Genotyping of commensal Neisseria spp strains by pulsed‐field gel electrophoresis and 16S rRNA gene sequencing

Abstract

Background

We investigated the diversity of the primary sequences of the 16S rRNA genes among 46 commensal Neisseria strains and evaluated the use of this approach as a molecular typing tool in comparison with PFGE analysis.

Methods

Identification to the genus was done using conventional methods and API NH (bio‐Mérieux^®). Identification to species level was based on 16S rRNA gene sequencing. PFGE analysis was done using SpeI.

Results

Fourteen, two, three and fourteen 16S rRNA sequence types were found among twenty Neisseria flavescens, two Neisseria sicca, five Neisseria macacae and nineteen Neisseria mucosa clinical isolates. Forty‐three different PFGE patterns were found among the tested strains.

Conclusion

We demonstrated a high diversity among 16S rRNA genes which was reflected by PFGE analysis.

1. Introduction

Phenotypic and genetic variation in bacteria can take bewilderingly complex forms even within a single genus. One of the most intriguing examples of this is the genus Neisseria which consists of Gram‐negative bacteria that colonize the mucous membranes of mammals.1 Neisseria spp colonization of the respiratory tract, a phenomenon commonly referred to as carriage, represents a successful commensal relationship between the host and the bacterium, with the host experiencing no detectable pathology. Commensal bacteria comprise a large part of the microbial world, playing important roles in human development, health and disease.2 However, little is known about the genomic content of commensals or how related they are to their pathogenic counterparts. Complex relatedness among Neisseria species makes it challenging to study their genotypic characterization. Especially their rRNA genes which are often organized as part of a multigene family. Members of the genus Neisseria contain four rRNA operons.3

Genotyping methods may be compared on the basis of a range of criteria, including sensitivity, availability, reproducibility, rapidity, ease of use, and cost. One of the most important characteristics is discriminatory power.4

One aim of our study was to establish if sequence differences exist in 16S rRNA gene sequences of commensal Neisseria clinical isolates, because if intraspecific variation exists in these genes it may be possible to use the method for subtyping. Also, during the course of this study, we compared the abilities of 16S rRNA sequencing‐based typing and pulsed‐field gel electrophoresis (PFGE) typing to differentiate clinical isolates of commensal Neisseria.

2. Material and Methods

We analyzed 55 Neisseria spp clinical isolates collected between 2003 and 2008, from various sources, from patients monitored in the Bone Marrow Transplant Center of Tunisia.

Neisseria perflava 8022, N. mucosa 8023, N. sicca 8024, Neisseria cinerea 8025, and Neisseria lactamica 9366 were used as quality‐control reference strains (R. Leclercq, CHU Caen).5

2.1. Bacterial DNA preparation

A bacterial pellet, obtained from centrifuging 2 mL of an overnight‐grown culture from a single colony, was washed twice in TE buffer (10 mmol/L Tris–Cl pH8, 1 mmol/L EDTA). Pelleted cells were suspended in 500 μL TEG (50 mmol/L Tris Hcl, 10 mmol/L EDTA, 100 mmol/L glucose) supplemented with 3 mg/mL lysozyme and 25 mg/L RNase. After an incubation period of 30 minutes at 37°C, the cells were lysed by the addition of 20 mg/mL proteinase K and 10% sodium dodecyl sulphate solution, and incubation for 30 minutes at 55°C. The solution was extracted twice with chloroform/isoamyl alcohol (24:1 v/v) and with phenol/chloroforme/isoamyl alcohol (25:24:1) by volume. Chromosomal DNA in the aqueous solution was pelleted with two volumes of ethanol and incubated for one night at −20°C. After brief centrifugation, the bacterial pellet was resuspended in 100 μL of sterile distilled water and stored at −20°C until use.

2.2. Bacterial identification

The identification of genus was based on conventional methods: Gram strain, oxidase test and API NH (bio‐Mérieux^®) characterization. The identification of species was based on 16S rRNA gene sequencing. For all strains, the 16S rRNA gene was amplified by PCR and sequenced using the primers up1‐F: AGAGTTTGATCCTGGCTCAG and up1‐R: GTTACCTTGTTACGACTT.6 The PCR thermal program consisted of initial denaturation at 95°C for 5 minutes, 30 cycles of amplification (denaturation at 95°C for 60 seconds, annealing at 54°C for 60 seconds and elongation at 72°C for 90 seconds) and final elongation at 72°C for 10 minutes.7 The products (1406 bp) were separated with an Applied Biosystems 3730xl DNA analyzer (96 capillary type). The resultant DNA sequences were assembled using the CLC WORKBENCH of computer programs. The nucleotide sequence of the 16S rRNA gene fragments were aligned and compared using the GenBank and EzGenome (http://ezgenome.ezbiocloud.net) databases. In our study, the criteria established for identification of the bacterial isolates were: ≥95% to ≥99% sequence similarity prototype strain sequence in the database defined a bacterial genus; ≥99% sequence similarity to the prototype strain sequence defined a bacterial species. Only strains showing concordant results with the two databases were included in this study.

2.3. 16S rRNA type determination

The nucleotide sequence of the 16S rRNA gene fragments were aligned and compared using the ClustalW program. A number was assigned to each different 16S rRNA gene sequence; a single base change was considered a new 16S rRNA type. When discrepancies in the alignment were obtained, the 16S rRNA gene amplification and sequencing of the entire gene were repeated.

2.4. PFGE

PFGE was done as described previously by Mechergui et al.8 Our 46 isolates were digested with SpeI, and the resulting fragments were separated by electrophoresis in CHEFF DR II (Biorad) in 1% MP agarose gel (Boehringer Mannheim) made with 0.5× TBE (Tris Borate 45 mmol/L/EDTA 1 mmol/L pH 8). The pulse was ramped from 0.5 to 30 seconds over 20 hours.

Lambda ladder DNA (New England BioLabs, Beverly, USA) was used as molecular weight PFGE marker. Banding patterns were inspected manually, and the criteria of Tenover et al.9 were used to determine strain relatedness.

3. Results

The nucleotide sequence of 16S rRNA gene fragment (1406 bp) from all our strains were compared to the previously identified sequences hosted on Genbank and EzGenome databases. We obtained the same identification result for 46 strains. These strains, based on the BLAST results, showed 99%‐100% sequence similarity to their nearest database entries.

They were assigned to four diverse species represented by N. flavescens (44%), N. mucosa (41%), N. macacae (11%) and N. sicca (4%).

Three (16S rrn type I‐1 to 16S rrn type I‐3), two (16S rrn type II‐1 and 16S rrn type II‐2), fourteen (16S rrn type III‐1 to 16S rrn type III‐14), and fourteen (16S rrn type IV‐1 to 16S rrn type IV‐14) 16S rRNA sequence types were, respectively, found among 5 N. macacae, 2 N. sicca, 19 N. mucosa and 20 N. flavescens isolates.

PFGE analysis detected 46 unique genome patterns among the tested strains (Figure S1) (Table 1).

Table 1.

PFGE and 16S rRNA gene types of the commensal Neisseria clinical isolates

4. Discussion

Since no reference “gold standard” is commonly used for speciation of Neisseria, we used 16S rRNA gene as an identification tool because the use of another identification method could lead us into error. Indeed, we could study the presumptive intraspecific diversity of 16S rRNA gene among strains belonging actually to different species when using 16S rRNA sequence–based identification.

It is established that heterogeneity exists even within the well‐conserved 16S rRNA gene. This is due to the frequently recombinant genotype of members of Neisseria genus.10 In fact, 16S rRNA gene of commensal Neisseria is affected by recombination events leading to genetic diversity.11 Also, when segments of the 16S rRNA gene are transferred from one species to another, this is likely to happen in just one of the copies of the ribosomal operons first.12 This would lead to strains with two different types of 16S rRNA genes.

Previous reports of transformation in Neisseriae have suggested that different regions of the genome may have different recombination rates. In N.  meningitidis, analysis of the 16S sequence data show that the 16S rRNA gene may recombine as frequently as the housekeeping genes.13 Lateral transfer and recombination do not lead to rapid changes in rRNA genes. One of the main reasons would be that the tertiary structure of the ribosomal RNAs is essential for the association with components of the translation apparatus, such as the ribosomal proteins. During evolution, gradual changes may have been introduced in the rRNA genes and ribosomal protein genes, leading to the slow emergence of new ribosomal complexes. This hypothesis is supported by the fact that mutations in stems of the stem‐loop structures in the 16S rRNA gene are often associated with mutations in opposing parts of the rRNA strand, leading to restoration of the stem structure.12

In the present paper, we found a large degree of diversity among 16S rRNA genes of commensal Neisseria strains, suggesting that 16S rRNA gene sequencing might be a useful molecular typing tool. In previous studies, interstrain variation in the 16S rRNA gene of N. meningitidis was used as a molecular typing tool.13, 14 In these studies, 16S typing was the most sensitive and specific typing tool to discriminate outbreak‐related isolates from sporadic isolates. The performance was even better than that of multilocus sequence typing. Also, some authors conclude that molecular typing by 16S rRNA sequence determination is not only more rapid but also more accurate than traditional typing methods.15 In fact, because of the strong conservation of regions in the rRNA genes and the presence of highly variable (noncoding) flanking regions, these genes are suitable targets for subtyping purposes.3 Also, the rRNA genes are universally present in all organisms, can be easily obtained using PCR with universal primers, and are easy to sequence. However, other authors show some shortcomings associated with 16S rRNA use as a typing tool due to the fact that it is, relatively, a so well conserved gene that it results in a limited resolving power.16 Indeed, the use of the 16S rRNA gene sequences for phylogeny studies has become extremely popular and has led to the reconstruction of the tree of life. In addition, the rRNA based analysis, is now a standard approach for studying microbial community dynamics at high resolution17 and to explore microbial diversity.18

As revealed by 16S rRNA sequences, there was a wide genetic diversity among PFGE patterns of commensal Neisseria spp. However, commensal Neisseria isolates with the same 16S rRNA type seemed to be genomically different since they belong to different clones. These data demonstrate that PFGE is more discriminating than is 16S rRNA sequence analysis for differentiating commensal Neisseria isolates. Indeed, the high discriminatory power of PFGE makes it the “gold standard” for DNA fingerprinting techniques. Compared with other methods, it often has superior discriminatory power because of two reasons. First, PFGE typing involves the whole genome rather than a short target sequence, thus, strains are effectively compared on a broad basis. Second, there is no requirement for prior knowledge of sequence data; all strains can be typed. However, there are also many disadvantages in using PFGE as a genotyping tool. Intra‐ and inter‐laboratory variability is a major problem, while bands on a gel can be difficult to interpret and data are not easily portable. In addition, the nature of the genetic variation being indexed is poorly understood; there is the question of whether bands of the same size in two isolates really represent the same pieces of DNA.

In the current study, no epidemiologic connection exists between our strains since they belong to the commensal endogenous flora of different patients. Indeed, it is established that the Neisseria species are believed to be non‐clonal bacteria with a high degree of genetic transfer within and between different species. 19

In conclusion, high genetic diversity was identified among non‐clonal clinical isolates of commensal Neisseria, either by 16S rRNA gene sequencing or by PFGE, with better discriminatory power for the latter technique.

Supporting information

 

Mechergui A, Achour W, Ben Hassen A. Genotyping of commensal Neisseria spp strains by pulsed‐field gel electrophoresis and 16S rRNA gene sequencing. J Clin Lab Anal. 2018;32:e22208 10.1002/jcla.22208