Introduction

Streptococcus species is gram-positive coccus that causes streptococcosis (septicemia disease) affecting both captive and wild populations of fresh water and marine fish species throughout the world. First Streptococcal infections in fish were reported to rainbow trout (Oncorhynchus mykiss) in Japan in 1958 (Hoshina et al. 1958). Fish farming one of major growing industry, facing problems of controlling streptococcal infection in cultured fish populations (Agnew and Barnes 2007; Austin and Austin 2007; Baeck et al. 2006; Shoemaker et al. 2001; Toranzo et al. 2005). Various bacterial agents caused streptococcosis such as Lactococcus garvieae, Streptococcus parauberis, Streptococcus iniae, Streptococcus agalactiae and Streptococcus difficilis (Nho et al. 2009; Toranzo et al. 2005). Out of above, two main etiologic agents S. iniae and S. parauberis found predominantly regardless of geographical regions.

Streptococcus parauberis was first reported from turbot (Scophthalmus maximus) cultured in Spain (Domeénech et al. 1996). Important fish species infected by S. parauberis were Olive flounder, Rainbow trout, cultured Turbot and Hybrid striped bass (Domeénech et al. 1996; Hoshina et al. 1958; Shoemaker et al. 2001). Apart from fish, S. parauberis also infect the dairy cow (Williams et al. 1990).

Another bacteria S. iniae has been also associated with disease outbreaks of different freshwater and marine fish species (Agnew and Barnes 2007). It is first isolated in 1976 from a subcutaneous abscess of a captive freshwater dolphin Inia geoffrensis (Pier and Madin 1976). It infects various fish species like, hybrid striped bass, Nile tilapia, hybrid tilapia, rainbow trout, red drum, rabbitfish, sea bass, flounder, barramundi and other fishes (Agnew and Barnes 2007; Al-Harbi 2011; Cheng et al. 2010; Klesius et al. 2006; Zlotkin et al. 1998). In addition to fish, S. iniae is also known to be an opportunistic human pathogen, which is threat to public health by causing bacteremic cellulitis, meningitis, endocarditis, and septic arthritis (Agnew and Barnes 2007; Al-Harbi 2011; Facklam et al. 2005; Lau et al. 2006; Sun et al. 2007; Weinstein et al. 1997). Both the bacterial agents showed that complex clinical symptoms during disease, which also vary with fish species (Table 1). Phylogeographically, S. iniae and S. parauberis were present in all over continents (Americas, Asia, Europe, Australia and Africa). The particulars of both bacterial agents (fish species, clinical symptoms and geographical region) were given in Table 1. The identification of bacterial infection was always challenging because of variation on phenotype characteristics due to effect of ecology, environment and host itself. Currently, there were several detection methods available for proper diagnostic and identification for S. iniae and S. parauberis. These detection methodologies varies from biochemical, molecular to immunological categories. The biochemical methods were depending upon phenotype characteristics of species and strains of bacteria and varied from plate cultivation, biochemical techniques, enzyme reactions, phenotypic analysis and whole cell fatty acid analysis (Bosshard et al. 2006; Cheng et al. 2010; Dodson et al. 1999; Klesius et al. 2006; Shoemaker et al. 2000). However, above techniques were time-consuming, cross reactive and pass through various downstream challenges like absence of proper-catalogued database for comparison, mixed nature of aquaculture environment, fewer amounts of biological samples or some time unknown tissue locations of infectious agents, which always make the decision difficult (Klesius et al. 2006). In molecular methodologies, candidate gene sequencing method is very appropriate for diagnosis and identification among bacterial isolates (Goh et al. 1998; Petti 2007; Poyart et al. 1998). Moreover, 16S rRNA gene sequencing method used preferable for over other candidate gene methods (Al-Harbi 2011; Austin and Austin 2007). Study shows that, 16S rDNA sequencing has become the reference method for bacterial taxonomy and identification due to its presence in almost all bacteria, relatively short of size (approximately ~1500 bp) as well as conserved in nature (Baker et al. 2003; Janda and Abbott 2007; Petti et al. 2005; Van de Peer et al. 1996). It also seems to be of interest in bacteria that remained unidentified or mis-identified by phenotypic methods (Drancourt et al. 2000; Petti et al. 2005). There are well defined Public database and software packages (GenBank, Nucleotide Sequence Database at European Molecular Biology Laboratory, DNA Data bank of Japan), Ribosomal Database project (RDP II), SmartGene IDNS, MicroSeq and Ribosomal Differentiation of Medical Microorganisms (RI-DOM) available for rapid phylogenetically analysis, due to vast number of bacterial 16S rDNA sequences deposited regularly (Bosshard et al. 2006; Woo et al. 2008; Maidak et al. 2000; Cole et al. 2007; Patel et al. 2000; Harmsen et al. 2003). The databases of RDP-II and SmartGene IDNS contain sequences downloaded from GenBank, whereas all sequences in the databases of RIDOM and MicroSeq were obtained by sequencing the 16S rDNA genes of bacterial strains of culture collections (Woo et al. 2008). Although, 16S rRNA sequencing method is not full proof of diagnosis due to various limitations attached to it, but many amendments and recommendations make it always preferential choice over other traditional methodologies (Drancourt et al. 2000; Mignard and Flandrois 2006; Stackebrandt and Goebel 1994).

Table 1 Streptoccocus bacterial agents and detail information of affected fishes, locations, host and clinical criteria with references
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Importantly, the existence of different types of Streptococcus species and strains of S. iniae and S. parauberis emphasizes the difficulties of definitive identification based on phenotypic traits alone (Fig. 1; Table 2). Continuously growing fish farming via uncontrolled exchange of fishes across various countries, creates problem of controlling various infections, which not only affect the health of human beings but also impart negative on economy (Shoemaker et al. 2000; Toranzo et al. 2005). Presently aquaculture is one of big industry, adopting strategies for maximum economic benefit with the culture of huge numbers of maximum varieties of fishes in bigger culture system (artificial or natural conditions). However, due to various risk factors, fishes were always facing chances of streptococcal infection, so there is urgent requirement to develop cheap and rapid method which helps in monitoring even at large sample size, regardless of any biological materials in any mixed clinical phenotype at first instance. The objective of this study was to review the use of 16S rDNA sequences to develop a rapid and cheapest method to detect and identify S. iniae and S. parauberis, in aquaculture industry thereby providing an improved diagnostic technique for this major fish pathogen.

Fig. 1
figure 1

Phylogeography study of bacterial agents (Streptococcus iniae and Streptococcus parauberis) of streptococcal diseases. Red color circle from 1 to 34 represent 34 strains of S. iniae and blue color square from 35 to 61 represents 27 strains of S. parauberis

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Table 2 Data on 34 strains of Streptococcus iniae and 27 strains of Streptococcus parauberis studied for phylogenetic and phylogeography analysis
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Materials and methods

Streptococcus iniae and Streptococcus parauberis isolates and geographical distribution

A total 61 bacterial strain (34 S. iniae and 27 S. parauberis) were selected from NCBI database belonging to various geographical regions of wormld (Table 2). The phylogeography analysis demonstrate bacterial distributions in the entire continent of earth (Table 2; Fig. 1).

Multiple sequence alignment and identification of variable and conserved regions

A total 61 bacterial strain (34 S. iniae and 27 S. parauberis) sequences were downloading from NCBI database. These sequences were aligned in BIOEDIT to find out the variation in sequences. We used BLAST (Basic Local Alignment Search Tool) searches in GenBank database for multiple sequence alignment of 61 strains of S. iniae and S. parauberis, and found the most hyper-variable region in 16S rRNA gene (Supplementary Fig. 1).

Phylogenetic analysis

Construction of a phylogenetic tree were performed using MEGA6 program via FASTA format (Tamura et al. 2013). The phylogenetic trees of S. iniae and S. parauberis together and separately constructed on the basis of Neighbor-joining method. Bootstrap evaluation of the branching patterns was analyzed with 1000 replications. The phylogenetic trees of S. iniae (from ID 1 to 34; red star mark) and S. parauberis (from ID 35 to 61; blue star mark) demonstrated in Fig. 2.

Fig. 2
figure 2

Phylogenetic analysis of total 61 bacterial strains of Streptococcus iniae and Streptococcus parauberis. Red color stars represent 34 strains of S. Iniae and blue color stars represent 27 strains of S. parauberis

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Primer design

Universal primer designed to be complementary to the conserved regions of the groups (61 bacterial strains) present in Table 2 (Fig. 3a, b; Supplementary Fig. 1). The transcripts were assessed by PCR using the primer sets of: 5′-ACCTCATAGCGGGGGATAAC-3′ and 5′-CGATCCGAAAACCTTCTTCA-3′.

Fig. 3
figure 3

a Structure of 16S rRNA gene under analysis (conserved and variable regions were indicated). Figure highlighted the amplified region of 302 base pair in 16SrRNA gene. b Schematic representation of conserved and variable regions and forward and reverse primer binding sites of 16S rRNA gene. Three representative strains of S. Iniae and S. parauberis were respectively selected to demonstrate the blue box (primer binding region) and red box (variable region of S. parauberis) in the amplified region of gene

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Streptococcal bacterial strain assessment

The two bacterial strains of S. iniae (SI-BS9) and S. parauberis (SPOF3K) were investigated for validation of primers. These two strains were obtained from microbiology department of Pusan National University, Busan, Korea. Genomic DNA (gDNA) extraction was conducted using the KIT (Qiagen) and primer pairs were tested against gDNA extracted from above two strains.

Primers were validated for temperature and concentration and standerised at annealing temperatures of between 54 and 58 °C. Cycling parameters included initial denaturing for 3 min at 95 °C; 35 cycles of 1 min at 94 °C, 1 min at 57 °C and 2 min at 72 °C. The amplification size is 302 base pair. A single and sharp peak was detected in each primer pair, which indicates that the primers amplify one specific product in PCR (Fig. 4a–d). No dimers derived from primer sets were detected. Further, PCR products were analyzed quantitatively using the Image-J program (Fig. 4b, d) and demonstrate the quality of primer set.

Fig. 4
figure 4

a PCR amplification of Streptococcus iniae genetic material (gDNA) with the universal primer at concentration from 1, 0.1, 0.05, 0.01, 0.005, 0.001, 0.0005, 0.0001, 0.00001 to 0 ng respectively, b PCR products were analyzed quantitatively using the Image-J program. The X-axis of the bar graph indicates concentrate of Streptococcus iniae gDNA samples and the Y-axis of the bar graph indicates the relative amplification levels. c PCR amplification of Streptococcus parauberis genetic material (gDNA) with the universal primer at concentration from 1, 0.1, 0.05, 0.01, 0.005, 0.001, 0.0005, 0.0001, 0.00001 to 0 ng respectively, d PCR products were analyzed quantitatively using the Image-J program. The X-axis of the bar graph indicates concentrate of Streptococcus parauberis gDNA samples and the Y-axis of the bar graph indicates the relative amplification levels

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16S rDNA quantification by real time PCR

The gram positive Streptococcus bacterial strains S. iniae and S. parauberis was subjected to quantitative Real Time PCR assay (Supplementary Fig. 2A, B).

Sensitivity of primer

The PCR has shown that prime can easily detect S. iniae and S. parauberis at 1 picogram of DNA concentrations respectively (Fig. 4a–d). The quantitative Real time PCR has shown that prime can easily detect S. iniae and S. parauberis at 0.1 pg of DNA concentrations respectively (Supplementary Fig. 2A, B).

Results and discussion

We have designed universal primer for the most variable region of 16S rRNA gene, of Streptococcus species (iniae and parabauris). Since, this primer was designed on the basis of 16S rDNA sequence variation information about all geographically important 61 strains, so it may act as effective “universal primer” which can be used on worldwide strains for diagnosis and identification purpose. The geographical representation of strains highlighted the importance of study for making single diagnosis marker for cosmopolitan S. iniae and S. parauberis bacterial agents (Table 2; Figs. 1, 2). Many study shows that genetic variations in any strains arise from gene mutations, insertions, deletions and/or genetic noise. These variations may reflect an evolutionary trend or may suggest that there is a relationship between serotype and virulence. So, our universal primer will be able to bring out the information of variation in various strains or even in new emerging strains arises due to the course of evolution as it is specifically designed for geographically distinct strains of S. iniae and S. parauberis (Fig. 1; Table 2). Another uniqueness of universal primer was its short product size which can be sequenced fast and cheap way. One of the benefit of choosing the strain-specific conserved gene (16S rRNA) over other candidate genes is thought to its representation for the physiological and virulence properties of an organism. This study will also be helpful for understanding evolutionary relationships and disease epidemiology like other earlier studies (Dobrindt and Hacker 2001; Wren 2000). Additional benefit of this primer is its sensitivity at a low amount of host DNA (1 and 0.01 pg of gDNA via PCR and Real Time PCR respectively) (Fig. 4a–d; Supplementary Fig. 2A, B). Comparison of various earlier important study of 16S rRNA gene primers based on bacterial agents, product size, biological experiment, suitability and cost effectiveness shows an important diagnostic and identification aspects of our study (Table 3). The universal primer may be able to amplify streptococcal bacterial species or strains, geographically presented in any part of the world so, caution should be taken while used. Various epidemiology studies suggest the presence of specific clinical phenotype in specific geographical regions in specific fishes, infected with S. iniae and S. parauberis diseases (Table 1). That’s why, firstly we have to notice previous data onto incidence of S. iniae and S. parauberis disease, in specific fishes and regions then apply the diagnosis with universal primer. The positive result itself not gives guarantee of bacterial infection (S. iniae and S. parauberis) but actually indicate the presence of specific variation in other bacterial species too. So, above result should be taken together with other epidemiological parameters for judging the possibilities of streptococcal infections (S. iniae and S. parauberis) in the fishes. For this reason, we have developed a proper parameter and algorithm for proper diagnosis on the basis of our universal primer (Fig. 5a, b).

Table 3 Comparison of various important study of 16S rRNA gene primers based on bacterial agents product size, biological experiment, their suitability and cost effectiveness with references
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Fig. 5
figure 5

a Algorithm for the identification of streptococcal diseases caused by S. iniae and S. parauberis. b Effective and appropriate control strategy for the streptococcal diseases caused by S. iniae and S. parauberis. Effective control strategy involved many steps and finally dependent on appropriate management decision

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Present challenges in diagnosis of Streptococcus

Fishes were always on risk for acquiring Streptococcus infections, which were sometimes face problems of identification with clinical laboratories due to under-diagnosis or un-identified or as a mis-identified (Lau et al. 2006). Evidence suggested that fish able to carry the pathogen asymptomatically (not show symptoms of disease), which may serve as a pathogen reservoir of future infections (Bromage et al. 1999; Eldar et al. 1995; Zlotkin et al. 1998). Moreover, standard bacteriological methods were not adequate for identification of many strains or sometimes even in new emerging fish pathogen. There were several reasons either it is not listed in the databases (RAPID Strep strip, VITEX systems, API 20E STREP, Rapid Strep 32, API CH 50, or the ATB Expression Systems) or downstream application failure for various reasons (Dodson et al. 1999; Facklam et al. 2005; Lau et al. 2006). Overall, making together diagnosis and identification more complicated. Comparative studies discuss in detail about various methodologies, their diagnosis capabilities and identified molecular methods as one of the important categories (Bosshard et al. 2006). Therefore, final detection cannot be determined without the support of molecular methods (genetic data).

Diagnosis based on molecular methods depends on pathogenic molecules related to candidate genes. Currently, it is difficult to show pathogenicity in all species of Streptococcus as it variate and depends on several factors which can change even from strain to strain in same species. Proper, understanding of pathogenicity of many species and strains were very important in molecular studies for deciding appropriate candidate gene as a diagnostic purpose. However, still research warranted to address this issue. Earlier research shows that pathogenicity of streptococcal species depends on the ability of bacteria to survive in host immune cells and induce their apoptosis by avoidance of host killing and for the establishment of infection (Woo and Park 2014; Zlotkin et al. 2003). In S. iniae pathogenicity depends on various virulence factors, which still needs to understand (Agnew and Barnes 2007; Zlotkin et al. 2003). In the molecular diagnosis, earlier studies of specific PCR on the other candidate genes like, 16S rRNA gene, the 16S–23S rRNA gene intergenic spacer region, the chaperonin HSP60 and the lactate oxidase gene (lctO) have been developed for rapid identification (Berridge et al. 1998; Goh et al. 1998; Mata et al. 2004; Zlotkin et al. 1998). However, candidate genes were varying from bacteria to bacteria, so this method has limitations in identification, whereas 16S rRNA gene make lead being conserved in nature. Although, diagnosis based on 16S rRNA gene also shows some difficulties in identification of bacteria such as the resolution of sequencing concerns sequence similarities or identity for the other Streptococcus groups (Janda and Abbott 2007; Petti 2007). A study reported that 16S rRNA gene sequence data not able to distinguish between recently diverged species (Janda and Abbott 2007).

Effective diagnosis of S. iniae and S. parauberis

A study shows that Fish industry results in an estimated loss of US $150 million annually (Shoemaker et al. 2001). So, immediate and rapid diagnosis of fish with our universal primer must alarm the fish producers at very advanced stage. Our universal primer diagnosis based on 16S rRNA may be used as both taxonomic purpose and conventional diagnostic purpose, as in addition to rapid, it is sensitive and specific to two main bacterial agents. Importantly, this universal primer can be used for multiplex PCR with another disease marker’s in mixed sample type. We have demonstrated in Fig. 3b, that there is internal variation (pink box) within primer range which can segregate the S. iniae and S. parauberis strains by multiplex. The protective measurement such as high quality of water, good health management system were considered as the best protective measures for disease control (Agnew and Barnes 2007). Continuous monitoring of phenotype of fish by random selection and immediate diagnosis of fish with a universal primer of 16S rRNA by matching the variation with the standard database will be the effective way of early diagnosis, which can lead to further appropriate control strategy (Fig. 5a).

Combined phylogenetic tree (S. iniae and S. parauberis) demonstrated the interrelation of both species in Fig. 2. Our phylogeography and phylogenetic study together show differentiation for geographical and serological strains, which provide useful information on epidemiology and evolutionary perspective of the S. iniae and S. parauberis strains. Recent advancement of gene sequencing and NGS technology help us to analyze single to huge biological samples in cost-effective way by restricting the target gDNA size (Table 3). In line of all above fact this study, offer new and rapid insights into S. iniae and S. parauberis specific potential diagnostic strategies through PCR, qPCR, Sequencing based on genetic analysis. Although, our in silico analysis demonstrated the validity of our universal primer in worldwide isolates (Supplementary Fig. 1), however large sample size indeed help us to validate more appropriately. Based on all above discussed fact and complications, our early diagnosis algorithm (Fig. 5b) will work as effective and proper tool for identification of S. iniae and S. parauberis infected fishes.

Conclusion

In conclusion, our universal primer is able to identify S. iniae and S. parauberis in rapid and cost effective manner along with high sensitivity and specificity, then previously reported primers. Our study highlighted the current scenario of S. iniae and S. parauberis diagnosis system. Based on our suggestion, improved management decisions on early diagnosis through combined clinical phenotype and 16S rRNA sequencing method, were the appropriate lead, which will be able to counter balances the negative economic impact caused by S. iniae and S. parauberis disease in aquaculture production systems.