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For Peer Review http://mc.manuscriptcentral.com/fems 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 ScholarOne Support 1-434/964-4100 FEMS Microbiology Ecology

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Page 1: For Peer Review - pure.knaw.nl · Raaijmakers, Jos; Netherlands Institute of Ecology, Microbial Ecology Keywords: aquaculture, beneficial microbes, microbiomes, emerging diseases,

For Peer Review

http://mc.manuscriptcentral.com/fems

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

ScholarOne Support 1-434/964-4100

FEMS Microbiology Ecology

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For Peer Review

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

15

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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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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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