Diversity and relative abundance of the bacterial pathogen, Flavobacterium spp., infecting reproductive ecotypes of kokanee salmon
© Lemay and Russello; licensee BioMed Central Ltd. 2014
Received: 29 July 2014
Accepted: 24 October 2014
Published: 4 November 2014
Understanding the distribution and abundance of pathogens can provide insight into the evolution and ecology of their host species. Previous research in kokanee, the freshwater form of sockeye salmon (Oncorhynchus nerka), found evidence that populations spawning in streams may experience a greater pathogen load compared with populations that spawn on beaches. In this study we tested for differences in the abundance and diversity of the gram-negative bacteria, Flavobacterium spp., infecting tissues of kokanee in both of these spawning habitats (streams and beaches). Molecular assays were carried out using primers designed to amplify a ~200 nucleotide region of the gene encoding the ATP synthase alpha subunit (AtpA) within the genus Flavobacterium. Using a combination of DNA sequencing and quantitative PCR (qPCR) we compared the diversity and relative abundance of Flavobacterium AtpA amplicons present in DNA extracted from tissue samples of kokanee collected from each spawning habitat.
We identified 10 Flavobacterium AtpA haplotypes among the tissues of stream-spawning kokanee and seven haplotypes among the tissues of beach-spawning kokanee, with only two haplotypes shared between spawning habitats. Haplotypes occurring in the same clade as F. psychrophilum were the most prevalent (92% of all reads, 60% of all haplotypes), and occurred in kokanee from both spawning habitats (streams and beaches). Subsequent qPCR assays did not find any significant difference in the relative abundance of Flavobacterium AtpA amplicons between samples from the different spawning habitats.
We confirmed the presence of Flavobacterium spp. in both spawning habitats and found weak evidence for increased Flavobacterium diversity in kokanee sampled from stream-spawning sites. However, the quantity of Flavobacterium DNA did not differ between spawning habitats. We recommend further study aimed at quantifying pathogen diversity and abundance in population-level samples of kokanee combined with environmental sampling to better understand the ecology of pathogen infection in this species.
KeywordsBacteria Bacterial coldwater disease Flavobacterium Pathogens Kokanee Sockeye salmon Oncorhynchus nerka
Pathogens can play an important role in the evolution of their hosts [1–3]. This can occur when variation in pathogen diversity over small spatial or temporal scales imposes divergent selection on populations of their host species [1, 4]. In salmonids, for example, genetic diversity associated with the major histocompatability complex can vary at micro-geographical scales [1, 5], reflecting local adaptation in response to heterogeneous pathogen regimes .
Kokanee, the freshwater form of sockeye salmon (Oncorhynchus nerka), occurs as two reproductive ecotypes, which differ in their choice of spawning habitat (streams vs. beaches) [6, 7]. Previous research found that the abundance of cDNA from several pathogens (bacteria, fungi, and a parasitic flatworm) was greater in pooled-transcriptome samples from the stream-spawning ecotype compared with the beach-spawning ecotype in Okanagan Lake, British Columbia (BC), Canada . Moreover, a subsequent genomic scan of kokanee in four lakes across BC identified genes involved with pathogen resistance as being putatively under divergent selection between stream and beach-spawning kokanee . These data suggest that kokanee may experience asymmetrical pathogen infection between spawning environments, however the lack of information on pathogen diversity within each spawning habitat has precluded a direct test of this hypothesis.
In this study, we measured the diversity and abundance of the gram-negative bacteria, Flavobacterium sp., infecting Okanagan Lake kokanee from their two divergent spawning habitats (streams and beaches). Flavobacterium was chosen for this study because its abundance was highly correlated with ecotype in pooled transcriptome samples , and because several Flavobacterium species are associated with high levels of salmonid mortality , with devastating economic impacts [11–13].
This study focused on Okanagan Lake, which is a long (135-km) and narrow (<5 km) post-glacial lake located in the southern interior of British Columbia, Canada. The large size of the lake (~350 km2) supports several spawning populations of both reproductive ecotypes [14, 15]. Current estimates suggest that there are ~200,000 spawning adult kokanee in Okanagan Lake. Kokanee are semelparous and philopatric, with the majority of adults spawning at an age of three years . Beach spawning has been observed at most undeveloped areas of the shoreline. Stream-spawning is currently monitored at 18 tributaries, of which 60% of stream spawning occurs at a single location (Mission Creek) . Stream and beach-spawning habitats experience differences in many abiotic factors such as seasonal temperature, turbidity, and rate of water-flow, which may affect the diversity of pathogens present in the two environments.
Samples used for each assay
1. Flavobacterium abundance:
2. Flavobacterium diversity:
Number of kokanee sampled
Number of colonies sequenced (number of haplotypes observed)
Flavobacterium DNA was isolated from each kokanee DNA sample using primers designed to amplify a ~200 nucleotide region of the gene encoding the ATP synthase alpha subunit (AtpA) of all species within the genus Flavobacterium [Fspp1_F: 5′-TTRTTAAGAAGACCACCRGG-3′, Fspp1_R: 5′- GGRATATATGCAGAAACGTCACC-3′]. This region was chosen because AtpA is part of a panel of genes used for strain identification in the species Flavobacterium psychrophilum, allowing comparisons with previously published sequence data.
Each PCR contained 2 μl DNA, 2.5 μl 10X PCR buffer, 2.5 μl dNTPs (2 mM), 1.0 μl forward primer (10 μM), 1.0 μl reverse primer (10 μM), and AmpliTaq Gold polymerase (0.5 units, Applied Biosystems) in a 25 μl total volume. Touchdown PCR protocol  was used with initial denaturation of 94°C for 10 minutes, then 10 cycles at 94°C for 30 seconds, 60°C for 30 seconds, 72°C for 60 seconds, with the annealing step decreasing by 1°C per cycle to 50°C. The annealing temperature was maintained at 50°C for an additional 30 cycles, followed by extension at 72°C for 2 minutes. All PCR products were purified using a Qiagen MinElute kit, diluted to 4 ng/μl, and ligated overnight at 4°C using the pGEM®-T Easy Vector System (Promega). Transformed cells were added to plates containing 100 μg/ml ampicillin, 0.5 mM IPTG, and 80 μg/ml X-Gal, and incubated for 16-20 hours at 37°C. White colonies were then boiled at 100°C for 10 minutes in 100 μl of TE buffer. We amplified cloned inserts from 100 colonies (50 from each ecotype) using T7 and Sp6 primers (Promega). Each PCR contained 1 μl colony boil, 1.25 μl 10X PCR buffer, 1.25 μl dNTPs (2 mM), 0.5 μl each primer (10 μM), and KAPATaq polymerase (0.5 units; KAPA Biosystems) in a 13.5 μl total volume. Each PCR had an initial denaturation of 94°C for 2 minutes, followed by 35 cycles at 94°C for 30 seconds, 50°C for 30 seconds, 72°C for 30 seconds, with a final extension at 72°C for 2 minutes. Sequencing was carried out in one direction using Sp6 on an Applied Biosystems 3130XL. Raw sequences were edited using Sequencher v. 5; five sequences were discarded from further analyses due to low quality and ambiguous bases.
A phylogenetic approach was then used to quantify the diversity of AtpA haplotypes among the remaining 95 sequences (47 stream, 48 beach; Additional file 1). We retained all distinct haplotypes irrespective of the number of reads matching the sequence. Unique haplotypes from each spawning habitat (streams and beaches) were unambiguously aligned with the AtpA region from the published genomes of nine Flavobacterium species (F. aquatile [GenBank: JX25684.1], F. branchiophilum [GenBank: NC016001.1], F. chungnamense [GenBank: JX256869.1], F. columnare [GenBank: CP003222.2], F. frigidarium [GenBank: HM443893.1], F. indicum [GenBank: NC017025.1], F. johnsoniae [GenBank; NC009441.1], F. koreense [GenBank: JX356867.1], F. psychrophilum [GenBank: NC009613.1]) using MUSCLE as implemented in Geneious v.6.1 (Biomatters). This alignment was then used to generate an unrooted neighbor-joining tree in Geneious v.6.1 (Biomatters); 1000 Bootstrap replicates were performed with a 50% support threshold.
Quantitative PCR (qPCR) was used to measure the relative abundance of Flavobacterium spp. present in kokanee sampled from Okanagan Lake. This assay was carried out using DNA extracted from operculum tissue of spawning adult kokanee collected in 2007 (n = 48) and 2010 (n = 48). All kokanee samples had been collected as part of previous research , and included samples from both ecotypes at seven different locations in Okanagan Lake (Table 1).
The total quantity of extracted DNA (fish and pathogen) was first determined for each sample using the Quant-iT™ Pico Green ds DNA Assay Kit (Invitrogen) run on a ViiA7 real-time PCR machine (Life Technologies). Quantitative PCR was carried out using the same AtpA primers described above to quantify the pathogen component of each DNA sample using an absolute quantification protocol on a ViiA7 real-time PCR machine (Life Technologies). Using the same primers as the assay for Flavobacterium diversity allows us to quantify the abundance of all documented haplotypes. To construct the standard curve we used F. psychrophilum DNA of known strain and concentration [Strain: CIP103534(T), isolated from coho salmon, Oncorhynchus kisutch]. For increased precision, three replicates of each concentration in the standard curve were used. Each PCR contained 1 μl of DNA template, 0.5 μl of 1 μM Fspp1_F forward primer, 0.5 μl of 10 μM Fspp2_R reverse primer, and 5.0 μl of Fast SYBR® Green Master Mix (Applied Biosystems) in a total volume of 10 μl. A two-step cycling protocol was carried out with an initial denaturation of 94°C for 2 minutes, followed by 55 cycles at 94°C for 30 seconds and 60°C for 30 seconds. A melt curve stage was added to the end of the protocol beginning at 60°C and increasing to a final temperature of 98°C.
For each individual kokanee, the inferred quantity of Flavobacterium spp. amplicons was normalized to the total DNA template concentration of the sample in order to derive a measure of pathogen infection per unit of kokanee DNA . Deviations from normality in this response variable (ng of Flavobacterium DNA per ng of kokanee DNA) precluded the use of parametric statistics; instead we tested for differences in Flavobacterium abundance between ecotypes from each sampling year using non-parametric Kruskal-Wallis tests implemented in R version 3.0.1 . In addition, results of the qPCR assay were visualized using box plots generated in R using the default parameters for generating whisker lengths and designating outliers.
Results and discussion
We tested for differences in the abundance and diversity of the salmonid pathogen, Flavobacterium spp., infecting kokanee salmon from two different spawning habitats (streams and beaches). Both of the molecular assays carried out in this study (DNA sequencing and qPCR) found evidence for the presence of Flavobacterium from all study-sites and both spawning environments in Okanagan Lake.
The phylogenetic results provide preliminary evidence that there may be differences in the composition of Flavobacteria species/strains between the two spawning habitats, however the small sample size (3-4 kokanee per spawning habitat) severely limits our ability to draw definitive conclusions. For example the small sample sizes may skew the observed distribution of rare haplotypes. Yet, the relatively high diversity of Flavobacterium AtpA haplotypes observed in the tissue of only seven kokanee samples provides evidence that individuals may be infected by multiple strains and/or species of Flavobacterium, however the small size of the amplicon (~200 base pairs) precludes determination of species identity.
It would be highly informative for future research to sequence larger regions and additional genes in order to determine the identity of species present. Alternatively, the use of high-throughput methods for quantifying microbial community assemblages, such as 16 s rRNA gene sequencing , could be used to provide insight into the composition of bacterial communities inhabiting kokanee from each spawning habitat. This approach has been used to quantify microbial communities in a diversity of study systems including plants , animals [22, 23], and soils , and provides an effective method to test for differences in bacterial community structure. For example, in Atlantic salmon, Salmo salar, 16 s rRNA gene analysis was used to identify bacterial communities putatively associated with infectious amoebic gill disease .
In order to better understand the ecological interactions between kokanee and their bacterial pathogens, it would also be useful for future research to examine Flavobacterium diversity and abundance from environmental samples in the two habitats. While F. psychrophilum is both horizontally and vertically transmitted to new hosts [26, 27], it can also persist for long periods of time (300 days) without a host . Therefore, the compliment of pathogens infecting fish tissues may not be an accurate estimate of the total diversity and abundance present in each habitat.
Genes associated with immune response are often identified as candidate regions for local adaptation in salmonids [29–33], including in kokanee , and it has been shown that patterns of divergence at these genes may result from localized differences in pathogen diversity across fine spatial or temporal scales [34–37]. While this current study only found weak evidence for differences in pathogen diversity in kokanee collected from different spawning habitats (streams and beaches), these results warrant further study. Future research aimed at quantifying pathogen diversity and abundance in population-level samples of kokanee combined with environmental sampling is needed to better understand the ecology of pathogen infection in this system.
Availability of supporting data
The data sets supporting the results of this article are included within the additional files.
We thank Eric Duchaud (French National Institute for Agricultural Research) for donating DNA standards and providing feedback on an earlier version of this manuscript. We also thank Katy Hind for assistance with the data analysis. This work was funded by Genome British Columbia (SOF130 to MR); ML was partially funded by an NSERC Postgraduate Fellowship.
- Fraser DJ, Weir LK, Bernatchez L, Hansen MM, Taylor EB: Extent and scale of local adaptation in salmonid fishes: review and meta-analysis. Heredity. 2011, 106 (3): 404-420. 10.1038/hdy.2010.167.PubMedPubMed CentralView ArticleGoogle Scholar
- Dionne M, Miller KM, Dodson JJ, Caron F, Bernatchez L: Clinal variation in MHC diversity with temperature: Evidence for the role of host-pathogen interaction on local adaptation in Atlantic salmon. Evolution. 2007, 61 (9): 2154-2164. 10.1111/j.1558-5646.2007.00178.x.PubMedView ArticleGoogle Scholar
- Eizaguirre C, Lenz TL, Sommerfeld RD, Harrod C, Kalbe M, Milinski M: Parasite diversity, patterns of MHC II variation and olfactory based mate choice in diverging three-spined stickleback ecotypes. Evol Ecol. 2011, 25 (3): 605-622. 10.1007/s10682-010-9424-z.View ArticleGoogle Scholar
- Matthews B, Harmon LJ, M’Gonigle L, Marchinko KB, Schaschl H: Sympatric and Allopatric Divergence of MHC Genes in Threespine Stickleback. Plos One. 2010, 5 (6): e10948-10.1371/journal.pone.0010948.PubMedPubMed CentralView ArticleGoogle Scholar
- Miller KM, Kaukinen KH, Beacham TD, Withler RE: Geographical heterogeneity in natural selection on an MHC locus in sockeye salmon. Genetica. 2001, 111: 237-257. 10.1023/A:1013716020351.PubMedView ArticleGoogle Scholar
- Taylor EB, Harvey S, Pollard S, Volpe J: Postglacial genetic differentiation of reproductive ecotypes of kokanee Oncorhynchus nerka in Okanagan Lake, British Columbia. Mol Ecol. 1997, 6 (6): 503-517. 10.1046/j.1365-294X.1997.00213.x.PubMedView ArticleGoogle Scholar
- Russello MA, Kirk SL, Frazer K, Askey P: Detection of outlier loci and their utility for fisheries management. Evol Appl. 2012, 5: 39-52. 10.1111/j.1752-4571.2011.00206.x.PubMedPubMed CentralView ArticleGoogle Scholar
- Lemay MA, Donnelly DJ, Russello MA: Transcriptome-wide comparison of sequence variation in divergent ecotypes of kokanee salmon. BMC Genomics. 2013, 14 (308): 308-PubMedPubMed CentralView ArticleGoogle Scholar
- Frazer KK, Russello MA: Lack of parallel genetic patterns underlying the repeated ecological divergence of beach and stream spawning kokanee salmon. J Evol Biol. 2013, 12: 2606-2621.View ArticleGoogle Scholar
- Nematollahi A, Decostere A, Pasmans F, Haesebrouck F: Flavobacterium psychrophilum infections in salmonid fish. J Fish Dis. 2003, 26 (10): 563-574. 10.1046/j.1365-2761.2003.00488.x.PubMedView ArticleGoogle Scholar
- Apablaza P, Loland AD, Brevik OJ, Ilardi P, Battaglia J, Nylund A: Genetic variation among Flavobacterium psychrophilum isolates from wild and farmed salmonids in Norway and Chile. J Appl Microbiol. 2013, 114 (4): 934-946. 10.1111/jam.12121.PubMedView ArticleGoogle Scholar
- Madetoja J, Dalsgaard I, Wiklund T: Occurrence of Flavobacterium psychrophilum in fish-farming environments. Dis Aquat Org. 2002, 52 (2): 109-118.View ArticleGoogle Scholar
- Vallejo RL, Wiens GD, Rexroad CE, Welch TJ, Evenhuis JP, Leeds TD, Janss LLG, Palti Y: Evidence of major genes affecting resistance to bacterial cold water disease in rainbow trout using Bayesian methods of segregation analysis. J Anim Sci. 2010, 88 (12): 3814-3832. 10.2527/jas.2010-2951.PubMedView ArticleGoogle Scholar
- Taylor EB, Kuiper A, Troffe PM, Hoysak D, Pollard S: Variation in developmental biology and microsatellite DNA in reproductive ecotypes of kokanee, Oncorhynchus nerka: implications for declining populations in a large British Columbia lake. Conserv Genet. 2000, 1: 231-249. 10.1023/A:1011553705015.View ArticleGoogle Scholar
- Askey PJ, Johnston NT: Self-regulation of the Okanagan Lake kokanee recreational fishery: Dynamic angler effort response to varying fish abundance and productivity. N Am J Fish Manag. 2013, 33 (5): 926-939. 10.1080/02755947.2013.818082.View ArticleGoogle Scholar
- Nicolas P, Mondot S, Achaz G, Bouchenot C, Bernardet JF, Duchaud E: Population structure of the fish-pathogenic bacterium Flavobacterium psychrophilum. Appl Environ Microbiol. 2008, 74 (12): 3702-3709. 10.1128/AEM.00244-08.PubMedPubMed CentralView ArticleGoogle Scholar
- Korbie DJ, Mattick JS: Touchdown PCR for increased specificity and sensitivity in PCR amplification. Nat Protoc. 2008, 3 (9): 1452-1456. 10.1038/nprot.2008.133.PubMedView ArticleGoogle Scholar
- Percell MK, Getchell RG, McClure CA, Garver KA: Quantitative polymerase chain reaction (PCR) for detection of aquatic animal pathogens in a diagnostic laboratory setting. J Aquat Anim Health. 2011, 23 (3): 148-161. 10.1080/08997659.2011.620217.View ArticleGoogle Scholar
- R Development Core Team: R: A language and environment for statistical computing. 2011, Vienna, Austria: R Foundation for Statistical ComputingGoogle Scholar
- Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R: Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. Isme J. 2012, 6 (8): 1621-1624. 10.1038/ismej.2012.8.PubMedPubMed CentralView ArticleGoogle Scholar
- Aleklett K, Hart M, Shade A: The microbial ecology of flowers: an emerging frontier in phyllosphere research. Botany. 2014, 92 (4): 14-View ArticleGoogle Scholar
- Kueneman JG, Parfrey LW, Woodhams DC, Archer HM, Knight R, McKenzie VJ: The amphibian skin-associated microbiome across species, space and life history stages. Mol Ecol. 2014, 23 (6): 1238-1250. 10.1111/mec.12510.PubMedView ArticleGoogle Scholar
- Delsuc F, Metcalf JL, Parfrey LW, Song SJ, Gonzalez A, Knight R: Convergence of gut microbiomes in myrmecophagous mammals. Mol Ecol. 2014, 23 (6): 1301-1317. 10.1111/mec.12501.PubMedView ArticleGoogle Scholar
- Fierer N, Leff JW, Adams BJ, Nielsen UN, Bates ST, Lauber CL, Owens S, Gilbert JA, Wall DH, Caporaso JG: Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc Natl Acad Sci U S A. 2012, 109 (52): 21390-21395. 10.1073/pnas.1215210110.PubMedPubMed CentralView ArticleGoogle Scholar
- Bowman JP, Nowak B: Salmonid gill bacteria and their relationship to amoebic gill disease. J Fish Dis. 2004, 27 (8): 483-492. 10.1111/j.1365-2761.2004.00569.x.PubMedView ArticleGoogle Scholar
- Brown LL, Cox WT, Levine RP: Evidence that the causal agent of bacterial cold-water disease Flavobacterium psychrophilum is transmitted within salmonid eggs. Dis Aquat Org. 1997, 29 (3): 213-218.View ArticleGoogle Scholar
- Madetoja J, Nyman P, Wiklund T: Flavobacterium psychrophilum, invasion into and shedding by rainbow trout Oncorhynchus mykiss. Dis Aquat Org. 2000, 43 (1): 27-38.PubMedView ArticleGoogle Scholar
- Madetoja J, Nystedt S, Wiklund T: Survival and virulence of Flavobacterium psychrophilum in water microcosms. FEMS Microbiol Ecol. 2003, 43 (2): 217-223. 10.1111/j.1574-6941.2003.tb01061.x.PubMedView ArticleGoogle Scholar
- McGlauflin MT, Schindler DE, Seeb LW, Smith CT, Habicht C, Seeb JE: Spawning habitat and geography influence population structure and juvenile migration timing of sockeye salmon in the Wood River Lakes, Alaska. Trans Am Fish Soc. 2011, 140 (3): 763-782. 10.1080/00028487.2011.584495.View ArticleGoogle Scholar
- Ackerman MW, Habicht C, Seeb LW: Single-nucleotide polymorphisms (SNPs) under diversifying selection provide increased accuracy and precision in mixed-stock analyses of sockeye salmon from the Copper River, Alaska. Trans Am Fish Soc. 2011, 140 (3): 865-881. 10.1080/00028487.2011.588137.View ArticleGoogle Scholar
- Gomez-Uchida DG-UD, Seeb JE, Smith MJ, Habicht C, Quinn TP, Seeb LW: Single nucleotide polymorphisms unravel hierarchical divergence and signatures of selection among Alaskan sockeye salmon (Oncorhynchus nerka) populations. BMC Evol Biol. 2011, 11: 48-10.1186/1471-2148-11-48.PubMedPubMed CentralView ArticleGoogle Scholar
- Creelman EK, Hauser L, Simmons RK, Templin WD, Seeb LW: Temporal and geographic genetic divergence: Characterizing sockeye salmon populations in the Chignik watershed, Alaska, using single-nucleotide polymorphisms. Trans Am Fish Soc. 2011, 140 (3): 749-762. 10.1080/00028487.2011.584494.View ArticleGoogle Scholar
- Beacham TD, McIntosh B, Wallace C: A comparison of stock and individual identification for sockeye salmon (Oncorhynchus nerka) in British Columbia provided by microsatellites and single nucleotide polymorphisms. Can J Fish Aquat Sci. 2010, 67 (8): 1274-1290. 10.1139/F10-061.View ArticleGoogle Scholar
- Cohen S, Tirindelli J, Gomez-Chiarri M, Nacci D: Functional implications of major histocompatibility (MH) variation using estuarine fish populations. Integr Comp Biol. 2006, 46 (6): 1016-1029. 10.1093/icb/icl044.PubMedView ArticleGoogle Scholar
- Dionne M, Miller KM, Dodson JJ, Bernatchez L: MHC standing genetic variation and pathogen resistance in wild Atlantic salmon. Philos Trans R Soc Lond B Biol Sci. 2009, 364 (1523): 1555-1565. 10.1098/rstb.2009.0011.PubMedPubMed CentralView ArticleGoogle Scholar
- Eizaguirre C, Lenz TL, Kalbe M, Milinski M: Divergent selection on locally adapted major histocompatibility complex immune genes experimentally proven in the field. Ecol Lett. 2012, 15 (7): 723-731. 10.1111/j.1461-0248.2012.01791.x.PubMedPubMed CentralView ArticleGoogle Scholar
- Bernatchez L, Landry C: MHC studies in nonmodel vertebrates: what have we learned about natural selection in 15 years?. J Evol Biol. 2003, 16 (3): 363-377. 10.1046/j.1420-9101.2003.00531.x.PubMedView ArticleGoogle Scholar
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