Mol. Cells 2018; 41(6): 495-505
Published online May 10, 2018
https://doi.org/10.14348/molcells.2018.2154
© The Korean Society for Molecular and Cellular Biology
Correspondence to : *Correspondence: khs307@pusan.ac.kr
Several bacterial etiological agents of streptococcal disease have been associated with fish mortality and serious global economic loss. Bacterial identification based on biochemical, molecular, and phenotypic methods has been routinely used, along with assessment of morphological analyses. Among these, the molecular method of 16S rRNA sequencing is reliable, but presently, advanced genomics are preferred over other traditional identification methodologies. This review highlights the geographical variation in strains, their relatedness, as well as the complexity of diagnosis, pathogenesis, and various control methods of streptococcal infections. Several limitations, from diagnosis to control, have been reported, which make prevention and containment of streptococcal disease difficult. In this review, we discuss the challenges in diagnosis, pathogenesis, and control methods and suggest appropriate molecular (comparative genomics), cellular, and environmental solutions from among the best available possibilities.
Keywords antimicrobial, aquaculture, geography, sequencing,
Aquaculture is among the fastest growing businesses in the food production industry (Bondad-Reantaso et al., 2005), and streptococcal infections have caused significant economic losses in the aquaculture industry (Austin and Austin, 2007; Toranzo et al., 2005).
Various bacterial agents cause streptococcosis;
Control of streptococcus infection mainly relies on the use of antimicrobial compounds, vaccinations, and environmental strategies (Cheng et al., 2010; Darwish and Hobbs, 2005; Hastein et al., 2005; Sommerset et al., 2005; Woo and Park, 2014), of which vaccines and antimicrobial compounds have been ineffective for various reasons (Agnew and Barnes, 2007; Park et al., 2009; Shoemaker et al., 2001; Toranzo et al., 2005). Environmental strategies have been used to control fish infections in their natural and artificial habitats by several methods (Holmer, 2010). In this review, we discuss the current status and challenges in diagnosis, pathogenesis, and control of streptococcal disease in fish and we suggest effective control strategies.
Streptococcal disease occurs in all continents (Americas, Asia, Europe, Africa, and Australia) (Table 1 and Fig. 1). Thousands of
Currently, the immediate and inexpensive diagnosis of streptococcosis in infected fish is difficult as fish exhibit similar clinical symptoms regardless of the etiological agent (Table 1 and Fig. 1) (Baeck et al., 2006; Muzquiz et al., 1999). Various issues of diagnosis are discussed below.
Clinical phenotype is the primary signature of bacterial infections that depends on various factors, so it is difficult to understand the precise cause of infection. A study of tilapia fish showed that clinical phenotypes and degree of lesions depend on several factors such as
Bacterial identification methods based on culture, morphology, or biochemical reactions are time- and resource-consuming. Some pathogen databases (RAPID Strep strip, VITEX systems, API 20E STREP, Rapid Strep 32 and ATB Expression System) are incomplete or incorrect, and result in improper identification of bacteria (Dodson et al., 1999; Facklam et al., 2005; Lau et al., 2006). Additionally, other challenges for accurate identification include the mixed nature of the aquaculture environment, low numbers of biological samples, or unknown tissue location in carriers (Klesius et al., 2006). Identification of
Molecular methods are based on several candidate genes (Table 2), that have been well characterized for diversity, including 16S rRNA, heat-shock genes (
Another molecular method, multilocus sequence typing (MLST; analyses of multiple genetic loci or housekeeping genes) is considered the “gold standard” of typing for many bacterial species (Maiden, 2006; Jolly et al., 2012). However, insufficient resolution among very closely related bacteria can be a problem (Achtman, 2008).
The pathogenesis of streptococcosis depends upon several factors that vary with fish species and bacterial species and isolates. Further details of virulence and pathogenicity of streptococcosis are given below.
Genetic virulence depends on several factors; for example,
Many streptococcal species are multi-host pathogens. Humans constantly face the risk of infection due to close interactions with the fish industry (Abdelsalam et al., 2010).
Disease control using antimicrobials, vaccination, and environmental strategies are used extensively; however, some are associated with various downstream challenges that are mentioned in Fig. 2 and discussed in detail below.
Streptococcal diseases in fish initially affect the skin, fins, gills, and external organs. Thus, controlling infections externally through liquid disinfecting agents that can dissolve in water very easily (copper sulfate and formalin) are a good option, however, these agents cause hazardous environmental side effects.
Antibiotic resistance genes are frequently transferred among bacterial species, leading to resistant
The capacity of bacteria to bypass any phagocyte activity and oxidative killing of host cells is a very important step utilized for vaccination strategies (Buchanan et al., 2008). Pathogenicity of streptococcal bacteria depends on their capability to survive in host immune cells. The bacteria induce internal apoptosis while avoiding killing host cells to establish infections (Woo and Park, 2014; Zlotkin et al., 2003). The pathogenesis of
The environment can modulate the innate immune system in fish, so any intensive culture systems immediately make fish susceptible to infection and provide a further source for the spread of infection (Magnadottir, 2006). Studies show that increased fish density and other stress factors can elicit harmful effects in fish (Eldar et al., 1995; Shoemaker et al., 2000; 2001). A system for improving water quality and monitoring fish health is another parameter that can decrease the chances of infection, as deteriorating water quality promotes the rapid spread of bacteria and mortality (Eldar et al., 1995). Various additional strategies, such as reducing fish density by using effective physical barriers (netting), and removing moribund fish are also considered to be effective steps (Shoemaker et al., 2000; 2001).
Effective control systems can be established through coordination and complete knowledge of the fishery industry, fish molecular and cellular biology, ecological conditions, bacterial molecular and cellular biology, and appropriate management. However, based on various studies, it is also clear that due to the unavailability of any effective and universal vaccines or antibiotics for fish diseases, environmental protective measures may be the best strategies for controlling streptococcal disease (Fig. 3).
Environmental control is most ideal as it is inexpensive, easily monitored, and is not associated with any side effects (Figs. 2 and 3). Here, we briefly discuss the important parameters that should be addressed for effective environmental control.
Studies have suggested that virulence factors play an important role in pathogenesis and disease (Barnett et al., 2015; Rajagopal, 2009). Thus, basic and advanced research at the cellular level can provide more knowledge of biological processes involved in fish resistance against streptococcal diseases. These studies should focus on understanding innate and adaptive responses through cellular (macrophages, T cell and B cell markers) and humoral (various immunoglobulin classes, complement factors, cytokines) pathways. Studies have shown that several factors are involved in the regulation of Group B streptococci (GBS) disease pathogenesis, including pore-forming toxins and several adherence and immune evasion factors, which are reviewed in detail in Table 1 of Rajagopal, 2009. Additionally, signal transduction systems (STSs) are also important drug targets for effective disease control (Barrett et al., 1998; Rajagopal, 2009). Several
Many immunostimulants can stimulate pathogen-associated molecular patterns (PAMPS), which are part of fish immune systems as pathogen recognition receptors (PRRs) and participate in maintaining innate immune protection for fish (Chettri et al., 2011).
Recently, dietary intake of bacterial components, polysaccharides, animal-derived nutrients, plant extracts, nutritional factors, and cytokines has been reported to be an effective method for immunostimulation in fish (Sakai, 1999; Villegas et al., 2006). Further advanced cellular studies of immunostimulants are required for understanding various downstream cellular activities such as hemotaxis, respiratory burst, phagocytosis, and lysozymes to establish the most effective stimulants for fish. Additionally, the development of a range of assays such as immunohistochemistry, immunocytochemistry, flow-cytometry, and gene expression technology combined with
Knowledge of genetic virulence factors is important for understanding disease mechanisms and progression. Unfortunately, studies have been limited to rat and mouse models for various streptococci so far. The molecular basis of virulence was described in detail by Bennedsen et al. in 2011 (Bennedsen et al., 2011; Springman, 2009). Virulence factors vary with the streptococci strain and host since host/external environments are also responsible for variable expression of virulent genes.
Some important genetic virulence factors like polysaccharide capsules gene (
The recent introduction of ‘next-generation’ sequencing technology has brought a revolution in bacterial research as many bacterial genomes and antimicrobial resistance and virulence genes are available for analysis (Chain et al., 2009; Kwong et al., 2015; Medini et al., 2008). Currently, the use of whole-genome sequencing (WGS) for typing any bacterial agent is possible in a cost effective and timely manner (Kwong et al., 2015). The Genus
Choosing conserved genes (e.g.,
In this review, based on the NCBI database, we selected and analyzed the 16S rRNA gene in 51 representative worldwide strains of streptococcus species (
Fully developed fishery management systems according to current challenges (diagnosis, pathogenesis, and control mechanism) are required. Understanding fish management at the local level is useful for the aquaculture industry (Aquilera et al., 2015). We therefore suggest an effective aquaculture management module that utilizes a scientific approach to reconcile complex data of various cellular, molecular, and environmental approaches, and monitoring programs generated through research surveys.
Our study has important implications for the epidemiology of streptococcosis in fish, provides important information about the current scenario and challenges in the fish industry, and suggests joint molecular (for diagnosis) and cellular (for control) strategies along with environmental control methods as appropriate (Tables 1, 2 and Figs. 1
Streptococcal infectious diseases, along with complicated control mechanisms, have contributed to a considerable decrease in fish production. This review highlights the current status of
Streptococcus bacterial agents and detailed information of affected fish species, locations, hosts, and clinical criteria
Species | Host | Fish species | Clinical Criteria | Geographical Location |
---|---|---|---|---|
Fish, Human | Hybrid striped bass, Nile tilapia, Hybrid tilapia, Rainbow trout, Red drum, Rabbitfish, Sea bass, Olive flounder, Barramundi, Wild fish | Hemorrhage, exophthalmia, abdominal distension, ascites, lesions (liver, kidney, spleen, and intestine) | Canada, Americas, Bahrain, Israel, Thailand, China, Japan, Singapore, Taiwan, Korea | |
Fish, Cow | Olive flounder, Rainbow trout, Cultured turbot, Hybrid striped bass | Chronic wasting syndrome, hemorrhagic septicemia, exophthalmia, meningitis with abnormal swimming | Israel, Italy, Japan, Spain, USA, China, Iran, Korea, Malaysia, India | |
Fish, Cow, Human, Chickens, Camels, Dogs, Horses, Cats, Frogs, Hamsters, Monkeys | Nile tilapia, Barcoo grunter, Golden pompano, Giant Queensland grouper, Ya-fish, Silver pomfret | Erratic swimming, appetite, lethargy, uncoordinated movements, exophthalmia (uni- or bi-lateral), intraocular hemorrhage, opaqueness of cornea, ascites | Europe, Turkey, China, Indonesia, Malaysia, Japan, Korea, Vietnam, Philippines, Americas | |
Fish, Cow, Human, Cat, Dog, Water buffalo | Rainbow trout, Yellowtail, Tilapia, Japanese eel, Grey mullet, Black rockfish, Catfish, Wild wrasse, Giant fresh water prawn, Olive flounder, Amberjack, kingfish | Melanosis, lethargy, erratic swimming, disorientation, fins, exophthalmia (uni- or bi-lateral), swollen abdomens, anal prolapses, hemorrhages (periorbital, perianal, buccal regions) | Turkey, Australia, South Africa, England, Portugal France, Balkans, Israel, Korea | |
Fish, Calves, Lamb, Human, Sheep, Dogs, Pig, Lamb, Cats | White spotted snapper, Kingfish, Grey mullet, Cobia, Hybrid red tilapia, Pompano, Basket mullet, Pompano, Golden pomfret, Amur sturgeon, Nile tilapia, Yellow tail, Amber-jack | Abnormal swimming, loss of orientation, exophthalmia | Brazil, Indonesia, Malaysia, Taiwan, China, Japan | |
Fish | Rainbow trout, Atlantic salmon, Brown trout | Loss of equilibrium, exophthalmia, melanosis, bleeding (jaw, eye, mouth, abdomen, fins, and anus), necropsy, transparent fluid accumulation, fibrinous deposits (heart, liver, spleen) | France, Italy, Spain |
Candidate genes used for differentiation and diagnosis of various Streptococcus bacterial agents
Candidate gene | References |
---|---|
Manganese-dependent superoxide dismutase gene ( | Kitten et al., 2012; Poyart et al., 2000 |
Heat shock protein ( | Hung et al., 2013; Teng et al., 2014 |
Ribosomal protein ( | Drancourt et al., 2013 |
Recombination and repair protein ( | Hung et al., 2013 |
Repair protein | Glazunova et al., 2013 |
Lactate oxidase gene ( | Zlotkin et al., 1998 |
rRNA | Clarridge et al., 2002 |
RNA polymerase | Drancourt et al., 2004 |
D-alanine-D-alanine ligase | Garnier et al., 1997 |
Picard et al., 2004 | |
Polysaccharide capsules gene ( | Lowe et al., 2007 |
Invasion associated gene ( | Rajagopal, 2009 |
Surface immunogenic protein ( | Springman et al., 2009 |
C5a peptidase ( | Springman et al., 2009 |
Serine protease ( | Springman et al., 2009 |
tRNA gene intergenic spacer region (ITS) | Tung et al., 2007 |
Epidemiological specification (accession number, strain, and geographical location) of Streptococcus bacterial agents based on 16S rRNA gene sequences from the NCBI database
Species | Accession number | Strain | Geographical region/country |
---|---|---|---|
DQ985468.1 | CGX | China | |
KY781829.1 | HNM-1 | China | |
KJ162337.1 | Ab130920 | China | |
KF815728.1 | WZMH110819 | China | |
KF555592.1 | NS1-2011 | Thailand | |
KC748467.1 | FC0924 | China | |
KM209199.1 | SK10-S | Indonesia | |
AB593340.1 | Feb-45 | Japan | |
AY942573.1 | LMG 14376 | Finland | |
FJ009631.1 | JJI51 | Korea | |
JQ780604.1 | partial sequence | Israel | |
KC836715.1 | RU37-6 | China | |
AF284579.2 | SAP 99 | Italy | |
KP137361.1 | F21 | Turkey | |
KP137342.1 | F57 | Turkey | |
KP240952.1 | CIFT MFB 10119(2) | India | |
KC699192.1 | CNM465_12 | Spain | |
LC071815.1 | JCM 5671 | Japan | |
AB596948.1 | JCM 5671 | Japan | |
DQ303183.1 | ATCC 13813 | Canada | |
AB002479.1 | ATCC 13813-NCTC 8181 | Japan | |
NR_117503.1 | ATCC 13813 | USA | |
NR_115728.1 | ATCC 13813 | USA | |
GU360730.1 | ATCC 13813 | Netherlands | |
KT869025.1 | SAG | Malaysia | |
KY635952.1 | S29 | Brazil | |
KY635949.1 | S73 | Brazil | |
AB002485.1 | ATCC 43078 | Japan | |
AB002500.1 | isolate L32 | Japan | |
AB002509.1 | isolate L9 | Japan | |
NR_027517.1 | ATCC 43078 | USA | |
DQ232540.1 | CIP 105120 | France | |
JN639380.1 | CCUG 7977A | Denmark | |
JN639434.1 | SK1333 | Denmark | |
JN639432.1 | CCUG 36637 | Denmark | |
JN639410.1 | CCUG 48101 | Denmark | |
AB002484.1 | ATCC 27957 | Japan | |
AY121361.1 | ATCC 12394 | China | |
AF015928.1 | ATCC 27957 | USA | |
AJ314611.1 | AC-2074 | Germany | |
AJ314609.1 | AC-2713 | Germany | |
AJ314610.1 | AC-2832 | Germany | |
LC145570.1 | JCM 12256 | Japan | |
KF111340.1 | TRF1 | USA | |
HM536980.1 | PW1537 | China | |
KX671996.1 | FJ6 | Iran | |
KF849271.1 | SI-IRI | Iran | |
AF352164.1 | FLG4 | China | |
KM659863.1 | Fish 10/10 LKF | South Africa | |
AM490375.1 | JIP 20-00 | France | |
AM490374.1 | JIP 27-01(2) | France |
Mol. Cells 2018; 41(6): 495-505
Published online June 30, 2018 https://doi.org/10.14348/molcells.2018.2154
Copyright © The Korean Society for Molecular and Cellular Biology.
Anshuman Mishra1, Gyu-Hwi Nam1,2, Jeong-An Gim1,2,3, Hee-Eun Lee1,2, Ara Jo1,2, and Heui-Soo Kim1,2,*
1Institute of Systems Biology, Pusan National University, Busan 46241, Korea, 2Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 46241, Korea, 3The Genomics Institute, Life Sciences Department, UNIST, Ulsan 44919, Korea
Correspondence to:*Correspondence: khs307@pusan.ac.kr
Several bacterial etiological agents of streptococcal disease have been associated with fish mortality and serious global economic loss. Bacterial identification based on biochemical, molecular, and phenotypic methods has been routinely used, along with assessment of morphological analyses. Among these, the molecular method of 16S rRNA sequencing is reliable, but presently, advanced genomics are preferred over other traditional identification methodologies. This review highlights the geographical variation in strains, their relatedness, as well as the complexity of diagnosis, pathogenesis, and various control methods of streptococcal infections. Several limitations, from diagnosis to control, have been reported, which make prevention and containment of streptococcal disease difficult. In this review, we discuss the challenges in diagnosis, pathogenesis, and control methods and suggest appropriate molecular (comparative genomics), cellular, and environmental solutions from among the best available possibilities.
Keywords: antimicrobial, aquaculture, geography, sequencing,
Aquaculture is among the fastest growing businesses in the food production industry (Bondad-Reantaso et al., 2005), and streptococcal infections have caused significant economic losses in the aquaculture industry (Austin and Austin, 2007; Toranzo et al., 2005).
Various bacterial agents cause streptococcosis;
Control of streptococcus infection mainly relies on the use of antimicrobial compounds, vaccinations, and environmental strategies (Cheng et al., 2010; Darwish and Hobbs, 2005; Hastein et al., 2005; Sommerset et al., 2005; Woo and Park, 2014), of which vaccines and antimicrobial compounds have been ineffective for various reasons (Agnew and Barnes, 2007; Park et al., 2009; Shoemaker et al., 2001; Toranzo et al., 2005). Environmental strategies have been used to control fish infections in their natural and artificial habitats by several methods (Holmer, 2010). In this review, we discuss the current status and challenges in diagnosis, pathogenesis, and control of streptococcal disease in fish and we suggest effective control strategies.
Streptococcal disease occurs in all continents (Americas, Asia, Europe, Africa, and Australia) (Table 1 and Fig. 1). Thousands of
Currently, the immediate and inexpensive diagnosis of streptococcosis in infected fish is difficult as fish exhibit similar clinical symptoms regardless of the etiological agent (Table 1 and Fig. 1) (Baeck et al., 2006; Muzquiz et al., 1999). Various issues of diagnosis are discussed below.
Clinical phenotype is the primary signature of bacterial infections that depends on various factors, so it is difficult to understand the precise cause of infection. A study of tilapia fish showed that clinical phenotypes and degree of lesions depend on several factors such as
Bacterial identification methods based on culture, morphology, or biochemical reactions are time- and resource-consuming. Some pathogen databases (RAPID Strep strip, VITEX systems, API 20E STREP, Rapid Strep 32 and ATB Expression System) are incomplete or incorrect, and result in improper identification of bacteria (Dodson et al., 1999; Facklam et al., 2005; Lau et al., 2006). Additionally, other challenges for accurate identification include the mixed nature of the aquaculture environment, low numbers of biological samples, or unknown tissue location in carriers (Klesius et al., 2006). Identification of
Molecular methods are based on several candidate genes (Table 2), that have been well characterized for diversity, including 16S rRNA, heat-shock genes (
Another molecular method, multilocus sequence typing (MLST; analyses of multiple genetic loci or housekeeping genes) is considered the “gold standard” of typing for many bacterial species (Maiden, 2006; Jolly et al., 2012). However, insufficient resolution among very closely related bacteria can be a problem (Achtman, 2008).
The pathogenesis of streptococcosis depends upon several factors that vary with fish species and bacterial species and isolates. Further details of virulence and pathogenicity of streptococcosis are given below.
Genetic virulence depends on several factors; for example,
Many streptococcal species are multi-host pathogens. Humans constantly face the risk of infection due to close interactions with the fish industry (Abdelsalam et al., 2010).
Disease control using antimicrobials, vaccination, and environmental strategies are used extensively; however, some are associated with various downstream challenges that are mentioned in Fig. 2 and discussed in detail below.
Streptococcal diseases in fish initially affect the skin, fins, gills, and external organs. Thus, controlling infections externally through liquid disinfecting agents that can dissolve in water very easily (copper sulfate and formalin) are a good option, however, these agents cause hazardous environmental side effects.
Antibiotic resistance genes are frequently transferred among bacterial species, leading to resistant
The capacity of bacteria to bypass any phagocyte activity and oxidative killing of host cells is a very important step utilized for vaccination strategies (Buchanan et al., 2008). Pathogenicity of streptococcal bacteria depends on their capability to survive in host immune cells. The bacteria induce internal apoptosis while avoiding killing host cells to establish infections (Woo and Park, 2014; Zlotkin et al., 2003). The pathogenesis of
The environment can modulate the innate immune system in fish, so any intensive culture systems immediately make fish susceptible to infection and provide a further source for the spread of infection (Magnadottir, 2006). Studies show that increased fish density and other stress factors can elicit harmful effects in fish (Eldar et al., 1995; Shoemaker et al., 2000; 2001). A system for improving water quality and monitoring fish health is another parameter that can decrease the chances of infection, as deteriorating water quality promotes the rapid spread of bacteria and mortality (Eldar et al., 1995). Various additional strategies, such as reducing fish density by using effective physical barriers (netting), and removing moribund fish are also considered to be effective steps (Shoemaker et al., 2000; 2001).
Effective control systems can be established through coordination and complete knowledge of the fishery industry, fish molecular and cellular biology, ecological conditions, bacterial molecular and cellular biology, and appropriate management. However, based on various studies, it is also clear that due to the unavailability of any effective and universal vaccines or antibiotics for fish diseases, environmental protective measures may be the best strategies for controlling streptococcal disease (Fig. 3).
Environmental control is most ideal as it is inexpensive, easily monitored, and is not associated with any side effects (Figs. 2 and 3). Here, we briefly discuss the important parameters that should be addressed for effective environmental control.
Studies have suggested that virulence factors play an important role in pathogenesis and disease (Barnett et al., 2015; Rajagopal, 2009). Thus, basic and advanced research at the cellular level can provide more knowledge of biological processes involved in fish resistance against streptococcal diseases. These studies should focus on understanding innate and adaptive responses through cellular (macrophages, T cell and B cell markers) and humoral (various immunoglobulin classes, complement factors, cytokines) pathways. Studies have shown that several factors are involved in the regulation of Group B streptococci (GBS) disease pathogenesis, including pore-forming toxins and several adherence and immune evasion factors, which are reviewed in detail in Table 1 of Rajagopal, 2009. Additionally, signal transduction systems (STSs) are also important drug targets for effective disease control (Barrett et al., 1998; Rajagopal, 2009). Several
Many immunostimulants can stimulate pathogen-associated molecular patterns (PAMPS), which are part of fish immune systems as pathogen recognition receptors (PRRs) and participate in maintaining innate immune protection for fish (Chettri et al., 2011).
Recently, dietary intake of bacterial components, polysaccharides, animal-derived nutrients, plant extracts, nutritional factors, and cytokines has been reported to be an effective method for immunostimulation in fish (Sakai, 1999; Villegas et al., 2006). Further advanced cellular studies of immunostimulants are required for understanding various downstream cellular activities such as hemotaxis, respiratory burst, phagocytosis, and lysozymes to establish the most effective stimulants for fish. Additionally, the development of a range of assays such as immunohistochemistry, immunocytochemistry, flow-cytometry, and gene expression technology combined with
Knowledge of genetic virulence factors is important for understanding disease mechanisms and progression. Unfortunately, studies have been limited to rat and mouse models for various streptococci so far. The molecular basis of virulence was described in detail by Bennedsen et al. in 2011 (Bennedsen et al., 2011; Springman, 2009). Virulence factors vary with the streptococci strain and host since host/external environments are also responsible for variable expression of virulent genes.
Some important genetic virulence factors like polysaccharide capsules gene (
The recent introduction of ‘next-generation’ sequencing technology has brought a revolution in bacterial research as many bacterial genomes and antimicrobial resistance and virulence genes are available for analysis (Chain et al., 2009; Kwong et al., 2015; Medini et al., 2008). Currently, the use of whole-genome sequencing (WGS) for typing any bacterial agent is possible in a cost effective and timely manner (Kwong et al., 2015). The Genus
Choosing conserved genes (e.g.,
In this review, based on the NCBI database, we selected and analyzed the 16S rRNA gene in 51 representative worldwide strains of streptococcus species (
Fully developed fishery management systems according to current challenges (diagnosis, pathogenesis, and control mechanism) are required. Understanding fish management at the local level is useful for the aquaculture industry (Aquilera et al., 2015). We therefore suggest an effective aquaculture management module that utilizes a scientific approach to reconcile complex data of various cellular, molecular, and environmental approaches, and monitoring programs generated through research surveys.
Our study has important implications for the epidemiology of streptococcosis in fish, provides important information about the current scenario and challenges in the fish industry, and suggests joint molecular (for diagnosis) and cellular (for control) strategies along with environmental control methods as appropriate (Tables 1, 2 and Figs. 1
Streptococcal infectious diseases, along with complicated control mechanisms, have contributed to a considerable decrease in fish production. This review highlights the current status of
. Streptococcus bacterial agents and detailed information of affected fish species, locations, hosts, and clinical criteria.
Species | Host | Fish species | Clinical Criteria | Geographical Location |
---|---|---|---|---|
Fish, Human | Hybrid striped bass, Nile tilapia, Hybrid tilapia, Rainbow trout, Red drum, Rabbitfish, Sea bass, Olive flounder, Barramundi, Wild fish | Hemorrhage, exophthalmia, abdominal distension, ascites, lesions (liver, kidney, spleen, and intestine) | Canada, Americas, Bahrain, Israel, Thailand, China, Japan, Singapore, Taiwan, Korea | |
Fish, Cow | Olive flounder, Rainbow trout, Cultured turbot, Hybrid striped bass | Chronic wasting syndrome, hemorrhagic septicemia, exophthalmia, meningitis with abnormal swimming | Israel, Italy, Japan, Spain, USA, China, Iran, Korea, Malaysia, India | |
Fish, Cow, Human, Chickens, Camels, Dogs, Horses, Cats, Frogs, Hamsters, Monkeys | Nile tilapia, Barcoo grunter, Golden pompano, Giant Queensland grouper, Ya-fish, Silver pomfret | Erratic swimming, appetite, lethargy, uncoordinated movements, exophthalmia (uni- or bi-lateral), intraocular hemorrhage, opaqueness of cornea, ascites | Europe, Turkey, China, Indonesia, Malaysia, Japan, Korea, Vietnam, Philippines, Americas | |
Fish, Cow, Human, Cat, Dog, Water buffalo | Rainbow trout, Yellowtail, Tilapia, Japanese eel, Grey mullet, Black rockfish, Catfish, Wild wrasse, Giant fresh water prawn, Olive flounder, Amberjack, kingfish | Melanosis, lethargy, erratic swimming, disorientation, fins, exophthalmia (uni- or bi-lateral), swollen abdomens, anal prolapses, hemorrhages (periorbital, perianal, buccal regions) | Turkey, Australia, South Africa, England, Portugal France, Balkans, Israel, Korea | |
Fish, Calves, Lamb, Human, Sheep, Dogs, Pig, Lamb, Cats | White spotted snapper, Kingfish, Grey mullet, Cobia, Hybrid red tilapia, Pompano, Basket mullet, Pompano, Golden pomfret, Amur sturgeon, Nile tilapia, Yellow tail, Amber-jack | Abnormal swimming, loss of orientation, exophthalmia | Brazil, Indonesia, Malaysia, Taiwan, China, Japan | |
Fish | Rainbow trout, Atlantic salmon, Brown trout | Loss of equilibrium, exophthalmia, melanosis, bleeding (jaw, eye, mouth, abdomen, fins, and anus), necropsy, transparent fluid accumulation, fibrinous deposits (heart, liver, spleen) | France, Italy, Spain |
. Candidate genes used for differentiation and diagnosis of various Streptococcus bacterial agents.
Candidate gene | References |
---|---|
Manganese-dependent superoxide dismutase gene ( | Kitten et al., 2012; Poyart et al., 2000 |
Heat shock protein ( | Hung et al., 2013; Teng et al., 2014 |
Ribosomal protein ( | Drancourt et al., 2013 |
Recombination and repair protein ( | Hung et al., 2013 |
Repair protein | Glazunova et al., 2013 |
Lactate oxidase gene ( | Zlotkin et al., 1998 |
rRNA | Clarridge et al., 2002 |
RNA polymerase | Drancourt et al., 2004 |
D-alanine-D-alanine ligase | Garnier et al., 1997 |
Picard et al., 2004 | |
Polysaccharide capsules gene ( | Lowe et al., 2007 |
Invasion associated gene ( | Rajagopal, 2009 |
Surface immunogenic protein ( | Springman et al., 2009 |
C5a peptidase ( | Springman et al., 2009 |
Serine protease ( | Springman et al., 2009 |
tRNA gene intergenic spacer region (ITS) | Tung et al., 2007 |
. Epidemiological specification (accession number, strain, and geographical location) of Streptococcus bacterial agents based on 16S rRNA gene sequences from the NCBI database.
Species | Accession number | Strain | Geographical region/country |
---|---|---|---|
DQ985468.1 | CGX | China | |
KY781829.1 | HNM-1 | China | |
KJ162337.1 | Ab130920 | China | |
KF815728.1 | WZMH110819 | China | |
KF555592.1 | NS1-2011 | Thailand | |
KC748467.1 | FC0924 | China | |
KM209199.1 | SK10-S | Indonesia | |
AB593340.1 | Feb-45 | Japan | |
AY942573.1 | LMG 14376 | Finland | |
FJ009631.1 | JJI51 | Korea | |
JQ780604.1 | partial sequence | Israel | |
KC836715.1 | RU37-6 | China | |
AF284579.2 | SAP 99 | Italy | |
KP137361.1 | F21 | Turkey | |
KP137342.1 | F57 | Turkey | |
KP240952.1 | CIFT MFB 10119(2) | India | |
KC699192.1 | CNM465_12 | Spain | |
LC071815.1 | JCM 5671 | Japan | |
AB596948.1 | JCM 5671 | Japan | |
DQ303183.1 | ATCC 13813 | Canada | |
AB002479.1 | ATCC 13813-NCTC 8181 | Japan | |
NR_117503.1 | ATCC 13813 | USA | |
NR_115728.1 | ATCC 13813 | USA | |
GU360730.1 | ATCC 13813 | Netherlands | |
KT869025.1 | SAG | Malaysia | |
KY635952.1 | S29 | Brazil | |
KY635949.1 | S73 | Brazil | |
AB002485.1 | ATCC 43078 | Japan | |
AB002500.1 | isolate L32 | Japan | |
AB002509.1 | isolate L9 | Japan | |
NR_027517.1 | ATCC 43078 | USA | |
DQ232540.1 | CIP 105120 | France | |
JN639380.1 | CCUG 7977A | Denmark | |
JN639434.1 | SK1333 | Denmark | |
JN639432.1 | CCUG 36637 | Denmark | |
JN639410.1 | CCUG 48101 | Denmark | |
AB002484.1 | ATCC 27957 | Japan | |
AY121361.1 | ATCC 12394 | China | |
AF015928.1 | ATCC 27957 | USA | |
AJ314611.1 | AC-2074 | Germany | |
AJ314609.1 | AC-2713 | Germany | |
AJ314610.1 | AC-2832 | Germany | |
LC145570.1 | JCM 12256 | Japan | |
KF111340.1 | TRF1 | USA | |
HM536980.1 | PW1537 | China | |
KX671996.1 | FJ6 | Iran | |
KF849271.1 | SI-IRI | Iran | |
AF352164.1 | FLG4 | China | |
KM659863.1 | Fish 10/10 LKF | South Africa | |
AM490375.1 | JIP 20-00 | France | |
AM490374.1 | JIP 27-01(2) | France |