, 1.0 mM, 1.2 mM, 1.4 mM, and 1.8 mM); (D) lanes 2–5 denote reaction temperatures (57 °C, 60 °C, 63 °C, and 65 °C); (E) lanes 2–7 denote reaction times (15 min, 30 min, 45 min, 60 min, 75 min, and 90 min); (F) lanes 2–10 denote betaine concentrations (0 mM, 0.2 mM, 0.4 mM, 0.6 mM, 0.8 mM, 1.0 mM, 1.2 mM, 1.4 mM, and 1.6 mM). (I) LAMP reaction causing changes in color. (II) Electrophoresis results of LAMP products on 2% agarose gel.
Figure 5. LAMP with different (A) ratios of inner and outer primers, (B) Mg2+ concentrations, (C) dNTPs concentrations, (D) annealing temperatures, (E) reaction times, and (F) betaine concentrations. Lane M denotes DL2000 DNA ladder. Lane1 denotes negative control. (A) Lanes 2–5 denote the ratios of inner and outer primers (2:1, 4:1, 6:1, and 8:1); (B) lanes 2–8 denote Mg2+ concentrations (0 mM, 2 mM, 3 mM, 4 mM, 8 mM, 10 mM, and 12 mM); (C) lanes 2–8 denote dNTP concentrations (0 mM, 0.4 mM, 0.8 mM, 1.0 mM, 1.2 mM, 1.4 mM, and 1.8 mM); (D) lanes 2–5 denote reaction temperatures (57 °C, 60 °C, 63 °C, and 65 °C); (E) lanes 2–7 denote reaction times (15 min, 30 min, 45 min, 60 min, 75 min, and 90 min); (F) lanes 2–10 denote betaine concentrations (0 mM, 0.2 mM, 0.4 mM, 0.6 mM, 0.8 mM, 1.0 mM, 1.2 mM, 1.4 mM, and 1.6 mM). (I) LAMP reaction causing changes in color. (II) Electrophoresis results of LAMP products on 2% agarose gel.
Agronomy 14 01096 g005
Figure 6. LAMP of DNA extracted from four Puccinia melanocephala isolates and twelve other fungal isolates. Lane M denotes DNA ladder; lane 1 denotes negative control (nuclease-free water); lanes 2–5 denote DNA of Puccinia melanocephala; lane 6 denotes DNA of Puccinia kuehnii; lanes 7–8 denote DNA of Hemileia vastatrix; lane 9 denotes DNA of Phakopsora ampelopsidis; lane 10 denotes DNA of Coleosporium plumierae; lanes 11–12 denote DNA of Ustilago scitaminea; lanes 13–14 denote DNA of Colletotichum falcatum; lane 15 denotes DNA of Leptosphaeria sacchari; lane 16 denotes DNA of Phytophthora nicotianae; and lane 17 denotes DNA of Aspergillus niger. (I) LAMP reaction causing a change in color. (II) Electrophoresis results of LAMP products on 2% agarose gel.
Figure 6. LAMP of DNA extracted from four Puccinia melanocephala isolates and twelve other fungal isolates. Lane M denotes DNA ladder; lane 1 denotes negative control (nuclease-free water); lanes 2–5 denote DNA of Puccinia melanocephala; lane 6 denotes DNA of Puccinia kuehnii; lanes 7–8 denote DNA of Hemileia vastatrix; lane 9 denotes DNA of Phakopsora ampelopsidis; lane 10 denotes DNA of Coleosporium plumierae; lanes 11–12 denote DNA of Ustilago scitaminea; lanes 13–14 denote DNA of Colletotichum falcatum; lane 15 denotes DNA of Leptosphaeria sacchari; lane 16 denotes DNA of Phytophthora nicotianae; and lane 17 denotes DNA of Aspergillus niger. (I) LAMP reaction causing a change in color. (II) Electrophoresis results of LAMP products on 2% agarose gel.
Agronomy 14 01096 g006
Figure 7. Sensitively of the LAMP assay, conventional PCR, and nested PCR for the detection of P. melanocephala using serial dilutions of the plasmid DNA template. Lane M denotes DNA ladder; lane 1 denotes negative control (nuclease-free water); lanes 2–3, 4–5, 6–7, 8–9, 10–11, 12–13, and 14–15 denote the DNA concentrations in the LAMP reaction starting from 100 ng/μL to subsequent 10-fold diluted DNA up to 10−4 ng/μL, respectively. (I) LAMP reaction causing a change in color. (II) Electrophoresis results of LAMP products on 2% agarose gel. (III) Results of conventional PCR using specific primer Pm1F/Pm1R. (IV) Results of nested PCR using specific primer PM2F/PM2R, followed by PM3F/PM3R.
Figure 7. Sensitively of the LAMP assay, conventional PCR, and nested PCR for the detection of P. melanocephala using serial dilutions of the plasmid DNA template. Lane M denotes DNA ladder; lane 1 denotes negative control (nuclease-free water); lanes 2–3, 4–5, 6–7, 8–9, 10–11, 12–13, and 14–15 denote the DNA concentrations in the LAMP reaction starting from 100 ng/μL to subsequent 10-fold diluted DNA up to 10−4 ng/μL, respectively. (I) LAMP reaction causing a change in color. (II) Electrophoresis results of LAMP products on 2% agarose gel. (III) Results of conventional PCR using specific primer Pm1F/Pm1R. (IV) Results of nested PCR using specific primer PM2F/PM2R, followed by PM3F/PM3R.
Agronomy 14 01096 g007
Table 1. Detection of P. melanocephala from sugarcane leaves exhibiting suspected symptoms of early SCBR using LAMP, nested PCR, and conventional PCR. Negative results obtained in asymptomatic leaves are not showed in Table 1.
Table 1. Detection of P. melanocephala from sugarcane leaves exhibiting suspected symptoms of early SCBR using LAMP, nested PCR, and conventional PCR. Negative results obtained in asymptomatic leaves are not showed in Table 1.
LocationNo.StrainsLAMPNested PCRConventional PCR
Guangxi Province
Longzhou1XLZ-PM1
2XLZ-PM2
3XLZ-PM3
4XLZ-PM4
5XLZ-PM5
Chongzuo1XLZ-PM1
2XLZ-PM2
3XLZ-PM3
4XLZ-PM4
Yunnan Province
Mangshi1NMS-PM1
2NMS-PM2
3NMS-PM3
4NMS-PM4
5NMS-PM5
6NMS-PM6
Guangdong Province
Leizhou1DLZ-PM1
2DLZ-PM2
3DLZ-PM3
4DLZ-PM4
5DLZ-PM6
6DLZ-PM7
7DLZ-PM8
8DLZ-PM9
9DLZ-PM10
10DLZ-PM11
11DLZ-PM12
12DLZ-PM14
13DLZ-PM15
Xuwen1DXW-PM17
2DXW-PM19
3DXW-PM20
4DXW-PM22
5DXW-PM23
6DXW-PM24
7DXW-PM26
Hainan Province
Danzhou1NDZ-PM1
2NDZ-PM2
3NDZ-PM3
4NDZ-PM4
5NDZ-PM5
Total (%) 85 a (34/40) b80 (32/40)55 (22/40)
a Number (N) outside parentheses denotes the positive rates (%) of P. melanocephala. b N/N in parentheses denote the number of P. melanocephala-positive and collected samples, respectively. The black circle (●) and hollow circle (○) in the Table 1 respectively denote P. melanocephala-positive and P. melanocephala-negative.
Table 2. LAMP reaction protocol.
Table 2. LAMP reaction protocol.
Reactive ComponentsVolumeFinal Concentration
10× Bst-DNA Polymerase Buffer2.5 μL-
Bst-DNA Polymerase
(New England Biolabs (Beijing), Ltd., Beijing, China)
1 μL8 U
F3 a (2.5 μM)2 μL0.2 μM
B3 b (2.5 μM)2 μL0.2 μM
FIP c (20 μM)2 μL1.6 μM
BIP d (20 μM)2 μL1.6 μM
dNTP (10 mM)3 μL1.2 mM
Mg2+ (25 mM)4 μL4 mM
Betaine (10 M)2 μL0.8 M
DNA template (about 50 ng)1 μL-
ddH2Oto 25 μL-
a,b F3 and B3 denote two outer primers for LAMP; c,d FIP (consisting of F1c and F2) and BIP (consisting of B1c and B2) denote two inner primers for LAMP.
Table 3. Optimal system of LAMP reaction.
Table 3. Optimal system of LAMP reaction.
Reactive ComponentsVolumeFinal Concentration
10× Bst-DNA Polymerase Buffer2.5 μL-
Bst-DNA Polymerase
(New England Biolabs (Beijing), Ltd.)
1 μL8 U
F3 a (2.5 μM)2 μL0.2 μM
B3 b (2.5 μM)2 μL0.2 μM
FIP c (20 μM)1.5 μL1.2 μM
BIP d (20 μM)1.5 μL1.2 μM
dNTP (10 mM)2.5 μL1.0 mM
Mg2+ (25 mM)6 μL6 mM
DNA template (about 50 ng)1 μL-
ddH2Oto 25 μL-
a,b F3 and B3 denote two outer primers for LAMP; c,d FIP (consisting of F1c and F2) and BIP (consisting of B1c and B2) denote two inner primers for LAMP.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Wu, W.; Wang, G.; Wang, H.; Zhu, L.; Liang, Y.; Gbokie, T., Jr.; Lu, Y.; Huang, X.; He, C.; Qin, J.; et al. Development and Evaluation of a Loop-Mediated Isothermal Amplifcation (LAMP) Assay for Specific and Sensitive Detection of Puccinia melanocephala Causing Brown Rust in Sugarcane. Agronomy 2024, 14, 1096. https://doi.org/10.3390/agronomy14061096

AMA Style

Wu W, Wang G, Wang H, Zhu L, Liang Y, Gbokie T Jr., Lu Y, Huang X, He C, Qin J, et al. Development and Evaluation of a Loop-Mediated Isothermal Amplifcation (LAMP) Assay for Specific and Sensitive Detection of Puccinia melanocephala Causing Brown Rust in Sugarcane. Agronomy. 2024; 14(6):1096. https://doi.org/10.3390/agronomy14061096

Chicago/Turabian Style

Wu, Weihuai, Guihua Wang, Han Wang, Liqian Zhu, Yanqiong Liang, Thomas Gbokie, Jr., Ying Lu, Xing Huang, Chunping He, Jianfeng Qin, and et al. 2024. "Development and Evaluation of a Loop-Mediated Isothermal Amplifcation (LAMP) Assay for Specific and Sensitive Detection of Puccinia melanocephala Causing Brown Rust in Sugarcane" Agronomy 14, no. 6: 1096. https://doi.org/10.3390/agronomy14061096

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop