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Exploring fish microbial communities to mitigate emerging
diseases in aquaculture
Journal: FEMS Microbiology Ecology
Manuscript ID FEMSEC-17-05-0231.R1
Manuscript Type: Minireview
Date Submitted by the Author: n/a
Complete List of Authors: de Bruijn, Irene; NIOO-KNAW, Department of Microbial Ecology Liu, Yiying; NIOO-KNAW, Department of Microbial Ecology Wiegertjes, Geert ; Wageningen Universiteit en Researchcentrum, Cell Biology and Immunology group, Department of Animal Sciences Raaijmakers, Jos; Netherlands Institute of Ecology, Microbial Ecology
Keywords: aquaculture, beneficial microbes, microbiomes, emerging diseases, fish
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Host immune response Protection against
pathogens
Factors that shape
microbiome
Nutrient acquisition
Host environment
Growth and development
Host genotype
Tolerance to abiotic stress
Functionality of microbiome
Fish microbiome
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Exploring fish microbial communities to mitigate 1
emerging diseases in aquaculture 2
3
Irene de Bruijn1^, Yiying Liu1^, Geert F. Wiegertjes2 and Jos M Raaijmakers1,3 4
1 Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands; 5
2 Cell Biology and Immunology group, Department of Animal Sciences, Wageningen University & Research, Wageningen, The Netherlands 6
3 Institute of Biology (IBL), Leiden University, Leiden, The Netherlands 7
8
^Shared first authors 9
Correspondence: I. de Bruijn, Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), 6708PB Wageningen, The 10
Netherlands. E-Mail: [email protected] 11
12
Running title: fish microbiome 13
Keywords: aquaculture, fish, emerging diseases, microbiomes, beneficial microbes 14
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Abstract 16
Aquaculture is the fastest-growing animal food sector worldwide and expected to further increase to feed the growing human population. 17
However, existing and (re-)emerging diseases are hampering fish and shellfish cultivation and yield. For many diseases, vaccination protocols 18
are not in place and the excessive use of antibiotics and other chemicals is of substantial concern. A more sustainable disease control strategy 19
to protect fish and shellfish from (re-)emerging diseases could be achieved by introduction or augmentation of beneficial microbes. To establish 20
and maintain a ‘healthy’ fish microbiome, a fundamental understanding of the diversity and temporal-spatial dynamics of fish-associated 21
microbial communities and their impact on growth and health of their aquatic hosts is required. This review describes insights in the diversity 22
and functions of the fish bacterial communities elucidated with next-generation sequencing and discusses the potential of the microbes to 23
mitigate (re-)emerging diseases in aquaculture. 24
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Introduction 26
The United Nations Food and Agricultural Organization (FAO) predicts that the world’s food and feed supply needs to grow by 70% to support 27
the growing human population by 2050. Currently, aquaculture is the fastest-growing animal food sector worldwide (FAO, 2014). However, fish 28
and shellfish production is limited by several emerging diseases caused by viruses, bacteria, fungi, oomycetes, amoebas and other 29
ectoparasites. Bacterial fish diseases are typically addressed by antibiotics (Romero et al., 2012, Cabello et al., 2013), viral diseases by 30
vaccination (Evensen & Leong, 2013) and parasitic diseases by chemical treatment (Burridge et al., 2010). However, the risk of antibiotic 31
resistance development and the transfer of antibiotic resistance genes to other animal pathogens, as well as concerns for environmental 32
impact and consumer safety, have stimulated the need for new sustainable control measures (Brandt et al., 2015). Vaccination is a sustainable 33
control measure, but various viral and bacterial fish diseases, and more specifically fungal and oomycete diseases, cannot yet be controlled by 34
vaccination (Evensen & Leong, 2013, Dhar et al., 2014, Hølvold et al., 2014). In addition, the oral delivery of efficacious and safe vaccines 35
remains a challenge, partly due to antigen breakdown of oral vaccines in the harsh gastric environment, the high tolerogenic gut environment 36
and inadequate vaccine design (reviewed in Embregts & Forlenza, 2016). Additional strategies for sustainable disease control include breeding 37
for disease resistance (Gjedrem, 2012), the use of plant extracts as prebiotics (Akhter et al., 2015, Van Hai, 2015) and augmentation or 38
introduction of beneficial microorganisms. 39
Beneficial microbes introduced into the aquaculture environment, also referred to as probiotics, are considered a highly promising and 40
sustainable strategy to mitigate fish diseases. To date, a range of potential probiotics have been investigated for their application in 41
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aquaculture, including bacteria, bacteriophages, fungi and yeasts (Verschuere et al., 2000, Hai, 2015, Newaj-Fyzul & Austin, 2015, Banerjee & 42
Ray, 2017). Despite the large number of promising candidates, however, only a few bacterial probiotics, for example Bactocell® (containing P. 43
acidilactici) (Lallemand-Animal-Nutrition, Gatesoupe, 1999, EFSA-FEEDAP, 2012), Aquastar® (consisting of a mix of Lactobacillus reuteri, 44
Bacillus subtilis, Enterococcus faecium and Pediococcus acidilactici) (Biomin®) and Sanolife (containing Bacillus subtillis, Bacillus licheniformis 45
and Bacillus pumilus) (INVE Aquaculture), have been commercialized (Ibrahem, 2015) or licensed for aquaculture in Europe (EFSA-BIOHAZ, 46
2017). The lack of consistency in performance and persistence under different environmental conditions, their relatively narrow activity 47
spectrum as well as current constraints for commercial application of probiotics, such as strict regulations for registration, shelf life, high 48
production costs, and highly specific storage and transport conditions of the microbial inoculants, are major concerns to the industry (Martínez 49
Cruz et al., 2012, Bentzon‐Tilia et al., 2016, Giatsis et al., 2016). 50
51
Microbiomes 52
In this review the microbiome is defined as described by Joshua Lederberg: “the totality of microbes, their genomes and their interactions in a 53
particular environment”. There is increasing evidence that microbial consortia rather than single microbial species are associated with health 54
and disease (Gilbert et al., 2016). The impact of microbial consortia on early development and health of their eukaryotic hosts is gaining 55
increased attention, with new ‘omics’-based technologies allowing for in-depth characterisations of microbial communities and functions in 56
diverse ecosystems. Indeed, contituents within the human gut microbiomes can significantly drive or suppress disease development (Round et 57
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al., 2010, Everard et al., 2013, Gilbert et al., 2016), whereas environmental changes or infections can substantially influence the human gut 58
microbiome by causing blooms of microbes that otherwise are present at low abundance (Stecher et al., 2013). In terrestrial farmed animals, 59
sudden changes like the use of antibiotics or dietary changes can cause substantial shifts in the gut microbial composition leading to disease 60
susceptibility (Gresse et al., Cisek & Binek, 2014, Fecteau et al., 2016, Fouhse et al., 2016). Similar observations have been made for the gut 61
of insects, whose microbiomes can influence insect development by increasing nutrient uptake and stimulating immunity maturation (Weiss & 62
Aksoy, 2011). Also for plants, microbiota play an important role in the protection against biotic and abiotic stress factors (Berendsen et al., 63
2012, Vorholt, 2012, Bulgarelli et al., 2013, Philippot et al., 2013, Turner et al., 2013, Mendes & Raaijmakers, 2015). In line with these findings, 64
microbial communities of fish may harbour substantial potential to modulate health and disease. Due to the complex structure of microbial 65
communities, disentangling interactions and identifying keystone species for specific functions is enormously challenging, especially when 66
environmental influences on population dynamics and activities are taken into account. Microbiome research of humans and other eukaryotes 67
typically describes correlations between microbiome composition and diseases, but it remains a challenge which taxonomic or functional 68
changes in the microbiome are actually causal for disease development or disease protection (Gilbert et al., 2016, Raaijmakers & Mazzola, 69
2016). Hence, a systems-based understanding of the dynamics and functions of microbial communities for their fish and shellfish hosts is 70
needed to enable a more profound selection of beneficial (micro)organisms for augmentation of microbial communities to achieve more 71
sustainable disease control strategies in aquaculture. This review describes the current state-of-the-art of fish microbial community research 72
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using next generation sequencing and provides an outlook into the functional potential of fish-associated microbes to control (re-)emerging 73
diseases in aquaculture. 74
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Diversity of fish microbiota 77
Traditionally, microbes associated with aquatic animals and their environment, have been isolated on general and selective agar media. Since 78
only a proportion of the viable microbes in various aquatic environments are culturable (Amann et al., 1995), culture-independent methods 79
have been developed to assess the composition and functional potential of aquatic microbiota. Besides quantitative PCR, denaturing gradient 80
gel electrophoresis (DGGE), temperature gradient gel electrophoresis (TGGE), terminal restriction fragment length polymorphism (T-RFLP), 81
clone library sequencing and other molecular techniques (reviewed in Ringø et al., 2016), more advanced ‘omics’ techniques, such as 16S/18S 82
rRNA gene and internal transcribed spacer (ITS) sequencing, metatranscriptomics and metagenomics are now rapidly advancing providing a 83
more in-depth insight in the composition and functions of microbiomes (Llewellyn et al., 2014, Romero et al., 2014, Ghanbari et al., 2015, 84
Merrifield & Rodiles, 2015, Colston & Jackson, 2016, Tarnecki et al., 2017). This review describes the elucidation of the diversity and functions 85
of the fish microbial communities by next generation sequencing methods (Supplementary Table 1), unless mentioned otherwise. 86
87
Microbial diversity of different fish tissues 88
The mucosal tissues, including the skin, olfactory system, gills and also the gut are in direct contact with the environment and thus are the first 89
contact points of the microbes with their host. Mucus covering these tissues can be considered as a primary guardian against external 90
environmental influences and consists of the high molecular weight glycoprotein mucin as well as other proteins, ions and lipids. The mucus 91
contains immune components like lectins, complement proteins, antimicrobial peptides, immunoglobulins, lysozymes and a variety of other 92
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enzymes, including proteases (Uribe et al., 2011, Brinchmann, 2016). The mucus provides a carbon source for commensal microbes that can 93
subsequently form a protective shield against invading pathogens (Hansen & Olafsen, 1999, Merrifield & Rodiles, 2015). 94
The mucus of the fish skin and gills generally contains more aerobic than anaerobic microbes (Merrifield & Rodiles, 2015). Although 95
difficult to estimate and compare, the fish skin typically harbours 102-104 bacteria per cm2, whereas the gills harbour 103-106 bacteria per gram 96
of tissue based on cultivation-based methods (Austin, 2006, Merrifield & Rodiles, 2015). The composition of the microbial communities of the 97
gills and skin are different; the protected niches of the gill lamellae contain more microbes that putitatively favor gas-exchange (Hansen & 98
Olafsen, 1999, Wang et al., 2010, Lowrey et al., 2015). For example, the gill microbiota of rainbow trout (Oncorhynchus mykiss) contains 99
mostly Proteobacteria and Bacteroidetes (Flectobacillus and Flavobacterium), while the skin contains more Actinobacteria and Firmicutes 100
(Lowrey et al., 2015). A recent study showed that the gills of common carp (Cyprinus carpio) and zebrafish (Danio rerio) contained ammonia 101
oxidising and denitrifying bacteria, such as Nitrosomas-like bacteria, that are thought to play an important role in detoxifying the excreted 102
ammonia (van Kessel et al., 2016). Another organ of interest in this context is the fish nose: in contrast to mammals, the olfactory system of fish 103
is an external organ not connected to the mouth and mostly consists of a diffuse lymphoid system (Tacchi et al., 2015). The bacterial 104
communities in the olfactory system of rainbow trout as determined by 16S rRNA sequencing, appear highly diverse but relatively comparable 105
to the skin microbiome (containing approximately 100 genera), with Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes as the major 106
phyla (Lowrey et al., 2015). Derived from cultivation-based methods, the fish gut generally houses up to 108 aerobic heterotrophic bacteria 107
represented by approximately 500 species and up to 105 anaerobic bacteria per gram of gut tissue (Austin, 2006, Montalban-Arques et al., 108
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2015). For most fish species, the most abundant phyla found in fish guts are typically Proteobacteria, Actinobacteria, Bacteroidetes and 109
Firmicutes (Sullam et al., 2012, Givens et al., 2015, Merrifield & Rodiles, 2015, Tran et al., 2017, Wang et al., 2017a). Lowrey et al (2015) 110
showed that even though the gut of the rainbow trout contains members of the major bacterial phyla, the microbial community gut is much less 111
diverse than that of the skin or gills and harbours mainly Tenericutes (Lowrey et al., 2015). Organs like kidney, brain, liver and muscle are 112
considered to be sterile in healthy individuals, but only few studies have explored this in fish in detail. 113
Furthermore, the diversity and functions of the fungal fish microbiota remain largely understudied. Based on PCR-DGGE, Wang et al. 114
(2010) reported the Ascomycota as the most dominant fungal phylum of the gills of gibel carp (Carassius auratus gibelio) and bluntnose black 115
bream (Megalobrama amblycephala Yih). Based on cultivation-based methods, the population density of yeasts ranged up to 107 CFU per 116
gram of gut content and the two most reported fungal phyla were the Ascomycota and Basidiomycota (Gatesoupe, 2007, Romero et al., 2014). 117
To date, only few studies have described Archaea or protozoa in the fish gut. The guts of grass carp (Ctenopharyngodon idellus) mainly 118
contained methanogenic archaea (Wu et al., 2015), while marine flounder (Platichthys flesus) and grey mullet (Mugil cephalus) consisted 119
mainly group II marine archaea based on clone library sequencing (van der Maarel et al., 1998). Ciliates belonging to the order of 120
Clevelandellida and Vestibuliferida were identified in the guts of several marine surgeonfish (Acanthurus achilles, A. gluttatus, Zebrasoma 121
rostsratum, Z. velifenim by microscopy (Grim et al., 2002). Protozoa have shown to be common in the gill when studied by microscopy 122
(Valtonen et al., 2003, Yokoyama et al., 2015), including the pathogenic species like Neoparamoeba perurans causing amoebic gill disease 123
and Ichthyophthirius multifiliis causing the white spot disease. 124
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125
Microbial community changes during early development 126
Most fish species lay eggs that are fertilized externally in the aquatic ecosystem. The fish egg surface consists of a thick inner layer (zona 127
radiata) and a thin outer layer (chorion or zona pellucida) that varies between fish species. The permeable eggshell is composed of fibrin-like 128
molecules and glycoproteins, including lectins to which microbes can adhere and colonize the eggs (Hansen & Olafsen, 1999, Olafsen, 2001, 129
Treasurer et al., 2005, Wedekind et al., 2010). In this context, salmonid eggs have been best studied, likely because of the economic 130
importance of Atlantic salmon (Salmo salar) for aquaculture. Population densities of bacteria on fish eggs can range from 103-106 CFU g-1, with 131
Aeromonas, Alteromonas, Arthrobacter, Flavobacterium, Moraxella, Pseudomonas and Streptomyces as the major bacterial genera (Hansen & 132
Olafsen, 1999, Liu et al., 2014). It is very likely that part of the fish egg microbiota was obtained via vertical transmission from the mother, as 133
was shown for the pathogenic bacteria Renibacterium salmoninarum (Bruno & Munro, 1986) and Flavobacterium psychrophilum (Long et al., 134
2014). Not only the surface, but also the internal tissue of eggs of freshwater and marine fish may contain bacteria (Hansen & Olafsen, 1999). 135
The major fungal and oomycete genera reported for Atlantic salmon eggs are Microdochium, Mortierella, Chytriomyces and Saprolegnia (Liu et 136
al., 2014). 137
Only few studies to date have investigated temporal changes in microbiome composition during egg development. For whitefish 138
(Coregenus spp.), the density of bacteria decreased from early (blastoderm visible) to late (late-eyed) stages of egg development with 139
Burkholderiales and Fusobacteria representing the largest groups in the early versus the late stage, respectively (Wilkins et al., 2015a). A large 140
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proportion of the 16S rRNA reads obtained with 454 sequencing did not have a match in the database using the stringent quality control (i.e. at 141
least 60% of the reads should have a match with a 16S rRNA gene in the database), suggesting that many unknown microbial species reside 142
on the fish eggs (Wilkins et al., 2015a). The largest group of microbiota on the surface of eggs of lake sturgeon (Acipenser fulvescens) shifted 143
from Betaproteobacteria, to Bacteriodetes to Alphaproteobacteria during early, middle and late development prior to hatching, respectively 144
(Fujimoto et al., 2013). Already before the yolksac is consumed, fish larvae start to ‘drink’ water and the gut becomes colonized by 145
microorganisms from the water. At later developmental stages, larvae are exposed to other microbiota, for example by ingestion of egg debris 146
or by microorganisms present in live and artificial feed (Hansen & Olafsen, 1999, Ringo & Birkbeck, 1999). For example, a shift occurred in 147
microbiota when grass carp larvae started ingesting; in earlier egg and non-feeding egg larval stages the Proteobacteria was the largest group 148
but upon ingestion 80% of the identified bacteria belonged to the Bacteriodetes (Wang et al., 2015). Thus, these initial studies suggest that 149
profound changes can already occur in the microbiome during early development of the fish. 150
Zebrafish is an important model species for research and well suited to study the dynamic changes of the microbiota during 151
development. A recent study showed that the density and diversity of the gut microbial community decreased with age, whereas the relative 152
abundance (eveness) of the different bacterial classes did not change with age (Stephens et al., 2016). Moreover, the microbial community 153
composition of the early life stages was more similar to the ambient water than adult fish and in the adult stages, there was more variation in 154
the gut community between individual fish. The relative abundance of the Fusobacteria (mainly genus Cetobacterium) was increased in the 155
adult gut compared to the juvenile stages (30% vs <1%, respectively) (Stephens et al., 2016). Supporting the observations in salmonids and in 156
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zebrafish, also the microbial diversity in grass carp, Chinese perch and Chinese catfish (Ctenopharyngodon idellus, Siniperca chuatsi, Silurus 157
meridionalis, respectively) decreased from larval to adult stages and showed no similarity to the ambient water microbiota (Yan et al., 2016). 158
Also in tilapia larvae, a significant change was observed in gut microbial communities during development (Giatsis et al., 2014). Because 159
larvae have incomplete digestive systems and have more diverse diets, including various planktonic organisms, Yan et al (2016) suggested 160
that they strongly rely on microbes for the digestion of feed. The diet is an important factor in colonization of the guts, as was shown for the 161
guts of rainbow trout larvae where an increase in bacterial abundance and diversity was observed upon first feeding and where Firmicutes 162
were most abundant in plant fed fish and Proteobacteria were most abundant in marine fed fish (Ingerslev et al., 2014b). In gilthead seabream 163
(Sparus aurata), Firmicutes and Bacteroidetes were more abundant in the late, Rotifer and Artemis fed larval stage compared to the early, non-164
feeding larvae (Califano et al., 2017). 165
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Impact of host genotype on fish microbiota 167
There are over 30,000 fish species worldwide, living in diverse environments. Host genetics is known to be important in shaping the microbial 168
community of fish (reviewed in Romero et al., 2014, Ghanbari et al., 2015). For example, using clone library sequencing, the fish species was 169
the most discriminating factor, besides site and time of sampling, for describing the diversity of the skin microbial communities of six different 170
fish species (Mugil cephalus, Lutjanus campechanus, Cynoscion nebulosus, Cynoscion arenarius, Micropogonias undulatus, and Lagodon 171
rhomboides) that were captured in different seasons in the Gulf of Mexico (Larsen et al., 2013). 172
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The importance of the host genetics in shaping the microbiome was demonstrated by Roeselers et al (2011) who identified a core 173
microbiota in the guts of laboratory-reared and wild zebrafish. A core microbiota was also observed on the surface of brown trout eggs reared 174
in different rivers (Wilkins et al., 2015b) and in the guts of rainbow trout kept in either aquarium or at a fish farm (Lyons et al., 2017c). The core 175
microbiota often comprises a small number of operational taxonomic units (OTUs), but which are highly abundant. For example, the core gut 176
microbiota of laboratory-reared and wild zebrafish comprised 21 OTUs of mainly Proteobacteria (Roeselers et al., 2011). Also the core 177
microbiota of three species of laboratory-reared or wild carp (Hypophthalmichthys nobilis, Hypophthalmichthys molitrix, Cyprinus carpio) 178
comprised only 5 OTUs classified to the orders Aeromonadales, Xanthomonadales, and Fusobacteriales but made up 35-40% of the total fecal 179
microbiome (Eichmiller et al., 2016). The core microbiota of the guts of aquaculture-reared and wild fine flounders (Paralichtys adspersus) 180
shared classes like Gammaproteobacteria, Alphaproteobacteria, Bacilli, Clostridia, and Actinobacteria and were present in at least 80% of the 181
samples (Ramírez & Romero, 2017a). The shared bacterial community between aquaculture-reared or laboratory-reared and wild fish suggest 182
that the host genetics plays a role in shaping the fish gut microbial community. In contrast, besides a core community, also a clear difference in 183
composition was observed in the guts of aquaculture-reared and wild fine flounders where the Proteobacteria was the most abundant phylum 184
in the wild species whereas the Firmicutes were the most abundant phylum in the aquaculture-reared species (Ramírez & Romero, 2017a). 185
Significant differences in egg-associated microbial composition and diversity were observed between individual maternal and paternal fish 186
(Wilkins et al., 2016), but the underlying mechanisms of how host genetics influences microbial community structure or whether genetic 187
information is transferred from microbiome to host are not yet understood. 188
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Effect of environmental conditions on the fish microbiota 190
Despite the importance of host genetics and diet, the composition of the gut microbiota is also determined by the microbiota present in 191
the ambient water and sediment (Sullam et al., 2012, Wu et al., 2012, Xing et al., 2013, Xu et al., 2013, Ghanbari et al., 2015, Kashinskaya et 192
al., 2015). The gut microbiota of Atlantic salmon reared in a recirculated aquarium facility and an open freshwater loch cage system in the West 193
of Scotland shared 19 out of 1850 OTUs, indicating that the environment significantly contributes to assembly of the gut microbiome (Dehler et 194
al., 2017). Due to environmental fluctuations, the ambient water conditions like temperature and nutrient levels change and affect microbiome 195
composition (Zarkasi et al., 2014, Bentzon‐Tilia et al., 2016, Zarkasi et al., 2016). The microbial community composition and densities of natural 196
waters are influenced by the seasons, as was shown for the bacterioplankton in the Western English Channel where annual day length was the 197
strongest determining factor (Gilbert et al., 2012). Also other studies showed seasonal effects on aquatic microbiota. For example, a higher 198
microbial diversity was observed in a Portuguese marine aquaculture system in the warmer season (Pereira et al., 2011) and variations in 199
Vibrio populations were correlated to the season and plankton composition (Turner et al., 2009). Potential mechanisms underlying seasonal 200
effects on fish microbiota are diverse. One of the seasonal factors involved is temperature. For example, the difference between the bacterial 201
community of brown trout eggs collected at different spawning locations in rivers in Switzerland were correlated with increasing temperature 202
and not with river location or with small genetic variations within the brown trout populations (Wilkins et al., 2015b). When investigating the 203
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Pseudomonas and Vibrio isolates from the Atlantic salmon gut, specific lineages were found only at colder temperatures during the seasons 204
(Hatje et al., 2014). 205
A second environmental factor determining the fish microbiome composition is water chemistry. To simulate the effect of acid rain and 206
subsequent acid stress, the Amazonian tambaqui (Colossoma macropomum) was exposed to acidic water (pH 4) for two weeks and 207
substantial shifts were observed in the gut and skin bacterial community, where the gut bacterial community appears more resilient (Sylvain et 208
al., 2016). Also salinity is an important factor; freshwater and seawater contain different microbes which have a major impact on the community 209
composition of the fish. This is best studied in salmon where the adults live in the sea and migrate to freshwater to spawn. During development, 210
the juvenile fish undergo a physiological process called smoltification and adapt from freshwater to their adult life in seawater. Upon transfer 211
from freshwater to seawater under controlled laboratory conditions, the skin microbiota of the mucus of salmon showed substantial differences 212
in relative frequencies of the bacterial taxa (decrease in bacterial eveness) and a higher diversity in seawater (Lokesh & Kiron, 2016). 213
Proteobacteria were abundant on the skin of fish living in both freshwater and seawater, but the Bacteroidetes, Actinobacteria, Firmicutes, 214
Cyanobacteria and Verrucomicrobia phyla became less abundant when salmon was transferred to seawater (Lokesh & Kiron, 2016). 215
Interestingly, after 4 weeks in seawater, only 23 out of 952 OTUs were in common with the freshwater community (Lokesh & Kiron, 2016), 216
indicating that the transition from freshwater to seawater has major and rapid effects on the skin microbiota. Also the total amount of taxa in the 217
intestinal microbiota from an adult marine salmon was significantly affected, with less Bacteroidetes, Firmicutes and Actinobacteria compared 218
to freshwater adults or other developmental stages (parr and smolt) (Llewellyn et al., 2016). Even though the Proteobacteria remained 219
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abundant, shifts in composition occurred with increasing salinity. In entire Black Molly (Poecilia sphenops) fish, the Gammaproteobacteria (in 220
particular Vibrio and Aeromonas) were detected at higher relative abundance at higher salinity levels (Schmidt et al., 2015). Vibrionales were 221
also more abundant in the guts of marine fish, while Aeromonodales and Enterobacteriales were more abundant in freshwater fish (Sullam et 222
al., 2012). Collectively, these studies indicate that water salinity has major effects on the skin and gut micriobiota. 223
224
Effect of feeding strategy on the fish microbiota 225
Diet can have a major impact on the fish gut microbiota. In a recent study with 15 different fish species, a more varied diet, i.e. omnivorous 226
versus piscivorous, resulted in a higher bacterial diversity in the guts (Givens et al., 2015). The gut microbiota of different wild fish species 227
caught from the same river showed different community between omnivorous, herbivorous, carnivorous and filter-feeding fish. Fusobacteria 228
were more abundant in carnivorous fish species, while Cyanobacteria were more abundant in filter-feeders (Liu et al., 2016). In another study, 229
Fusobacteria were more abundant in the guts of omnivorous fish compared to carnivorous and herbivorous fish, Bacteroidetes were more 230
abundant in marine herbivorous fish and Firmicutes were more abundant in carnivorous fish compared to the other feeding strategies (Sullam 231
et al., 2012). The microbial gut communities of salmon or rainbow trout fed with either fish meal or fish meal free diets resulted in shifts in 232
specific bacterial genera such as a higher abundance of Lactobacillus and Staphylococcus in a grain-based diet (Wong et al., 2013, Schmidt et 233
al., 2016). The microbial gene composition in the guts of rye-grass fed grass carp showed a higher abundance of genes involved in the 234
biosynthesis and metabolism of carbohydrates, lipids and amino acids compared to fish fed on diets containing fish meal (Ni et al., 2014). 235
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These results support the findings that also the type of feed, including lipid and fatty acid content (reviewed in Ringø et al., 2016), is an 236
important factor in shaping the gut microbial community. 237
238
Effects of the microbiota on fish health 239
Pathogenic microorganisms are an integral component of fish microbiomes, but despite their presence they often do not cause disease. 240
Similar to mammals and plants, pathogens can become more prevalent and cause infection and disease, a process referred to as dysbiosis, 241
when the fish commensal microbial community balance is disturbed (Sagvik et al., 2008, Stecher et al., 2013, Turner et al., 2013, Romero et 242
al., 2014, Montalban-Arques et al., 2015, Moya & Ferrer, 2016). For example, in the guts of healthy largemouth bronze gudgeon (Coreius 243
guichenoti) pathogenic Aeromonas species were present, but in higher abundance in furunculosis diseased fish (Li et al., 2016), indicating that 244
in healthy individuals the virulence and the prevalence of pathogens are suppressed. A similar phenomen was observed in the guts of 245
seahorse (Hippocampus spp.) by PCR-DGGE where pathogenic Vibrio spp were suppressed in healthy individuals (Li et al., 2015a). In 246
general, the microbial population is less diverse in diseased fish compared to healthy fish. This was also observed in the guts of “red-247
operculum” diseased crucian carp, and in addition, Cetobacterium, Cyanobacterium, and Clostridiaceae OTUs were more abundant in healthy 248
fish whereas Aeromonas, Vibrio and Shewanella OTUs were more abundant in diseased individuals (Li et al, 2017). 249
The imbalances in the protective commensal microbial community can be induced by changes in the environment, including water 250
conditions, temperature, seasonal changes, climate change, antibiotic usage or changes in rearing conditions. Another disturbance could be 251
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infection by a primary pathogen that causes a microbial imbalance, and which allows a secondary pathogen to invade. This was shown in a 252
large study where bacterial community shifts occurred in the skin mucus during salmon lice infection in Atlantic salmon post-smolts and a 253
higher abundance of genera containing potential secondary bacterial pathogens (Pseudomonas, Flavobacterium) was observed in fish with 254
high lice infestation (Llewellyn et al., 2017). A similar phenomenon was observed in Atlantic salmon eggs in which the Saprolegnia-infected 255
eggs showed higher abundance of potential bacterial fish pathogens (Vibrio, Aeromonas) (Liu et al., 2014). 256
Next to host factors involved in protection against pathogens, commensal microbes play important functions that contribute to host 257
health and protection against pathogens (Merrifield & Rodiles, 2015, Parra et al., 2015, Salinas, 2015, Xu et al., 2016). These functions include 258
direct protective effects against pathogens via antibiosis, competition for resources or niche exclusion, but also indirect effects by stimulating 259
the host immune response and nutrient uptake thereby increasing fish health (Figure 1). 260
261
Direct effects of microbiota on pathogens 262
Commensal microbes may prevent pathogen infection by several mechanisms, including 1) niche exclusion, as was reported for several 263
probiotic bacteria which colonized mucosal tissues and occupied infection sites; 2) competition for essential resources, including nutrients and 264
iron; and 3) antibiosis (Verschuere et al., 2000, Ibrahem, 2015, Banerjee & Ray, 2017). Iron is essential for growth and microorganisms acquire 265
iron by producing iron-chelating compounds (siderophores). Commensal microbes can compete with pathogens via siderophores with a higher 266
affinity for iron (Ahmed & Holmström, 2014) or by cross-feeding on the siderophores produced by the pathogen (Raaijmakers et al., 1995). 267
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Next to niche exclusion and competition, commensal microorganisms can antagonize pathogens via the production of antimicrobial 268
compounds, also referred to as antibiosis. Various studies have shown that several members of the fish gut microbiome produce compounds 269
that inhibit the growth of pathogens (Sugita et al., 1997, Ringø et al., 2000, Liu et al., 2010, Caruffo et al., 2015). For example, the cell-free 270
supernatant of more than 70% of the lactic acid isolates obtained from the gut of Atlantic salmon had the ability to inhibit growth of the fish 271
pathogen Aeromonas salmonicida (Ringø & Holzapfel, 2000). In addition, metagenomic analyses of the seabass gut microbiome showed an 272
increased proportion of genes encoding antimicrobial compounds, like beta-lactamases, upon stress caused by starvation (Xia et al., 2014). 273
Several skin bacterial isolates of rainbow trout, for example Arthrobacter, Psychrobacter and Pseudococcus isolates, inhibited the growth of 274
Saprolegnia australis and Mucor hiemalis in in vitro dual culture assays, or when testing cell-free supernatants (Lowrey et al., 2015, Salinas, 275
2015). Also, Frondihabitans and Pseudomonas species protected Atlantic salmon eggs from Saprolegnia diclina infection, most likely by 276
competitive niche exclusion and the production of lipopeptide surfactants with zoosporidical and growth-inhibitory activities (Liu et al., 2014, Liu 277
et al., 2015). Collectively, these studies indicate that direct effects of commensal members of the microbiome contribute to the protection of fish 278
against pathogens. 279
280
Indirect effects of microbiota on pathogens: modulation of host immune responses 281
Fish possess an immune system similar to other vertebrates combining innate (natural) and acquired (adaptive) immunity. However, the 282
immune system of fish also has several differences compared to the mammalian immune system, and even has differences between fish 283
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species. For example, in fish, bone marrow and lymph nodes are not present and the major immune organs are the thymus, the head kidney 284
(bone marrow equivalent) and spleen (Secombes & Wang, 2012). In general, innate immunity does not require prior exposure to be effective 285
and cells of the innate immune system (neutrophils, macrophages, natural killer cells amongst others) can thus respond immediately. Fish are 286
considered to rely relatively strongly on innate immunity, especially at lower temperatures (Magnadottir, 2006). Adaptive immunity, in contrast, 287
is mediated largely by lymphocytes and is characterised by memory and therefore is slower in its response. This is not any different for the fish 288
immune system (Zhu et al., 2013). Innate immune cells of fish, in particular phagocytic cell types such as neutrophils and macrophages, which 289
are similar to innate immune cells of other vertebrates, can express several different receptors for recognition of a variety of patterns expressed 290
by bacterial, viral and fungal pathogens (microbial-associated molecular patterns (MAMPs)). These patterns can include, among others, 291
microbe-derived surface molecules such as lipoproteins, lipopolysaccharides, peptidoglycan, and bacterial flagellin, but can also include 292
microbe-derived double-stranded RNA or unmethylated CpG motifs in bacterial DNA (Pietretti & Wiegertjes, 2014). In general, phagocytic 293
receptors will mediate ingestion, whereas sensing receptors mediate recognition; the complete process is targeted to destroy phagocytosed 294
microbes (Neumann et al., 2001). Subsequently, antigen-presenting cells, including macrophages, present fragments of the ingested 295
pathogens to T lymphocytes which subsequently secrete cytokines to direct protective immunity, which is similar to warm-blooded vertebrates. 296
Both T and B lymphocytes typically employ receptors based on rearranged genes, building unique and highly specific T- and B-cell receptors 297
on lymphocytes (Magadan et al., 2015). With the appropriate cytokine help, B lymphocytes differentiate into plasma cells, secreting large 298
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quantities of specific immunoglobulins (Ig, or antibodies). Both T and B lymphocytes can differentiate into memory cells, leading to highly 299
specific secondary immune responses. 300
Commensal microbes play an important role in shaping the immune response against pathogens. Several yeasts have been shown to 301
stimulate the immune response, growth, development and metabolism of the fish hosts due to cell wall components like β-glucans and chitin 302
(Gatesoupe, 2007, Petit & Wiegertjes, 2016). As in humans (Nutsch & Hsieh, 2012), the immune system is able to distinguish between 303
commensals and pathogens in fish, by activating specific pathways and cytokines upon pathogen attack (Gomez et al., 2013, Kelly & Salinas, 304
2017). It has been proposed that Igs are important for the immune system to differentiate between commensal microbiota and pathogens, 305
since the majority of the microbes in mucosal tissues of fish have been found coated with host Igs (Zhang et al., 2010, Xu et al., 2013). The 306
microbiota are coated with different Ig isotypes, depending on the exact mucosal tissue (Gomez et al., 2013, Tacchi et al., 2014), suggesting 307
that mucosal tissues in fish may have their own specific adaptive immunity (Salinas, 2015). Upon colonization of zebrafish larvae, commensal 308
bacteria were shown to elicit a mild inflammatory reaction, induce genes involved in priming of the innate immunity (Galindo-Villegas et al., 309
2012, Chu & Mazmanian, 2013), and activate the innate immune response (Nayak, 2010, Maynard et al., 2012, Montalban-Arques et al., 310
2015). The zebrafish gut microbiota, although different from the mammalian microbiota in terms of dominant phyla, induces a conserved host 311
response during colonization and development and the composition of the gut microbiota clearly affects the inflammatory response (reviewed 312
in Brugman et al., 2009). With regard to the very early stages of fish development, fish eggs lack adaptive immunity and have to rely on 313
maternally transferred Ig and components of the complement system or rely on innate immune factors of their own, such as lectins and 314
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lysozyme (Hansen & Olafsen, 1999, Huttenhuis et al., 2006, Løvoll et al., 2006). Therefore, it is expected that the microbiome of fish eggs have 315
a more direct effect in the defence against pathogens, which was shown for the pathogen Saprolegnia on salmon eggs (Liu et al., 2014). 316
317
Indirect effects of microbiota on fish health: modulation of nutrient uptake 318
Commensal gut microbes also aid the fish in nutrient acquisition (Nayak, 2010, Montalban-Arques et al., 2015, Borrelli et al., 2016). Germ-free, 319
gnotobiotic zebrafish have a reduced number of goblet and enteroendocrine cells in the gut, resulting in larvae defective in the uptake of 320
protein macromolecules (Bates et al., 2006). As a consequence, germ-free zebrafish had a lower body weight, lived shorter and exhibited 321
anxiety-like behaviour (Montalban-Arques et al., 2015). The gut microbes can produce exogenous enzymes to facilitate the digestion of food 322
and degradation of large and complex molecules, such as chitin, protein and starch (Austin, 2006, Nayak, 2010, Ray et al., 2012, Merrifield & 323
Rodiles, 2015, Montalban-Arques et al., 2015). The presence of short chain fatty acids (SFCA), which is implicated to be important for gut 324
functioning and immune stimulation in both mammalian and fish gut, indicate fermentation of sugars by the gut microbes, mainly lactic acid 325
bacteria (Montalban-Arques et al., 2015). In a study combining 16S rRNA gene sequencing and metabolomics, the gut microbial and 326
metabolome profiles of five species of carp significantly correlated and showed for example that lactic and phosphoric acid could be correlated 327
with a higher Clostridium content (Li et al., 2017b). The gut microbes can also produce vitamins and eicosapentaenoic acid (EPA, an omega-3 328
fatty acid that is essential for metabolism) to enhance the health of the host (Austin, 2006). Protozoa have been detected microscopically in the 329
fish gut of surgeonfish (Naso tonganus) that contain food vacuoles ingesting bacteria and flagellates (Grim, 2006) and are postulated as 330
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potential contributors to the fish gut composition and nutrient uptake, but more research is needed to determine their functions for the hosts 331
(Romero et al., 2014). The gut community of rainbow trout contained more Firmicutes in fish with a plant-fed diet compared to a high 332
abundance of Bacteriodetes, Proteobacteria and Actinobacteria in the guts of fish with a marine-fed diet. When challenged with pathogenic 333
Yersinia ruckeri, the survival was not affected by diet type, however, a higher abundance was observed of the genus Yersinia in the guts of the 334
marine-fed fish, as well as higher IL1β and Mbl2 gene transcription (Ingerslev et al., 2014a). This suggests that the type of diet influences the 335
microbial population and could potentially promote the microbial subpopulation providing protection against pathogens. 336
337
Outlook 338
Fish tissues are home to diverse microbial communities whose composition is influenced by ambient water quality (i.e. pH, oxygen levels, 339
salinity), environmental factors (i.e. season, temperature), host age, host genotype, feeding strategy and rearing conditions (feed, stress, 340
antibiotics usage) (Figure 1). Similar to the human microbiome, a high percentage of variation in microbiome composition is observed between 341
individual fish belonging to the same species (Bolnick et al., 2014b, Givens et al., 2015, Schmidt et al., 2015). For example, the relative 342
abundance of the Proteobacteria ranged from 1% in one individual up to 98% of another individual in stickleback (Bolnick et al., 2014b). Even 343
under controlled laboratory conditions, it can be difficult to control the composition of microbial populations between replicate tanks (Giatsis et 344
al., 2014, Giatsis et al., 2016, Schmidt et al., 2016). This high variation between and within studies complicates the identification of keystone 345
microbial species involved in fish disease protection. 346
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Comparing the microbiota of healthy and diseased fish belonging to the same species that are in the same developmental stage and 347
are kept under the same conditions is one of the approaches to identify microbiota and mechanisms involved in disease protection. Only few 348
microbiome studies comparing healthy and diseased fish have been described (Table 1) and therefore it is difficult to get a comprehensive 349
picture which microbes or microbial consortia are most promising for disease protection. Moreover, classic microbiological techniques, 350
including isolations and functional characterisation of single microbial isolates or consortia, will be required to validate the potential functions of 351
the microbiota in fish health and to test their efficacy in aquaculture. 352
Microbes are diverse and several can perform the same function. Hence, it might not be that important who is there, but more what they 353
are doing (Louca et al., 2016, Moya & Ferrer, 2016). Therefore, the challenge is to study ‘function over phylogeny’ (Gibbons, 2017) by moving 354
away from only a taxonomic description of the microbiota. Instead, studying functional characteristics that are most important in the direct or 355
indirect protection of fish against pathogens should be investigated. This can be achieved by studying the frequency and diversity of 356
biosynthetic gene clusters, their transcription, and the in situ production of the corresponding proteins and metabolites (Franzosa et al., 2015). 357
Combining these technologies will minimize the over- or underrepresentation of certain bacterial families caused by DNA extraction methods 358
(Kashinskaya et al., 2017) and PCR-bias when only investigating rRNA amplicon sequencing (Chakravorty et al., 2007, Sinclair et al., 2015, 359
Stoddard et al., 2015). These approaches will provide a better insight in the disease ecology and microbial functional potential of the fish 360
microbiota and enable to search for keystone microbes, microbial consortia and traits involved in disease protection that can be either 361
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augmented in the indigenous microbial population or introduced as probiotics for sustainable protection against (re-)emerging fish diseases 362
(Bentzon‐Tilia et al., 2016, Stentiford et al., 2017). 363
The selection of probiotics is tedious and need to fulfil many requirements, including pH tolerance, colonization ability and efficacy 364
(Banerjee & Ray, 2017). Prebiotics are indigestible carbohydrates that stimulate specific beneficial microbes during hydrolysis in the gut, 365
stimulating fish health (Song et al., 2014, Akhter et al., 2015). Synbiotics (Gibson & Roberfroid, 1995) entail a combination of pre- and 366
probiotics where the prebiotic is included to stimulate the colonization and/or immune-stimulatory activity of the probiotic, and is currently 367
receiving increased attention (Ringø & Song, 2016, Huynh et al., 2017). The underlying mechanisms of the pre-, pro- or synbiotics will still need 368
clarification, but these approaches, in combination with the production shifts to recirculation aquaculture systems (RAS) to stabilise the 369
environmental conditions like temperature and salinity, will have a high potential towards more sustainable land-based forms of aquaculture. 370
Another approach is host-mediated microbiome engineering (Mueller & Sachs, 2015), which describes the steering of the microbiome towards 371
an increased host performance by artificial selection of the microbiomes over multiple generations. Nowadays, the use of probiotics focuses on 372
the application in fish feed, however, also external applications should be considered to boost the skin immune response against skin diseases 373
caused by fungi and other parasites. 374
Overall, it is evident that the fish microbiome has enormous potential for fish health, helping the host in its defence against pathogen 375
colonization and infection. A mechanistic understanding of how specific microbes or microbial consortia, including their metabolites, act against 376
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pathogens and trigger the fish immune response may provide practical means to engineer the indigenous fish microbiome for enhancing 377
disease control and fish health. 378
379
Acknowledgements 380
This work was financially supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 381
634429 ParaFishControl (Advanced Tools and Research Strategies for Parasite Control in European farmed fish) and the NWO Applied and 382
Engineering sciences (project 14224). This output reflects only the authors’ view and the European Union cannot be held responsible for any 383
use that may be made of the information contained therein. This manuscript is publication number xxxx of Netherlands Institute of Ecology 384
(NIOO-KNAW). All authors declare no conflict of interest. 385
386
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Table 1. Overview of studies comparing the fish microbiomes of healthy and diseased individuals.
Host Tissue Disease Technique Reference
Atlantic salmon (Salmo salar) eggs Saprolegniosis 16S rRNA - Phylochip Liu et al., 2014
skin Salmon lice 16S rRNA - Illumina MiSeq
Llewellyn et al., 2017
Largemouth bronze gudgeon (Coreius guichenoti)
gut Furunculosis 16S rRNA - Illumina MiSeq
Li et al., 2016
Seahorse (Hippocampus spp.) gut Intestinal disease 16S rRNA - DGGE Li et al., 2015 Crucian carp (Carassius auratus)
gut Red-Operculum 16S rRNA - Illumina MiSeq
Li et al., 2017
Rainbow trout (Oncorhynchus mykiss)
gut Yersinia 16S rRNA - Illumina HiSeq
Ingerslev et al., 2014a
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Figure legends Figure 1. Schematic overview of different life-support functions of the fish microbiome and the impact of the host and ambient environment on the microbiome diversity, assembly and functions.
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Host immune response Protection against
pathogens
Factors that shape
microbiome
Nutrient acquisition
Host environment
Growth and development
Host genotype
Tolerance to abiotic stress
Functionality of microbiome
Fish microbiome
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Supplementary table 1. Overview of studies describing fish microbiome analyses by next generation sequencing methods.
Host Tissue Aim of study Technique Reference
Atlantic cod (Gadus morhua) gut host development, origin of microbiota
16S rRNA - 454 Bakke et al., 2015
variation between individuals 16S rRNA - 454 Star et al., 2013
Atlantic salmon (Salmo salar) gut description community 16S rRNA - Ion Torrent Gajardo et al., 2016
diet 16S rRNA - 454 Zarkasi et al., 2016
diet 16S rRNA - Illumina HiSeq Schmidt et al., 2016
geographical origin 16S rRNA - Illumina MiSeq Llewellyn et al., 2016
rearing environment 16S rRNA - Illumina MiSeq Dehler et al., 2017
temperature environment 16S rRNA - 454 Zarkasi et al., 2014
skin rearing environment 16S rRNA - Ion Torrent Lokesh & Kiron, 2016
Salmon lice-diseased vs healthy 16S rRNA - Illumina MiSeq Llewellyn et al., 2017
Atlantic sharpnose (Rhizoprionodon terraenovae)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Bighead carp (Hypophthalmichthys nobilis)
gut feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
host comparison 16S rRNA - 454 Li et al., 2014
host comparison 16S rRNA - 454 Li et al., 2015
host genotype 16S rRNA - 454 Li et al., 2017a
rearing environment, diet, host 16S rRNA - Illumina HiSeq Eichmiller et al., 2016
Black molly (Poecilia sphenops)
entire fish
salinity 16S rRNA - Illumina HiSeq Schmidt et al., 2015
Black sea bass (Centropristis striata)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Bluegill (Lepomis macrochirus) gut host comparison 16S rRNA - 454 Larsen et al., 2014
Blunt snout bream (Megalobrama amblycephala)
gut feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
host genotype 16S rRNA - 454 Li et al., 2017b
Brown trout (Salmo trutta) eggs host genotype, environment 16S rRNA - Illumina MiSeq Wilkins et al., 2016
geographical origin 16S rRNA - 454 Wilkins et al., 2015
Butterflyfish (Chaetodonlunulatus lunulatus, C. ornatissimus, C. reticulatus and C. vagabundus)
gill host comparison 16S rRNA - 454 Reverter et al., 2017
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Catfish (Panaque) gut diet 16S rRNA - 454 Di Maiuta et al., 2013
Channel catfish (Ictalurus punctatus)
gut host comparison 16S rRNA - 454 Larsen et al., 2014
Chinese perch (Siniperca chuatsi)
gut feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
host comparison, host development 16S rRNA - Illumina MiSeq Yan et al., 2016
Cichlid (Amphilophus astorquii, A. zaliosus, A. amarillo, A. sagittae)
gut geographic origin, limnetic vs benthic
16S rRNA - Illumina MiSeq Franchini et al., 2014
Cichlid (Haplotaxodon microlepis, H. trifasciatus, Plecodus straeleni, Perissodus microlepis, P. eccentricus)
gut host comparison, diet 16S rRNA - 454 Baldo et al., 2015
Clownfish (Amphiprion percula)
heads effect suspended sediment 16S rRNA - 454 Hess et al., 2015
Common carp (Cyprinus carpio)
gut transgenic gcGH 16S rRNA - 454 Li et al., 2013
description community 16S rRNA - 454 van Kessel et al., 2011
feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
rearing environment, diet, host 16S rRNA - Illumina HiSeq Eichmiller et al., 2016
Crevalle jack (Caranx hippos) gut host comparison 16S rRNA - 454 Givens et al., 2015
Crucian carp (Carassius cuvieri)
gut host genotype 16S rRNA - 454 Li et al., 2017b
Red-Operculum-diseased vs healthy
16S rRNA - Illumina MiSeq Li et al., 2017b
host comparison 16S rRNA - 454 Li et al., 2015
Eurasian perch (Perca fluviatilis)
gut diet (littoral carbon), sex 16S rRNA - 454 Bolnick et al., 2014b
Fathead minnows (Pimephales promelas)
gut antimicrobial treatment 16S rRNA - Illumina MiSeq Narrowe et al., 2015
Fine flounder (Paralichthys adspersus)
gut rearing environment 16S rRNA - Ion Torrent Ramírez & Romero, 2017a
Freshwater drum (Aplodinotus grunniens)
gut rearing environment, diet, host comparison
16S rRNA - Illumina HiSeq Eichmiller et al., 2016
Gibel carp (Carassius auratus gibelio)
gut environmental origin of microbiota 16S rRNA - 454 Wu et al., 2013
Gilthead seabream (Sparus gut diet 16S rRNA - 454 Estruch et al., 2015
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aurata) diet 16S rRNA - 454 Kormas et al., 2014
host development 16S rRNA - 454 Califano et al., 2017
Gizzard shad (Dorosoma cepedianum)
gut geographical origin 16S rRNA - 454 Ye et al., 2014
Goldfish (Carassius auratus) gut feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
rearing environment, diet, host 16S rRNA - Illumina HiSeq Eichmiller et al., 2016
Grass carp (Ctenopharyngodon idellus)
gut diet 16S rRNA - Illumina HiSeq Ni et al., 2014
environmental origin of microbiota 16S rRNA - 454 Wu et al., 2012
feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
host comparison 16S rRNA - 454 Li et al., 2015
host genotype 16S rRNA - 454 Li et al., 2017b
host comparison, host development 16S rRNA - Illumina MiSeq Yan et al., 2016
Great barracuda (Sphyraena barracuda)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Hogchoker (Trinectes maculatus)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Japanese seabass (Lateolabrax japonicus)
gut diet 16S rRNA - 454 Wang et al., 2017
King mackerel (Scomberomorus cavalla)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Largemouth bass (Micropterus salmoides)
gut host comparison 16S rRNA - 454 Larsen et al., 2014
Largemouth bronze gudgeon (Coreius guichenoti)
gut Furunculosis-diseased vs healthy 16S rRNA - Illumina MiSeq Li et al., 2016
Mahi-mahi (Coryphaena hippurus)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Mummichog (Fundulus heteroclitus)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Nile tilapia (Oreochromis niloticus; genetically improved farmed)
gut origin of microbes 16S rRNA - 454 Fan et al., 2017
Nile tilapia (Oreochromis niloticus)
gut diet 16S rRNA - 454 Ran et al., 2016
enzyme and probiotic supplementation
16S rRNA - Ion Torrent Adeoye et al., 2016
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host development and environment 16S rRNA - 454 Giatsis et al., 2014
host development, environment and probiotic
16S rRNA - 454 Giatsis et al., 2016
probiotic 16S rRNA - 454 Ran et al., 2015
probiotic 16S rRNA - Ion Torrent Standen et al., 2015
rearing environment 16S rRNA - 454 Giatsis et al., 2015
salinity 16S rRNA - Illumina HiSeq Zhang et al., 2016
vertebrate comparison 16S rRNA - Illumina HiSeq Kohl et al., 2014
Paddlefish (Polyodon spathala)
gut host comparison 16S rRNA - 454 Li et al., 2014
Parrotfish (Chlorurus sordidus, Scarus niger)
gut host comparison, feeding strategy 16S rRNA - 454 Miyake et al., 2015
Pinfish (Lagodon rhomboides) gut host comparison 16S rRNA - 454 Givens et al., 2015
Prussian carp (Carassius gibelio)
gut
environmental origin of microbiota 16S rRNA - Illumina MiSeq Kashinskaya et al., 2015
validation DNA extraction methods 16S rRNA - 454 Kashinskaya et al., 2017
Rabbitfish (Siganus stellatus) gut host, feeding strategy 16S rRNA - 454 Miyake et al., 2015
Rainbow trout (Oncorhynchus mykiss)
gut description community 16S rRNA - 454 Etyemez & Balcazar, 2015
description community 16S rRNA - Illumina MiSeq Lyons et al., 2017a
diet 16S rRNA - Illumina HiSeq Ingerslev et al., 2014b
diet 16S rRNA - Illumina MiSeq Lyons et al., 2017b
diet 16S rRNA - Illumina MiSeq Michl et al., 2017
diet 16S rRNA - 454 Desai et al., 2012
diet, Yersinia-infection 16S rRNA - Illumina HiSeq Ingerslev et al., 2014a
diet, rearing density 16S rRNA - 454 Wong et al., 2013
rearing environment 16S rRNA - Illumina MiSeq Lyons et al., 2017a
skin, gill, gut, olfactory organ
tissue specificity 16S rRNA - 454 Lowrey et al., 2015
Red drum (Sciaeops ocellatus) gut host comparison 16S rRNA - 454 Givens et al., 2015
Red Snapper (Lutjanus campechanus)
gill, gut, blood
description community 16S rRNA - 454 Tarnecki et al., 2016
Sandbar shark (Carcharhinus gut host comparison 16S rRNA - 454 Givens et al., 2015
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plumbeus)
Seabass (Dicentrarchus labrax)
gut diet 16S rRNA - 454 Carda-Dieguez et al., 2014
skin mucus
geographical origin 16S rRNA - 454 Pimentel et al., 2017
Siberian sturgeon (Acipenser baerii)
gut
prebiotic, probiotic 16S rRNA - 454 Geraylou et al., 2013a
prebiotic 16S rRNA - 454 Geraylou et al., 2013b
Silver carp (Hypophthalmichthys molitrix)
gut
feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
host genotype 16S rRNA - 454 Li et al., 2017b
rearing environment, diet, host 16S rRNA - Illumina HiSeq Eichmiller et al., 2016
geographical origin 16S rRNA - 454 Ye et al., 2014
Silver perch (Bairdiella chrysoura)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Southern catfish (Silurus meridionalis)
gut host comparison, host development 16S rRNA - Illumina MiSeq Yan et al., 2016
Southern flounder (Paralichthys lethostigma)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Spanish mackerel (Scomberomorus maculatus)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Spinner shark (Carcharhinus brevipinna)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Spotted coral grouper (Epinephelus sexfasciatus)
gut host comparison, polluted environment
16S rRNA - Illumina MiSeq Hennersdorf et al., 2016b
Striped burrfish (Chilomycterus schoepfi)
gut host comparison 16S rRNA - 454 Givens et al., 2015
Surgeonfish (Acanthurus gahhm, A. nigrofuscus, A. sohal, Ctenochaetus striatus, Naso elegans, N. hexacanthus, N. unicornis, Zebrasoma desjardinii, Z. xanthurum)
gut host comparison, feeding strategy 16S rRNA - 454 Miyake et al., 2015
Tambaqui (Colossoma macropomum)
gut, skin pH effect 16S rRNA - Illumina MiSeq Sylvain et al., 2016
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Threespine stickleback (Gasterosteus aculeatus)
gut diet (littoral carbon), sex 16S rRNA - 454 Bolnick et al., 2014b
MHC genotype 16S rRNA - Illumina HiSeq Bolnick et al., 2014a
probiotics and host genotype 16S rRNA - Illumina MiSeq Smith et al., 2015
Tiger grouper (Epinephelus fuscoguttatus)
gut
environment 16S rRNA - Illumina MiSeq Hennersdorf et al., 2016a
host comparison, polluted environment
16S rRNA - Illumina MiSeq Hennersdorf et al., 2016b
Topmouth culter (Culter alburnus)
gut feeding strategy 16S rRNA - Illumina MiSeq Liu et al., 2016
Turbot (Scophthalmus maximus)
gut taxonomic and functional diversity Total DNA - Illumina HiSeq Xing et al., 2013
Western mosquitofish (Gambusia affinis)
gut antibiotic treatment 16S rRNA - Illumina HiSeq Carlson et al., 2015
Yellowtail amberjack (Seriola lalandi)
gut rearing environment 16S rRNA - Ion Torrent Ramírez & Romero, 2017b
Yellowtail scad (Atule mate) gut host, polluted environment 16S rRNA - Illumina MiSeq Hennersdorf et al., 2016b
Zebrafish (Danio rerio) gut behavior, stress, probiotic 16S rRNA - Illumina MiSeq Davis et al., 2016
diet 16S rRNA - 454 Rurangwa et al., 2015
diet 16S rRNA - Illumina HiSeq Wong et al., 2015
diet 16S rRNA - Illumina MiSeq Gaulke et al., 2016
diet 16S rRNA - 454 Semova et al., 2012
host development 16S rRNA - Illumina HiSeq Stephens et al., 2016
probiotic treatment 16S rRNA - Ion Torrent Borrelli et al., 2016
rearing environment 16S rRNA - 454 Roeselers et al., 2011
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