Abstract
We hypothesized that lactic acid bacteria (LAB) present in sediments at aquaculture sites can be employed as an indicator for the early prediction of deterioration, as the concentration of organic acids controls hydrogen sulfide production via sulfate-reducing bacteria. We selected two aquaculture sites with different acid volatile sulfide (AVS-S) values, St. OJ (average AVS-S = 0.24 mg S/g dry mud) and St. UM (average AVS-S = 1.16 mg S/g dry mud), which were less and critically deteriorated, respectively, and examined our hypothesis by performing a 3-year-long survey in Tanabe Bay, Wakayama Prefecture, Japan. In St. UM, the bacterial community showed positive correlations with AVS-S values and water contents. With AVS-S accumulation at the site, the abundances of LAB decreased below the detection limit, suggesting that LAB viable counts may be unsuitable for predicting early deterioration at sites with severe AVS-S accumulation. In St. OJ, the LAB viable counts, organic acid content, and AVS-S values increased after the beginning of sea bream aquaculture, and the bacterial community showed high correlations with the LAB counts, succinic and total organic acid concentrations, and the abundance of the class Bacilli. These on-site experiments indicated that LAB counts can be a reasonable indicator for evaluating deterioration in aquaculture sites.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Apostolaki ET, Tsagaraki T, Tsapakis M, Karakassis I (2007) Fish farming impact on sediments and macrofauna associated with seagrass meadows in the Mediterranean. Estuar Coast Shelf S 75:408–416. https://doi.org/10.1016/j.ecss.2007.05.024
Aylagas E, Atalah J, Sánchez-Jerez P, Pearman JK, Casado N, Asensi J, Toledo-Guedes K, Carvalho SA (2021) A step towards the validation of bacteria biotic indices using DNA metabarcoding for benthic monitoring. Mol Ecol Resour 21:1889–1903. https://doi.org/10.1111/1755-0998.13395
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodríguez AM, Chase J, Cope EK, Da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, Koester I, Kosciolek T, Kreps J, Langille MGI, Lee J, Ley R, Liu Y-X, Loftfield E, Lozupone C, Maher M, Marotz C, Martin BD, McDonald D, McIver LJ, Melnik AV, Metcalf JL, Morgan SC, Morton JT, Naimey AT, Navas-Molina JA, Nothias LF, Orchanian SB, Pearson T, Peoples SL, Petras D, Preuss ML, Pruesse E, Rasmussen LB, Rivers A, Robeson MS, Rosenthal P, Segata N, Shaffer M, Shiffer A, Sinha R, Song SJ, Spear JR, Swafford AD, Thompson LR, Torres PJ, Trinh P, Tripathi A, Turnbaugh PJ, Ul-Hasan S, van der Hooft JJJ, Vargas F, Vázquez-Baeza Y, Vogtmann E, von Hippel M, Walters W, Wan Y, Wang M, Warren J, Weber KC, Williamson CHD, Willis AD, Xu ZZ, Zaneveld JR, Zhang Y, Zhu Q, Knight R, Caporaso JG (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37:852–857. https://doi.org/10.1038/s41587-019-0209-9
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583. https://doi.org/10.1038/nmeth.3869
Choi A, Lee TK, Cho H, Lee W-C, Hyun J-H (2022) Shifts in benthic bacterial communities associated with farming stages and a microbiological proxy for assessing sulfidic sediment conditions at fish farms. Mar Pollut Bull 178:113603. https://doi.org/10.1016/j.marpolbul.2022.113603
FAO (2020) The state of world fisheries and aquaculture 2020. https://www.fao.org/documents/card/en/c/ca9229en. Accessed 10 May 2022
Frühe L, Dully V, Forster D, Keeley NB, Laroche O, Pochon X, Robinson S, Wilding TA, Stoeck T (2021) Global trends of benthic bacterial diversity and community composition along organic enrichment gradients of salmon farms. Front Microbiol 12:637811. https://doi.org/10.3389/fmicb.2021.637811
Glöckner FO, Yilmaz P, Quast C, Gerken J, Beccati A, Ciuprina A, Bruns G, Yarza P, Peplies J, Westram R, Ludwig W (2017) 25 years of serving the community with ribosomal RNA gene reference databases and tools. J Biotechnol 261:169–176. https://doi.org/10.1016/j.jbiotec.2017.06.1198
Hammer Ø, Harper DAT, Ryan PD (2001) PAST: Paleontological statistics software package for education and data analysis. Palaeontol Electron 4. http://palaeo-electronica.org/2001_1/past/issue1_01.htm
Jørgensen BB (2006) Bacteria and marine biogeochemistry. Mar Geochem. https://doi.org/10.1007/3-540-32144-6_5
Kawahara N, Shigematsu K, Miura S, Miyadai T, Kondo R (2008) Distribution of sulfate-reducing bacteria in fish farm sediments on the coast of southern Fukui Prefecture. Japan Plankton Benthos Res 3:42–45. https://doi.org/10.3800/pbr.3.42
Kawahara N, Shigematsu K, Miyadai T, Kondo R (2009) Comparison of bacterial communities in fish farm sediments along an organic enrichment gradient. Aquaculture 287:107–113. https://doi.org/10.1016/j.aquaculture.2008.10.003
Keller KL, Wall JD (2011) Genetics and molecular biology of the electron flow for sulfate respiration in Desulfovibrio. Front Microbiol 2:135. https://doi.org/10.3389/fmicb.2011.00135
Kondo R, Kitada H, Kawai A, Hata Y (1990) Low molecular fatty acids in the marine sediments of eutrophic coastal regions. Nippon Suisan Gakkaishi 56:519–523. https://doi.org/10.2331/suisan.56.519
Kondo R, Nishijima T, Hata Y (1993) Effect of temperature on the production of low molecular fatty acids within an anoxic marine sediment slurry. Nippon Suisan Gakkaishi 59:1189–1194. https://doi.org/10.2331/suisan.59.1189
Kondo R, Nishijima T, Hata Y (1995) Kinetic study on the mineralization of low molecular fatty acids in an anoxic marine sediment. Fish Sci 61:482–486. https://doi.org/10.2331/fishsci.61.482
Kondo R, Nedwell DB, Purdy KJ, Silva SQ (2004) Detection and enumeration of sulphate-reducing bacteria in estuarine sediments by competitive PCR. Geomicrobiol J 21:145–157. https://doi.org/10.1080/01490450490275307
Kondo R, Shigematsu K, Butani J (2008) Rapid enumeration of sulphate-reducing bacteria from aquatic environments using real-time PCR. Plankton Benthos Res 3:180–183. https://doi.org/10.3800/pbr.3.180
Kondo R, Shigematsu K, Kawahara N, Okamura T, Yoon YH, Sakami T, Yokoyama H, Koizumi Y (2012) Abundance of sulphate-reducing bacteria in fish farm sediments along the coast of Japan and South Korea. Fish Sci 78:123–131. https://doi.org/10.1007/s12562-011-0439-3
Kwon MJ, O’Loughlin EJ, Boyanov MI, Brulc JM, Johnston ER, Kemner KM, Antonopoulos DA (2016) Impact of organic carbon electron donors on microbial community development under iron- and sulfate-reducing conditions. PLoS One 11:e0146689. https://doi.org/10.1371/journal.pone.0146689
Laanbroek HJ, Pfennig N (1981) Oxidation of short-chain fatty acids by sulfate-reducing bacteria in freshwater and in marine sediments. Arch Microbiol 128:330–335. https://doi.org/10.1007/BF00422540
Letelier-Gordo CO, Aalto SL, Suurnäkki S, Pedersen PB (2020) Increased sulfate availability in saline water promotes hydrogen sulfide T production in fish organic waste. Aquac Eng 89:102062. https://doi.org/10.1016/j.aquaeng.2020.102062
Luna GM, Corinaldesi C, Dell’Anno A, Pusceddu A, Danovaro R (2013) Impact of aquaculture on benthic virus–prokaryote interactions in the Mediterranean Sea. Water Res 47:1156–1168. https://doi.org/10.1016/j.watres.2012.11.036
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17:10–12. https://doi.org/10.14806/ej.17.1.200
Ministry of Agriculture, Forestry, and Fisheries of Japan (2024) https://www.maff.go.jp/j/kokuji_tuti/tuti/t0000507.html/. Accessed 10 Feb 2024
Miyamoto Y, Iwanaga C (2012) Biochemical responses to anoxia and hypoxia in the ark shell Scapharca kagoshimensis. Plankton Benthos Res 7:167–174. https://doi.org/10.3800/pbr.7.167
Muyzer G, Stams AJM (2008) The ecology and biotechnology of sulphate-reducing bacteria. Nat Rev Microbiol 6:441–454. https://doi.org/10.1038/nrmicro1892
Orellana LH, Francis TB, Ferraro M, Hehemann JH, Fuchs BM, Amann RI (2022) Verrucomicrobiota are specialist consumers of sulfated methyl pentoses during diatom blooms. ISME J 16:630–641. https://doi.org/10.1038/s41396-021-01105-7
Plugge CM, Zhang W, Scholten JCM, Stams AJM (2011) Metabolic flexibility of sulfate-reducing bacteria. Front Microbiol 2:81. https://doi.org/10.3389/fmicb.2011.00081
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucl Acids Res 41:D590–D596. https://doi.org/10.1093/nar/gks1219
Quero GM, Ape F, Manini E, Mirto S, Luna GM (2020) Temporal changes in microbial communities beneath fish farm sediments are related to organic enrichment and fish biomass over a production cycle. Front Mar Sci 7:524. https://doi.org/10.3389/fmars.2020.00524
R Core Team (2021) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/
Ringø E, Van Doan H, Lee SH, Soltani M, Hoseinifar SH, Harikrishnan R, Song SK (2020) Probiotics, lactic acid bacteria and bacilli: interesting supplementation for aquaculture. J Appl Microbiol 129:116–136. https://doi.org/10.1111/jam.14628
Robinson G, Caldwell GS, Wade MJ, Free A, Jones CLW, Stead SM (2016) Profiling bacterial communities associated with sediment-based aquaculture bioremediation systems under contrasting redox regimes. Sci Rep 6:38850. https://doi.org/10.1038/srep38850
Rognes T, Flouri T, Nichols B, Quince C, Mahé F (2016) VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584. https://doi.org/10.7717/peerj.2584
Rosa TL, Mirto S, Mazzola A, Danovaro R (2001) Differential responses of benthic microbes and meiofauna to fish-farm disturbance in coastal sediments. Environ Pollut 112:427–434. https://doi.org/10.1016/S0269-7491(00)00141-X
Rubio-Portillo E, Villamor A, Fernandez-Gonzalez V, Antón J, Sanchez-Jerez P (2019) Exploring changes in bacterial communities to assess the influence of fish farming on marine sediments. Aquaculture 506:459–464. https://doi.org/10.1016/j.aquaculture.2019.03.051
Schleifer KH (2009) Phylum XIII. Firmicutes Gibbons and Murray 1978, 5. In: De Vos P, Garrity GM, Jones D, Krieg N, Ludwig W, Rainey F, Schleifer K-H, Whitman W (eds) Bergey’s manual of systematic bacteriology, vol 3. Springer, New York, pp 19–20 https://doi.org/10.1007/978-0-387-68489-5_3
Sica MG, Brugnoni LI, Marucci PL, Cubitto MA (2012) Characterization of probiotic properties of lactic acid bacteria isolated from an estuarine environment for application in rainbow trout (Oncorhynchus mykiss, Walbaum) farming. Antonie Van Leeuwenhoek 101:869–879. https://doi.org/10.1007/s10482-012-9703-5
Staley JT, Whitman WB (2010) Phylum XIX. Fusobacteria Garrity and Holt 2001, 140. In: Krieg NR, Ludwig W, Whitman WB, Hedlund BP, Paster BJ, et al. (eds) Bergey’s manual of systematic bacteriology, vol 4. Springer, New York, pp 747–774. https://doi.org/10.1007/978-0-387-68572-4_8
Takeuchi J, Taguchi Y, Satake K, Mori T (1988) Methods for the determination of the number and the activity of sulfate-reducing bacteria. Jpn J Water Poll Res 11:38–49 (English abstract is available). https://cir.nii.ac.jp/crid/1390282680057473152
Uede T (2008) Validity of acid volatile sulfide as environmental index and experiment for fixing its standard value in aquaculture farms along the coast of Wakayama Prefecture, Japan. Nippon Suisan Gakkaishi 74:402–411 (in Japanese with English abstract) https://doi.org/10.2331/suisan.74.402
Vezzulli L, Chelossi E, Riccardi G, Fabiano M (2002) Bacterial community structure and activity in fish farm sediments of the Ligurian Sea (western Mediterranean). Aquac Int 10:123–141. https://doi.org/10.1023/A:1021365829687
Wang C, Wang Y, Liu P, Sun Y, Song Z, Hu X (2021) Characteristics of bacterial community structure and function associated with nutrients and heavy metals in coastal aquaculture area. Environ Pollut 275:116639. https://doi.org/10.1016/j.envpol.2021.116639
Yamamoto T, Matsuda O, Hashimoto T, Imose H (1999) Relationship observed among loss of ignition, oxidation-reduction potential and acid-volatile sulfide content of surface sediment from the Seto Inland Sea, Japan. Bull Coast Oceanogr 36: 171–176 (in Japanese with English abstract). https://www.jstage.jst.go.jp/article/engankaiyo/36/2/36_171/_pdf
Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C, Schweer T, Peplies J, Ludwig W, Glöckner FO (2014) The SILVA and “All-Species Living Tree Project (LTP)” taxonomic frameworks. Nucl Acids Res 42:D643–D648. https://doi.org/10.1093/nar/gkt1209
Yokoyama H (2002) Impact of fish and pearl farming on the benthic environments in Gokasho Bay: evaluation from seasonal fluctuations of the macrobenthos. Fish Sci 68:258–268. https://doi.org/10.1046/j.1444-2906.2002.00420.x
Acknowledgements
We appreciate the assistance provided by Ryodai Kawaguchi, Masashi Matsuoka, Ryo Wakai, Mitsuha Sugisaki, Yusuke Sugi, Masayoshi Miyamoto, and Kosuke Fujita in analyzing the samples. We are thankful to the members of the Laboratory of Microbiology, Faculty of Fisheries Sciences, Hokkaido University, for analyzing organic acid by HPLC. We are grateful to the late S. Miyashita, S. Masuma, T. Nasu, and the other staff members of the Aquaculture Research Institute, Kindai University, for their cooperation. This work was supported by JSPS KAKENHI [grant number 18K05798] and a 2016 Kindai University Research Enhancement Grant [grant number SR09] to EN.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest with regard to the contents of this article.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Fujiwara-Nagata, E., Nakase, G., Kuroda, K. et al. Early prediction of environmental deterioration in a coastal fish farming area using lactic acid bacteria as an indicator. Fish Sci 90, 505–517 (2024). https://doi.org/10.1007/s12562-024-01756-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12562-024-01756-3