The bacterium Flavobacterium psychrophilum is a serious pathogen in many fish species, especially salmonids, that is responsible for considerable economic losses worldwide. In order to treat infections and to develop vaccines, the genetic diversity of this bacterium needs to be known. We assessed the genetic diversity of F. psychrophilum isolates from apparently healthy rainbow trout raised in several fish farms in the same watershed in France. Two different genotyping methods revealed high diversity. The majority of isolates were unrelated to clonal complex sequence type 10 (CC-ST10), the clonal complex that is predominant worldwide and associated with disease in rainbow trout. In addition, we found 13 novel sequence types. These results suggest that a diverse subpopulation of F. psychrophilum may be harbored by rainbow trout.
KEYWORDS: PFGE, MLST, mPCR, aquaculture
ABSTRACT
Flavobacterium psychrophilum affects salmonid health worldwide and causes economic losses. The genetic diversity of the pathogen must be considered to develop control methods. However, previous studies have reported both high and low levels of genetic diversity. The present longitudinal study aimed at assessing the genetic diversity of F. psychrophilum at a small temporal and geographic scale. Four farms located on the same watershed in France were studied. Rainbow trout (Oncorhynchus mykiss) batches were monitored, and apparently healthy individuals were sampled over 1 year. A total of 288 isolates were recovered from fish organs (gills and spleen) and eggs. Pulsed field gel electrophoresis revealed high genetic diversity. Multilocus sequence typing performed on a selection of 31 isolates provided congruent results, as follows: 18 sequence types (STs) were found, of which 13 were novel. The mean gene diversity (H = 0.8413) was much higher than that previously reported for this host species, although the sampling was restricted to a single watershed and 1 year. Seven isolates out of 31 were assigned to clonal complex ST10 (CC-ST10), which is the predominant clonal complex in the main salmonid production areas. A split decomposition tree reflected a panmictic population. This finding is important for aquaculture veterinarians in their diagnostic procedure, as the choice of adequate antibiotic treatment is conditioned by the correct identification of the causative agent. Furthermore, this study expands our knowledge on genetic diversity required for the development of an effective vaccine against F. psychrophilum.
IMPORTANCE The bacterium Flavobacterium psychrophilum is a serious pathogen in many fish species, especially salmonids, that is responsible for considerable economic losses worldwide. In order to treat infections and to develop vaccines, the genetic diversity of this bacterium needs to be known. We assessed the genetic diversity of F. psychrophilum isolates from apparently healthy rainbow trout raised in several fish farms in the same watershed in France. Two different genotyping methods revealed high diversity. The majority of isolates were unrelated to clonal complex sequence type 10 (CC-ST10), the clonal complex that is predominant worldwide and associated with disease in rainbow trout. In addition, we found 13 novel sequence types. These results suggest that a diverse subpopulation of F. psychrophilum may be harbored by rainbow trout.
INTRODUCTION
Flavobacterium psychrophilum, a Gram-negative bacterium, is the causative agent of bacterial cold water disease (BCWD) and rainbow trout fry syndrome (RTFS) in freshwater salmonid fish (1). First identified as a fish pathogen in the United States (2), F. psychrophilum infections have been observed since the mid-1980s in all other areas of salmonid production, i.e., Europe (3), South America (4), Asia (5), and Oceania (6). They are responsible for economic losses for fish farmers (7). Antibiotic treatments are currently the primary therapeutic strategy available to control F. psychrophilum infections, but their extensive usage has contributed to the development of antimicrobial resistance (8–10). Challenges in vaccine development and disappointing vaccination results have delayed the field application of an F. psychrophilum vaccine (11, 12). Only recently has extensive research produced some promising vaccination results (13–15). However, no broad-spectrum commercial vaccine is yet available. To develop preventive and therapeutic control methods, including follow-up of farm infections, information about the genetic diversity of the bacterial population at different scales is a prerequisite. Since 2007, studies of bacterial genetic diversity have mainly used the following two typing methods: pulsed field gel electrophoresis (PFGE) and multilocus sequence typing (MLST).
PFGE is based on the restriction of the whole bacterial genome with one or more specific restriction enzymes and is often considered the gold standard in epidemiological studies for some important foodborne pathogens, such as members of Listeria and Salmonella (16, 17). MLST is based on the sequencing of several housekeeping genes and the analysis of differences in their single-nucleotide polymorphisms (SNPs) to understand the structure of the bacterial population (e.g., clonal, epidemic, or panmictic) (18). Different methods have been proposed to describe F. psychrophilum genetic diversity. Several authors have applied PFGE (19–21), but different restriction enzymes were used in these studies and it is therefore impossible to compare their results. A standardized MLST scheme was described (22) and extensively used (23–31); the corresponding results are available in a common database (http://pubmlst.org/fpsychrophilum/) (Table 1). In addition to differences in the genotyping method, heterogeneity in sampling strategies can be found in the literature. Studies have considered different sample types (e.g., fish, water, or sediment), different fish species, different health statuses (fish clinical cases versus asymptomatic carriers), and different numbers of isolates; the geographic and temporal scales also have varied. Depending on the typing method chosen, the protocol used, and the samples analyzed, the results obtained for the description of F. psychrophilum diversity can be incongruent. For example, using PFGE, the F. psychrophilum population has been described as diverse by some authors (10, 19, 32), whereas others found it homogeneous (21, 33). The aim of this study was to characterize the genetic diversity of F. psychrophilum isolated from farmed rainbow trout (Oncorhynchus mykiss) at the watershed level. The originality of this study resides in the small geographical and temporal scales (watershed of 200 km2; 1-year study period), the inclusion in the study of only apparently healthy fish, and the use of multiple typing methods (PFGE and MLST) to better investigate the population structure of F. psychrophilum associated with rainbow trout. A secondary objective was to identify serotypes by multiplex PCR (mPCR) to further characterize the isolated strains.
TABLE 1.
Sampling schemes to assess F. psychrophilum diversity by MLST and results found in the literature
| Origin of isolates | Host | Flavobacteriosis status in hosts | Time scale | No. of isolates | No. of STs | Gene diversity (H) (mean ± SE) | Reference |
|---|---|---|---|---|---|---|---|
| United States, Europe, Israel, Chile, Japan | O. mykiss | With clinical signs and unknown | 1986–2000 | 25 | 16 | 0.5333 | Nicolas et al. (22); H index reported in Siekoula-Nguedia et al. (23) |
| France | O. mykiss | With clinical signs | 2007–2010 | 66 | 15 | 0.4313 | Siekoula-Nguedia et al. (23) |
| Switzerland | O. mykiss, Salmo trutta fario, S. trutta lacustris | With clinical signs or skin and gills lesions | 1993–2012 | 84 | 27 | 0.493 ± 0.030 | Strepparava et al. (26); H index reported in Avendaño-Herrera et al. (27) |
| Japan | 16 fish species + river water | Sampling irrespective of disease status | 1993–2006 | 120 | 35 | 0.658 ± 0.026 | Fujiwara-Nagata et al. (25); H index reported in Avendaño-Herrera et al. (27) |
| Chile | O. mykiss, Salmo salar, O. kisutch | Most fish presented clinical signs | 2005–2011 | 94 | 15 | 0.485 ± 0.050 | Avendaño-Herrera et al. (27) |
| Denmark, Norway, Finland, Sweden | 10 fish species (mostly salmonids) | Not specified | 1983–2012 | 560 | 81 | 0.6127 ± 0.042 | Nilsen et al. (28) |
| O. mykiss | Not specified | 1983–2012 | 448 | 47 | 0.4589 ± 0.062 | Nilsen et al. (28) | |
| United States | O. mykiss, O. kisutch, O. tshawytscha | Majority of isolates from fish with clinical signs | 1981–2013 | 96 | 34 | 0.75 ± 0.03 | Van Vliet et al. (29) |
| O. mykiss | Majority of isolates from fish with clinical signs | 1991–2013 | 54 | 11 | 0.32 ± 0.07 | Van Vliet et al. (29) | |
| United States and Canada | 10 fish species (mostly salmonids) | With clinical signs and apparently healthy | 1981–2018 | 314 | 66 | 0.68 ± 0.04 | Knupp et al. (30) |
| O. mykiss | With clinical signs and apparently healthy | 1981–2018 | 260 | 45 | 0.48 ± 0.06 | Knupp et al. (30) | |
| California | O. tshawytscha, O. mykiss | Moribund or freshly dead fish | 2015–2018 | 49 | 11 | Not reported | Sebastião et al. (31) |
| France (watershed level) | O. mykiss | Apparently healthy | 2011–2012 | 31 | 18 | 0.8413 | This study |
RESULTS
A total of 288 isolates from 104 fish were identified as F. psychrophilum by culture and PCR. This represents an overall prevalence of 6.73% (104/1,545). In addition, 2 pooled egg samples were positive for F. psychrophilum (prevalence in eggs 6.25%, 2/32). The prevalence of F. psychrophilum in fish varied largely between farms and months (Table 2). It is worth noting that this was the prevalence of F. psychrophilum in apparently healthy animals with no signs of flavobacteriosis. However, farms 1, 2, and 4 experienced flavobacteriosis outbreaks during this 1-year sampling period, and 14 out of the 18 monitored batches were treated with the antibiotic florfenicol at least once.
TABLE 2.
Prevalence of Flavobacterium psychrophilum by farm and month, and average water temperature
| Sampling date | Prevalence by farm (positive fish/sampled fish)b |
Prevalence at the watershed level (% [positive fish/sampled fish]) | Avg water temp (°C) | |||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||
| March 2011 | 2/15 | 9/60a | 0/30 | 11/30a | 14.7 (22/150) | 9.25 |
| April 2011 | 2/15 | 12/60a | 3/30a | 10/30 | 18 (27/150) | 11 |
| May 2011 | NA | 2/60a | 2/30a | 0/15 | 3.8 (4/105) | 12.75 |
| June 2011 | 0/30 | 1/60a | 0/30 | 0/15 | 0.7 (1/135) | 12.56 |
| July 2011 | 0/30 | 0/60 | 0/30 | 6/15 | 4.4 (6/135) | 14.18 |
| September 2011 | 0/15 | 0/60a | 0/30 | 0/30 | 0 (0/135) | 15.87 |
| October 2011 | NA | 0/60a | 0/30 | 1/30 | 0.8 (1/120) | 13.91 |
| November 2011 | 1/15 | 5/60a | 0/30 | 3/15 | 7.5 (9/120) | 10.12 |
| December 2011 | 2/15 | 0/15 | 0/30 | 9/30 | 12.2 (11/90) | 9.25 |
| January 2012 | 1/15 | 2/60a | 0/30 | 0/30 | 2.2 (3/135) | 9.56 |
| February 2012 | 1/15 | 9/60a | 0/30 | 1/30a | 7.4 (10/135) | 6 |
| March 2012 | 1/15 | 7/60a | 0/30 | 0/30 | 5.2 (7/135) | 8.23 |
| Overall prevalence | 4.7% (10/210) | 6.9% (47/675) | 1.4% (5/360) | 14% (42/300) | 6.7 (104/1545) | |
aReport of florfenicol administration in the 4 weeks prior to sampling.
bNA, not applicable.
Genetic diversity assessed by PFGE.
A PFGE analysis was performed on all F. psychrophilum isolates and two reference strains, namely, JIP 02/86 and LNPAA PO1/88. Seven isolates were nontypeable and thus were excluded from further analysis. Isolates whose profiles showed a ≥98% similarity were considered a same pulsotype. In the final set of 281 profiles, 103 pulsotypes were identified (see Fig. S1 in the supplemental material). They were grouped in 14 clusters (similarity, ≥80%) and 12 singletons, and the minimum degree of similarity observed was 62%. C1 and C6 were the largest clusters. C1 comprised 154 isolates assigned into 36 pulsotypes, whereas C6 comprised 74 isolates assigned into 29 pulsotypes. The two reference strains JIP 02/86 and LNPAAP 01/88 were associated with clusters C1 and C6, respectively. The other clusters were composed of 2 to 12 isolates (Fig. S1).
Genetic diversity assessed by MLST.
A total of 18 different sequence types (STs) were obtained from the 31 selected isolates (Table 3). Five of these STs (ST2, ST90, ST92, ST95, and ST98) were already described in the literature (22, 23). The other 13 STs (ST182 and ST219 to ST230) were novel, representing 42% of isolates. Except for three isolates belonging to ST182, all novel STs were found only once in our isolate set.
TABLE 3.
MLST allele types and sequence types of 31 F. psychrophilum isolates and reference strains
| Selection criteria (subset) | Isolate | AT by locus type |
STa | ||||||
|---|---|---|---|---|---|---|---|---|---|
| trpB | gyrB | dnaK | fumC | murG | tuf | atpA | |||
| Same fish, same pulsotype (α) | A133 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 |
| A138 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| A139 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| A141 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| A142 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| A145 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| A146 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| A147 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| Same fish, different pulsotype (β) | B65 | 2 | 2 | 2 | 2 | 2 | 48 | 2 | 98 |
| B66 | 29 | 37 | 8 | 1 | 43 | 3 | 52 | 226 | |
| B68 | 8 | 53 | 8 | 7 | 30 | 54 | 45 | 227 | |
| B95 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 | |
| B97 | 18 | 43 | 8 | 11 | 28 | 3 | 2 | 228 | |
| B98 | 4 | 3 | 2 | 9 | 22 | 49 | 3 | 229 | |
| B99 | 4 | 2 | 2 | 2 | 2 | 49 | 2 | 230 | |
| B100 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | |
| Different fish, various pulsotypes (γ) | A6 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 90 |
| A24 | 3 | 2 | 2 | 2 | 2 | 41 | 2 | 92 | |
| A67 | 4 | 2 | 22 | 3 | 12 | 3 | 3 | 221 | |
| A81 | 15 | 53 | 8 | 7 | 30 | 54 | 45 | 182 | |
| A88 | 15 | 53 | 8 | 7 | 30 | 54 | 45 | 182 | |
| A97 | 35 | 49 | 2 | 11 | 42 | 3 | 3 | 222 | |
| B2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | |
| B47 | 2 | 49 | 2 | 11 | 42 | 3 | 3 | 223 | |
| B50 | 4 | 2 | 22 | 3 | 12 | 3 | 51 | 224 | |
| B57 | 18 | 21 | 8 | 7 | 28 | 19 | 44 | 225 | |
| C31 | 4 | 2 | 2 | 2 | 2 | 41 | 2 | 95 | |
| C34 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | |
| D3 | 15 | 53 | 8 | 7 | 30 | 54 | 45 | 182 | |
| D4 | 35 | 61 | 8 | 7 | 28 | 19 | 44 | 219 | |
| D6 | 1 | 15 | 1 | 1 | 1 | 2 | 1 | 220 | |
| Reference strains | JIP 02/86 | 8 | 8 | 2 | 2 | 2 | 2 | 2 | 20 |
| LNPAA P01/88 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | |
Novel STs are underlined.
Moreover, 75 polymorphic sites were observed (Table 4) in the 5,808 bp corresponding to the concatenated sequences of the 7 loci. The number of single-nucleotide polymorphism (SNP) sites differed according to the locus and ranged from 4 at the fumC locus to 20 at the atpA locus. The mean gene diversity (H) was 0.8413 with the lowest H value (0.7059) obtained for the dnaK locus (Table 4).
TABLE 4.
MLST loci and genetic variations
| Locus | Length (bp) | No. of polymorphic sites | Gene diversity (H) |
|---|---|---|---|
| trpB | 789 | 6 | 0.8954 |
| gyrB | 1,077 | 15 | 0.8497 |
| dnaK | 882 | 6 | 0.7059 |
| tuf | 795 | 13 | 0.8562 |
| fumC | 750 | 4 | 0.8487 |
| murG | 681 | 11 | 0.8889 |
| atpA | 834 | 20 | 0.8431 |
| Concatenated sequences | 5,808 | 75 | 0.8413 |
No correlation between ST and sampled organ was evidenced; the same ST could be isolated from both gills and spleen (Table 5, subset α). More than one ST could be found in the same individual fish, revealing cocarriage, as seen in subset β. Different STs were even isolated from the same organ from the same fish.
TABLE 5.
Comparative results of PFGE, MLST, and mPCR in the subset of 31 isolates analyzed by the three methods
| Selection criteria (subset) | Isolate | Organ | Pulsotype | PFGE cluster or singleton | MLST type | Included in clonal complex ST10 | mPCR serotype |
|---|---|---|---|---|---|---|---|
| Same fish, same pulsotype (α) | A133 | Gills | P17 | C1 | ST90 | No | T2 |
| A138 | Spleen | ||||||
| A139 | Spleen | ||||||
| A141 | Spleen | ||||||
| A142 | Spleen | ||||||
| A145 | Gills | ||||||
| A146 | Gills | ||||||
| A147 | Gills | ||||||
| Same fish, different pulsotypes (β) | B65 | Gills | P74 | C6 | ST98 | Yes | T1 |
| B66 | Gills | P48 | C5 | ST226 | No | T0 | |
| B68 | Spleen | P85 | S8 | ST227 | No | T1 | |
| B95 | Gills | P9 | C1 | ST90 | No | T1 | |
| B97 | Gills | P90 | C9 | ST228 | No | T0 | |
| B98 | Spleen | P97 | C12 | ST229 | No | T0 | |
| B99 | Spleen | P84 | C7 | ST230 | Yes | T2 | |
| B100 | Spleen | P83 | C7 | ST2 | Yes | T2 | |
| Different fish, various pulsotypes (γ) | A6 | Gills | P6 | C1 | ST90 | No | T1 |
| A81 | Gills | P36 | S5 | ST182 | No | T1 | |
| B57 | Gills | P38 | C3 | ST225 | No | T0 | |
| D4 | Spleen | P40 | C3 | ST219 | No | T0 | |
| A97 | Gills | P46 | C5 | ST222 | No | T0 | |
| A88 | Gills | P51 | C6 | ST182 | No | T1 | |
| D3 | Spleen | P53 | C6 | ST182 | No | T1 | |
| A24 | Spleen | P55 | C6 | ST92 | Yes | T2 | |
| D6 | Gills | P56 | C6 | ST220 | No | T2 | |
| B2 | Spleen | P62 | C6 | ST2 | Yes | T1 | |
| C34 | Gills | P70 | C6 | ST2 | Yes | T2 | |
| C31 | Egg | P70 | C6 | ST95 | Yes | T2 | |
| B50 | Gills | P93 | C11 | ST224 | No | T0 | |
| A67 | Gills | P95 | C11 | ST221 | No | T0 | |
| B47 | Gills | P100 | S11 | ST223 | No | T0 | |
| Reference straina | JIP 02/86 | - | P29 | C1 | ST20 | Yes | T0 |
| LNPAAP 01/88 | - | P73 | C6 | ST2 | Yes | T1 |
Reference strains were added for comparison.
Figure 1 shows the relatedness of the 31 isolates using the eBURST software. With default parameters (single-locus variant [SLV]), five pairs of STs were linked. With relaxed settings (double-locus variant [DLV]), the links of ST2 and ST98 were enlarged; they were also related with ST92, ST95, and ST230. ST92 and ST95 were already described as belonging to CC-ST10, with ST2 initially suspected of being the founder (23). Seven isolates were assigned to CC-ST10 (Table 5). The eBURST method detected an additional pair of related isolates (ST219-ST225) by using relaxed settings. Three singletons, namely, ST226, ST228, and ST229, completed the eBURST representation (Fig. 1).
FIG 1.
eBURST diagram. Single-locus variants (SLVs) are joined by full lines, and double-locus variants (DLVs) are joined by dotted lines. STs within the ST10 clonal complex are encircled.
The SplitsTree software was used on concatenated sequences of all STs to reveal recombination events. A dense network structure was observed (Fig. 2), indicative of recombination events particularly at the CC level, which reflected a panmictic population for these 31 isolates.
FIG 2.
Split decomposition analysis. STs within the ST10 clonal complex are encircled.
Serotype identification.
Serotypes T0, T1, and T2 were found in the set of 31 isolates tested (Table 5). More than one serotype could be found in the same host, also revealing cocarriage.
Comparison of PFGE, MLST, and serotyping.
No perfect correlation between PFGE and MLST was observed, but they mostly provided congruent results (Table 5).
Congruence in subset α.
In this subset encompassing 8 isolates, a unique ST, ST90, was found. This was a congruent result, as all these isolates belonged to the same pulsotype (i.e., >98% similarity) and originated from the same individual fish. In addition, all of these isolates belonged to serotype T2, which further showed the homogeneity in this subset of isolates.
Congruence in subset β.
In subset β (same fish, different pulsotypes), no ST was detected more than once. MLST was discriminant enough to tell apart two pulsotypes that belonged to the same cluster (i.e., >80% similarity by PFGE). However, isolates that were unrelated by PFGE and by MLST belonged to the same serotype.
Cocarriage events were evidenced by all three methods. For instance, isolates B65, B66, and B68, retrieved from the same fish, presented three different pulsotypes, three different STs, and two different serotypes. Similarly, isolates B95, B97, B98, B99, and B100, retrieved from the same fish, represented five different pulsotypes, five different STs, and three different serotypes (Table 5). Interestingly, isolates that belonged to CC-ST10 and isolates that did not belong to this CC co-occurred within the same host and even in the same organ. This phenomenon was observed in both individual fishes included in this subset.
Congruence in subset γ.
These 15 isolates, retrieved from different fish, harbored different pulsotypes, except for isolates C31 and C34 (from an egg and a juvenile of farm 3, sampled on the same day). Twelve STs were found, with ST182 and ST2 being detected more than once. In these two cases, MLST was not able to capture the diversity found by PFGE. In particular, three isolates were assigned to ST182, and two of these isolates shared some degree of relatedness (same PFGE cluster); however, one isolate was unrelated (singleton by PFGE). These three isolates were identified as belonging to serotype T1. Interestingly, the two isolates assigned to ST2 also belonged to the same PFGE cluster but displayed different serotypes (T1 and T2).
However, MLST was superior in one case. The epidemiologically related isolates C31 and C34 (from an egg and a juvenile of farm 3, sampled on the same date) showed the same pulsotype and the same serotype, but MLST assigned them to ST2 and ST95, respectively, both being members of CC-ST10.
Congruence between subsets of isolates.
When considering the total set of isolates, ST90 and ST2 were present in more than one subset. All isolates assigned to ST90 belonged to the same PFGE cluster, thus being somehow related. In addition, more than one serotype was detected within ST90. ST2 encompassed isolates belonging to different PFGE clusters (C6 and C7) and different serotypes (T1 and T2). The reference strain LNPAA P01/88 was also assigned to ST2. Both ST2 and ST90 were detected in several organs, individual hosts, and farms, but only ST2 was included in CC-ST10. All isolates that were included in CC-ST10 belonged to PFGE clusters C6 and C7. These two clusters showed approximately 77% similarity (Fig. S1). No serotype was clearly correlated with being included in CC-ST10.
DISCUSSION
A total of 288 F. psychrophilum isolates were recovered during a year of longitudinal monitoring on four fish farms located in a same watershed of about 200 km2, which represents a small spatial scale in comparison to most previous studies. As expected, positive samples were collected mostly during the cold period (December to April), with an average water temperature ranging from 6 to 11°C. However, some positive samples were also found during summer, as previously described by Ngo et al. (32). The highest water temperature was recorded in September (15.87°C), which coincides with the absence of F. psychrophilum in fish samples.
In previous studies using PFGE to genotype F. psychrophilum strains and explore their genetic diversity, the following four enzymes were used: BlnI (19, 33), XhoI (19, 33), SacI (20, 32, 33), and StuI (10, 21). Results reported in these studies were very diverse and may seem contradictory. For example, the minimal similarity among isolates ranged from 12% (10) to 80% (21). Some studies found homogeneity (21, 33), whereas others describe wide genetic diversity in the F. psychrophilum population (10, 19, 20, 32). The diversity of results and conclusions reported in the literature is likely due to variations in the design and sampling strategy used in these studies.
However, many studies described host-specific F. psychrophilum lineages and a more uniform pattern for the host O. mykiss than that for other salmonids. In our study, F. psychrophilum isolates were obtained under restrictive sampling conditions to avoid the effect of host population heterogeneity, i.e., a 1-year study period, a single host species, a small geographical scale, and only apparently healthy fish. In spite of this, the minimal similarity was 62% in our set of isolates assessed by PFGE with the SalI restriction enzyme. This diversity suggests some genetic variability in the sampled population but also pinpoints the existence of dominant clusters since only two of them, namely, C1 and C6, comprised 60% of the total number of isolates analyzed.
MLST performed on 31 isolates selected according to PFGE typing results identified 18 different STs, including 13 novel ones. The mean gene diversity (H = 0.8413) suggested a higher genetic variability in our sample set than that in other studies (Table 1). For isolates retrieved from a wide range of hosts, the H value ranged from 0.485 (33) to 0.75 (29). Other studies that included a single host, O. mykiss, reported an H value ranging from 0.32 (29) to 0.48 (30). A major difference explaining this H value could be the sampling scheme and the health status of fish (diseased fish versus asymptomatic carriers). In the present study, both PFGE and MLST detected a high genetic diversity in F. psychrophilum associated with apparently healthy rainbow trout farmed in the same watershed. However, it remains unknown whether these isolates were avirulent or the fish were latent carriers. It is also unknown how the antibiotic treatments that took place in the enrolled farms during the study period may have affected our assessment of bacterial genetic diversity.
In this diverse bacterial population, there may be isolates associated with a specific location, such as a watershed, a river, a fish farm, or a raceway, whereas other isolates could be more transmissible and present a more global diffusion in salmonid production areas, as previously described for strains belonging to CC-ST10 (34). In agreement with this hypothesis, Knupp et al. (30) described how singletons appeared to be geographically limited and associated with one fish farm.
With 75 SNPs observed, variability is noticeable in our sample. The panmictic population structure of F. psychrophilum was already described in the literature (22, 27). Recombination has been known to play a major role in the F. psychrophilum population structure (30, 34), but our results suggest that the contribution of mutations is greater than previously reported (23). Conducted in the same country as the present study (France) but on a much larger geographical scale (22 different watersheds), the study by Siekoula-Nguedia et al. (23) revealed only two new SNP sites in 66 clinical isolates corresponding to 15 STs. In contrast, we found 4 new SNP sites in 31 isolates corresponding to 18 STs. Thus, mutation may be an unforeseen driving force for the diversification of F. psychrophilum. In addition, a novel ST in CC-ST10 was found, as well as more recombination in split representation than what was described in other studies (28).
The serotype identification by mPCR revealed the presence of serotypes that are typically associated with rainbow trout (T1 and T2), which is in agreement with host specificity. However, serotype T0 was also frequently detected in our data set. This serotype is mainly found in isolates retrieved from coho salmon (Oncorhynchus kisutch). This result is not surprising, as Rochat et al. (35) reported 20 F. psychrophilum isolates from rainbow trout in France that belonged to this serotype.
Cocarriage was found by all three typing techniques, with up to five STs and three serotypes (T0, T1, and T2) for isolates retrieved from a single fish. Cocarriage was already described in Japan (25), Switzerland (26), and United States (20, 30). The efficacy of a vaccine against BCWD could be compromised by cocarriage, as virulent and nonvirulent strains can coexist in the same fish (36). On the other hand, coinfection by multiple pathogenic serotypes could also be the cause of disease. A broad-spectrum vaccine providing protection against multiple strains may help overcome vaccination failures against BCWD.
Further research is needed to elucidate the clinical significance of the isolates retrieved from apparently healthy fish in this study. For example, a set of experimental challenges may shed light on the pathogenicity of the newly identified isolates, including those belonging to CC-ST10. In veterinary diagnosis, it is important to consider the nonpathogenic subpopulation versus the disease-associated bacterial subpopulation to identify the causative agent correctly and choose the appropriate antibiotic treatment. Furthermore, it would be interesting to analyze archived isolates from worldwide locations with the aim of comparing isolates from diseased fish with isolates from apparently healthy fish.
In conclusion, this study has found an unprecedented high genetic diversity in F. psychrophilum retrieved from rainbow trout. MLST has proved to be an adequate tool to assess genetic diversity in this bacterial species. It may be also successfully used in epidemiological studies, such as the study of flavobacteriosis outbreaks, transmission routes, and detection of reservoirs, among others. An interesting option would be to combine MLST and mPCR serotyping of the investigated isolates. This can be the most time-effective option for obtaining relevant information on both genetic relatedness and phenotypic determinants of immunogenicity of the isolates. However, one might expect that in the near future, whole-genome sequencing will potentially become a key tool in the molecular epidemiology of aquaculture pathogens due to its large discriminatory power (37).
MATERIALS AND METHODS
Study population and study sample.
Farm selection criteria. Four rainbow trout farms, all located on the same watershed in Brittany (northwestern [NW] France), participated in a 1-year study between March 2011 and March 2012. Farms were enrolled if they met the following criteria: (i) rainbow trout was the only species farmed; (ii) the veterinarian in charge had identified flavobacteriosis outbreaks in the 2 years prior to the beginning of the study; and (iii) they were located within the same watershed, with no other fish farming facility between them. The origin of eggs and fish and the commercial links between the farms were investigated by means of a questionnaire. The four farms participating in this study were characterized as follows (Fig. 3). Farm 1 was positioned at the river head, with no other aquaculture facility upstream. This was a grow-out operation that received fingerlings from farm 3 and from a facility located in a distant watershed in central France. Farm 2 (downstream of farm 1) was a hatchery and grow-out facility that bought eggs from farm 3 and from a distant watershed in southwestern (SW) France. When fish reached 300 g, they were either transferred to farm 4 (same owner) or sold to other fish farms. Farm 3 was a broodfish farm located on the head of a side branch of the river, with no aquaculture facility upstream. The farmer reported being able to self-restock; hence, no fish or eggs were introduced from other sites. Farm 4 was located downstream of all other studied farms and was owned and managed by the same farmer as farm 2. Adult fish of about 300 g body weight originating from farm 2 were further raised in farm 4 until they reached 500 g.
FIG 3.
Schematic representation of the sampling area encompassing the four fish farms (1 to 4) on the same watershed. The arrow indicates the direction of the water flow. The watershed size is approximately 200 km2.
Batch and animal selection criteria.
Based on the size of the farm, two to four batches were selected per site and monitored throughout their production cycle. A batch was defined as a group of individuals that originated from the same brood stock, was kept at all times under the same conditions (same hatchery tray and same raceway), and was not mixed with individuals that did not meet these conditions. When a selected batch was transferred to another enrolled farm, it continued to be monitored in the new location. When a farm sold a selected batch to a nonenrolled farm, another batch of younger fish was selected and started being monitored at the site.
On a monthly basis, 15 individual fish per batch were randomly chosen, provided that they showed no signs of flavobacteriosis. Specifically, fish had to display no dark skin pigmentation, exophthalmia, fin erosions, and abnormal swimming behavior. Fish were discarded if internal organs presented gross lesions at necropsy and were replaced with apparently healthy fish from the same batch. However, it is important to note that isolates retrieved from fish that lack disease signs are not necessarily avirulent, as fish can be latent carriers (36).
A total of 12 sampling events per site took place, with 1,545 individual fish from 18 batches sampled in all 4 farms. Additionally, 32 pools of eggs from farm 3 were processed. Sampling events took place each month, with the exception of August because most of the farms were in a fallowing period. At each sampling event, water temperature was recorded as well as whether any vaccination and/or any antibiotic treatment had taken place since the last sampling event (date, reason, and compound).
Animal use and organ sampling.
Fish were culled by percussive stunning in compliance with European animal welfare regulation (Council Regulation [EC] no. 1099/2009). At all times and sites, at least one person in possession of the French habilitation for experimentation with aquatic organisms was present (authors S.C. and C.F. and field technicians) and supervised less experienced staff. The spleen and gills of asymptomatic fish with no gross lesions were sampled. The freshly cut surface of the organ was printed and streaked onto a petri dish with FLP agar. Eggs were pooled and rolled over the surface of the FLP agar. Agar plates were stored at room temperature until arrival to the laboratory (8 to 24 h after sample collection).
Bacterial isolation and identification.
The previously streaked FLP agar plates were placed at 17°C for 48 to 72 hours (38). Colonies (up to five per organ) were picked from each plate and individually subcultured. The resulting colonies were selected after a preliminary phenotypic and biochemical characterization, based on Gram-negative, catalase-positive, and flexirubin pigment-positive test results (39). Two F. psychrophilum reference strains were used as positive controls (JIP 02/86 and LNPAA PO1/88) and were grown under the same conditions (17°C for 48 to 72 hours on FLP agar medium). Genomic DNA was extracted and purified using a Wizard genomic DNA purification kit (Promega, France). Rapid molecular identification was carried out following a duplex PCR described in a previous study (23).
PFGE protocol.
Genomic DNA samples of confirmed F. psychrophilum isolates were prepared in agarose plugs from pure cultures. Briefly, strains were grown for 72 h at 17°C on FLP plates. Three or four colonies were resuspended in FLP broth and incubated under shaking conditions for 48 h at 17°C. Then, the culture was centrifuged for 5 min at 5,000 × g and the pellet suspended in about 2 ml of cell suspension buffer (Tris 100 mM and EDTA 100 mM [pH 8.0]) to obtain an optical density at 625 nm (OD625) of 1.2 to 1.8. A total of 20 μl of 20 mg/ml proteinase K (BioSolve) was added to 400 μl of the bacterial suspension subsequently mixed with 400 μl of 2.0% agarose (pulsed field certified agarose; Bio-Rad) in Tris-EDTA (TE) buffer (10 mM Tris and 1 mM EDTA [pH 8.0]) and 1.0% SDS (sodium dodecyl sulfate; Eurobio) at 55°C. A total of 100 μl of the mix was shed in a plug mold. After solidification, agarose plugs were treated with lysis buffer (50 mM Tris, 50 mM EDTA, and 1.0% sarcosyl [pH 8.0]) and 25 μl of proteinase K for 3 h at 37°C under shaking conditions. The plugs were washed twice in sterile water for 15 min at 50°C and four times in TE buffer for 15 min at 50°C. Plugs were stored in TE buffer at 4°C. Each plug was divided in two and only one part was digested with 40 U of SalI (New England BioLabs) at 37°C overnight. The F. psychrophilum reference strains LNPAA P01/88 and JIP 02/86 were prepared in the same way for each gel and used as a control. The migration was performed using a 1% agarose gel in 0.5× Tris-borate-EDTA (TBE) buffer at 14°C in a ChefDRIII apparatus (Bio-Rad) with an electric field of 6.0 V cm−1 and a 120° angle. Pulse times were 1 to 12 s for 18.5 h. A standard molecular weight ladder, MidRange II PFG markers (New England BioLabs), was added in triplicate to each gel for better gel comparisons. Gels were stained with ethidium bromide and visualized on a UV transilluminator.
Analysis of PFGE patterns.
The genetic analyses were performed using BioNumerics software (version 6.5; Applied Maths). Each gel was checked by the curve densitometric function for the presence or absence of bands. For each PFGE run, a clustering of patterns was performed using the unweighted pair group method with arithmetic mean (UPGMA) approach (as in reference 40) and the Dice similarity coefficient (41). The optimization was 1.5%, and the band position tolerance was 1.5%. According to the guidelines for interpreting chromosomal DNA restriction patterns produced by PFGE (42), patterns with ≥80% similarity were considered the same cluster of closely or possibly related isolates, and patterns with <80% similarity were considered to represent different (separate) clusters of unrelated isolates.
Multilocus sequence typing.
For MLST analysis, 31 F. psychrophilum isolates were selected according to their origin (same individual fish host [subsets α and β] or different individual fish hosts [subset γ]), and their relatedness was assessed by PFGE. Three subsets were defined as follows: α, 8 isolates originating from the same fish and showing >98% similarity (i.e., same pulsotype); β, 8 isolates originating from the same fish that belonged to different pulsotypes; and γ, 15 isolates retrieved from different fish, displaying various pulsotypes, and representing the 4 study farms. Detailed information about these 31 isolates is given in Table 6 (farm, fish weight and life stage, sampling date, and organ).
TABLE 6.
Set of F. psychrophilum isolates selected for diversity assessment by MLST
| Isolate | Farm | Fish identification | Life stage | Batch avg wt (g) | Organ | PFGE pulsotype | PFGE group (cluster/singleton) | Water temp (°C) | Sampling date | Subset |
|---|---|---|---|---|---|---|---|---|---|---|
| A138 | 2 | C-14 | Juvenile | 140.9 | Spleen | P17 | C1 | 10 | 04-2011 | α |
| A139 | ||||||||||
| A141 | ||||||||||
| A142 | ||||||||||
| A133 | Gills | |||||||||
| A145 | ||||||||||
| A146 | ||||||||||
| A147 | ||||||||||
| B65 | 4 | F-8 | Juvenile | 121.8 | Gills | P74 | C6 | 13 | 07-2011 | β |
| B66 | P48 | C5 | ||||||||
| B68 | Spleen | P85 | S8 | |||||||
| B95 | 4 | A-11 | Juvenile | 156.8 | Gills | P9 | C1 | 9 | 12-2011 | β |
| B97 | P90 | C9 | ||||||||
| B98 | Spleen | P97 | C12 | |||||||
| B99 | P84 | C7 | ||||||||
| B100 | P83 | C7 | ||||||||
| D3 | 1 | J-13 | Adult | 698.7 | Spleen | P53 | C6 | 7 | 03-2011 | γ |
| D4 | 1 | J-14 | Adult | 698.7 | Spleen | P40 | C3 | 7 | 03-2011 | γ |
| D6 | 1 | J-2 | Adult | 754.4 | Gills | P56 | C6 | 9 | 04-2011 | γ |
| A6 | 2 | A-Al9 | Fry | 0.3 | Gills | P6 | C1 | 9.5 | 03-2011 | γ |
| A24 | 2 | B-Tp2 | Juvenile | 4.8 | Spleen | P55 | C6 | 9.5 | 03-2011 | γ |
| A67 | 2 | D-P7 | Adult | 251.4 | Gills | P95 | C11 | 9.5 | 03-2011 | γ |
| A81 | 2 | B-1 | Juvenile | 9.4 | Gills | P36 | S5 | 10 | 04-2011 | γ |
| A88 | 2 | B-7 | Juvenile | 9.4 | Gills | P51 | C6 | 10 | 04-2011 | γ |
| A97 | 2 | B-12 | Juvenile | 9.4 | Gills | P46 | C5 | 10 | 04-2011 | γ |
| C31 | 3 | O-OLS2 | Egg | Egg | P70 | C6 | 12 | 05-2011 | γ | |
| C34 | 3 | H-15 | Juvenile | 16.5 | Gills | P70 | C6 | 12 | 05-2011 | γ |
| B2 | 4 | F-T1 | Juvenile | 67.7 | Spleen | P62 | C6 | 10 | 03-2011 | γ |
| B47 | 4 | F-T2 | Juvenile | 152.9 | Gills | P100 | S11 | 10 | 04-2011 | γ |
| B50 | 4 | F-T10 | Juvenile | 152.9 | Gills | P93 | C11 | 10 | 04-2011 | γ |
| B57 | 4 | G-P5 | Adult | 264.1 | Gills | P38 | C3 | 10 | 04-2011 | γ |
Seven housekeeping genes (trpB, gyrB, dnaK, fumC, murG, tuf, and atpA) were used for the MLST scheme as already described by Nicolas et al. (22) and optimized by Siekoula-Nguedia et al. (23). The F. psychrophilum reference strain JIP 02/86 was used as an amplification positive control. The PCR products were sequenced (LGC Genomics, Berlin, Germany) using M13 forward and reverse primers (23). Chromatograms were checked visually, and sequences were assembled using the Phred and Phrap programs (43, 44). The numbered allele types (ATs) were combined in order to define a sequence type (ST) using an in-house script (P. Nicolas, INRAE).
Population genetic analysis.
Gene diversity (H) was determined using the LIAN 3.5 software (http://guanine.evolbio.mpg.de/cgi-bin/lian/lian.cgi.pl) and was calculated as follows: H = [n/(n − 1)] (1 − pi2), in which n is the number of samples and pi is the relative frequency of the ith allele. The eBURST v3 software was used to assign STs into clonal complexes (CCs) (45). These CCs were statistically assessed by the bootstrap method (n = 1,000) with both default settings (a minimum of six alleles shared) and relaxed settings (a minimum of five alleles shared). If not assigned into a CC, STs were classified as singletons. The split decomposition tree was obtained with Splitstree software (46).
Serotype identification by PCR.
All isolates that had been analyzed by both PFGE and MLST were characterized by the multiplex PCR-based serotyping scheme described by Rochat et al. (35). The reference strains LNPAPP 01/88 and JIP 02/86 were included as positive controls in the PCR assay (serotypes T1 and T0, respectively). This enabled us to further investigate the genetic variability within groups of related strains.
Supplementary Material
ACKNOWLEDGMENTS
We grateful to Mickaelle Larhantec and Isabelle Perray for their technical assistance, to the aquaculture veterinarians for their involvement, and to the fish farmers for their welcome and open access to their farms. We also thank the “Plateau Fédératif de Biologie Moléculaire” of Oniris for providing the equipment used to carry out the experiments and Jean-François Bernardet for critical reading of the manuscript.
The French “Agence Nationale de la Recherche” grant 07-GMGE supported the equipment dedicated to sequence treatments. C.S.-N. was supported by grants from the “Pays de la Loire” region, INRAE, and UMR BioEpAR.
Footnotes
Supplemental material is available online only.
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