Profiling the genes associated with osmoadaptation and their variation by seasonally in Tuz Lake

Year 2023, Volume: 32 Issue: 2, 174 - 191, 30.12.2023

Suzan Sahin Dogan Aytaç Kocabaş

https://doi.org/10.53447/communc.1206230

Abstract

Hypersaline environments are one of the extreme habitats in the world. Microorganisms living in a hypersaline environment have developed various molecular adaptation strategies to overcome these extreme conditions. The study aims to investigate the genes associated with osmoadaptation seasonal variation in Tuz Lake by PICRUSt2. Dada2 pipelines were applied for filtering, dereplication, chimera identification, and merging paired-end reads to construct table.qza and rep_seqs.qza files. Therefore, the PICRUSt2 was applied to analyze the metabolic function of archaeal and bacterial diversity in Tuz Lake by using table.qza and rep_seqs.qza files. As a result of metabolic functions based on 16S rDNA amplicon data, the genes related to potassium accumulation played an important role in osmoregulation in Tuz Lake, where the archaea population was dominant. Furthermore, bacteriorhodopsin, halorhodopsin, and sensory rhodopsin functions were determined. The abundance of bacteriorhodopsin and halorhodopsin were increased in summer and spring, respectively.

Keywords

Tuz Lake, PICRUSt2, hypersaline, metabolic functions, osmoregulation

Supporting Institution

TUBITAK (Turkish Scientific and Technical Research Council)

Project Number

117Z966

Thanks

This work was supported by the TUBITAK (Turkish Scientific and Technical Research Council) – [Project no: 117Z966].

References

• Simachew, A., Lanzén, A., Gessesse, A., Øvreås, L., Prokaryotic community diversity along an increasing salt gradient in a soda ash concentration pond, Microbial Ecology, 71 (2) (2016), 326–338. https://doi.org/10.1007/s00248-015-0675-7.
• Paul, S., Bag, S.K., Das, S., Harvill, E.T., Dutta, C., Molecular signature of hypersaline adaptation: insights from genome and proteome composition of halophilic prokaryotes, Genome Biology, 9 (4) (2008), R70. https://doi.org/10.1186/gb-2008-9-4-r70.
• Rhodes, M.E., Fitz-Gibbon, S.T., Oren, A., House, C.H., Amino acid signatures of salinity on an environmental scale with a focus on the Dead Sea, Environmental Microbiology, 12 (9) (2010), 2613–2623. https://doi.org/10.1111/j.1462-2920.2010.02232.x.
• Lentzen, G., Schwarz, T., Extremolytes: natural compounds from extremophiles for versatile applications, Applied Microbiology and Biotechnology, 72 (4) (2006), 623–634. https://doi.org/10.1007/s00253-006-0553-9.
• Check Hayden, E., Technology: The $1,000 genome, Nature, 507 (7492) (2014), 294–295. https://doi.org/10.1038/507294a.
• Hauser, M., Steinegger, M., Söding, J., MMseqs software suite for fast and deep clustering and searching of large protein sequence sets, Bioinformatics, 32 (9) (2016), 1323–1330. https://doi.org/10.1093/bioinformatics/btw006.
• Douglas, G.M., Maffei, V.J., Zaneveld, J.R., Yurgel, S.N., Brown, J.R., Taylor, C.M., Huttenhower, C., Langille, M.G.I., PICRUSt2 for prediction of metagenome functions, Nature Biotechnology, 38 (6) (2020), 685–688. https://doi.org/10.1038/s41587-020-0548-6.
• Akpolat, C., Fernández, A.B., Caglayan, P., Calli, B., Birbir, M., Ventosa, A., Prokaryotic communities in the Thalassohaline Tuz Lake, Deep Zone, and Kayacik, Kaldirim and Yavsan salterns (Turkey) assessed by 16S rRNA amplicon sequencing, Microorganisms, 9 (7) (2021), 1525. https://doi.org/10.3390/microorganisms9071525.
• Çınar, S., Mutlu, M.B., Prokaryotic community compositions of the hypersaline sediments of Tuz Lake demonstrated by cloning and high-throughput sequencing, Microbiology, 89 (6) (2020), 756–768. https://doi.org/10.1134/S0026261720060028.
• Şahin Doğan, S., Kocabaş, A., Seasonal dynamics of eukaryotic microbial diversity in hypersaline Tuz Lake characterized by 18S rDNA sequencing, Journal of Eukaryotic Microbiology, (2023),. https://doi.org/10.1111/jeu.12993.
• Sahin Dogan, S., Kocabaş, A., Seasonal gene profiling in Tuz Lake with regard to biogeochemical cycling, Kahramanmaraş Sütçü İmam Üniversitesi Tarım ve Doğa Dergisi, (2023). https://doi.org/10.18016/ksutarimdoga.vi.1212062.
• Doğan, S.Ş., Kocabaş, A., Metagenomic assessment of prokaryotic diversity within hypersaline Tuz Lake, Turkey, Microbiology, 90 (5) (2021), 647–655. https://doi.org/10.1134/S0026261721050118.
• Ausubel, F., Brent, R., Kingston, R.E.,Moore, D.D.,Seidman, J.G., Smith, J.A., Struhl K., Short protocols in molecular biology, third edition, John Wiley & Sons, New York, 1996. https://doi.org/10.1002/bmb.1996.5690240143.
• Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Lozupone, C.A., Turnbaugh, P.J., Fierer, N., Knight, R., Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample, Proceedings of the National Academy of Sciences, 108 (supplement_1) (2011), 4516–4522. https://doi.org/10.1073/pnas.1000080107.
• Andrews, S., FastQC: A quality control tool for high throughput sequence data, (2010).
• Callahan, B.J., McMurdie, P.J., Rosen, M.J., Han, A.W., Johnson, A.J.A., Holmes, S.P., DADA2: High-resolution sample inference from Illumina amplicon data, Nature Methods, 13 (7) (2016), 581–583. https://doi.org/10.1038/nmeth.3869.
• Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., Glöckner, F.O., The SILVA ribosomal RNA gene database project: improved data processing and web-based tools, Nucleic Acids Research, 41 (D1) (2012), D590–D596. https://doi.org/10.1093/nar/gks1219.
• Bolyen, E., Rideout, J.R., Dillon, M.R., Bokulich, N.A., Abnet, C.C., Al-Ghalith, G.A., Alexander, H., Alm, E.J., Arumugam, M., Asnicar, F., Bai, Y., Bisanz, J.E., Bittinger, K., Brejnrod, A., Brislawn, C.J., Brown, C.T., Callahan, B.J., Caraballo-Rodríguez, A.M., Chase, J., Cope, E.K., Da Silva, R., Diener, C., Dorrestein, P.C., Douglas, G.M., Durall, D.M., Duvallet, C., Edwardson, C.F., Ernst, M., Estaki, M., Fouquier, J., Gauglitz, J.M., Gibbons, S.M., Gibson, D.L., Gonzalez, A., Gorlick, K., Guo, J., Hillmann, B., Holmes, S., Holste, H., Huttenhower, C., Huttley, G.A., Janssen, S., Jarmusch, A.K., Jiang, L., Kaehler, B.D., Kang, K. Bin, Keefe, C.R., Keim, P., Kelley, S.T., Knights, D., Koester, I., Kosciolek, T., Kreps, J., Langille, M.G.I., Lee, J., Ley, R., Liu, Y.-X., Loftfield, E., Lozupone, C., Maher, M., Marotz, C., Martin, B.D., McDonald, D., McIver, L.J., Melnik, A. V., Metcalf, J.L., Morgan, S.C., Morton, J.T., Naimey, A.T., Navas-Molina, J.A., Nothias, L.F., Orchanian, S.B., Pearson, T., Peoples, S.L., Petras, D., Preuss, M.L., Pruesse, E., Rasmussen, L.B., Rivers, A., Robeson, M.S., Rosenthal, P., Segata, N., Shaffer, M., Shiffer, A., Sinha, R., Song, S.J., Spear, J.R., Swafford, A.D., Thompson, L.R., Torres, P.J., Trinh, P., Tripathi, A., Turnbaugh, P.J., Ul-Hasan, S., van der Hooft, J.J.J., Vargas, F., Vázquez-Baeza, Y., Vogtmann, E., von Hippel, M., Walters, W., Wan, Y., Wang, M., Warren, J., Weber, K.C., Williamson, C.H.D., Willis, A.D., Xu, Z.Z., Zaneveld, J.R., Zhang, Y., Zhu, Q., Knight, R., Caporaso, J.G., Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2, Nature Biotechnology, 37 (8) (2019), 852–857. https://doi.org/10.1038/s41587-019-0209-9.
• Markowitz, V.M., Chen, I.-M.A., Palaniappan, K., Chu, K., Szeto, E., Grechkin, Y., Ratner, A., Jacob, B., Huang, J., Williams, P., Huntemann, M., Anderson, I., Mavromatis, K., Ivanova, N.N., Kyrpides, N.C., IMG: the integrated microbial genomes database and comparative analysis system, Nucleic Acids Research, 40 (D1) (2012), D115–D122. https://doi.org/10.1093/nar/gkr1044.
• Parks, D.H., Tyson, G.W., Hugenholtz, P., Beiko, R.G., STAMP: statistical analysis of taxonomic and functional profiles, Bioinformatics, 30 (21) (2014), 3123–3124. https://doi.org/10.1093/bioinformatics/btu494.
• Doğan, S.Ş., Metagenomik yaklaşım ile Tuz gölündeki alg, bakteri ve arke çeşitliliğinin araştırılması, Karamanoğlu Mehmetbey University, 2022.
• Langille, M.G.I., Zaneveld, J., Caporaso, J.G., McDonald, D., Knights, D., Reyes, J.A., Clemente, J.C., Burkepile, D.E., Vega Thurber, R.L., Knight, R., Beiko, R.G., Huttenhower, C., Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences, Nature Biotechnology, 31 (9) (2013), 814–821. https://doi.org/10.1038/nbt.2676.
• Zeng, B., Han, S., Wang, P., Wen, B., Jian, W., Guo, W., Yu, Z., Du, D., Fu, X., Kong, F., Yang, M., Si, X., Zhao, J., Li, Y., The bacterial communities associated with fecal types and body weight of rex rabbits, Scientific Reports, 5 (1) (2015), 9342. https://doi.org/10.1038/srep09342.
• Lopes, L.D., Pereira e Silva, M. de C., Andreote, F.D., Bacterial abilities and adaptation toward the rhizosphere colonization, Frontiers in Microbiology, 7 (2016). https://doi.org/10.3389/fmicb.2016.01341.
• Yuan, Z., Druzhinina, I.S., Labbé, J., Redman, R., Qin, Y., Rodriguez, R., Zhang, C., Tuskan, G.A., Lin, F., Specialized microbiome of a halophyte and its role in helping non-host plants to withstand salinity, Scientific Reports, 6 (1) (2016), 32467. https://doi.org/10.1038/srep32467.
• Hariharan, J., Sengupta, A., Grewal, P., Dick, W.A., Functional predictions of microbial communities in soil as affected by long‐term tillage practices, Agricultural & Environmental Letters, 2 (1) (2017). https://doi.org/10.2134/ael2017.09.0031.
• Oren, A., Microbial life at high salt concentrations: phylogenetic and metabolic diversity, Saline Systems, 4 (1) (2008) 2. https://doi.org/10.1186/1746-1448-4-2.
• Hoffmann, T., Bremer, E., Guardians in a stressful world: the Opu family of compatible solute transporters from Bacillus subtilis, Biological Chemistry, 398 (2) (2017), 193–214. https://doi.org/10.1515/hsz-2016-0265.
• Oren, A., Diversity of halophilic microorganisms: environments, phylogeny, physiology, and applications, Journal of Industrial Microbiology & Biotechnology, 28 (1) (2002), 56–63. https://doi.org/10.1038/sj/jim/7000176.
• Gregory, G.J., Boyd, E.F., Stressed out: Bacterial response to high salinity using compatible solute biosynthesis and uptake systems, lessons from Vibrionaceae, Computational and Structural Biotechnology Journal, 19 (2021), 1014–1027. https://doi.org/10.1016/j.csbj.2021.01.030.
• Rath, H., Reder, A., Hoffmann, T., Hammer, E., Seubert, A., Bremer, E., Völker, U., Mäder, U., Management of osmoprotectant uptake hierarchy in Bacillus subtilis via a SigB-dependent antisense RNA, Frontiers in Microbiology, 11 (2020), 1-17. https://doi.org/10.3389/fmicb.2020.00622.
• He, Q., He, Z., Joyner, D.C., Joachimiak, M., Price, M.N., Yang, Z.K., Yen, H.-C.B., Hemme, C.L., Chen, W., Fields, M.M., Stahl, D.A., Keasling, J.D., Keller, M., Arkin, A.P., Hazen, T.C., Wall, J.D., Zhou, J., Impact of elevated nitrate on sulfate-reducing bacteria: a comparative study of Desulfovibrio vulgaris, The ISME Journal, 4 (11) (2010), 1386–1397. https://doi.org/10.1038/ismej.2010.59.
• Wargo, M.J., Homeostasis and catabolism of choline and glycine betaine: Lessons from Pseudomonas aeruginosa, Applied and Environmental Microbiology, 79 (7) (2013), 2112–2120. https://doi.org/10.1128/AEM.03565-12.
• Fernández, A.B., Ghai, R., Martin-Cuadrado, A.-B., Sánchez-Porro, C., Rodriguez-Valera, F., Ventosa, A., Prokaryotic taxonomic and metabolic diversity of an intermediate salinity hypersaline habitat assessed by metagenomics, FEMS Microbiology Ecology, 88 (3) (2014), 623–635. https://doi.org/10.1111/1574-6941.12329.
• Oyewusi, H.A., Muhammad, M., Abdul Wahab, R., Huyop, F., A review on enzymatic response to salt stress and genomic/metagenomic analysis of adaptation protein in hypersaline environment, The Journal of Tropical Life Science, 11 (3) (2021), 339–360.
• Kırkağaç, M., Gümüş, E., Yokuş, G., Tuz Gölü’nde çevresel faktörlerin Artemia Populasyonu’na etkisi, Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 7 (2) (2017), 303–312.
• Ding, R., Yang, N., Liu, J., The osmoprotectant switch of potassium to compatible solutes in an extremely halophilic archaea Halorubrum kocurii 2020YC7, Genes, 13 (6) (2022), 939. https://doi.org/10.3390/genes13060939.
• Saum, S.H., Müller, V., Salinity-Dependent switching of osmolyte strategies in a moderately halophilic bacterium: glutamate induces proline biosynthesis in Halobacillus halophilus, Journal of Bacteriology, 189 (19) (2007), 6968–6975. https://doi.org/10.1128/JB.00775-07.
• Williams, T.J., Allen, M.A., DeMaere, M.Z., Kyrpides, N.C., Tringe, S.G., Woyke, T., Cavicchioli, R., Microbial ecology of an Antarctic hypersaline lake: genomic assessment of ecophysiology among dominant haloarchaea, The ISME Journal, 8 (8) (2014), 1645–1658. https://doi.org/10.1038/ismej.2014.18.
• Inoue, K., del Carmen Marín, M., Tomida, S., Nakamura, R., Nakajima, Y., Olivucci, M., Kandori, H., Red-shifting mutation of light-driven sodium-pump rhodopsin, Nature Communications, 10 (1) (2019), 1993. https://doi.org/10.1038/s41467-019-10000-x.
• Nakajima, Y., Tsukamoto, T., Kumagai, Y., Ogura, Y., Hayashi, T., Song, J., Kikukawa, T., Demura, M., Kogure, K., Sudo, Y., Yoshizawa, S., Presence of a haloarchaeal halorhodopsin-like Cl- pump in marine bacteria, Microbes and Environments, 33 (1) (2018), 89–97. https://doi.org/10.1264/jsme2.ME17197.
• Ghai, R., Pašić, L., Fernández, A.B., Martin-Cuadrado, A.-B., Mizuno, C.M., McMahon, K.D., Papke, R.T., Stepanauskas, R., Rodriguez-Brito, B., Rohwer, F., Sánchez-Porro, C., Ventosa, A., Rodríguez-Valera, F., New abundant microbial groups in aquatic hypersaline environments, Scientific Reports, 1 (1) (2011), 135. https://doi.org/10.1038/srep00135.
• Mongodin, E.F., Nelson, K.E., Daugherty, S., DeBoy, R.T., Wister, J., Khouri, H., Weidman, J., Walsh, D.A., Papke, R.T., Sanchez Perez, G., Sharma, A.K., Nesbo, C.L., MacLeod, D., Bapteste, E., Doolittle, W.F., Charlebois, R.L., Legault, B., Rodriguez-Valera, F., The genome of Salinibacter ruber: convergence and gene exchange among hyperhalophilic bacteria and archaea, Proceedings of the National Academy of Sciences, 102 (50) (2005), 18147–18152. https://doi.org/10.1073/pnas.0509073102.
• Sharma, A.K., Walsh, D.A., Bapteste, E., Rodriguez-Valera, F., Ford Doolittle, W., Papke, R.T., Evolution of rhodopsin ion pumps in haloarchaea, BMC Evolutionary Biology, 7 (1) (2007), 79. https://doi.org/10.1186/1471-2148-7-79.