مقایسه تنوع جمعیت باکتری‌های همراه بلوط ایرانی در دو روش شناسایی مبتنی بر کشت و مستقل از کشت (متاژنومیکس)

نویسندگان

1 دانشجوی دکتری بیوتکنولوژی جنگل، گروه جنگلشناسی و اکولوژی جنگل دانشگاه علوم کشاورزی و منابع طبیعی گرگان.

2 *نویسنده مسئول: دانشیار، گروه جنگلشناسی و اکولوژی جنگل دانشکده علوم جنگل دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

3 کرج پژوهشکده بیوتکنولوژی کشاورزی ایران

4 استاد، گروه بیوتکنولوژی میکروبی پژوهشگاه بیوتکنولوژی کشاورزی ایران (ABRII)، کرج، ایران

5 دانشیار، دانشکده علوم و زیست فنآوری، دانشگاه شهید بهشتی، تهران، ایران.

چکیده

هدف: در طی یک دهه گذشته حدود 30-20 درصد جنگلهای زاگرس با معضلی به نام زوال بلوط مواجه شده­اند. تحقیق حاضر با هدف بررسی تنوع باکتریایی مناطق جنگلی سالم و زوال یافته از طریق مقایسه نتایج دو روش مبتنی بر کشت و مستقل از کشت طراحی و انجام شد.
مواد و روش‌ها: از بافت­های مختلف درختان بلوط و خاک اطراف آنها در جنگل­های مناطق مختلف استان ایلام نمونه برداری انجام شد. در روش مبتنی بر کشت با استفاده از روش­های میکروبیولوژی و مولکولی، باکتری­های موجود در نمونه­ها جداسازی و شناسایی تا سطح جنس و گونه شناسایی شدند. به منظور مطالعه متاژنومیکس در روش مستقل از کشت، DNA میکروبی به طور مستقیم از نمونه­ها استخراج و با آماده سازی کتابخانه متاژنومی با استفاده از آغازگرهای عمومی و نشانگر، تنوع باکتریایی با استفاده از پلتفرم Miseq کمپانی Illumina مورد بررسی قرار گرفت و در ادامه نتایج دو روش مورد مقایسه قرار گرفت.
نتایج: بر اساس روش مبتنی بر کشت، تنها 3 فیلوم شناسایی شد، در صورتیکه در روش متاژنومیکسی، تعداد 9416 OTU بدست آمد که به 12 فیلوم تقسیم بندی شدند. در هر دو روش 3 خانواده Bacillaceae، Enterobacteriacea و Xanthomonadaceae به عنوان خانواده­های غالب مشاهده شدند. تنوع گونه­ایی در یک نمونه (تنوع آلفا) در نمونه رایزوسفر و در مناطق ایوان و گله جار نسبت به سایر نمونه­ها بیشتر بود که در روش مبتنی بر کشت نیز این دو منطقه از تنوع گونه­ای بیشتر برخوردار بودند. تنوع گونه­ایی در بین نمونه­ها (تنوع بتا) در مناطق ایوان، گله­جار، چوار، تنگ­دالاب و ارغوان از نظر ترکیب گونه­ای مشابه بودند. اما جامعه باکتریایی ساقه و برگ نسبت به سایر نمونه­ها شباهت بیشتری داشتند و بالک و رایزوسفر هم از نظر ترکیب گونه­ای شباهت بیشتری با یکدیگر داشتند.
نتیجه‌گیری: در روش متاژنومیکس جنس­های با تنوع خیلی کم هم شناسایی می­شود در صورتیکه در روش مبتنی بر کشت احتمال این موضوع ضعیف است. ضمنا در روش مستقل از کشت می­توان تنوع آلفا و بتا را به شکل جامع­تری بررسی کرد. در روش مبتنی بر کشت می­توان جمعیت باکتریایی را تا سطح گونه شناسایی کرد در صورتیکه در روش مستقل از کشت معمولا تا سطح جنس شناسایی می­شود. لذا پیشنهاد می­شود در مطالعات بررسی جوامع میکروبی ترکیب دو روش مبتنی و مستقل از کشت همزمان استفاده شود.

کلیدواژه‌ها


عنوان مقاله [English]

A comparative study of culture dependent and independent techniques (metagenomics) of bacterial communities associated with Persian oak tree

نویسندگان [English]

  • Elaheh Ahmadi 1
  • Davoud Azadfar 2
  • Mozhgan Kowsari 3
  • Gholamreza Salehi Jouzani 4
  • Masood Tohidfar 5
1 PhD Candidate, Department of Silviculture and forest ecology, Gorgan university of Agricultural Science and Natural Resources
2 Corresponding author. Associate Professor, Department of Silviculture and forest ecology, Gorgan university of Agricultural Science and Natural Resources, Gorgan, Iran
3 Assistant Professor, Microbial Biotechnology Department, Agricultural Biotechnology Research Institute of Iran (ABRII), Karaj, Iran
4 Professor, Microbial Biotechnology Department, Agricultural Biotechnology Research Institute of Iran (ABRII), Karaj, Iran
5 Science and biotechnology faculty, Shaid beheshti. Tel.: 02129903244. Fax: 021 29903244
چکیده [English]

Objective
During the last decade, about 20-30% of the Zagros forests have faced a problem called oak decline. The aim of present study was to investigate the bacterial diversity in the healthy and declined forest areas by comparing two methods culture-dependent and culture-independent methods.
Materials and methods
Sampling was done from different tissue and soil of oak trees in the forests of Ilam province. In the culture-based method, using microbiological and molecular methods the bacteria in the samples were isolated and identified to the genus and species level. In order to study metagenomics in culture-independent method, total microbial DNA was extracted directly from the samples and prepared metagenomic library using conventional and index primer, the diversity of bacterial was examined using Illumina's Miseq platform and then the results of the two methods were compared.
Results
Based on the culture-based method, only 3 phylum were identified, while in the metagenomics method, 9416 OTUs were obtained, that were divided into 12 phylum. In both methods, 3 families of Bacillaceae, Enterobacteriacea and Xanthomonadaceae were observed as the dominant families. The species diversity within a sample (Alpha diversity) was higher in the rhizosphere sample and in the Eyvan and Gale jar areas than other samples. The species diversity between samples (Beta diversity) was in Eyvan, Gale jar, Chavar, Tangedalab and Arghavan appear more similar to each other than the sites samples. Bacterial community of stems and leaves were more similar and also bulk and rhizosphere were more similar in bacterial species composition.
Conclusions
In the metagenomics method, very few species are identified, while in the culture method, the probability of this is low. Also, in the culture-independent method, alpha and beta diversity can be studied more comprehensively. In the culture-based method, the bacterial population can be identified up to the species level, while in the culture-independent method, it is usually identified up to the genus level. Therefore, it is suggested to use a combination of two methods simultaneously in studies of microbial communities.

کلیدواژه‌ها [English]

  • Bacterium
  • Diversity
  • Oak Decline
  • Phylogeny
  • Metagenome
Ahmadi E, Kowsari M, Azadfar D, Salehi Jouzani, GR (2018) Rapid and economical protocols for genomic and metagenomic DNA extraction from oak (Quercus brantii Lindl.). Ann For Sci 75(2), 1-14.
Ahmadi E, Kowsari M, Azadfar D, Salehi Jouzani, GR (2019) Bacillus pumilus and Stenotrophomonas maltophilia as two potentially causative agents involved in Persian oak decline in Zagros forests (Iran). For Pathol 49(5), e12541.
Alidadi A, Kowsari M, Javan-Nikkhah M et al. (2019) New pathogenic and endophytic fungal species associated with Persian oak in Iran. Eur J Plant Pathol 155(3), 1017-1032.
Anderson MJ (2001) A new method for non‐parametric multivariate analysis of variance.           Austral Ecol 26(1), 32-46.
Arbuzova EN, Kulinich OA, Mazurin ES, Zinov’eva SV (2014) About of the etiology of pine wilt disease in Russia. Dokl Biol Sci 457(1), 244-247
Bálint M, Bahram M, Eren AM et al. (2016) Millions of reads, thousands of taxa: microbial community structure and associations analyzed via marker genes. FEMS Microbiol Rev 40(5), 686-700.
Bedrood F, Hedayat Gh, Valipour (2021) Application of the Logical Framework Analysis for planning and evaluation of oak decline’s forest management plan. Iran J For Pop Res 29(1), 1-10.
Brady C, Denman S, Kirk S et al. (2010) Description of Gibbsiella quercinecans gen. nov., sp. nov., associated with Acute Oak Decline. Syst Appl Microbiol 33, 444–450.
Brady C, Hunter G, Kirk S et al. (2014) Gibbsiella greigii sp. nov., a novel species associated with oak decline in the USA. Syst Appl Microbiol 37, 417–422.
Brockett BF, Prescott CE, Grayston SJ (2012) Soil moisture is the major factor influencing microbial community structure and enzyme activities across seven biogeoclimatic zones in western Canada. Soil Biol Biochem 44(1), 9-20.
Brown N (2013) Epidemiology of acute oak decline in Great Britain. PhD thesis, Imperial College London. pp. 260.
Bulgarelli D, Schlaeppi K, Spaepen S et al. (2013) Structure and functions of the bacterial microbiota of plants. Annu Rev Plant Biol 64, 807-838.
Callahan BJ, McMurdie PJ, Rosen MJ et al. (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13(7), 581-583.
Caporaso JG, Kuczynski J, Stombaugh J et al. (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7, 335-336.
Citlali FG, Desgarennes D, Flores-Núñez VM, Partida-Martínez LP (2018) The microbiome of desert CAM plants: lessons from amplicon sequencing and metagenomics. In Metagenomics (pp. 231-254). Academic Press.
Cregger MA, Veach AM, Yang ZK et al. (2018) The Populus holobiont: dissecting the effects of plant niches and genotype on the microbiome. Microbiome 6(1), 1-14.
Cruz AT, Cazacu AC, Allen CH (2007) Pantoea agglomerans, a plant pathogen causing human disease. J Clin Microbiol 45(6), 1989-1992.
Czajkowski R, De Boer WJ, Van Veen JA, Van Der Wolf JM (2010) Downward vascular translocation of a green fluorescent protein-tagged strain of Dickeya sp. (biovar 3) from stem and leaf inoculation sites on potato. Phytopathology 100 (11), 1128-1137.
Delfan S, Badehian Z, Zarafshar M, Graham JH (2021) Oak decline alters leaves and fruit of Persian oak (Quercus brantii Lindl.). Flora 284, e151926.
Delmont TO, Robe P, Cecillon S et al. (2011) Accessing the Soil Metagenome for Studies of Microbial Diversity. Appl Environ Microbiol 101, 1315–1324.
Denman S, Brady C, Kirk S, Cleenwerck I, Venter S, Coutinho T, De Vos P (2012) Brenneria goodwinii sp. nov., associated with acute oak decline in the UK. Int J Syst Evol Microbiol 62, 2451–2456.
Denman S, Brown N, Kirk S et al. (2014) A description of the symptoms of Acute Oak Decline in Britain and a comparative review on causes of similar disorders on oak in Europe. Forestry doi:10.1093/forestry/cpu010.
Denman S, Doonan J, Ransom-Jones E et al. (2018) Microbiome and infectivity studies reveal complex polyspecies tree disease in Acute Oak Decline. ISME j 12(2), 386-399.
Denman S, Plummer S, Kirk S, et al (2016) Isolation studies reveal a shift in the cultivable microbiome of oak affected with Acute Oak Decline. Syst Appl Microbiol 39(7), 484-490.
DeSantis TZ, Hugenholtz P, Larsen N et al. (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72, 5069-5072.
Dixon P (2003) VEGAN, a package of R functions for community ecology. J Veg Sci 14(6), 927-930.
Doonan J, Denman S, McDonald JE, Golyshin PN (2019) Shotgun metagenomic sequencing analysis of soft-rot Enterobacteriaceae in polymicrobial communities. In Metagenomics (pp. 85-97). Humana Press, New York, NY.
Fadiji AE, Babalola OO (2020) Metagenomics methods for the study of plant-associated microbial communities: a review.    J Microbiol Methods 170, e105860.
Frank DN, Pace NR (2008) Gastrointestinal microbiology enters the metagenomics era. Curr Opin Gastroenterol 24(1), 4-10.
Gans J, Wolinsky M, Dunbar J (2005) Computational improvements reveal great bacterial diversity and high metal toxicity in soil. Science 309, 1387-1390.
Haas JC, Street NR, Sjödin A et al. (2018) Microbial community response to growing season and plant nutrient optimisation in a boreal Norway spruce forest. Soil Biol Biochem 125, 197-209.
Hardoim PR, Van Overbeek LS, Berg G et al. (2015) The hidden world within plants: ecological and evolutionary considerations for defining functioning of microbial endophytes. Microbiol Mol Biol Rev 79(3), 293-320.
He LX, Wu XQ, Xue Q, Qiu XW (2016) Effects of Endobacterium (Stenotrophomonas maltophilia) on pathogenesis-related gene expression of pine wood nematode (Bursaphelenchus xylophilus) and pine wilt disease. Int J Mol Sci 17(6), 778.
Jaric M, Segal J, Silva-Herzog E et al. (2013) Better primer design for metagenomics applications by increasing taxonomic distinguishability. BMC Proc 7(7), 1-10.
Jin H, Yang XY, Yan ZQ et al. (2014) Characterization of rhizosphere and endophytic bacterial communities from leaves, stems and roots of medicinal Stellera chamaejasme L. Syst Appl Microbiol 37(5), 376-385.
Li B, Qiu W, Tan QM et al. (2009) Association of a Bacillus species with leaf and twig dieback of Asian pear (Pyrus pyrifolia) in China. Plant Pathol 91(3), 705-708.
Lin X, Tfaily MM, Steinweg JM et al. (2014) Microbial Community Stratification Linked to Utilization of Carbohydrates and Phosphorus Limitation in a Boreal Peatland at Marcell Experimental Forest, Minnesota, USA. Appl Environ Microbiol 80 (11), 3518.
Lladó S, López-Mondéjar R, Baldrian P (2017) Forest soil bacteria: diversity, involvement in ecosystem processes, and response to global change. Microbiol Mol Biol Rev 81(2), e00063-16.
Mohan Singh S, Sahab Yadav L, Kumar Singh S et al. (2011). Phosphate solubilizing ability of two Arctic Aspergillus niger strains. Polar Res 30(1), 7283.
Moradi-Amirabad Y, Rahimian H, Babaeizad V, Denman S (2019) Brenneria spp. and Rahnella victoriana associated with acute oak decline symptoms on oak and hornbeam in Iran. For Pathol 49(4), e12535.
Nahid SH, Yasir S, Ali A (2012) Defining optimum metagenomic procedure for microbial diversity analysis in wheat rhizosphere. Adv Appl Sci Res 3(1), 407-411.
O’Donnell JL, Kelly RP, Lowell NC, Port JA (2016) Indexed PCR primers induce template-specific bias in large-scale DNA sequencing studies. PLoS One 11(3), e0148698.
Oksanen J, Guillaume Blanchet F, Kindt R et al. (2016) vegan: community ecology package. R package version 2.3-3.
Penton CR, Gupta VSR, Tiedje JM et al. (2014) Fungal Community Structure in Disease Suppressive Soils Assessed by 28S LSU Gene Sequencing. PLoS ONE 9(4), e93893. doi:10.1371/journal.pone.0093893.
Ping Y, Pan X, Li W et al. (2019) The soil bacterial and fungal diversity were determined by the stoichiometric ratios of litter inputs: evidence from a constructed wetland. Sci Rep 9(1), 1-7.
Pourhashemi M, Sadeghi SMM (2020) A Review on Ecological Causes of Oak Decline Phenomenon in Forests of Iran. Iran J Appl Ecol 8(16), 148-164.
Poza-Carrion C, Aguilar I, Gallego FJ et al. (2008) Brenneria quercina and Serratia spp. isolated from Spanish oak trees: molecular characterization and development of PCR primers. Plant Pathol 57, 308- 319.
Rosselli R, Squartini A (2015) Metagenomics of Plant–Microbe Interactions. G. Sablok et al. (eds.), Advances in the Understanding of Biological Sciences Using Next Generation Sequencing (NGS) Approaches. (eds. Sablok, G., Kumar, S., Ieno, S., Kuo, J. & Varotto, C.) 63–78 (Springer International Publishing, 2015). doi: 10.1007/978-3-319-17157-9_5.
Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4, 406-425.
Schaad NW, Jones JB, Chun W (2001) Laboratory Guide for Identification of Plant Pathogenic Bacteria. APS Press St. Paul., Minnesota, USA 373 pp.
Singh JS (2014) Cyanobacteria: a vital bio-agent in eco-restoration of degraded lands and sustainable agriculture. Clim Chang Environ Su 2(2), 133-137.
Stefani FO, Bell TH, Marchand C et al. (2015) Culture-dependent and-independent methods capture different microbial community fractions in hydrocarbon-contaminated soils. PloS one 10(6), e0128272.
Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol 24, 1596-1599.
Vorholt JA (2012) Microbial life in the phyllosphere. Nat Rev Microbiol 10, 828–40.
Wang X, Tang C, Severi J et al. (2016) Rhizosphere priming effect on soil organic carbon decomposition under plant species differing in soil acidification and root exudation. New Phytol 211(3), 864-873.
Whipps J, Hand P, Pink D, Bending GD (2008) Phyllosphere microbiology with special reference to diversity and plant genotype. J Appl Microbiol 105(6), 1744-1755.
White TJ, Bruns T, Lee SJW, Taylor JW (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. PCR protocols: a guide to methods and applications 18, 315-322.
Zhou J, Bruns MA, Tiedje JM (1996) DNA recovery from soils of diverse composition. Appl Environ Microb 62, 316–322.
Zhou J, He Z, Yang Y (2015) High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats. MBio 6(1), e02288-14.