Abstract
In order to evaluate the suitability of 16S rRNA nucleotide sequence similarity for the classification of new Mycobacterium isolates at the species level, we systematically studied the pairwise identity values of this gene for 131 Mycobacterium species with standing in nomenclature. Only one of the studied species, M. poriferae (0.76%), strictly respected the 95% and 98.65% threshold values currently recommended to determine the affiliation of bacterial isolates to an existing or new genus or species, respectively. All other species exhibited at least an identity value >98.65% and/or <95% with another Mycobacterium species. Therefore, we suggest that interpretation of interspecies 16S rRNA identity values should be made cautiously when classifying a new mycobacterial isolate at the species level.
Keywords: 16S rRNA, Mycobacterium, sequence similarity, taxonomy, threshold value
Introduction
Taxonomy provides scientists with essential information, enabling them to understand the relationships between living organisms and their different ecosystems [1]. For prokaryotes, taxonomy allows the reliable identification of microbial strains from clinical or environmental samples [2]. Bacterial taxonomy was initiated in the late 19th century, when phenotypic characteristics were incorporated into bacterial description, including motility, growth requirements, morphology, staining properties, colony size and colour, and chemical reactions [3]. Between the mid-1950s and the 1980s, new parameters were progressively added, notably chemotaxonomy [4], numerical taxonomy, genomic DNA-DNA hybridization and G+C content [5]. In the 1980s, the advent of DNA amplification and sequencing techniques, in particular of the 16S rRNA gene, constituted a major step forwards by facilitating bacterial classification [6], [7]. The 16S rRNA gene is a highly conserved gene that is made of nine hypervariable domains separated by more preserved fragments in which universal primers can be designed. More than three million 16S rRNA gene sequences are currently available in public databases [8]. In 1996, Vandamme et al. [9] suggested that polyphasic taxonomy, which takes into account all available phenotypic and genotypic data and integrates them into a consensus classification, should include 16S rRNA gene sequence identity. In 2010, Tindall et al. [10], in a reevaluation of the various available methods, proposed a combination of phenotypic and genotypic criteria within which 16S rRNA gene sequence similarity, and phylogeny was included as a first-line tool.
In 1994, scientists considered two strains as belonging to different species if they shared 16S rRNA gene sequence similarity values <97% and to a distinct genus if this value was <95% [11]. The cutoff value at the species level was later reevaluated at 98.7% [12] and then 98.65% [13]. However, several authors have shown that these thresholds, originally designed to standardize the use of sequences of 16S rRNA genes in taxonomy, are not applicable to multiple genera. In 2015, we demonstrated that many of the current bacterial species with validly published names do not respect the 95% and 98.7% thresholds [14].
In 2000, Woo et al. [15] proposed that 16S rRNA gene sequencing was the reference standard for the identification of Mycobacterium species. Genotypic investigations based on the sequencing of the 16S rRNA gene have played a significant role in the taxonomic classification of members of the genus Mycobacterium [16]. However, to date, no systematic study of the degree of 16S rRNA divergence among Mycobacterium species has been conducted.
Here we evaluate the value of current 16S rRNA cutoff values at the species and genus levels by systematically calculating the pairwise degree of 16S rRNA similarity between all Mycobacterium species with standing in nomenclature.
Methods
Collection of 16S rRNA gene sequences from members of the genus Mycobacterium
Within the List of Prokaryotic Names with Standing in Nomenclature website (http://www.bacterio.net/mycobacterium.html), we selected all Mycobacterium species with a validly published name as of 25 March 2016, and we collected the 16S rRNA gene accession numbers from type strains.
As a result of the wide heterogeneity in length and quality of the 16S rRNA gene sequences of type strains, we did not use sequences shorter than 1320 nt. We created a FASTA format file containing all selected sequences.
16S rRNA gene sequence analysis: calculation of pairwise 16S rRNA gene sequence similarities
Sequences were aligned using Muscle software with default settings [17]. In this study, pairwise 16S rRNA gene sequence similarities between all species of the genus Mycobacterium were first estimated by MEGA 5 phylogeny software [18]. Then the highest and lowest values computed by this software were more accurately determined by pairwise BLASTN. We defined as expected values of interspecies 16S rRNA gene sequence similarity percentages that were between 95% and 98.65% or intraspecies percentages that were greater than 98.65% [13], and as abnormal values interspecies percentages that were >98.65% or <95% [14] or intraspecies percentages of <98.65%.
Results
Of the 182 Mycobacterium species and subspecies with a validly published name at the time of our study and for which a 16S rRNA sequence was available, we included 131 species with 16S rRNA sequences longer than 1320 nt (Table 1). For two of those species, M. avium and M. fortuitum, we included two subspecies (Table 1). The phylogenetic distribution of the studied Mycobacterium species is presented in Fig. 1. Among the 131 studied species, the pairwise 16S rRNA gene sequence similarity values ranged from 93.00% between M. chelonae and M. kyorinense to 100% between M. fortuitum subsp. acetamidolyticum and M. fortuitum subsp. fortuitum, M. africanum and M. caprae, M. farcinogenes, M. houstonense and M. senegalense, M. gastri and M. kansasii, M. mucogenicum and M. phocaicum, M. murale and M. tokaiense, and M. paraseoulense and M. seoulense, respectively (Supplementary Table S1).
Table 1.
List of species with standing in nomenclature used in our study
| Species | Accession no. | Size (bp) |
|---|---|---|
| Mycobacterium abscessus subsp. bolletii | AY859681 | 1481 |
| Mycobacterium africanum | AF480605 | 1433 |
| Mycobacterium agri | AJ429045 | 1456 |
| Mycobacterium aichiense | X55598 | 1456 |
| Mycobacterium alvei | AF023664 | 1465 |
| Mycobacterium anyangense | KJ855063 | 1420 |
| Mycobacterium arosiense | EF054881 | 1493 |
| Mycobacterium arupense | DQ157760 | 1487 |
| Mycobacterium asiaticum | AF480595 | 1466 |
| Mycobacterium aubagnense | AY859683 | 1482 |
| Mycobacterium aurum | X55595 | 1458 |
| Mycobacterium austroafricanum | X93182 | 1462 |
| Mycobacterium avium subsp. avium | AJ536037 | 1472 |
| Mycobacterium avium subsp. silvaticum | EF521891 | 1442 |
| Mycobacterium bouchedurhonense | EF591053 | 1498 |
| Mycobacterium branderi | AF480574 | 1469 |
| Mycobacterium brisbanense | AY012577 | 1499 |
| Mycobacterium brumae | AF480576 | 1449 |
| Mycobacterium canariasense | AY255478 | 1433 |
| Mycobacterium caprae | AJ131120 | 1524 |
| Mycobacterium celatum | L08169 | 1460 |
| Mycobacterium celeriflavum | KJ607136 | 1442 |
| Mycobacterium chelonae | AY457072 | 1481 |
| Mycobacterium chitae | X55603 | 1457 |
| Mycobacterium chlorophenolicum | X79292 | 1466 |
| Mycobacterium chubuense | AF480597 | 1472 |
| Mycobacterium conceptionense | AY859684 | 1483 |
| Mycobacterium confluentis | AJ634379 | 1504 |
| Mycobacterium conspicuum | X88922 | 1433 |
| Mycobacterium cosmeticum | AY449728 | 1507 |
| Mycobacterium crocinum | DQ534008 | 1398 |
| Mycobacterium diernhoferi | AF480599 | 1458 |
| Mycobacterium doricum | AF264700 | 1450 |
| Mycobacterium duvalii | U94745 | 1502 |
| Mycobacterium elephantis | AJ010747 | 1517 |
| Mycobacterium fallax | AF480600 | 1470 |
| Mycobacterium farcinogenes | AY457084 | 1483 |
| Mycobacterium flavescens | X52932 | 1454 |
| Mycobacterium fluoranthenivorans | AJ617741 | 1494 |
| Mycobacterium fortuitum subsp. acetamidolyticum | FR733720 | 1505 |
| Mycobacterium fortuitum subsp. fortuitum | AY457066 | 1483 |
| Mycobacterium fragae | JQ898451 | 1452 |
| Mycobacterium frederiksbergense | AJ276274 | 1474 |
| Mycobacterium gadium | X55594 | 1456 |
| Mycobacterium gastri | AF480602 | 1469 |
| Mycobacterium genavense | X60070 | 1449 |
| Mycobacterium goodii | Y12872 | 1417 |
| Mycobacterium gordonae | X52923 | 1461 |
| Mycobacterium hassiacum | U49401 | 1491 |
| Mycobacterium heidelbergense | AJ000684 | 1445 |
| Mycobacterium hodleri | X93184 | 1459 |
| Mycobacterium holsaticum | AJ310467 | 1526 |
| Mycobacterium houstonense | AY457067 | 1483 |
| Mycobacterium interjectum | HM037998 | 1431 |
| Mycobacterium intermedium | X67847 | 1441 |
| Mycobacterium intracellulare | AJ536036 | 1440 |
| Mycobacterium iranicum | HQ009482 | 1450 |
| Mycobacterium kansasii | AJ536035 | 1470 |
| Mycobacterium komossense | X55591 | 1462 |
| Mycobacterium koreense | JF271826 | 1474 |
| Mycobacterium kubicae | AF133902 | 1321 |
| Mycobacterium kyorinense | AB370111 | 1470 |
| Mycobacterium lacus | AF406783 | 1470 |
| Mycobacterium lentiflavum | AF480583 | 1452 |
| Mycobacterium litorale | GU997640 | 1380 |
| Mycobacterium llatzerense | AJ746070 | 1397 |
| Mycobacterium madagascariense | AB537170 | 1470 |
| Mycobacterium mageritense | AJ699399 | 1497 |
| Mycobacterium malmoense | X52930 | 1457 |
| Mycobacterium mantenii | FJ042897 | 1471 |
| Mycobacterium marinum | AF456240 | 1522 |
| Mycobacterium marseillense | EU266632 | 1440 |
| Mycobacterium microti | AF480584 | 1484 |
| Mycobacterium monacense | AF107039 | 1473 |
| Mycobacterium moriokaense | AJ429044 | 1493 |
| Mycobacterium mucogenicum | AY457074 | 1482 |
| Mycobacterium murale | AB537171 | 1459 |
| Mycobacterium nebraskense | AY368456 | 1506 |
| Mycobacterium neoaurum | AF480593 | 1470 |
| Mycobacterium neworleansense | AY457068 | 1483 |
| Mycobacterium noviomagense | EU239955 | 1478 |
| Mycobacterium novocastrense | U96747 | 1513 |
| Mycobacterium obuense | X55597 | 1458 |
| Mycobacterium pallens | DQ370008 | 1435 |
| Mycobacterium paraense | KJ948996 | 1480 |
| Mycobacterium paraffinicum | GQ153270 | 1492 |
| Mycobacterium parafortuitum | X93183 | 1460 |
| Mycobacterium paragordonae | KC525204 | 1393 |
| Mycobacterium parakoreense | JF271823 | 1465 |
| Mycobacterium parascrofulaceum | AY337273 | 1468 |
| Mycobacterium paraseoulense | DQ536404 | 1522 |
| Mycobacterium paratuberculosis | X52934 | 1458 |
| Mycobacterium parmense | AF466821 | 1529 |
| Mycobacterium peregrinum | AY457069 | 1483 |
| Mycobacterium phlei | AF480603 | 1461 |
| Mycobactérie phocaicum | AY859682 | 1482 |
| Mycobacterium porcinum | AY457077 | 1483 |
| Mycobacterium poriferae | AF480589 | 1449 |
| Mycobacterium pseudoshottsii | AY570988 | 1453 |
| Mycobacterium psychrotolerans | AJ534886 | 1516 |
| Mycobacterium pulveris | AJ429046 | 1492 |
| Mycobacterium pyrenivorans | AJ431371 | 1481 |
| Mycobacterium rhodesiae | AJ429047 | 1485 |
| Mycobacterium riyadhense | EU274642 | 1475 |
| Mycobacterium rufum | AY943385 | 1322 |
| Mycobacterium rutilum | DQ370011 | 1417 |
| Mycobacterium scrofulaceum | AF480604 | 1466 |
| Mycobacterium sediminis | KC010490 | 1515 |
| Mycobacterium senegalense | AY457081 | 1483 |
| Mycobacterium senuense | DQ536408 | 1526 |
| Mycobacterium seoulense | DQ536403 | 1522 |
| Mycobacterium septicum | AY457070 | 1483 |
| Mycobacterium setense | EF138818 | 1336 |
| Mycobacterium sherrisii | AY353699 | 1510 |
| Mycobacterium shinjukuense | AB268503 | 1505 |
| Mycobacterium shottsii | AY005147 | 1491 |
| Mycobacterium simiae | X52931 | 1479 |
| Mycobacterium smegmatis | AJ131761 | 1482 |
| Mycobacterium sphagni | FR733719 | 1505 |
| Mycobacterium stomatepiae | AM884331 | 1471 |
| Mycobacterium szulgai | X52926 | 1454 |
| Mycobacterium thermoresistibile | X55602 | 1464 |
| Mycobacterium tokaiense | AF480590 | 1451 |
| Mycobacterium triplex | U57632 | 1474 |
| Mycobacterium triviale | DQ058405 | 1362 |
| Mycobacterium tusciae | AF058299 | 1409 |
| Mycobacterium ulcerans | AB548725 | 1475 |
| Mycobacterium vaccae | AF480591 | 1439 |
| Mycobacterium vulneris | EU834055 | 1471 |
| Mycobacterium wolinskyi | AY457083 | 1485 |
| Mycobacterium yongonense | JF738056 | 1395 |
Fig. 1.
Phylogenetic distribution of Mycobacterium species used in present study based on comparison of 16S rRNA sequences. Sequences were aligned by MUSCLE [14], and phylogenetic inferences were obtained by maximum likelihood method and Kimura two-parameter model in MEGA software. Numbers at nodes are percentages of bootstrap values obtained by repeating analysis 1000 times to generate majority consensus tree. Pseudonocardia acaciae (EU921261) was used as outgroup.
Of the 131 studied Mycobacterium species, 90 (68.7%) exhibited at least one 16S rRNA gene sequence similarity value greater than 98.65% with another species in this genus (Table 2, Supplementary Table S1). Among 131 studied species, 123 (93.9%) exhibited at least one 16S rRNA gene sequence similarity value lower than 95% with another species in the genus (Table 2, Supplementary Table S1). Only one (0.76%) of the 131 studied species, i.e. M. poriferae, exhibited only expected values (Table 2, Supplementary Table S1). At the intraspecies level, only expected values were observed.
Table 2.
Species that do not respect pairwise similarity thresholds of <95% and >98.65%
| Species (accession no.) | No. for <95% threshold | No. for >98.65% threshold |
|---|---|---|
| Mycobacterium abscessus subsp. bolletii (AY859681) | 41 | 2 |
| Mycobacterium africanum (AF480605) | 23 | 7 |
| Mycobacterium agri (AJ429045) | 32 | 0 |
| Mycbacterium aichiense (X55598) | 18 | 1 |
| Mycobacterium alvei (AF023664) | 17 | 13 |
| Mycobacterium anyangense (KJ855063) | 3 | 5 |
| Mycobacterium arosiense (EF054881) | 16 | 11 |
| Mycobacterium arupense (DQ157760) | 12 | 0 |
| Mycobacterium asiaticum (AF480595) | 6 | 4 |
| Mycobacterium aubagnense (AY859683) | 6 | 3 |
| Mycobacterium aurum (X55595) | 23 | 0 |
| Mycobacterium austroafricanum (X93182) | 17 | 1 |
| Mycobacterium avium subsp. avium (AJ536037) | 30 | 9 |
| Mycobacterium avium subsp. silvaticum (EF521891) | 23 | 13 |
| Mycobacterium bouchedurhonense (EF591053) | 20 | 11 |
| Mycobacterium branderi (AF480574) | 66 | 0 |
| Mycobacterium brisbanense (AY012577) | 1 | 1 |
| Mycobacterium brumae (AF480576) | 32 | 0 |
| Mycobacterium canariasense (AY255478) | 20 | 4 |
| Mycobacterium caprae (AJ131120) | 17 | 7 |
| Mycobacterium celatum (L08169) | 23 | 0 |
| Mycobacterium celeriflavum (KJ607136) | 0 | 1 |
| Mycobacterium chelonae (AY457072) | 47 | 2 |
| Mycobacterium chitae (X55603) | 17 | 0 |
| Mycobacterium chlorophenolicum (X79292) | 0 | 3 |
| Mycobacterium chubuense (AF480597) | 0 | 1 |
| Mycobacterium conceptionense (AY859684) | 2 | 17 |
| Mycobacterium confluentis (AJ634379) | 1 | 0 |
| Mycobacterium conspicuum (X88922) | 8 | 3 |
| Mycobacterium cosmeticum (AY449728) | 6 | 6 |
| Mycobacterium crocinum (DQ534008) | 5 | 6 |
| Mycobacterium diernhoferi (AF480599) | 23 | 5 |
| Mycobacterium doricum (AF264700) | 42 | 1 |
| Mycobacterium duvalii (U94745) | 3 | 2 |
| Mycobacterium elephantis (AJ010747) | 6 | 0 |
| Mycobacterium fallax (AF480600) | 2 | 0 |
| Mycobacterium farcinogenes (AY457084) | 2 | 21 |
| Mycobacterium flavescens (X52932) | 36 | 0 |
| Mycobacterium fluoranthenivorans (AJ617741) | 10 | 5 |
| Mycobacterium fortuitum subsp. fortuitum (AY457066) | 6 | 16 |
| Mycobacterium fortuitum subsp. acetamidolyticum (FR733720) | 6 | 16 |
| Mycobacterium fragae (JQ898451) | 17 | 0 |
| Mycobacterium frederiksbergense (AJ276274) | 11 | 3 |
| Mycobacterium gadium (X55594) | 6 | 0 |
| Mycobacterium gastri (AF480602) | 26 | 7 |
| Mycobacterium genavense (X60070) | 11 | 4 |
| Mycobacterium goodii (Y12872) | 11 | 3 |
| Mycobacterium gordonae (X52923) | 27 | 1 |
| Mycobacterium hassiacum (U49401) | 52 | 0 |
| Mycobacterium heidelbergense (AJ000684) | 5 | 5 |
| Mycobacterium hodleri (X93184) | 5 | 0 |
| Mycobacterium holsaticum (AJ310467) | 1 | 0 |
| Mycobacterium houstonense (AY457067) | 2 | 21 |
| Mycobacterium interjectum (HM037998) | 1 | 1 |
| Mycobacterium intermedium (X67847) | 2 | 0 |
| Mycobacterium intracellulare (AJ536036) | 29 | 12 |
| Mycobacterium iranicum (HQ009482) | 13 | 0 |
| Mycobacterium kansasii (AJ536035) | 26 | 7 |
| Mycobacterium komossense (X55591) | 10 | 0 |
| Mycobacterium koreense (JF271826) | 6 | 1 |
| Mycobacterium kubicae (AF133902) | 1 | 1 |
| Mycobacterium kyorinense (AB370111) | 70 | 0 |
| Mycobacterium lacus (AF406783) | 17 | 14 |
| Mycobacterium lentiflavum (AF480583) | 4 | 6 |
| Mycobacterium litorale (GU997640) | 20 | 0 |
| Mycobacterium llatzerense (AJ746070) | 14 | 1 |
| Mycobacterium madagascariense (AB537170) | 3 | 1 |
| Mycobacterium mageritense (AJ699399) | 0 | 1 |
| Mycobacterium malmoense (X52930) | 57 | 5 |
| Mycobacterium mantenii (FJ042897) | 5 | 7 |
| Mycobacterium marinum (AF456240) | 12 | 7 |
| Mycobacterium marseillense (EU266632) | 22 | 14 |
| Mycobacterium microti (AF480584) | 23 | 6 |
| Mycobacterium monacense (AF107039) | 35 | 1 |
| Mycobacterium moriokaense (AJ429044) | 0 | 3 |
| Mycobacterium mucogenicum (AY457074) | 4 | 11 |
| Mycobacterium murale (AB537171) | 1 | 0 |
| Mycobacterium nebraskense (AY368456) | 20 | 12 |
| Mycobacterium neoaurum (AF480593) | 5 | 4 |
| Mycobacterium neworleansense (AY457068) | 2 | 17 |
| Mycobacterium noviomagense (EU239955) | 48 | 0 |
| Mycobacterium novocastrense (U96747) | 44 | 0 |
| Mycobacterium obuense (X55597) | 21 | 0 |
| Mycobacterium pallens (DQ370008) | 5 | 6 |
| Mycobacterium paraense (KJ948996) | 0 | 1 |
| Mycobacterium paraffinicum (GQ153270) | 3 | 6 |
| Mycobacterium parafortuitum (X93183) | 3 | 6 |
| Mycobacterium paragordonae (KC525204) | 17 | 2 |
| Mycobacterium parakoreense (JF271823) | 2 | 0 |
| Mycobacterium parascrofulaceum (AY337273) | 6 | 1 |
| Mycobacterium paraseoulense (DQ536404) | 10 | 16 |
| Mycobacterium paratuberculosis (X52934) | 45 | 8 |
| Mycobacterium parmense (AF466821) | 46 | 0 |
| Mycobacterium peregrinum (AY457069) | 9 | 15 |
| Mycobacterium phlei (AF480603) | 4 | 0 |
| Mycobacterium phocaicum (AY859682) | 4 | 10 |
| Mycobacterium porcinum (AY457077) | 4 | 16 |
| Mycobacterium poriferae (AF480589) | 0 | 0 |
| Mycobacterium pseudoshottsii (AY570988) | 22 | 6 |
| Mycobacterium psychrotolerans (AJ534886) | 6 | 1 |
| Mycobacterium pulveris (AJ429046) | 2 | 1 |
| Mycobacterium pyrenivorans (AJ431371) | 4 | 0 |
| Mycobacterium rhodesiae (AJ429047) | 6 | 12 |
| Mycobacterium riyadhense (EU274642) | 10 | 18 |
| Mycobacterium rufum (AY943385) | 37 | 0 |
| Mycobacterium rutilum (DQ370011) | 17 | 6 |
| Mycobacterium scrofulaceum (AF480604) | 7 | 8 |
| Mycobacterium sediminis (KC010490) | 37 | 0 |
| Mycobacterium senegalense (AY457081) | 2 | 21 |
| Mycobacterium senuense (DQ536408) | 30 | 0 |
| Mycobacterium seoulense (DQ536403) | 10 | 16 |
| Mycobacterium septicum (AY457070) | 8 | 13 |
| Mycobacterium setense (EF138818) | 14 | 16 |
| Mycobacterium sherrisii (AY353699) | 3 | 7 |
| Mycobacterium shinjukuense (AB268503) | 42 | 0 |
| Mycobacterium shottsii (AY005147) | 16 | 7 |
| Mycobacterium simiae (X52931) | 6 | 6 |
| Mycobacterium smegmatis (AJ131761) | 15 | 7 |
| Mycobacterium sphagni (FR733719) | 3 | 10 |
| Mycobacterium stomatepiae (AM884331) | 2 | 4 |
| Mycobacterium szulgai (X52926) | 33 | 2 |
| Mycobacterium thermoresistible (X55602) | 48 | 1 |
| Mycobacterium tokaiense (AF480590) | 0 | 1 |
| Mycobacterium triplex (U57632) | 3 | 6 |
| Mycobacterium triviale (DQ058405) | 2 | 0 |
| Mycobacterium tusciae (AF058299) | 25 | 0 |
| Mycobacterium ulcerans (AB548725) | 16 | 7 |
| Mycobacterium vaccae (AF480591) | 31 | 1 |
| Mycobacterium vulneris (EU834055) | 26 | 12 |
| Mycobacterium wolinskyi (AY457083) | 2 | 0 |
| Mycobacterium yongonense (JF738056) | 15 | 14 |
For each studied species, we indicate for each threshold numbers of pairwise comparisons for which abnormal values were observed.
Discussion
Over the past decade, several authors suggested that the inter- and intraspecies discriminatory power of 16S rRNA gene sequences was insufficient for some bacterial genera [19], [20]. As examples, Streptococcus pneumoniae and S. mitis exhibit only a 3 nt difference (99.7% identity), which would classify them in the same species. In contrast, major interspecies differences may be observed, as is the case in the genus Clostridium, with C. tetani and C. innocuum exhibiting a 104 nt divergence (93.7% identity). The strict application of the 95% threshold would justify their classification in distinct genera [19]. In addition, in 2010, Pei et al. [21] identified an intragenomic sequence divergence greater than 1.3% among 16S rRNA genes copies in 11 bacterial species. Among these, Borrelia afzelii, an agent of Lyme disease in humans, exhibits a similarity of only 79.62% between its two 16S rRNA gene copies [21]. Thus, a strict application of the 98.65% threshold would classify these bacteria in different species depending on the 16S rRNA gene copy analysed [21], [22]. According to Rossi-Tamisier et al. [14], among 158 studied bacterial genera, only members of 17 genera strictly respected the 95% and 98.65% thresholds. Among other studied genera, the percentage of species that respected strictly both thresholds varied from 0 (Brucella) to 93.9% (Nocardia) [14].
In the present report, we observed that the currently used 16S rRNA gene sequence similarity thresholds for delineating bacterial species are valid for only 0.76% of 131 studied Mycobacterium species with standing in nomenclature. Because our study covers 71.97% of the currently validly published Mycobacterium species names, we believe that the 95% and 98.65% thresholds are not suitable for this genus and should at the maximum be used as indicators, not as a reference standard, for classifying new Mycobacterium species.
Acknowledgement
This study was funded by the Fondation Méditerranée Infection.
Footnotes
Supplementary data related to this article can be found at https://doi.org/10.1016/j.nmni.2017.12.009.
Conflict of interest
None declared.
Appendix A. Supplementary data
The following is the supplementary data related to this article:
References
- 1.Gevers D., Cohan F.M., Lawrence J.G., Spratt B.G., Coenye T., Feil E.J. Opinion: Re-evaluating prokaryotic species. Nat Rev Microbiol. 2005;3:733–739. doi: 10.1038/nrmicro1236. [DOI] [PubMed] [Google Scholar]
- 2.Moore E.R., Mihaylova S.A., Vandamme P., Krichevsky M.I., Dijkshoorn L. Microbial systematics and taxonomy: relevance for a microbial commons. Res Microbiol. 2010;161:430–438. doi: 10.1016/j.resmic.2010.05.007. [DOI] [PubMed] [Google Scholar]
- 3.Lehmann K.B., Neumann R. 1896. Atlas und Gundriss des Bakteriologie und Lehrbuch der speziellen bakteriologischen Diagnostik. Munich. [Google Scholar]
- 4.Minnikin D.E., Alshamaony L., Goodfellow M. Differentiation of Mycobacterium, Nocardia, and related taxa by thin-layer chromatographic analysis of whole-organism methanolysates. J Gen Microbiol. 1975;88:200–204. doi: 10.1099/00221287-88-1-200. [DOI] [PubMed] [Google Scholar]
- 5.Brenner D.J., Fanning G.R., Johnson K.E., Citarella R.V., Falkow S. Polynucleotide sequence relationships among members of Enterobacteriaceae. J Bacteriol. 1969;98:637–650. doi: 10.1128/jb.98.2.637-650.1969. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Coenye T., Vandamme P. Use of the genomic signature in bacterial classification and identification. Syst Appl Microbiol. 2004;27:175–185. doi: 10.1078/072320204322881790. [DOI] [PubMed] [Google Scholar]
- 7.Konstantinidis K.T., Tiedje J.M. Prokaryotic taxonomy and phylogeny in the genomic era: advancements and challenges ahead. Curr Opin Microbiol. 2007;10:504–509. doi: 10.1016/j.mib.2007.08.006. [DOI] [PubMed] [Google Scholar]
- 8.Quast C., Pruesse E., Yilmaz P., Gerken J., Schweer T., Yarza P. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–D596. doi: 10.1093/nar/gks1219. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Vandamme P., Pot B., Gillis M., De Vos P., Kersters K., Swings J. Polyphasic taxonomy, a consensus approach to bacterial systematics. Microbiol Rev. 1996;60:407–438. doi: 10.1128/mr.60.2.407-438.1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Tindall B.J., Rossello-Mora R., Busse H.J., Ludwig W., Kämpfer P. Notes on the characterization of prokaryote strains for taxonomic purposes. Int J Syst Evol Microbiol. 2010;60:249–266. doi: 10.1099/ijs.0.016949-0. [DOI] [PubMed] [Google Scholar]
- 11.Stackebrandt E., Goebel B.M. Taxonomic note: a place for DNA-DNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology. Int J Syst Bact. 1994;44:846–849. [Google Scholar]
- 12.Stackebrandt E., Ebers J. Taxonomic parameters revisited: tarnished gold standards. Microbiol Today. 2006;33:152–155. [Google Scholar]
- 13.Kim M., Oh H.S., Park S.C., Chun J. Towards a taxonomic coherence between average nucleotide identity and 16S rRNA gene sequence similarity for species demarcation of prokaryotes. Int J Syst Evol Microbiol. 2014;64:346–351. doi: 10.1099/ijs.0.059774-0. [DOI] [PubMed] [Google Scholar]
- 14.Rossi-Tamisier M., Benamar S., Raoult D., Fournier P.E. Cautionary tale of using 16S rRNA gene sequence similarity values in identification of human-associated bacterial species. Int J Syst Evol Microbiol. 2015;65:1929–1934. doi: 10.1099/ijs.0.000161. [DOI] [PubMed] [Google Scholar]
- 15.Woo P.C., Tsoi H.W., Leung K.W., Lum P.N., Leung A.S., Ma C.H. Identification of Mycobacterium neoaurum isolated from a neutropenic patient with catheter-related bacteremia by 16S rRNA sequencing. J Clin Microbiol. 2000;38:3515–3517. doi: 10.1128/jcm.38.9.3515-3517.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Tortoli E. Impact of genotypic studies on mycobacterial taxonomy: the new mycobacteria of the 1990s. Clin Microbiol Rev. 2003;16:319–354. doi: 10.1128/CMR.16.2.319-354.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Edgar R.C. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinform. 2004;5:113. doi: 10.1186/1471-2105-5-113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Tamura K., Peterson D., Peterson N., Stecher G., Nei M., Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28:2731–2739. doi: 10.1093/molbev/msr121. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Bosshard P.P., Zbinden R., Abels S., Boddinghaus B., Altwegg M., Bottger E.C. 16S rRNA gene sequencing versus the API 20 NE system and the VITEK 2 ID-GNB card for identification of nonfermenting Gram-negative bacteria in the clinical laboratory. J Clin Microbiol. 2006;44:1359–1366. doi: 10.1128/JCM.44.4.1359-1366.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Mignard S., Flandrois J.P. 16S rRNA sequencing in routine bacterial identification: a 30-month experiment. J Microbiol Methods. 2006;67:574–581. doi: 10.1016/j.mimet.2006.05.009. [DOI] [PubMed] [Google Scholar]
- 21.Pei A.Y., Oberdorf W.E., Nossa C.W., Agarwal A., Chokshi P., Gerz E.A. Diversity of 16S rRNA genes within individual prokaryotic genomes. Appl Environ Microbiol. 2010;76:3886–3897. doi: 10.1128/AEM.02953-09. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Acinas S.G., Marcelino L.A., Klepac-Ceraj V., Polz M.F. Divergence and redundancy of 16S rRNA sequences in genomes with multiple rrn operons. J Bacteriol. 2004;186:2629–2635. doi: 10.1128/JB.186.9.2629-2635.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.