Genotyping of Listeria monocytogenes isolates by high-resolution melting curve (HRM) analysis of tandem repeat locus

doi:10.21203/rs.3.rs-183849/v1

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Genotyping of Listeria monocytogenes isolates by high-resolution melting curve (HRM) analysis of tandem repeat locus

https://doi.org/10.21203/rs.3.rs-183849/v1

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published 28 Feb, 2022

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Listeria monocytogenes is responsible for causing listeriosis, a type of food poisoning with high mortality. This bacterium is mainly transmitted to humans through the consumption of contaminated foods. Detection of L. monocytogenes through molecular methods is crucial for food safety and clinical diagnosis. Present techniques are characterized by low discrimination power and high cost, as well as being time-consuming and taking several days to give the final result. In our study, MLVA-HRM was investigated as an alternative method for a fast and precise method for the genotyping of L. monocytogenes isolates. Forty-eight isolates of L. monocytogenes obtained from the microbial bank of Department of Microbiology, Iran University of Medical Sciences, were typed by MLVA-HRM analysis using five VNTR loci. A total of 43 diﬀerent types were obtained. This research demonstrated the usefulness of the MLVA-HRMA method and its ability to discriminate L. monocytogenes isolates. Since this method is easier and more efficient than existing methods, it can be widely used in food processing plants and diagnostic laboratories as a fast and accurate method.

Molecular Biology

Listeria monocytogenes

MLVA-HRMA

VNTR locus

Molecular typing

Listeria monocytogenes is responsible for causing listeriosis, a type of food poisoning.
Present techniques are characterized by low discrimination power and high cost, as well as being time-consuming.
MLVA-HRM was investigated as an alternative method for a fast and precise method for the genotyping of monocytogenes isolates.

Listeria monocytogenes is a Gram-positive, motile, non-spore forming, and food-borne pathogen that can cause listeriosis in high-risk individuals, including infants, the elderly, and immunocompromised patients [1, 2]. L. monocytogenes is widely distributed in the environment and has the ability to survive and grow in harsh conditions, such as low temperatures and high saline levels [3]. L. monocytogenes is an environmental organism that typically infects the food processing industry and it is estimated that 99% of human listeriosis infections are caused by the consumption of contaminated foods [4]. Listeriosis is linked with a high rate of hospitalization (85–90%) and the mortality rate for this disorder is 20-30%, which is higher than infections caused by other food poisoning pathogens [5, 6].

Thus, in recent decades, L. monocytogenes has become a major concern in the food industry and public health, and the identification of L. monocytogenes species for food safety, epidemiological studies, and clinical diagnosis is very critical [7].

There are several methods for the classification of bacterial isolates, such as multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), and restriction enzyme analysis [8, 9].

Although each of these methods has its advantage in isolating different bacterial species, the typing technique should be simple and easy. PFGE is the current gold standard for typing of L. monocytogenes isolates, however, it is time-consuming and hard to standardize, which prevents the exchange of typing results between laboratories [10]. The MLVA method requires capillary electrophoresis and the MLST method requires a large sequence analysis [11, 12]. Therefore, considering the importance of typing food-related bacteria, it is very crucial to use a fast, cheap, and easy method to differentiate the strains [13].

High-resolution melting (HRM) is a quantitative PCR (QPCR)-based method developed to detect changes in nucleic acid sequences. This method monitors changes in DNA sequences according to the changes of melting temperatures of real-time PCR products [14]. Through our research, five variable numbers of tandem repeat (VNTR) loci were selected for the genotyping of L. monocytogenes isolates. VNTR is a region in DNA where a short nucleotide sequence called tandem repeats (TRs) with various numbers are located in different strains of bacteria [15, 16]. Today, this difference in the number of VNTR is used as a suitable target for assessing bacterial genotyping [17]. In this study, we used the HRM method, which is a simple and fast method for the analysis of VNTR and genotyping of L. monocytogenes strains.

Bacterial Strains and Growth Conditions

In this study, L. monocytogenes ATCC 19115 and 47 clinical L. monocytogenes strains from the Microbial bank of Department of Microbiology affiliated to Iran University of Medical Sciences, Tehran, Iran, were used (Table 1) [18]. Isolates were cultured on Brain Heart Infusion (BHI) agar (Merck, Darmstadt, Germany) at 37°C for 48 h. DNA of the samples was extracted with a DNA Extraction kit (Roche, Germany) according to the manufacturer’s protocol. DNA purity and concentration were assessed using a NanoDrop Spectrophotometer (Thermo Scientific, USA).

MLVA-HRM

In this study, we used 5 VNTR loci for MLVA-HRMA based on the previously designed primers [19]. The PCR amplification and HRMA were performed using a Rotor-Gene thermal cycler (Corbett Life Sciences, Sydney, Australia). The PCR reaction solution was performed with a total of 20 µL, containing 1 µL of each forward and reverse primers, 1 μL of template DNA (0.5 μg), 4 μl of 5× Hot Firepol Eva Green HRM Mix (Solis BioDyne), and 13 μL of sterile distilled water.

The thermal program was performed by an initial denaturation at 95 °C for 5 min followed by 40 cycles of 95 °C for 30 s, 54 °C for 22 s, and 72 °C for 40 s for VNTR locus 1 (Lm_10), 95 °C for 30 s, 52 °C for 22 s, and 72 °C for 40 s for VNTR locus 2 (Lm_11), 95 °C for 30 s, 55.5 °C for 30 s, and 72 °C for 30 s for VNTR locus 3 (Lm_23), 95 °C for 30 s, 54 °C for 30 s, 72 °C for 45 s for VNTR locus 4 (Lm_32) and 95 °C for 30 s, 57 °C for 22 s, and 72 °C for 40 s for VNTR locus 5 (LM_TR6).

After PCR amplification, the HRM step was performed. For HRM step the fluorescence was measured by increasing the temperature from 75° to 95°C with a rate of 0.1 °C/s. In case of nucleotide changes in different strains, various curves are produced.

The melting curve and different plots of strain 6 were used as the baseline control. Each strain with equal waveform was grouped. Then, two strains were randomly selected from each group and the PCR reaction was performed for the studied genes using a DNA thermal cycler (PeqLab, Germany) with the following proﬁle: initial denaturation at 94°C for 5 min, 30 cycles of denaturation at 94°C for 30 s, annealing at 52°C for 22 s, and extension at 72°C for 40 s, with a final extension step at 72°C for 5 min. The PCR product was sent for sequencing to Takapozist Company, Iran (on behalf of Bioneer Company, Korea). The allele number was determined and imputed for each locus into BioNumerics (Applied Maths, Sint-Martens-Latem, Belgium) to draw the UPGMA dendrogram and the minimum spanning tree for all the studied L. monocytogenes.

MLVA-HRM

For the 48 L. monocytogenes strains, we performed HRM on 5 VNTR loci to determine the STs. The difference plot and melting curves of 48 L. monocytogenes strains for 5 VNTR regions were drawn (Figure 1, Figure 2). According to similar peak waveforms for 48 L. monocytogenes strains, the Lm_10, Lm_11, Lm_23, Lm_32, and LM_TR6 loci were divided into 6, 3, 5, 7, and 2 types, respectively. After sequencing and calculating the number of alleles and imputing each locus into BioNumerics and combining the allele numbers of the 5 loci, UPGMA dendrogram and the minimum spanning tree for 48 strains of L. monocytogenes were drawn and 48 strains of L. monocytogenes were finally divided into 43 HRM groups (Figure 3, Figure 4).

Molecular typing of L. monocytogenes isolates plays an important role in identifying the source of infection and preventing the spread of this pathogen [20]. Currently, various methods are used for molecular typing of L. monocytogenes from various sources, including PFGE, MLST, and more recently WGS, which requires a lot of work and cost [21, 22]. MLVA (multilocus variable-number tandem-repeat analysis) is another molecular typing method that comes with practical benefits such as speed and ease of use. This method uses capillary electrophoresis for diagnosis [23]. VNTR loci in the bacterial genome often mutate, leading to changes in the number of tandem repeats and successive changes in nucleic acid. Changes in the number of VNTR repeats are used by the MLVA method for the molecular typing of different isolates [13, 24]. To evaluate the appropriateness and the suitability of the MLVA method for routine monitoring and subtyping of L. monocytogenes isolates from meat products, Belén Martín and colleagues collected 113 isolates of L. monocytogenes from meat [25]. Their study showed that MLVA is a reliable method for L. monocytogenes typing with a higher discriminating power than MLST, especially for serotype 1/2c isolates [25]. Lindstad et al. compared MLVA with the PFGE method to evaluate the resolution power of the MLVA method for molecular typing of L. monocytogenes isolates and their results showed that the MLVA method was slightly more discriminatory for Norwegian isolates (28 MLVA profiles and 24 PFGE profiles) [26].

In HRM, changes in nucleotide sequences and diversity in the chain length of PCR products are indicated by changes in the melting curve [27]. In a study by Ohshima et al., analysis of MLVA was performed using the HRM method as a simple and rapid method for differentiating L. monocytogenes isolates. The study also compared the ability of MLVA-HRMA, MLVA using capillary electrophoresis, and multilocus sequence typing (MLST) to differentiate between strains. This study demonstrated that the MLVA-HRM method was more discriminant than MLST and MLVA using capillary electrophoresis [28]. In a study by Catharina H. et al., for phylogenetic analysis, MLST and MLVA were performed on 58 Vibrio parahaemolyticus isolates, and the results gained by both methods were compared with the PFGE patterns obtained in their previous study. Their results showed that HRM-MLVA was able to separate isolates in the same PFGE cluster with the same ST [29].

In this research, we used the MLVA-HRM method with 5 VNTR loci as a simple and fast typing method that was able to differentiate L. monocytogenes strains. The MLVA-HRM method was able to discriminate L. monocytogenes strains, which we believe could be a valuable alternative to costly and time-consuming techniques.

Acknowledgments:

This study was financially supported by Iran University of Medical Sciences (Tehran, Iran), for which we are very grateful.

Conflict of Interests

The authors declare that they have no competing interests.

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Table 1. Serotypes and sources of Listeria monocytogenes strains.

source	serotype	strain
Goat	1/2c	1
Placental bit	1/2c	2
Cheese	1/2c	3
Cheese	1/2c	4
Placental bit	1/2c	5
ATCC 19115	4b	6
Neonatal blood	1/2c,3c	7
Rectal swab	1/2c	8
Ice cream	1/2c	9
Cheese	1/2c	10
Vaginal swab	4b	11
Sheep	1/2a	12
Vaginal swab	1/2c	13
Sheep	1/2c	14
Cattle	1/2c	15
Sheep	1/2c	16
Rectal swab	1/2c	17
Goat	1/2c	18
Placental bit	1/2c	19
Cattle	4b	20
Neonatal blood	1/2c,3c	21
Sheep	1/2c	22
Milk	1/2c,3c	23
Tilapia fillet	1/2b,3b	24
Neonatal blood	1/2c,3c	25
Placental bit	1/2c	26
Cattle	1/2c	27
Vaginal swab	1/2a	28
Stool	1/2c	29
Stool	1/2c	30
Stool	1/2c	31
Stool	1/2c	32
Stool	1/2c	33
Stool	4e	34
Stool	1/2c	35
Placental bit	4b,4d	36
Vaginal swab	1/2a, 3a	37
Vaginal swab	1/2b,3b	38
Vaginal swab	1/2a, 3a	39
Vaginal swab	1/2a,3a	40
Placental bit	1/2c,3c	41
Placental bit	1/2a, 3a	42
Caspian tyulka	1/2a, 3a	43
Vaginal swab	1/2c,3c	44
Caspian tyulka	1/2c,3c	45
Blood	1/2c,3c	46
Neonatal blood	1/2c,3c	47
Rainbow trout	1/2a, 3a	48

PDF

Journal Publication

published 28 Feb, 2022

Read the published version in The Brazilian Journal of Infectious Diseases →

Version 1

posted 18 Feb, 2021

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Genotyping of Listeria monocytogenes isolates by high-resolution melting curve (HRM) analysis of tandem repeat locus

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Abstract

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Highlights

Introduction

Materials And Methods

Results

Discussion

Declarations

References

Table 1

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