Seasonal dynamics of microbial community in ... - Wiley Online Library

Aquaculture Research, 2015, 46, 1233–1240

doi:10.1111/are.12281

Seasonal dynamics of microbial community in an aquaculture system for Nile tilapia (Oreochromis niloticus) Juliana Alves Resende1, V^ ania L ucia Silva1, Dion eia Evangelista Cesar2, Alessandro Del’Duca2, 1 Cl audia Oliveira Fontes & Cl audio Galuppo Diniz1 1

Department of Parasitology, Microbiology and Immunology, Laboratory of Bacterial Physiology and Molecular

Genetics, Institute of Biological Sciences, Federal University of Juiz de Fora, Juiz de Fora, Brazil 2

Department of Biology, Laboratory of Ecology and Molecular Biology of Microorganisms, Institute of Biological

Sciences, Federal University of Juiz de Fora, Juiz de Fora, Brazil Correspondence: C G Diniz, Laboratory of Bacterial Physiology and Molecular Genetics, Department of Parasitology, Microbiology and Immunology, Institute of Biological Sciences, Federal University of Juiz de Fora, 36.036-900, Juiz de Fora, MG, Brazil. E-mail: [email protected]

Abstract

Introduction

Studies on bacterial abundance and diversity will improve the understanding of the microbial ecology to optimize aquaculture production, water quality, disease control and environmental impact of effluents. We comparatively evaluated an aquaculture system in dry and rainy seasons by Fluorescent in situ Hybridization (FISH) and culture-dependent methodology. Overall, a negative correlation between seasonality in bacterial and flagellates abundance was observed. Alpha-, beta-, gamma-proteobacteria and Cytophaga-Flavobacter were observed with seasonal variation. Putative pathogenic bacteria such as coagulase-negative Staphylococcus, non-fermenter Gram-negative rods (Pseudomonas sp. and Burkholderia sp.), and Enterobacteriaceae were also detected in this study with significant seasonal variation. Focusing on medically important bacteria, our data show that microbial diversity in the environment associated with aquaculture, as it is practiced, may be altered in growth ponds used for fish cultivation. As an ecological consequence, potentially pathogenic bacteria might be released in high concentrations to the downstream environments posing potential threats to human and animal health.

Although aquaculture is a growing commercial activity worldwide, there are only a few studies that have focused on the microbiological quality and risks associated with aquatic environments (Resende, Silva, Fontes, Souza-Filho, Oliveira, Coelho, Cesar & Diniz 2012). An understanding of the microbial ecology in aquaculture systems is needed to optimize farming production, nutrient cycles, nutrition of farmed animals, water quality, disease control and the environmental impact of effluents (Al-Harbi & Uddin 2004). A high concentration of readily labile organic matter may result in an increase in potentially pathogenic bacteria in the human and animal population (Baccarin & Camargo 2005; Zhang, Zhang & Fang 2009). Add to that the fact that many of these organisms harbour antibiotic resistance genes, eventually found in plasmids, transposons and integrons, which are able to transfer to different bacterial water and soil communities (Baquero, Martınez & Cant on 2008). The continuous mixing of water masses, residence time, input of nutrients from different sources and variation in climatic conditions may lead to different patterns of microbial abundance and diversity in aquaculture ponds (Baccarin & Camargo 2005; Santeiro, Pinto-Coelho & Sipa uba-Tavares 2006; Kawahara, Shigematsu, Miyadai & Kondo 2009).

Keywords: Aquaculture, fluorescent in situ hybridization, microbial ecology, seasonal variation

© 2013 John Wiley & Sons Ltd

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Seasonal variation of microbial diversity in aquaculture J A Resende et al.

Variations in bacterial communities may also occur in aquatic environments depending on the actions of predators such as flagellates, which may also be regulated according to nutrient availability (Samuelsson, Berglund, Haecky & Andersson 2002; Simek, Horn ak, Masın, Christaki, Nedoma, Weinbauer & Dolan 2003; Zhao, Yu, Feng & Shen 2003; Jardillier, Basset, Domaizon, Belan, Amblard, Richardot & Debroas 2004). Seasonal variations such as drought and rainy seasons also influence the relationship between bacterial dynamics, nutrients and predators. According to the nutritional conditions in aquatic environments, it is accepted that bacterial cell size and morphology may vary affecting trophic interactions (Nakano & Kawabata 2000). According to literature, prospective studies are needed to better understand microbial diversity and sanitary risks in aquaculture environments, as this activity is increasingly becoming one of the most profitable commercial activities in both developed and developing geographical regions around the World (Resende et al. 2012). So, this study is aimed at understanding the microbial community structure in the aquaculture system of the Nile tilapia, comparing dry and rain seasons by Fluorescent in situ Hybridization (FISH) and by culture-dependent methodology focused on the occurrence of medically important bacteria. Materials and methods Water samples Twenty-seven water samples (water-fed canal, n = 3 and growth ponds, n = 24) were collected at different sites in the EPAMIG Nile tilapia (Oreochromis niloticus, Linnaeus, 1758) Aquaculture Farm located in the city of Leopoldina, Minas Gerais State, Brazil (latitude 21°34′29″ S and longitude 42°38′29″ W). The samples were collected equally during two different periods: August (2009) (winter/dry season), January (2010) (summer/rainy season 1) and February (2010) (summer/rainy season 2). During the winter, low precipitation was recorded as usual (5.7 mm average monthly rainfall). During the summer, precipitation was higher as expected (216.5 mm in January and 133.9 mm in February). During the summer period, the ponds received high inflow from the water-fed canal. The

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differences in rainfall and inflow between summer and winter were considered as seasonal patterns. Surface water temperature was measured in situ using a mercury thermometer. Water samples (20 mL) were collected from between 0 and 20 cm under the surface using sterile bottles. All samples were brought to the laboratory and processed within 4 h of collection. They were concentrated into 2 mL by centrifugation at 8000 g for 10 min at 4°C. Abundance of bacteria and flagellates Water samples were fixed with 20% paraformaldehyde (2% final concentration), filtered through a Nuclepore polycarbonate filter (pore size, 0.2 lm; Whatman, VWR, Canada) and stored at 20°C until the hybridization process occured. Subsequently, the samples were subjected to FISH protocol (Cottrell & Kirchman 2000), were oligonucleotide probed and rRNA-targeted to identify the bacterial community composition. The filters were divided into pieces and each piece was soaked with 30 lL of hybridization solution with a final concentration of 2.5 ng ll 1. They were Cy3-labelled, oligonucleotide probed and incubated overnight at 42°C. After hybridization, the sample was transferred into a wash solution containing 20 mM Tris-HCl (pH 7.4), 5 mM EDTA, 0.01% sodium dodecyl sulphate and a concentration of NaCl appropriate for the probe. It was heated at 48ºC for 15 min. Cells were stained with 2 lg mL 1of DAPI (4′,6-diami-dino-2-phenylindole) to count the total of bacterial cells and flagellates using an Olympusâ BX-60 microscope fitted with a Cy3 filter 41007a (Chroma, Bellows Falls, USA) and a DAPI filter 31000 (Chroma). Oligonucleotide probes (Operon Technologies Inc., Alameda, CA) were used to identify a-, b- and c-subclasses of Proteobacteria, the Cytophaga-Flavobacterium group, Gram-positive high-GC bacteria, Vibrio spp., Aeromonas spp., Enterococcus spp., Bacillus spp., Streptococcus spp. and Pseudomonas fluorescens. For the evaluation of the Lactobacillus group, a mix of four specific probes was used; Lactobacillus brevis, Lactobacillus collinoides, Lactobacillus coryniformis and Lactobacillus farciminis (Table 1). A negative control probe (5′- 3CC TAG TGA CGC CGT CGA C - 3′), which has no specific use for any particular group of bacteria, was used to evaluate the efficiency of hybridization.

© 2013 John Wiley & Sons Ltd, Aquaculture Research, 46, 1233–1240



Table 1 rRNA-targeted oligonucleotide probes of different bacterial species used in this research Probe

Taxon

Sequence (5′–3′)

Reference

Alf986

Alpha-proteobacteria

GGTAAGGTTCTGCGCGTT

Bet42a

Beta-proteobacteria

GCCTTCCCACTTCGTTT

Gam42a CF319a HGC69a

GCCTTCCCACATCGTTT TGGTCCGTGTCTCAGTAC TATAGTTACCACCGCCGT

Vib572a

Gamma-proteobacteria Cytophaga-Flavobacter Gram-positive high-GC bacteria Vibrio spp.

Manz, Amann, Ludwig, Vancanneyt & Schleifer 1996; Manz, Amann, Ludwig, Wagner & Schleifer 1992; Manz et al. 1992; Manz et al. 1996; Manz et al. 1992;

Aero2

Aeromonas spp.

GTA ACG TCA CAG CCA GCA GA

Enter2

Enterococcus spp.

TCC ATC AGC GAC ACC CGA AA

Bacil1 Lbrev Lcoll Lcory Lfarc PsAg1 Str

Bacillus spp. Lactobacillus brevis Lactobacillus collinoides Lactobacillus coryniformis Lactobacillus farciminis Pseudomonas fluorescens Streptococcus spp.

GCC GCC TTT CAA TTT CGA AC CAT TCA ACG GAA GCT CGT TC CTT GAT TTA ACG GGA TG GCT TCG GTC GAC GTC AGT AGC TTC AAT CTT CAG GAT GAT AAC TCG TCA TCA GCT C CAC TCT CCC CTT CTG CAC

ACC ACC TGC ATG CGC TTT

Bacterial isolation in aquaculture ponds Selective cultures (0.1 mL) were grown in Hypertonic Manitol and Bile Esculin Agar (Himedia Laboratories, India) for Gram-positive cocci (GPC) and in Eosin–Methylene Blue Agar (Himedia Laboratories, India) for both Gram-negative enterobacteria (ENT) and non-fermenting Gram-negative rods (NFR). After incubation (18–24 h at 37ºC), 1–5 different representative colonies were selected and cultivated in Brain Heart Infusion Agar (Himedia Laboratories, Mumbai, India) and stocked by freezing for further experiments. The GPC were presumptively identified by their morphotinctorial characteristics after Gram staining, as well as their ability to hydrolyse esculin and produce catalase. Species identification was performed using the commercial system BBL Crystal Rapid Gram-Positive ID Kit (Becton & Dickinson, San Diego, USA), according to the manufacturer’s instructions. The Gram-negative bacteria ENT and NFR were presumptively identified by morphotinctorial characteristics after Gram staining, as well as their ability to ferment carbohydrate and be motile. Species identification was performed using the commercial systems Bactray I, II and III (Laborclin,

Huggett, Crocetti, Kjelleberg & Steinberg 2008; , Kopeck fago, Kyselkova y, Frapoli, De gova -Mareckova , Grundmann & Sa €nne-Loccoz 2009; Moe che, Sanguin, Pote , Navarro, Demane Bernillon, Mavingui, Wildi, Vogel & Simonet 2008; Ichijo, Yamaguchi, Tani & Nasu 2010; Blasco, Ferrer & Pardo 2003;

Boye, Ahl & Molin 1995; Trebesius, Leitritz, Adler, Schubert, Autenrieth & Heesemann 2000

Pinhais/PR, Brazil), according the manufacturer’s instructions. Statistical analysis The ANOVA one-way analysis variance test and a posteriori Tukey test were used for the comparison of bacterial abundance and flagellate protozoa abundance, as well as to compare the different periods and different bacterial groups analysed. The significance level was set as P < 0.05. The relationships between quantitative variables were determined by Pearson’s correlation coefficient. Results Surface water temperature ranged between 23.0°C (August - 2009) and 28.0°C (January/February 2010). The average bacterial abundance was higher in growth ponds (6.5 2.8 9 106 cells mL 1) than in the water-fed canal (0.94 0.5 9 106 cells mL 1). Bacterial abundance was significantly higher during the summer 1 and 2 periods in both the water-fed canal and in the growth ponds (Fig. 1). Flagellate abundance was significantly higher in the growth ponds than in water-fed canal.


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Figure 1 Mean values for bacterial density (Cells 9 106 mL 1) observed in water samples collected from the water-fed canal and growth ponds in different seasons. Different lowercase letters, and ‘*’ indicate a statistically significant difference (P < 0.05).

During the winter period, flagellate abundance was higher in the water-fed canal and in the growth ponds (Fig. 2). A negative correlation between the bacterial and flagellate abundance was observed in the winter and summer 1 and 2 periods in both the water-fed canal (r = - 0.99) and the growth ponds (r = 0.78). The water-fed canal and growth ponds showed differences when considering the structure of the bacterial community. During the rainy season, Cytophaga-Flavobacteria and High-GC bacteria were dominant in the water-fed canal with values ranging from 20.9 9.1% and 15.0 5.8% of the

Figure 2 Mean values for flagellate protozoa (Ind 9 10 mL 1) observed in water samples collected from the water-fed canal and growth ponds in different seasons. Different lowercase letters, and ‘*’ indicate a statistically significant difference (P < 0.05).

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total bacterial abundance respectively. During the dry season, there was no difference between the major groups. In the growth ponds, the microbial community varied during the different seasons. During the dry season, the dominant groups were beta-, gamma-proteobacteria and CytophagaFlavobacteria; accounting for 32.7%, 18.1% and 13.2% of the total bacterial abundance respectively. The abundance of alpha-proteobacteria and high-GC groups was higher during the summer 1 and 2 periods (Fig. 3). With regard to specific groups, the use of fluorescent in situ hybridization showed a significant difference in the water-fed canal during the winter. However, in the growth ponds, there was an increased abundance of all evaluated bacterial groups. During the summer 1 and 2 periods, Bacillus spp., Lactobacillus spp. and Enterococcus spp. were more prevalent in the water-fed canal, representing 26.5%, 24.5% and 20.8% of the total bacterial abundance respectively. In the growth ponds, the dry conditions resulted in the predominance of Aeromonas spp., Enterococcus spp., Lactobacillus spp., Pseudomonas fluorescens and Streptococcus spp., while there was a decrease in the rainy season of all specific groups (Fig. 4). Using a culture-dependent approach, 165 (n = 165) bacteria samples were recorded. Representative strains of ENT were the most frequent (n = 76, 46.0%), followed by NFR (n = 55, 33.3%) and GPC (n = 34, 20.6%). No significant differences were observed in the sampled sites considering variations of the same bacterial group. However, considering the frequency of bacterial collection in the different water sources (water-fed canal and growth ponds), the ENT strains were the most abundant in every environment, whereas NFR and GPC were equally distributed (Fig. 5). Among isolated GPC, 14 different species were identified, although three strains (8.8%) had no identification score according to the methodology used in this study. The most prevalent GPC species were Staphylococcus epidermidis (14.7%), Enterococcus casseliflavus/gallinarum (11.7%), Pediococcus pentosaceus (8.8%), Staphylococcus galinarum (8.8%) and Staphylococcus xylosus (8.8%). Of 131 Gramnegative rods, 58.0% were ENT, while 42.0% were NFR. Looking at ENT, the most prevalent species were Serratia sp. (30.2%), Klebsiella sp. (14.4%), Plesiomonas sp. (13.1%), Escherichia sp. (11.8%), Hafnia sp. (6.5%) and Enterobacter sp. (5.2%). Among the NFR, the most prevalent species were




Figure 3 Seasonal variation in bacterial groups hybridized with different oligonucleotide probes. Alf986 (alpha-proteobacteria), Bet42a (beta-proteobacteria), Gam42a (gamma-proteobacteria), CF319a (Cytophaga–Flavobacterium), HGC69a (Gram-positive high-GC bacteria). Different lowercase letters indicate a statistically significant difference (P < 0.05).

Pseudomonas sp. (36.3%) Burkholderia sp. (21.8%), Chromobacterium sp. (10.9%) and Stenotrophomonas sp. (10.9%). As observed by GPC, seven NFR strains (12.7%) did not result in an identification score according to the methodology used in this study. Discussion Our results show that the maximum bacterial abundance was the highest recorded in studies conducted in aquaculture and freshwater systems of different trophic levels considering the same approach; that is epifluorescence counting after bacterial staining with DAPI (Jardillier et al. 2004; Gich, Schubert, Bruns, Hoffelner & Overmann 2005; Almeida, Cunha, Santos, Salvador & Gomes 2007). In general aquatic ecosystems, bacteria can be limited by top-down and bottom-up factors. Top-down factors are related to predation mainly by higher trophic levels (protozoa) and lysis by viruses, while bottom-up factors are related to

nutrient source or, more rarely, by temperature variation (Pace & Cole 1994). In this study, flagellates were more abundant during the dry season in both the water-fed canal and growth ponds. The negative seasonal correlation between bacterial and flagellate abundance observed may suggest a top-down control of the bacterial community, which explains the decrease in the amount of bacteria during the dry season. Regarding the bottom-up control in the growth ponds, the availability of nutrients should not limit bacteria counted as nutrient concentrations are constant because of daily fish feeding and supply of autochthonous nutrients. So, the dilution effect of nutrients would not be a predominant factor (Andrushchyshyn, Magnusson & Williams 2006). The growth ponds showed higher counts of bacteria than the water-fed canal due to the higher nutrient concentration. These results suggest that aquaculture activity increases the number of microorganisms and changes the overall microbial structure in the growth ponds implying an increase


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Figure 4 Seasonal variation in bacterial groups hybridized with different oligonucleotide probes. Vib572a (Vibrio spp.), Aero2 (Aeromonas spp.), Enter2 (Enterococcus spp.), Bacil1 (Bacillus spp.), PsAg1 (Pseudomonas spp.), Str (Streptococcus spp.). For Lactobacillus density evaluation a mix of four probes were used as follows: Lbrev, Lcoll, Lcory and Lfarc (*). Different lowercase letters indicate a statistically significant difference (P < 0.05).

Figure 5 Distribution of putative pathogenic bacteria according to the culture-dependent approach ENT (Gram-negative enterobacteria), NFR (non-fermenting Gram-negative rods) and GPC (Gram-positive cocci).

in aquaculture-related bacteria in ecosystems downstream of aquaculture discharge. Other authors suggest evidence of the seasonal variation in species and abundance of hybrid tilapia in intestines. A maximum load of bacteria was found in the summer and in highly eutrophic environments. They suggested that one of the reasons was the high surface temperature that was close to optimum for many mesophilic bacteria (Al-Harbi & Uddin 2004). In this study, no significant temperature variation was observed that would be suitable for mesophilic microorganisms.

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All the evaluated microbial groups in the waterfed canal were also found in the growth ponds regardless of the FISH or culture-dependent methodology, suggesting the input of bacteria through the water-fed canal. However, the distribution of major bacterial groups, alpha-, beta- and gammaproteobacteria and Cytophaga-Flavobacter was not similar in the two environments with seasonal variation. There was change in the density of some dominant groups across the seasons. For example, alpha-, beta- and gamma-proteobacteria showed obvious seasonal variation in the growth




ponds. In contrast, in the water-fed canal, no difference was observed between these groups. Studies have suggested that similar environmental features produce similar bacterial communities. Thus, bacterial communities tend to be homogeneous across time but exhibit a certain degree of spatial heterogeneity, even within small areas (Hewson, Jacobson & Fuhrman 2007). It would be speculative that variations recorded for specific bacterial groups in the water-fed canal and growth ponds were mainly influenced by season. According to literature, some other factors that we did not evaluate in this study such as chemical treatments, introduction of nonindigenous bacterial of faecal origin by birds and terrestrial animals, may affect the seasonal pattern of specific bacterial density (Almeida et al. 2007). With regard to medically important bacteria, our data show that microbial diversity in the environment associated with aquaculture, as it is practiced, may be altered in growth ponds relating to fish cultivation. Similar results were reported by other authors, implying that this is not related to a particular aquaculture system (Al-Harbi & Uddin 2004; Heuer, Kruse, Grave, Collignon, Karunasagar & Angulo 2009; Zhang et al. 2009). The GPC group was the least identified bacteria. Indeed, these bacteria are not frequent in the aquatic environment. However, factors such as external contamination may modulate the bacterial community structure especially taking into account the surrounding environment (Almeida et al. 2007; Carneiro, Figueiredo, Pereira, Leal & Logato 2007; Sakami 2008). As a whole, our data suggest evidence that bacterial density varies seasonally as a result of selective predation and other factors such as the dilution effect. The bacteria groups evaluated by FISH and culture-dependent methodology were present in both environments, suggesting that different microbial groups reach aquaculture environments due to influx in the water-fed canal, although the ecosystem allows their persistency. On the other hand, the occurrence of medically important bacteria raises the discussion on the sanitary safety of aquaculture systems as they are practiced once these bacteria are increased in the growth ponds. As an ecological consequence, these potentially pathogenic bacteria might spread from the aquaculture environment to the surrounding areas reaching humans and other animals posing potential health threats.

Acknowledgments This study was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) and by the Research Support Foundation of Minas Gerais (FAPEMIG). The authors would like to thank Maria Angelica Esteves Pires for technical assistance and all the students who collaborated on this study. References Al-Harbi A.H. & Uddin M.N. (2004) Seasonal variation in the intestinal bacterial flora of hybrid tilapia (Oreochromis niloticus 9 Oreochromis aureus) cultured in earthen ponds in Saudi Arabia. Aquaculture 229, 37–44. Almeida A., Cunha A., Santos L., Salvador S. & Gomes A. (2007) Evaluation of the impact of two aquaculture systems on bacterial communities of the estuarine system Ria de Aveiro. In: Current Research Topics in Applied Microbiology and Microbial Biotechnology (ed. by A. Mendez-Vilas), pp. 236–239. World Scientific Publishing. Singapore. Andrushchyshyn O.P., Magnusson A.K. & Williams D.D. (2006) Responses of intermittent pond ciliate populations and communities to in situ bottom-up and topdown manipulations. Aquatic Microbial Ecology 42, 293–310. Baccarin A.E. & Camargo A.F.M. (2005) Characterization and evaluation of the impact of feed management on the effluents of Nile Tilapia (Oreochromis niloticus) culture. Brazilian Archives of Biology and Technology 48, 81–90. Baquero F., Martınez J.L. & Cant on R. (2008) Antibiotics and antibiotic resistance in water environments. Current Opinion in Biotechnology 19, 260–265. Blasco L., Ferrer S. & Pardo I. (2003) Development of specific fluorescent oligonucleotide probes for in situ identification of wine lactic acid bacteria. FEMS Microbiology Letters 225, 115–123. Boye M., Ahl T. & Molin S. (1995) Application of a strain-specific rRNA oligonucleotide probe targeting Pseudomonas fluorescens Ag1 in a mesocosm study of bacterial release into the environment. Applied and Environmental Microbiology 61, 1384–1390. Carneiro D.O., Figueiredo H.C.P., Pereira D.J. Jr, Leal C.A.G. & Logato P.V.R. (2007) Profile of antimicrobial resistance in bacterial populations recovered from different Nile tilapia (Oreochromis niloticus) culture systems. Brazilian Journal of Veterinary Research and Animal Science 59, 869–876. Cottrell M.T. & Kirchman D.L. (2000) Community composition of marine bacterioplankton determined by 16S rRNA gene clone libraries and Fluorescence in situ Hybridization. Applied and Environmental Microbiology 66, 5116–5122.


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