The animal gastrointestinal tract fosters a vast and complex population of microbes known as the gut microbiota, which plays crucial roles in host health and development. Microbial ecologists have used next generation sequencing (NGS) technologies to gather data on diverse microbial communities from all kinds of environmental samples. Consequently, much attention has focused on using bacterial symbiosis in the fish gut to elucidate host-microbe interactions, and its responses to environmental and host-specific factors. However, little is known about how fish gut microbiota respond when their fish hosts migrate or move across habitats. The grey mullet (Mugil cephalus L.) is an important fishery and aquaculture species in many countries. The species is a well-known catadromous species that migrates several times over its different life stages. For example, grey mullet eggs are laid in seawater environment, young fish first develop in the ocean and then migrate to brackish and freshwater to grow into adults before migrating back into ocean to reproduce during the breeding season. Interestingly, three grey mullet cryptic species migrate into the Taiwan strait from various migration routes to produce offspring. This fascinating life history–involving crossing between ecosystems makes the grey mullet an ideal model organism for studying the influence of migration and salinity transition on the structure of gut microbiota. Therefore, I conducted a comprehensive study in five chapters to investigate the influence of migration and changes in water regimes on the gut microbial community of the grey mullet.

The first chapter includes background information and objectives of the study, and the second presents our findings on the diversity and composition of gut microbial communities in wild migrating fish into breeding grounds to clarify how host genetic background and historical environmental microflora influences on the the fish gut microbiota composition. We found that the bacteria in the gut communities of three cryptic species of the M. cephalus species complex are strongly influenced by host genetic variations, while long-distance migration governs the structure of the gut microbiota. Our results suggest that rapidly changes in salinity are an important factor shaping the fish gut microbial communities.

For that reason, in Chapter 3, I mainly focus on how salinity change affects the structure and composition of gut microflora by examining an artificial transition from seawater to freshwater. Our results revealed that the transitioned fish had a different bacterial community compared to the fish maintained in seawater. Furthermore, microbial interaction networks were generated to deeply understand how microbial interactions change in response to environmental perturbation. Using the generalized Lotka-Volterra model, we generated two different complex interaction networks in the two treated groups, and found that many rare and low-abundant species were actually very important in the community because they formed a high number of connections to other microbial members. These results suggest that changes in salinity not only strong influence the complexity of the gut community, but also enhance the roles of keystone taxa in interaction networks.

To validate the robustness of the interaction network model, Chapter 4 describes feeding trials using Enterococcus faecalis as a representative of the keystone taxa Enterococcaceae to validate the interactions inferred in the previous chapter. The changes in the relative abundance of Enterococcaceae and the bacterial families they interact with are investigated to clarify their relationships. Finally, in Chapter 5 thesis, I provide some general conclusions and discuss ways to improve our “observation-modelling-validation” framework to make it into a method for investigating gut microbiota dynamics that will be a tool to 1) predict the stability and reactivity of microbial populations in response to environmental disturbance and, 2) identify the key microbial interactions that have the potential to be widely applied in aquaculture.

Alberdi, A., Aizpurua, O., Bohmann, K., Zepeda-Mendoza, M. L., & Gilbert, M. T. P. (2016). Do vertebrate gut metagenomes confer rapid ecological adaptation?. Trends in ecology & evolution, 31(9), 689-699.
Allameh, S. K., Ringø, E., Yusoff, F. M., Daud, H. M., & Ideris, A. (2014). Properties of Enterococcus faecalis, a new probiotic bacterium isolated from the intestine of snakehead fish (Channa striatus Bloch). African Journal of Microbiology Research, 8(22), 2215-2222.
Alshawaqfeh, M., Serpedin, E., & Younes, A. B. (2017). Inferring microbial interaction networks from metagenomic data using SgLV-EKF algorithm. BMC genomics, 18(3), 228.
Annamalai, N., Kumar, A., Saravanakumar, A., Vijaylakshmi, S., & Balasubramanian, T. (2011). Characterization of protease from Alcaligens faecalis and its antibacterial activity on fish pathogens. Journal of environmental biology, 32(6), 781.
Austin, B. (2006). The bacterial microflora of fish, revised. TheScientificWorldJournal, 6, 931-945.
Banerjee, S., Schlaeppi, K., & van der Heijden, M. G. (2018). Keystone taxa as drivers of microbiome structure and functioning. Nature Reviews Microbiology, 16(9), 567-576.
Baños, A., Ariza, J. J., Nuñez, C., Gil-Martínez, L., García-López, J. D., Martínez-Bueno, M., & Valdivia, E. (2019). Effects of Enterococcus faecalis UGRA10 and the enterocin AS-48 against the fish pathogen Lactococcus garvieae. Studies in vitro and in vivo. Food Microbiology, 77, 69-77.
Barberán, A., Casamayor, E. O., & Fierer, N. (2014). The microbial contribution to macroecology. Frontier in Microbiology (5): 203.
Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. Icwsm, 8(2009), 361-362.
Bell, G. R., Hoskins, G. E., & Hodgkiss, W. (1971). Aspects of the characterization, identification, and ecology of the bacterial flora associated with the surface of stream-incubating Pacific salmon (Oncorhynchus) eggs. Journal of the Fisheries Board of Canada, 28(10), 1511-1525.
Binder, T. R., Cooke, S. J. & Hinch, S. G. (2011). The Biology of Fish Migration. In: Farrell A.P., (ed.), Encyclopedia of Fish Physiology: From Genome to Environment. 3, 1921–1927. Academic Press, San Diego.
Borruel, N., Manichanh, C., Burgdorf, K. S., Arumugam, M., Raes, J. J., Li, R. Q., & Qin, J. J. (2010). A human gut microbial gene catalogue established by metagenomic sequencing [J]. Nature, 464(7285), 59-65.
Braga, R. M., Dourado, M. N., & Araújo, W. L. (2016). Microbial interactions: Ecology in a molecular perspective. Brazilian Journal of Microbiology, 47, 86-98.
Bron, P. A., Van Baarlen, P., & Kleerebezem, M. (2012). Emerging molecular insights into the interaction between probiotics and the host intestinal mucosa. Nature Reviews Microbiology, 10(1), 66-78.
Bucci, V., Tzen, B., Li, N., Simmons, M., Tanoue, T., Bogart, E., ... & Olle, B. (2016). MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses. Genome biology, 17(1), 1-17.
Buffie, C. G., Bucci, V., Stein, R. R., McKenney, P. T., Ling, L., Gobourne, A., ... & Littmann, E. (2015). Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature, 517(7533), 205-208.
Butt, R. L., & Volkoff, H. (2019). Gut microbiota and energy homeostasis in fish. Frontiers in endocrinology, 10, 9.
Byadgi, O., Chen, Y. C., Barnes, A. C., Tsai, M. A., Wang, P. C., & Chen, S. C. (2016). Transcriptome analysis of grey mullet (Mugil cephalus) after challenge with Lactococcus garvieae. Fish & Shellfish Immunology, 58, 593-603.
Cardona, L. (2000). Effects of salinity on the habitat selection and growth performance of Mediterranean flathead grey mullet Mugil cephalus (Osteichthyes, Mugilidae). Estuarine, Coastal and Shelf Science, 50(5), 727-737.
Chen, C. Y., Chen, P. C., Weng, F. C. H., Shaw, G. T. W., & Wang, D. (2017). Habitat and indigenous gut microbes contribute to the plasticity of gut microbiome in oriental river prawn during rapid environmental change. PloS one, 12(7), e0181427.
Chow, C. E. T., Sachdeva, R., Cram, J. A., Steele, J. A., Needham, D. M., Patel, A., ... & Fuhrman, J. A. (2013). Temporal variability and coherence of euphotic zone bacterial communities over a decade in the Southern California Bight. The ISME journal, 7(12), 2259-2273.
Coyte, K. Z., Schluter, J., & Foster, K. R. (2015). The ecology of the microbiome: networks, competition, and stability. Science, 350(6261), 663-666.
Cram, J. A., Chow, C. E. T., Sachdeva, R., Needham, D. M., Parada, A. E., Steele, J. A., & Fuhrman, J. A. (2015). Seasonal and interannual variability of the marine bacterioplankton community throughout the water column over ten years. The ISME journal, 9(3), 563-580.
De Silva, S. S. (1980). Biology of juvenile grey mullet: a short review. Aquaculture, 19(1), 21-36.
Dehler, C. E., Secombes, C. J., & Martin, S. A. (2017). Seawater transfer alters the intestinal microbiota profiles of Atlantic salmon (Salmo salar L.). Scientific reports, 7(1), 1-11.
Dong, Y., Zhao, Y., Zhang, W., Li, Y., Zhou, F., Liu, C., ... & Xiao, T. (2014). Bacterial diversity and community structure in the East China Sea by 454 sequencing of the 16S rRNA gene. Chinese Journal of Oceanology and Limnology, 32(3), 527-541.
Durand, J. D., Shen, K. N., Chen, W. J., Jamandre, B. W., Blel, H., Diop, K., ... & Borsa, P. (2012). Systematics of the grey mullets (Teleostei: Mugiliformes: Mugilidae): molecular phylogenetic evidence challenges two centuries of morphology-based taxonomy. Molecular Phylogenetics and Evolution, 64(1), 73-92.
Edwards, D. K., Jasny, E., Yoon, H., Horscroft, N., Schanen, B., Geter, T., ... & Wittman, V. (2017). Adjuvant effects of a sequence-engineered mRNA vaccine: translational profiling demonstrates similar human and murine innate response. Journal of Translational Medicine, 15(1), 1-18.
El-Jeni, R., Böhme, K., El Bour, M., Calo-Mata, P., Kefi, R., Barros-Velázquez, J., & Bouhaouala-Zahar, B. (2019). Rapid genus identification of selected lactic acid bacteria isolated from Mugil cephalis and Oreochromis niloticus organs using MALDI-TOF. Annals of Microbiology, 69(1), 1-15.
Engel, P., & Moran, N. A. (2013). The gut microbiota of insects–diversity in structure and function. FEMS microbiology reviews, 37(5), 699-735.
Fan, P., Bian, B., Teng, L., Nelson, C. D., Driver, J., Elzo, M. A., & Jeong, K. C. (2020). Host genetic effects upon the early gut microbiota in a bovine model with graduated spectrum of genetic variation. The ISME journal, 14(1), 302-317.
FAO. (2016). The state of world fisheries and aquaculture 2016. Contributing to food security and nutrition for all. FAO, Rome. ISBN 978-92-5-109185-2, 1–190. www.fao.org/3/a-i5555e.pdf.
Faust, K., & Raes, J. (2012). Microbial interactions: from networks to models. Nature Reviews Microbiology, 10(8), 538-550.
Fisher, C. K., & Mehta, P. (2014). Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression. PloS one, 9(7), e102451.
Friedman, J., & Alm, E. J. (2012). Inferring correlation networks from genomic survey data. PLoS Comput Biol, 8(9), e1002687.
Fuhrman, J. A. (2009). Microbial community structure and its functional implications. Nature, 459(7244), 193-199.
Fuhrman, J. A., Cram, J. A., & Needham, D. M. (2015). Marine microbial community dynamics and their ecological interpretation. Nature Reviews Microbiology, 13(3), 133-146.
Gao, X., Huynh, B. T., Guillemot, D., Glaser, P., & Opatowski, L. (2018). Inference of significant microbial interactions from longitudinal metagenomics data. Frontiers in Microbiology, 9, 2319.
Gaulke, C. A., & Sharpton, T. J. (2018). The influence of ethnicity and geography on human gut microbiome composition. Nature Medicine, 24(10), 1495-1496.
Giatsis, C., Sipkema, D., Smidt, H., Heilig, H., Benvenuti, G., Verreth, J., & Verdegem, M. (2015). The impact of rearing environment on the development of gut microbiota in tilapia larvae. Scientific Reports, 5(1), 1-15.
Givens, C. E., Ransom, B., Bano, N., & Hollibaugh, J. T. (2015). Comparison of the gut microbiomes of 12 bony fish and 3 shark species. Marine Ecology Progress Series, 518, 209-223.
Gómez, G. D., & Balcázar, J. L. (2008). A review on the interactions between gut microbiota and innate immunity of fish. FEMS Immunology & Medical Microbiology, 52(2), 145-154.
Gonze, D., Coyte, K. Z., Lahti, L., & Faust, K. (2018). Microbial communities as dynamical systems. Current Opinion in Microbiology, 44, 41-49.
Hai, N. V. (2015). The use of probiotics in aquaculture. Journal of Applied Microbiology, 119(4), 917-935.
Hamady, M., & Knight, R. (2009). Tools, techniques, and challenges Microbial community profiling for human microbiome projects. Genome Research, 19, 1141-1152.
Hamid, A., Sakuda, T., and Kakimoto, D. (1979). Microflora in the alimentary tract of gray mullet—4. Estimation of enzymic activity of the intestinal bacteria. Bulletin of the Japanese Society of Scientific Fisheries. 45: 99–106.
Haugland, R. A., Siefring, S. C., Wymer, L. J., Brenner, K. P., & Dufour, A. P. (2005). Comparison of Enterococcus measurements in freshwater at two recreational beaches by quantitative polymerase chain reaction and membrane filter culture analysis. Water Research, 39(4), 559-568.
He, Q., Hou, Q., Wang, Y., Li, J., Li, W., Kwok, L. Y., ... & Zhong, Z. (2018). Comparative genomic analysis of Enterococcus faecalis: insights into their environmental adaptations. BMC Genomics, 19(1), 527.
Herren, C. M., & McMahon, K. D. (2018). Keystone taxa predict compositional change in microbial communities. Environmental Microbiology, 20(6), 2207-2217.
Hervé, M. (2020). RVAideMemoire. R package version 0.9-74.
Hirano, H., & Takemoto, K. (2019). Difficulty in inferring microbial community structure based on co-occurrence network approaches. BMC Bioinformatics, 20(1), 1-14.
Hooper, L. V., & Macpherson, A. J. (2010). Immune adaptations that maintain homeostasis with the intestinal microbiota. Nature Reviews Immunology, 10(3), 159-169.
Hsiao, A., Ahmed, A. S., Subramanian, S., Griffin, N. W., Drewry, L. L., Petri, W. A., ... & Gordon, J. I. (2014). Members of the human gut microbiota involved in recovery from Vibrio cholerae infection. Nature, 515(7527), 423-426.
Hunt, D. E., & Ward, C. S. (2015). A network-based approach to disturbance transmission through microbial interactions. Frontiers in Microbiology, 6, 1182.
Ivanova, M. I., Sievers, S. A., Guenther, E. L., Johnson, L. M., Winkler, D. D., Galaleldeen, A., ... & Eisenberg, D. S. (2014). Aggregation-triggering segments of SOD1 fibril formation support a common pathway for familial and sporadic ALS. Proceedings of the National Academy of Sciences, 111(1), 197-201.
Jones, S. R. (2001). The occurrence and mechanisms of innate immunity against parasites in fish. Developmental & Comparative Immunology, 25(8-9), 841-852.
Karl, D. M., & Church, M. J. (2014). Microbial oceanography and the Hawaii Ocean Time-series programme. Nature Reviews Microbiology, 12(10), 699-713.
Karl, J. P., Hatch, A. M., Arcidiacono, S. M., Pearce, S. C., Pantoja-Feliciano, I. G., Doherty, L. A., & Soares, J. W. (2018). Effects of psychological, environmental and physical stressors on the gut microbiota. Frontiers in Microbiology, 9, 2013.
Karoline, F., Leo, L., & Didier, G. (2015). de Vos Willem M, Raes Jeroen. Metagenomics meets time series analysis: unraveling microbial community dynamics. Current Opinion in Microbiology, 25, 56-66.
Ke, D., Picard, F. J., Martineau, F., Ménard, C., Roy, P. H., Ouellette, M., & Bergeron, M. G. (1999). Development of a PCR assay for rapid detection of enterococci. Journal of Clinical Microbiology, 37(11), 3497-3503.
Kim, S., & Jazwinski, S. M. (2018). The gut microbiota and healthy aging: a mini-review. Gerontology, 64(6), 513-520.
Kokou, F., Sasson, G., Friedman, J., Eyal, S., Ovadia, O., Harpaz, S., ... & Mizrahi, I. (2019). Core gut microbial communities are maintained by beneficial interactions and strain variability in fish. Nature Microbiology, 4(12), 2456-2465.
Kumar, S., Stecher, G., & Tamura, K. (2016). MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular Biology and Evolution, 33(7), 1870-1874.
Lai, K. P., Lin, X., Tam, N., Ho, J. C. H., Wong, M. K. S., Gu, J., ... & Tse, W. K. F. (2020). Osmotic stress induces gut microbiota community shift in fish. Environmental Microbiology, 22(9), 3784-3802.
Langille, M. G., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., & Reyes, J. A. & Beiko, RG (2013). Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology, 31(9), 814.
Lavoie, E. G., Wangdi, T., & Kazmierczak, B. I. (2011). Innate immune responses to Pseudomonas aeruginosa infection. Microbes and Infection, 13(14-15), 1133-1145.
Le, M. H., & Wang, D. (2020). Structure and membership of gut microbial communities in multiple fish cryptic species under potential migratory effects. Scientific Reports, 10(1), 1-12.
Lee, K., Lee, K. M., Kim, D., & Yoon, S. S. (2017). Molecular determinants of the thickened matrix in a dual-species Pseudomonas aeruginosa and Enterococcus faecalis biofilm. Applied and Environmental Microbiology, 83(21).
Lee, S., Nam, Y., Koo, J. Y., Lim, D., Park, J., Ock, J., ... & Park, S. B. (2014). A small molecule binding HMGB1 and HMGB2 inhibits microglia-mediated neuroinflammation. Nature Chemical Biology, 10(12), 1055-1060.
Letunic, I., & Bork, P. (2007). Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics, 23(1), 127-128.
Leung, C., Rivera, L., Furness, J. B., & Angus, P. W. (2016). The role of the gut microbiota in NAFLD. Nature Reviews Gastroenterology & Hepatology, 13(7), 412-425.
Lewis, W. B., Moore, F. R., & Wang, S. (2017). Changes in gut microbiota of migratory passerines during stopover after crossing an ecological barrier. The Auk: Ornithological Advances, 134(1), 137-145.
Ley, R. E., Hamady, M., Lozupone, C., Turnbaugh, P. J., Ramey, R. R., Bircher, J. S., ... & Gordon, J. I. (2008). Evolution of mammals and their gut microbes. Science, 320(5883), 1647-1651.
Lin, Y. H., Chen, Y. S., Wu, H. C., Pan, S. F., Yu, B., Chiang, C. M., ... & Yanagida, F. (2013). Screening and characterization of LAB‐produced bacteriocin‐like substances from the intestine of grey mullet (Mugil cephalus L.) as potential biocontrol agents in aquaculture. Journal of Applied Microbiology, 114(2), 299-307.
Lindh, M. V., Sjöstedt, J., Andersson, A. F., Baltar, F., Hugerth, L. W., Lundin, D., ... & Pinhassi, J. (2015). Disentangling seasonal bacterioplankton population dynamics by high‐frequency sampling. Environmental Microbiology, 17(7), 2459-2476.
Livak, K. J., & Schmittgen, T. D. (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. Methods, 25(4), 402-408.
Llewellyn, M. S., Boutin, S., Hoseinifar, S. H., & Derome, N. (2014). Teleost microbiomes: the state of the art in their characterization, manipulation and importance in aquaculture and fisheries. Frontiers in Microbiology, 5, 207.
Llewellyn, M. S., McGinnity, P., Dionne, M., Letourneau, J., Thonier, F., Carvalho, G. R., ... & Derome, N. (2016). The biogeography of the Atlantic salmon (Salmo salar) gut microbiome. The ISME journal, 10(5), 1280-1284.
Lugo-Martinez, J., Ruiz-Perez, D., Narasimhan, G., & Bar-Joseph, Z. (2019). Dynamic interaction network inference from longitudinal microbiome data. Microbiome, 7(1), 54.
Magnadóttir, B. (2006). Innate immunity of fish (overview). Fish & Shellfish Immunology, 20(2), 137-151.
Mainali, K., Bewick, S., Vecchio-Pagan, B., Karig, D., & Fagan, W. F. (2019). Detecting interaction networks in the human microbiome with conditional Granger causality. PLoS Computational Biology, 15(5), e1007037.
Marino, S., Baxter, N. T., Huffnagle, G. B., Petrosino, J. F., & Schloss, P. D. (2014). Mathematical modeling of primary succession of murine intestinal microbiota. Proceedings of the National Academy of Sciences, 111(1), 439-444.
Martinez Arbizu, P. (2017). pairwiseAdonis: Pairwise multilevel comparison using adonis. R package version 0.0, 1.
Mascarenhas, R., Ruziska, F. M., Moreira, E. F., Campos, A. B., Loiola, M., Reis, K., ... & Veiga, R. (2020). Integrating Computational Methods to Investigate the Macroecology of Microbiomes. Frontiers in Genetics, 10, 1344.
McDonald, D., Price, M. N., Goodrich, J., Nawrocki, E. P., DeSantis, T. Z., Probst, A., ... & Hugenholtz, P. (2012). An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. The ISME journal, 6(3), 610-618.
McMurdie, P. J., & Holmes, S. (2014). Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Computational Biology, 10(4), e1003531.
Morris, R. M., Vergin, K. L., Cho, J. C., Rappé, M. S., Carlson, C. A., & Giovannoni, S. J. (2005). Temporal and spatial response of bacterioplankton lineages to annual convective overturn at the Bermuda Atlantic Time‐series Study site. Limnology and Oceanography, 50(5), 1687-1696.
Mounier, J., Monnet, C., Vallaeys, T., Arditi, R., Sarthou, A. S., Hélias, A., & Irlinger, F. (2008). Microbial interactions within a cheese microbial community. Applied and Environmental Microbiology, 74(1), 172-181.
Nami, Y., Abdullah, N., Haghshenas, B., Radiah, D., Rosli, R., & Yari Khosroushahi, A. (2014). A newly isolated probiotic Enterococcus faecalis strain from vagina microbiota enhances apoptosis of human cancer cells. Journal of Applied Microbiology, 117(2), 498-508.
Nayak, S. K. (2010). Role of gastrointestinal microbiota in fish. Aquaculture Research, 41(11), 1553-1573.
Ng, S. H., Stat, M., Bunce, M., & Simmons, L. W. (2018). The influence of diet and environment on the gut microbial community of field crickets. Ecology and Evolution, 8(9), 4704-4720.
Oksanen, J., Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., … & Wagner, H. (2016). vegan: Community Ecology Package. R package version 2.4-1.
Paine, R. T. (1966). Food web complexity and species diversity. The American Naturalist, 100(910), 65-75.
Palenik, B., Brahamsha, B., Larimer, F. W., Land, M., Hauser, L., Chain, P., ... & Paulsen, I. (2003). The genome of a motile marine Synechococcus. Nature, 424(6952), 1037-1042.
Parker, A., Lawson, M. A., Vaux, L., & Pin, C. (2018). Host‐microbe interaction in the gastrointestinal tract. Environmental Microbiology, 20(7), 2337-2353.
Parks, D. H., Mankowski, T., Zangooei, S., Porter, M. S., Armanini, D. G., Baird, D. J., ... & Beiko, R. G. (2013). GenGIS 2: Geospatial analysis of traditional and genetic biodiversity, with new gradient algorithms and an extensible plugin framework. PloS One, 8(7), e69885.
Parks, D. H., Tyson, G. W., Hugenholtz, P., & Beiko, R. G. (2014). STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics, 30(21), 3123-3124.
Power, M. E., & Tilman, D. Estes] A, Menge BA, Bond W], Mills LS, Daily G, Castilla] C, Lubchenco J, Paine RT. (1996). Challenges in the quest for keystones. BioScience, 46, 609-62.
Risely, A., Waite, D., Ujvari, B., Klaassen, M., & Hoye, B. (2017). Gut microbiota of a long‐distance migrant demonstrates resistance against environmental microbe incursions. Molecular Ecology, 26(20), 5842-5854.
Rodriguez-Estrada, U., Satoh, S., Haga, Y., Fushimi, H., & Sweetman, J. (2013). Effects of inactivated Enterococcus faecalis and mannan oligosaccharide and their combination on growth, immunity, and disease protection in rainbow trout. North American Journal of Aquaculture, 75(3), 416-428.
Roeselers, G., Mittge, E. K., Stephens, W. Z., Parichy, D. M., Cavanaugh, C. M., Guillemin, K., & Rawls, J. F. (2011). Evidence for a core gut microbiota in the zebrafish. The ISME journal, 5(10), 1595-1608.
Romero, J., & Navarrete, P. (2006). 16S rDNA-based analysis of dominant bacterial populations associated with early life stages of coho salmon (Oncorhynchus kisutch). Microbial Ecology, 51(4), 422-430.
Romero, J., Ringø, E., & Merrifield, D. L. (2014). The gut microbiota of fish. Aquaculture nutrition: Gut health, probiotics and prebiotics, 75-100.
Röttjers, L., & Faust, K. (2019). Can we predict keystones?. Nature Reviews Microbiology, 17(3), 193.
Ruan, Q., Dutta, D., Schwalbach, M. S., Steele, J. A., Fuhrman, J. A., & Sun, F. (2006). Local similarity analysis reveals unique associations among marine bacterioplankton species and environmental factors. Bioinformatics, 22(20), 2532-2538.
Rudi, K., Angell, I. L., Pope, P. B., Vik, J. O., Sandve, S. R., & Snipen, L. G. (2018). Stable core gut microbiota across the freshwater-to-saltwater transition for farmed Atlantic salmon. Applied and Environmental Microbiology, 84(2).
Russo, P., Iturria, I., Mohedano, M. L., Caggianiello, G., Rainieri, S., Fiocco, D., ... & Spano, G. (2015). Zebrafish gut colonization by mCherry-labelled lactic acid bacteria. Applied Microbiology and Biotechnology, 99(8), 3479-3490.
Salminen, S., Nybom, S., Meriluoto, J., Collado, M. C., Vesterlund, S., & El-Nezami, H. (2010). Interaction of probiotics and pathogens—benefits to human health?. Current Opinion in Biotechnology, 21(2), 157-167.
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., ... & Sahl, J. W. (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75(23), 7537-7541.
Shaw, G. T. W., Pao, Y. Y., & Wang, D. (2016). MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles. BMC Bioinformatics, 17(1), 488.
Shaw, G. T. W., Liu, A. C., Weng, C. Y., Chou, C. Y., & Wang, D. (2017). Inferring microbial interactions in thermophilic and mesophilic anaerobic digestion of hog waste. PloS One, 12(7), e0181395.
Shaw, G. T. W., Weng, C. Y., Chen, C. Y., Weng, F. C. H., & Wang, D. (2019). A systematic approach re-analyzing the effects of temperature disturbance on the microbial community of mesophilic anaerobic digestion. Scientific Reports, 9(1), 1-14.
Shaw, G. T. W., Liu, A. C., Weng, C. Y., Chen Y. C., Chen C. Y., Weng F. C. H., Wang D. & Chou C. Y. (2020). A network-based approach to deciphering a dynamic microbiome’s response to a subtle perturbation. Scientific Reports (10), 19530.
Shehata, A. A., Tarabees, R., Basiouni, S., ElSayed, M. S., Gaballah, A., & Krueger, M. (2020). Effect of a potential probiotic candidate Enterococcus faecalis-1 on growth performance, intestinal microbiota, and immune response of commercial broiler chickens. Probiotics and Antimicrobial Proteins, 12(2), 451-460.
Shen, K. N., Chang, C. W., & Durand, J. D. (2015). Spawning segregation and philopatry are major prezygotic barriers in sympatric cryptic Mugil cephalus species. Comptes Rendus Biologies, 338(12), 803-811.
Shen, K. N., Jamandre, B. W., Hsu, C. C., Tzeng, W. N., & Durand, J. D. (2011). Plio-Pleistocene sea level and temperature fluctuations in the northwestern Pacific promoted speciation in the globally-distributed flathead mullet Mugil cephalus. BMC Evolutionary Biology, 11(1), 83.
Sheu, D. S., Wang, Y. T., & Lee, C. Y. (2000). Rapid detection of polyhydroxyalkanoate-accumulating bacteria isolated from the environment by colony PCR. Microbiology, 146(8), 2019-2025.
Shreiner, A. B., Kao, J. Y., & Young, V. B. (2015). The gut microbiome in health and in disease. Current Opinion in Gastroenterology, 31(1), 69.
Sommer, F., & Bäckhed, F. (2013). The gut microbiota—masters of host development and physiology. Nature Reviews Microbiology, 11(4), 227-238.
Song, H. S., Cannon, W. R., Beliaev, A. S., & Konopka, A. (2014). Mathematical modeling of microbial community dynamics: a methodological review. Processes, 2(4), 711-752.
Springer, A., Fichtel, C., Al‐Ghalith, G. A., Koch, F., Amato, K. R., Clayton, J. B., ... & Kappeler, P. M. (2017). Patterns of seasonality and group membership characterize the gut microbiota in a longitudinal study of wild Verreaux's sifakas (Propithecus verreauxi). Ecology and Evolution, 7(15), 5732-5745.
Stein, R. R., Bucci, V., Toussaint, N. C., Buffie, C. G., Rätsch, G., Pamer, E. G., ... & Xavier, J. B. (2013). Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota. PLoS Computational Biology, 9(12), e1003388.
Stephens, W. Z., Burns, A. R., Stagaman, K., Wong, S., Rawls, J. F., Guillemin, K., & Bohannan, B. J. (2016). The composition of the zebrafish intestinal microbial community varies across development. The ISME journal, 10(3), 644-654.
Succurro, A., & Ebenhöh, O. (2018). Review and perspective on mathematical modeling of microbial ecosystems. Biochemical Society Transactions, 46(2), 403-412.
Sullam, K. E., Essinger, S. D., Lozupone, C. A., O’CONNOR, M. P., Rosen, G. L., Knight, R. O. B., ... & Russell, J. A. (2012). Environmental and ecological factors that shape the gut bacterial communities of fish: a meta‐analysis. Molecular Ecology, 21(13), 3363-3378.
Suzuki, K. (1965). Biology of striped mullet Mugil cephalus Linne. I. Food content of young. Prefectural University of Mie, Faculty of Fisheries Report, 5, 295-305.
Tabrett, A., & Horton, M. W. (2020). The influence of host genetics on the microbiome. F1000Research, 9.
Thomson, J. M. (1963). Synopsis of biological data on the grey mullet Mugil cephalus Linnaeus 1758.
Thomson, J. M. (1966). The grey mullets. Oceanography and Marine Biology Annual Reviews, 4, 301-335.
Turnbaugh, P. J., Hamady, M., Yatsunenko, T., Cantarel, B. L., Duncan, A., Ley, R. E., ... & Egholm, M. (2009). A core gut microbiome in obese and lean twins. Nature, 457(7228), 480-484.
Vandenberghe, J., Thompson, F. L., Gomez-Gil, B., & Swings, J. (2003). Phenotypic diversity amongst Vibrio isolates from marine aquaculture systems. Aquaculture, 219(1-4), 9-20.
Vergin, K. L., Beszteri, B., Monier, A., Thrash, J. C., Temperton, B., Treusch, A. H., ... & Giovannoni, S. J. (2013). High-resolution SAR11 ecotype dynamics at the Bermuda Atlantic Time-series Study site by phylogenetic placement of pyrosequences. The ISME journal, 7(7), 1322-1332.
Wang, A. R., Ran, C., Ringø, E., & Zhou, Z. G. (2018). Progress in fish gastrointestinal microbiota research. Reviews in Aquaculture, 10(3), 626-640.
Wang, G. X., Li, F. Y., Cui, J., Wang, Y., Liu, Y. T., Han, J., & Lei, Y. (2011). Immunostimulatory activities of a decapeptide derived from Alcaligenes faecalis FY‐3 to crucian carp. Scandinavian Journal of Immunology, 74(1), 14-22.
Wang, M., Yi, M., Lu, M., Gao, F., Liu, Z., Huang, Q., ... & Zhu, D. (2020). Effects of probiotics Bacillus cereus NY5 and Alcaligenes faecalis Y311 used as water additives on the microbiota and immune enzyme activities in three mucosal tissues in Nile tilapia Oreochromis niloticus reared in outdoor tanks. Aquaculture Reports, 17, 100309.
Weber, J. M. (2009). The physiology of long-distance migration: extending the limits of endurance metabolism. Journal of Experimental Biology, 212(5), 593-597.
Weng, F. C. H., Shaw, G. T. W., Weng, C. Y., Yang, Y. J., & Wang, D. (2017). Inferring microbial interactions in the gut of the Hong Kong whipping frog (Polypedates megacephalus) and a validation using probiotics. Frontiers in Microbiology, 8, 525.
Whitfield, A. K., Panfili, J., & Durand, J. D. (2012). A global review of the cosmopolitan flathead mullet Mugil cephalus Linnaeus 1758 (Teleostei: Mugilidae), with emphasis on the biology, genetics, ecology and fisheries aspects of this apparent species complex. Reviews in Fish Biology and Fisheries, 22(3), 641-681.
Wilcove, D. S., & Wikelski, M. (2008). Going, going, gone: is animal migration disappearing. PLoS Biology, 6(7), e188.
Wong, S., & Rawls, J. F. (2012). Intestinal microbiota composition in fishes is influenced by host ecology and environment. Molecular Ecology, 21(13), 3100-3102.
Wu, D. M., Wang, J. X., Liu, X. H., Fan, Y. P., Jiang, R., Liu, M. H., ... & Liu, X. Z. (2017). Composition and predictive functional analysis of bacterial communities in the surface seawater of the Changjiang Estuary. PeerJ Preprints. (No. e3079v1).
Wu, G. D., Chen, J., Hoffmann, C., Bittinger, K., Chen, Y. Y., Keilbaugh, S. A., ... & Sinha, R. (2011). Linking long-term dietary patterns with gut microbial enterotypes. Science, 334(6052), 105-108.
Wu, H. M., Tien, Y. J., & Chen, C. H. (2010). GAP: A graphical environment for matrix visualization and cluster analysis. Computational Statistics and Data Analysis, 54(3), 767-778.
Xia, J. H., Lin, G., Fu, G. H., Wan, Z. Y., Lee, M., Wang, L., ... & Yue, G. H. (2014). The intestinal microbiome of fish under starvation. BMC Genomics, 15(1), 266.
Yamahara, K. M., Walters, S. P., & Boehm, A. B. (2009). Growth of enterococci in unaltered, unseeded beach sands subjected to tidal wetting. Applied and Environmental Microbiology, 75(6), 1517-1524.
Yamashiro, Y. (2017). Gut microbiota in health and disease. Annals of Nutrition and Metabolism, 71(3-4), 242-246.
Yan, Q., Li, J., Yu, Y., Wang, J., He, Z., Van Nostrand, J. D., ... & Li, X. (2016). Environmental filtering decreases with fish development for the assembly of gut microbiota. Environmental Microbiology, 18(12), 4739-4754.
Yang, Q., Lü, Y., Zhang, M., Gong, Y., Li, Z., Tran, N. T., ... & Li, S. (2019). Lactic acid bacteria, Enterococcus faecalis Y17 and Pediococcus pentosaceus G11, improved growth performance, and immunity of mud crab (Scylla paramamosain). Fish & Shellfish Immunology, 93, 135-143.
Yang, X., Xie, L., Li, Y., & Wei, C. (2009). More than 9,000,000 unique genes in human gut bacterial community: estimating gene numbers inside a human body. PloS One, 4(6), e6074.
Zhang, C. X., Wang, H. Y., & Chen, T. X. (2019). Interactions between Intestinal Microflora/Probiotics and the Immune System. BioMed Research International, 2019.
Zhang, Y., Zhao, Z., Dai, M., Jiao, N., & Herndl, G. J. (2014). Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea. Molecular Ecology, 23(9), 2260-2274.
Zhao, P., Irwin, D. M., & Dong, D. (2016). Host genetics is associated with the gut microbial community membership rather than the structure. Molecular BioSystems, 12(5), 1676-1686.
Zheng, X., Dai, X., & Huang, L. (2016). Spatial variations of prokaryotic communities in surface water from India ocean to Chinese marginal seas and their underlining environmental determinants. Frontiers in Marine Science, 3, 17.