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Diversity, Composition, Taxa Biomarkers, and Functional Genes of Fish Gut Microbes in Peat Swamp Forests and its Converted Areas in North Selangor, Malaysia

Hamidu Saadu, Jumria Sutra, Amalia Mohd Hashim, Ahmad Ismail, Syaizwan Zahmir Zulkifli and Mohammad Noor Azmai Amal

Pertanika Journal of Tropical Agricultural Science, Volume 44, Issue 3, August 2021

DOI: https://doi.org/10.47836/pjtas.44.3.07

Keywords: Composition, diversity, fish gut microbes, functional genes, peat swamp forests, taxa biomarkers

Published on: 30 August 2021

The aquatic organisms in peat swamp forests are under threat due to habitat degradation resulting from human activities. This study determines the fish gut microbes’ diversity, composition, taxa biomarkers, and functional genes in peat swamp forests and its converted areas in North Selangor, Malaysia. Three undisturbed and disturbed areas nearby the peat swamp forests were selected. First, the 16S amplicon metagenomic analysis was conducted to assess the composition and diversity of bacterial communities in fish gut contents from both areas. Then, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) and Linear discriminant analysis Effect Size (LEfSe) were used to predict disease/pathogen related functional genes. This study revealed Proteobacteria, Firmicutes, Bacteroidetes, Fusobacteria, and Actinobacteria as the predominant phyla in both studied areas. In contrast, bacterial community profiles of disturbed and undisturbed areas were slightly dissimilar. Metagenome predictions revealed that genes are related to metabolism, environmental information processing, genetic information processing, cellular processes, human diseases, and organismal systems. Further investigation revealed six potential biomarker genes, including chronic myeloid leukaemia in an undisturbed area, Vibrio cholerae infection, bladder cancer, pathogenic Escherichia coli infection, Staphylococcus aureus infection, and pertussis in disturbed areas. This study revealed that the fish gut microbiome could be used as an indicator in comparing the undisturbed and disturbed ecosystems.

  • Aw, Y. K., Ong, K. S., Lee, L. H., Cheow, Y. L., Yule, C. M., & Lee, S. M. (2016). Newly isolated Paenibacillus tyrfis sp. nov. from Malaysian tropical peat swamp soil with broad spectrum antimicrobial activity. Frontiers in Microbiology, 7, 219. https://doi.org/10.3389/fmicb.2016.00219

  • Banerjee, S., Azad, S. A., Vikineswary, S., Selvaraj, O. S., & Mukherjee, T. K. (2000). Phototrophic bacteria as fish feed supplement. Asian-Australian Journal of Animal Science, 13(7), 991-994. https://doi.org/10.5713/ajas.2000.991

  • Beier, D., & Gross, R. (2006). Regulation of bacterial virulence by two-component systems. Current Opinion in Microbiology, 9(2), 143-152. https://doi.org/10.1016/j.mib.2006.01.005

  • Bray, J. R., & Curtis, J. T. (1957). An ordination of the upland forest communities of southern Wisconsin. Ecological Monographs, 27(4), 326-349. https://doi.org/10.2307/1942268

  • Bučević, P. V., Šitum, M., Chow, C. E. T., Chan, L. S., Roje, B., & Terzić, J. (2018). The urinary microbiome associated with bladder cancer. Scientific Reports, 8(1), 12157. https://doi.org/10.1038/s41598-018-29054-w

  • Bueno, E., Pinedo, V., & Cava, F. (2020). Adaptation of Vibrio cholerae to hypoxic environments. Frontiers in Microbiology, 11, 739. https://doi.org/10.3389/fmicb.2020.00739

  • Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., & Knight, R. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 7(5), 335-336. https://doi.org/10.1038/nmeth.f.303

  • Chávez-Romero, Y., Navarro-Noya, Y. E., Reynoso-Martínez, S. C., Sarria-Guzmán, Y., Govaerts, B., Verhulst, N., & Luna-Guido, M. (2016). 16s metagenomics reveals changes in the soil bacterial community driven by soil organic C, N-fertilizer and tillage-crop residue management. Soil and Tillage Research, 159, 1-8. https://doi.org/10.1016/j.still.2016.01.007

  • Don, J. B., Noel, R. K., & James, T. S. (2005). Part B: The Gammaproteobacteria. In Bergey’s manual of systematic bacteriology (2nd ed., pp. 1107-1109). Springer.

  • Egerton, S., Culloty, S., Whooley, J., Stanton, C., & Ross, R. P. (2018). The gut microbiota of marine fish. Frontiers in Microbiology, 9(873), 1-17. https://doi.org/10.3389/fmicb.2018.00873

  • Evariste, L., Barret, M., Mottier, A., Mouchet, F., Gauthier, L., & Pinelli, E. (2019). Gut microbiota of aquatic organisms: A key endpoint for ecotoxicological studies. Environmental Pollution, 248, 989-999. https://doi.org/10.1016/j.envpol.2019.02.101

  • Giang, P. T., Sakalli, S., Fedorova, G., Tilami, S. K., Bakal, T., Najmanova, L., & Grabic, R. (2018). Biomarker response, health indicators, and intestinal microbiome composition in wild brown trout (Salmo trutta m. fario L.) exposed to a sewage treatment plant effluent-dominated stream. Science of the Total Environment, 625, 1494-1509. https://doi.org/10.1016/j.scitotenv.2018.01.020

  • Givens, C., Ransom, B., Bano, N., & Hollibaugh, J. (2015). Comparison of the gut microbiomes of 12 bony fish and 3 shark species. Marine Ecology Progress Series, 518, 209–223. https://doi.org/10.3354/meps11034

  • Guivier, E., Pech, N., Chappaz, R., & Gilles, A. (2020). Microbiota associated with the skin, gills, and gut of the fish Parachondrostoma toxostoma from the Rhône basin. Freshwater Biology, 63(3), 446-459. https://doi.org/10.1111/fwb.13437

  • Haas, B. J., Gevers, D., Earl, A. M., Feldgarden, M., Ward, D. V., & Giannoukos, G. (2011). Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Research, 21, 494-504. https://doi.org/10.1101/gr.112730.110

  • Hammad, A. M., Watanabe, W., Fujii, T., & Shimamoto, T. (2012). Occurrence and characteristics of methicillin-resistant and -susceptible Staphylococcus aureus and methicillin-resistant coagulase-negative staphylococci from Japanese retail ready-to-eat raw fish. International Journal of Food Microbiology, 156(3), 286–289.

  • Hammer, Ø., Harper, D. A., & Ryan, P. D. (2001). PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica, 4(1), 1-9.

  • Humphreys, D., Singh, V., & Koronakis, V. (2016). Inhibition of WAVE regulatory complex activation by a bacterial virulence effector counteracts pathogen phagocytosis. Cell Reports, 17(3), 697–707. https://doi.org/10.1016/j.celrep.2016.09.039

  • Jonsson, V., Österlund, T., Nerman, O., & Kristiansson, E. (2016). Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics. BMC Genomics, 17(1), 1-12. https://doi.org/10.1186/s12864-016-2386-y

  • Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., & Huttenhower, C. (2013). Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology, 31(9), 814-821. https://doi.org/10.1038/nbt.2676

  • Li, Z., Tian, J., Lai, Y., Lee, C.-H., Cai, Z., & Yu, C.-F. (2020). Puffer fish gut microbiota studies revealed unique bacterial co-occurrence patterns and new insights on tetrodotoxin producers. Marine Drugs, 18(5), 278. https://doi.org/ 10.3390/md18050278

  • Magoč, T., & Salzberg, S. L. (2011). FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics, 27(21), 2957-2963. https://doi.org/10.1093/bioinformatics/btr507

  • Mai, G., Chen, L., Li, R., Liu, Q., Zhang, H., & Ma, Y. (2019). Common core bacterial biomarkers of bladder cancer based on multiple datasets. BioMed Research International, 2019, 4824909. https://doi.org/10.1155/2019/4824909

  • Mushi, D. (2018). Clostridium perfringens identifies source of pollution and reference streams in a tropical highland environment. Journal of Water and Health, 16(4), 501-507. https://doi.org/10.2166/wh.2018.192

  • Nayak, S. K. (2010). Role of gastrointestinal microbiota in fish. Aquaculture Research, 41(11), 1553-1573. https://doi.org/10.1111/j.1365-2109.2010.02546.x

  • Nguyen, N. L., Yu, W. J., Gwak, J. H., Kim, S. J., Park, S. J., Herbold, C. W., & Rhee, S. K. (2018). Genomic insights into the acid adaptation of novel methanotrophs enriched from acidic forest soils. Frontiers in Microbiology, 9, 1982. https://doi.org/10.3389/fmicb.2018.01982

  • Nolorbe-Payahua, C. D., de Freitas, A. S., Roesch, L. F. W., & Zanette, J. (2020). Environmental contamination alters the intestinal microbial community of the livebearer killifish Phalloceros caudimaculatus. Heliyon, 6(6), e04190. https://doi.org/10.1016/j.heliyon.2020.e04190

  • Nowell, P. C. (2007). Discovery of the Philadelphia chromosome: A personal perspective. Journal of Clinical Investigation, 117(8), 2033-2035. https://doi.org/10.1172/JCI31771

  • Oliveira, R. V., Oliveira, M. C., & Pelli, A. (2017). Disease infection by Enterobacteriaceae family in fishes: A review. Journal of Microbiology and Experimentation, 4(5), 128. https://doi.org/10.15406/jmen.2017.04.00128

  • Pandey, V. K., & Mishra, P. K. (2020). Nanoconjugates for detection of waterborne bacterial pathogens. Waterborne Pathogens, 2020, 363-384. https://doi.org/10.1016/B978-0-12-818783-8.00018-9

  • Posa, M. R. C., Wijedasa, L. S., & Corlett, R. T. (2011). Biodiversity and conservation of tropical peat swamp forests. BioScience, 61(1), 49-57. https://doi.org/10.1525/bio.2011.61.1.10

  • Sedlar, K., Kupkova, K., & Provaznik, I. (2017). Bioinformatics strategies for taxonomy independent binning and visualization of sequences in shotgun metagenomics. Computational and Structural Biotechnology Journal, 15, 48-55. https://doi.org/10.1016/j.csbj.2016.11.005

  • Segata, N., Izard, J., Waldron, L., Gevers, D., Miropolsky, L., Garrett, W. S., & Huttenhower, C. (2011). Metagenomic biomarker discovery and explanation. Genome Biology, 12(6), 1-60. https://doi.org/10.1186/gb-2011-12-6-r60

  • Selangor State Forestry Department. (2014). Integrated management plan for North Selangor Peat Swamp Forest 2014-2023. Retrieved from file:///C:/Users/user/Downloads/201511_imp-nspsf-vol-1_web-03%20(2).pdf

  • Spahni, R., Joos, F., Stocker, B. D., Steinacher, M., & Yu, Z. C. (2013). Transient simulations of the carbon and nitrogen dynamics in northern peat lands: From the last glacial maximum to the 21st century. Climate of the Past, 9(3), 1287-1308. https://doi.org/10.5194/cp-9-1287-2013

  • Sule, H. A., Ismail, A., & Amal, M. N. A. (2016). A review of the ichthyofauna of Malaysian peat swamp forest. Pertanika Journal of Tropical Agricultural Science, 39(4), 421-458.

  • Sule, H. A., Ismail, A., Amal, M. N. A., Zulkifli, S. Z., & Roseli, M. A. M. (2019). Associations between the presence of bacteria and the physico-chemical parameters of water in peat swamp forest, paddy field and oil palm plantation in north Selangor, Malaysia. Pertanika Journal of Tropical Agricultural Science, 42(1), 185-207.

  • Sun, H., Terhonen, E., Koskinen, K., Paulin, L., Kasanen, R., & Asiegbu, F. O. (2014). Bacterial diversity and community structure along different peat soils in boreal forest. Applied Soil Ecology, 74(2014), 37-45. https://doi.org/10.1016/j.apsoil.2013.09.010

  • Szymańska, B., & Długosz, A. (2017). The role of the BLCA-4 nuclear matrix protein in bladder cancer. Postepy Hig Med Dosw, 2017(71), 681-691. https://doi.org/ 10.5604/01.3001.0010.3847

  • Too, C., Keller, A., Sickel, W., Lee, S., & Yule, C. M. (2018). Microbial community structure in a Malaysian tropical peat swamp forest: The influence of tree species and depth. Frontiers in Microbiology, 9, 2859. https://doi.org/10.3389/fmicb.2018.02859

  • Udayangani, R. M. C., Dananjaya, S. H. S., Fronte, B., Kim, C. H., Lee, J., & De Zoysa, M. (2017). Feeding of nano scale oats β-glucan enhances the host resistance against Edwardsiella tarda and protective immune modulation in zebrafish larvae. Fish and Shellfish Immunology, 60, 72-77. https://doi.org/10.1016/j.fsi.2016.11.035

  • Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2017). Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73(16), 5261-5267. https://doi.org/10.1128/AEM.00062-07

  • Wang, X., Li, Q., Sui, J., Zhang, J., Liu, Z., Du, J. and Liu, X. (2019). Isolation and characterization of antagonistic bacteria Paenibacillus jamilae HS-26 and their effects on plant growth. BioMed Research International, 2019, 3638926. https://doi.org/10.1155/2019/3638926

  • Ward, N. L., Challacombe, J. F., Janssen, P. H., Henrissat, B., Coutinho, P. M., Wu, M., & Kuske, C. R. (2009). Three genomes from the Phylum Acidobacteria provide insight into the lifestyles of these microorganisms in soils. Applied and Environmental Microbiology, 75(7), 2046-2056. https://doi.org/10.1128/AEM.02294-08

  • Yukgehnaish, K., Kumar, P., Sivachandran, P., Marimuthu, K., Arshad, A., Paray, B. A., & Arockiaraj, J. (2020). Gut microbiota metagenomics in aquaculture: Factors influencing gut microbiome and its physiological role in fish. Reviews in Aquaculture, 12(3), 1903-1927. https://doi.org/10.1111/raq.12416

  • Zhang, J., Wang, X., Huo, D., Li, W., Hu, Q., Xu, C., & Li, C. (2014). Metagenomic approach reveals microbial diversity and predictive microbial metabolic pathways in Yucha, a traditional Li fermented food. Scientific Reports, 6(1), 32524. https://doi.org/10.1038/srep32524

  • Zhang, R., Liu, L.-L., Wang, X.-W., Guo, C.-Y., & Zhu, H. (2020). Dietary tea polyphenols induce changes in immune response and intestinal microbiota in Koi carp, Cyprinus carpio. Aquaculture, 516, 734636. https://doi.org/10.1016/j.aquaculture.2019.734636

  • Zhang, T., Yang, C., Qu, H., Xia, Y., Wang, Y., Li, A. D., & Liu, R. (2016). Discovery of new cellulases from the metagenome by a metagenomics-guided strategy. Biotechnology for Biofuels, 9(1), 138. https://doi.org/10.1186/s13068-016-0557-3

ISSN 1511-3701

e-ISSN 2231-8542

Article ID

JTAS-2242-2021

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