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  • بررسی تنوع میکروبی و پیش بینی ژن های عملکردی موثر در تجزیه ترکیبات آروماتیک در آب خلیج نایبند

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آدرس مقاله


کد مقاله : JMW-2205-2019 (R1) بازدید : 266 صفحه: 207 - 219

10.30495/jmw.2022.1958743.2019

20.1001.1.20083068.1401.15.0.4.6

نوع مقاله: پژوهشی

بررسی تنوع میکروبی و پیش بینی ژن های عملکردی موثر در تجزیه ترکیبات آروماتیک در آب خلیج نایبند

محورهای موضوعی : میکروب شناسی محیطی

مهسا حریرفروش 1 , محمد علی آموزگار 2 , محمود شوندی 3 , پروانه صفاریان 4

1 - گروه زیست شناسی، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران
2 - استاد، گروه میکروبیولوژی، پردیس علوم، دانشگاه تهران، تهران، ایران
3 - دانشیار، گروه تحقیقاتی میکروبیولوژی و بیوتکنولوژی، پژوهشگاه صنعت نفت، تهران، ایران
4 - استادیار،گروه زیست شناسی، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران

تاریخ دریافت : 1401/02/28 تاریخ پذیرش : 1401/08/15 تاریخ انتشار : 1401/09/15

کلید واژه: خلیج نایبند, توالی یابی نسل جدید, هیدروکربن های آروماتیک, آلودگی نفت, تنوع میکروبی, ژن‌های عمکلردی,

چکیده مقاله :

سابقه و هدف: خلیجنایبند به دلیل مجاورت با منطقه صنعتی عسلویه در معرض آلایندههای نفتی است. قرار گرفتن طولانی مدت در معرض آلایندهها بر جمعیت میکروبی تأثیر میگذارد و جمعیت را به سمت میکروبهای تجزیه کننده نفت سوق میدهد. در این مطالعه به بررسی تنوع میکروبی در آب‌های خلیج نایبند و پیش‌بینی ژن‌های عمکلردی موثر در تجزیه هیدروکربن‌های آروماتیک تحت شرایط هوازی و بی‌هوازی می‌پردازیم.مواد و روشها: برای استخراج DNA از نمونه آب خلیجنایبند از روش استاندارد فنلکلروفرم استفاده شد. توالی یابیDNA استخراج شده با تکنیک توالییابی نسل جدید انجام شد. سپس قطعه مبتنی بر ژن 16S rRNAتجزیه وتحلیل شد. همچنین پیش‌بینی ژن‌های عملکردی موثر در تخریب هیدروکربن‌های آروماتیک تحت شرایط هوازی و بیهوازی انجام شد.یافتهها: آلودگی هیدروکربن‌های آروماتیک در آب خلیجنایبند منجر به غالبشدن اعضای اشنوسپیرالسOceanospirillales (24/67%)، سلویبریونالس Cellvibrionales (28/95%)، سار11-کلد SAR11 clade (20/97%)، رودوباکتریالسRhodobacterales (6/17%)، رودواسپیرالس Rhodospirillales (7/12%) و فلاووباکتریالس Flavobacteriales (5/5%) شده است. ردههای آلفاپروتئوباکتریا Alphaproteobacteria (26/18%) و گاماپروتئوباکتریا Gammaproteobacteria (42/23%) بیشترین فراوانی را داشتند. با توجه به آنالیز دادهها (PICRUSt) ژن‌های موثر در تجزیه نفتالین در شرایط بی‌هوازی بیشترین فراوانی را در نمونه داشتند.نتیجهگیری: قرار گرفتن طولانی مدت در معرض آلودگی نفتی بر جمعیت میکروبی تأثیر میگذارد. جمعیت میکروبی منطقه نایبند نیز به دلیل مجاورت با منطقه نفتی پارس جنوبی و ورود آلایندههای نفتی به آب در جهت غالب شدن اعضای تجزیه کننده هیدروکربنها پیش رفته است.

چکیده انگلیسی:

Background & Objective: Nayband Gulf is subjected to oil pollution due to the proximity to Assaluyeh industrial region. Prolonged exposure to contaminants affects the microbial population and shifts the population to the predominance of oil-degrading microbes. In this study, we  investigate the microbial diversity in Nayband Gulf waters and predict the genes involved in aromatic hydrocarbon degradation under aerobic and anaerobic conditions.Materials & Methods: Phenol-chloroform method was performed for extracting DNA from the Nayband Gulf water sample. Extracted DNA sequencing was performed by new generation  sequencing technique. Then 16S rRNA gene-based amplicon sequencing was analyzed. Functional genes involved in the degradation of aromatic hydrocarbons under aerobic and anaerobic conditions were predicted from 16S rRNA gene sequences.Results: Our findings indicate that aromatic hydrocarbons contamination in Nayband Gulf water resulted in the enrichment of Oceanospirillales (24.67%), Cellvibrionales (28.95%), SAR11 clade (20.97%), Rhodobacterales (6.17%), Rhodospirillales (7.12%) and Flavobacteriales (5.50%).  Alphaproteobacteria (26.18%) and Gammaproteobacteria (42.23%) had the highest percentage. According to Phylogenetic Investigation of Communities by Reconstruction of Unobserved States, the genes involved in degradation of naphthalene under anaerobic conditions were most abundant in the sample.Conclusion: The results of this study showed that long-term exposure to oil pollution and oil spills affects the microbial population. The microbial population of Nayband Gulf region, due to its proximity to the South Pars oil & gas region and the entry of oil pollutants into the water, has caused the domination of petroleum hydrocarbons degrading bacteria. 

منابع و مأخذ:

References

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_||_

References

  1. Neethu CS, Saravanakumar C, Purvaja R, Robin RS, Ramesh R. Oil-Spill Triggered Shift in Indigenous Microbial Structure and Functional Dynamics in Different Marine Environmental Matrices. Sci Rep [Internet]. 2019;9(1):1–13. Available from: http://dx.doi.org/10.1038/s41598-018-37903-x
    2.
  2. Ivshina IB, Kuyukina MS, Krivoruchko A V., Elkin AA, Makarov SO, Cunningham CJ, et al. Oil spill problems and sustainable response strategies through new technologies. Environ Sci Process Impacts [Internet]. 2015;17(7):1201–19. Available from: http://dx.doi.org/10.1039/C5EM00070J
    3.
  3. Kyrklund T, Dreij, K. Human health effects of polycyclic aromatic hydrocarbons as ambient air pollutants; 978-92-890-5653-3, Copenhagen. WHO Regional Office for Europe 2021.
    4.
  4. Coil D, Lester E, Higman B. Oil Degradation in the Sea. Gr Truth Trekking [Internet]. 2010;(November):1.Availablefrom:http://www.groundtruthtrekking.org/Issues/AlaskaOilandGas/OilDegradation.html
    5.
  5. Mishra AK, Kumar GS. Weathering of Oil Spill: Modeling and Analysis. Aquat Procedia [Internet].2015;4(Icwrcoe):435–42.Availablefrom:http://dx.doi.org/10.1016/j.aqpro.2015.02.058
    6.
  6. Xu X, Liu W, Tian S, Wang W, Qi Q, Jiang P, et al. Petroleum Hydrocarbon-Degrading Bacteria for the Remediation of Oil Pollution Under Aerobic Conditions: A Perspective Analysis. Front Microbiol. 2018;9(December):1–11.
    7.
  7. Hu P, Dubinsky EA, Probst AJ, Wang J, Sieber CMK, Tom LM, et al. Simulation of Deepwater Horizon oil plume reveals substrate specialization within a complex community of hydrocarbon degraders. Proc Natl Acad Sci U S A. 2017;114(28):7432–7.
    8.
  8. Hassanshahian M, Abarian M, Cappello S. Biodegradation of Aromatic Compounds. Biodegrad Bioremediation Polluted Syst - New Adv Technol. 2015;(January 2016).
    9.
  9. Ghosal D, Ghosh S, Dutta TK, Ahn Y. Current state of knowledge in microbial degradation of polycyclic aromatic hydrocarbons (PAHs): A review. Front Microbiol. 2016;7(AUG).
    10.
  10. Joydas T V., Qurban MA, Borja A, Krishnakumar PK, Al-Suwailem A. Macrobenthic community structure in the northwestern Arabian Gulf, twelve years after the 1991 oil spill. Front Mar Sci. 2017;4(AUG):1–18.
    11.
  11. Rezaei Somee M, Dastgheib SMM, Shavandi M, Ghanbari Maman L, Kavousi K, Amoozegar MA, et al. Distinct microbial community along the chronic oil pollution continuum of the Persian Gulf converge with oil spill accidents. Sci Rep [Internet]. 2021;11(1):1–15. Available from: https://doi.org/10.1038/s41598-021-90735-0
    12.
  12. Martín-Cuadrado AB, López-García P, Alba JC, Moreira D, Monticelli L, Strittmatter A, et al. Metagenomics of the deep Mediterranean, a warm bathypelagic habitat. PLoS One. 2007;2(9).
    13.
  13. Franzosa EA, Hsu T, Sirota-Madi A, Shafquat A, Abu-Ali G, Morgan XC, et al. Sequencing and beyond: integrating molecular “omics” for microbial community profiling. Nat Rev Microbiol [Internet]. 2015 Jun 18 [cited 2022 May 9];13(6):360–72. Available from: https://pubmed.ncbi.nlm.nih.gov/25915636/
    14.
  14. Estaki M, Jiang L, Bokulich NA, McDonald D, González A, Kosciolek T, et al. QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data. Curr Protoc Bioinforma. 2020;70(1):1–46.
    15.
  15. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006;72(7):5069–72.
    16.
  16. Mukherjee A, Chettri B, Langpoklakpam JS, Basak P, Prasad A, Mukherjee AK, et al. Bioinformatic Approaches Including Predictive Metagenomic Profiling Reveal Characteristics of Bacterial Response to Petroleum Hydrocarbon Contamination in Diverse Environments. Sci Rep. 2017;7(1):1–22.
    17.
  17. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75(23):7537–41.
    18.
  18. Sun J, Steindler L, Thrash JC, Halsey KH, Smith DP, Carter AE, et al. One Carbon Metabolism in SAR11 Pelagic Marine Bacteria. 2011;6(8).
    19.
  19. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol [Internet]. 2009 Dec [cited 2022 May 7];75(23):7537–41. Available from: https://journals.asm.org/doi/full/10.1128/AEM.01541-09
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  20. Murillo AA, Molina V, Salcedo-Castro J, Harrod C. Editorial: Marine Microbiome and Biogeochemical Cycles in Marine Productive Areas. Front Mar Sci. 2019;6(October):1–3.
    21.
  21. Hazen TC, Dubinsky EA, DeSantis TZ, Andersen GL, Piceno YM, Singh N, et al. Deep-sea oil plume enriches indigenous oil-degrading bacteria. Science (80- ). 2010;330(6001):204–8.
    22.
  22. Xu X, Liu W, Tian S, Wang W, Qi Q, Jiang P, et al. Petroleum Hydrocarbon-Degrading Bacteria for the Remediation of Oil Pollution Under Aerobic Conditions: A Perspective Analysis. Front Microbiol. 2018 Mar 29;9:2885.
    23.
  23. Yakimov MM, Timmis KN, Golyshin PN. Obligate oil-degrading marine bacteria. 2007;
    24.
  24. Gregson BH, Mckew BA, Holland RD, Nedwed TJ, Prince RC, Mcgenity TJ, et al. Marine Oil Snow , a Microbial Perspective. 2021;8(January).
    25.
  25. Mason OU, Scott NM, Gonzalez A, Robbins-Pianka A, Bælum J, Kimbrel J, et al. Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill. ISME J. 2014;8(7):1464–75.
    26.
  26. Bamforth SM, Singleton I. Bioremediation of polycyclic aromatic hydrocarbons: Current knowledge and future directions. J Chem Technol Biotechnol. 2005;80(7):723–36.
    27.
  27. Fernandes GL, Shenoy BD, Damare SR. Diversity of Bacterial Community in the Oxygen Minimum Zones of Arabian Sea and Bay of Bengal as Deduced by Illumina Sequencing. Front Microbiol. 2020;10(January):1–14.
    28.
  28. Bacosa HP, Erdner DL, Rosenheim BE, Shetty P, Seitz KW, Baker BJ, et al. Hydrocarbon degradation and response of seafloor sediment bacterial community in the northern Gulf of Mexico to light Louisiana sweet crude oil. ISME J [Internet]. 2018;12(10):2532–43. Available from: http://dx.doi.org/10.1038/s41396-018-0190-1
    29.
  29. Kasai Y, Kishira H, Sasaki T, Syutsubo K, Watanabe K, Harayama S. Predominant growth of Alcanivorax strains in oil- contaminated and nutrient-supplemented sea water. 2002;4: 141–7.
    30.
  30. Lazure P. A model of the general circulation in the Persian Gulf and in the Strait of A model of the general circulation in the Persian Gulf and in the Strait of Hormuz : Intraseasonal to interannual variability. 2015;(May 2018).
    31.
  31. St John E, Reysenbach AL. Nanoarchaeota. Encycl Microbiol. 2019 Jan 1;274–9.
    32.
  32. Okoh A, Ajisebutu S, Babalola G, Trejo-Hernandcz MR. Potential of Burkholderia cepacia RQ1 in the biodégradation of heavy crude oil. Int Microbiol. 2001;4(2):83–7.
    33.

 

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