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Metabarkodlama yaklaşımıyla Tuz Gölü, Türkiye mikroorganizmalarının belirlenmesi için bir pilot çalışma

Year 2020, Issue: 19, 366 - 374, 31.08.2020
https://doi.org/10.31590/ejosat.682557

Abstract

Mikroskopi ve kültür tekniklerine dayanan geleneksel mikrobiyal yöntemler oldukça etkili olmalarına rağmen, çevresel örneklerde bulunan mikrobiyal türlerin yüksek çeşitliliğini tanımlamakta zaman zaman yetersiz kalmaktadır. Geçtiğimiz son yirmi yılda, moleküler teknikler önemli düzeyde gelişmiştir ve genomik yaklaşımlar mikroorganizmaların dağılımını daha kapsamlı ve nicel olarak tanımlamak için kullanılmaktadır. Bu pilot çalışmada, Tuz Gölü'nde bulunan prokaryotik ve ökaryotik mikroorganizmaların çeşitliliği metabarkodlama yaklaşımıyla araştırılmıştır. 16S / 18S rDNA dizilemesi sonuçlarına göre, örneklerde ortalama 29 arkeal, 23 bakteriyel ve 61 ökaryotik OTU belirlenmiştir ve prokaryotik OTU`ların oranı %65,3'tür. Tüm örneklerde, en çok belirlenen arkeal OTU Euryarchaeota şubesinden Haloquadratum walsbyi`e aittir ve en yaygın bakteriyel OTU`lar ise Salinibacter cinsinin üyelerine aittir. 18S rDNA sekanslama sonuçlarına göre, en çok gözlenen ökaryotik OTU, Dunaliella salina`dır. Bu çalışmada, in vitro kültürü yapılamayan birçok prokaryotik ve ökaryotik OTU tespit edilmiş ve veritabanlarındaki 16S rDNA sekanslarına % 97'den az benzerliği (% 92) olan bir OTU belirlenmiştir. Elde edilen sonuçlar, Tuz Gölü'ndeki mikrobiyal toplulukların yapısının ve bileşiminin aydınlatılmasına katkıda bulunma potansiyeline sahiptir.

Supporting Institution

Hacettepe Üniversitesi

Project Number

FHD-2017-16050

Thanks

Çalışmanın planlanması sırasındaki yardımcı ve eleştirel yorumları için Prof. Dr. Hatice Mergen, Doç. Dr. Sırma Çapar Dinçer ve Deniz Eyice’ye teşekkür ederim. Bu çalışma Hacettepe Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi (FHD-2017-16050 numaralı proje) tarafından desteklenmiştir.

References

  • Abdallah MB, Karray F, Mhiri N, Mei N, Quéméneur M, Cayol JL, et al. (2016). Prokaryotic diversity in a Tunisian hypersaline lake, Chott El Jerid. Extremophiles, 20, 125-138.
  • Abdelfattah A, Malacrinò A, Wisniewski M, Cacciola SO & Schena L. (2017). Metabarcoding: a powerful tool to investigate microbial communities and shape future plant protection strategies. Biol Control, 120, 1–10.
  • Amann RI, Lin C, Key R, Montgomery L and Stahl DA. (1992). Diversity among Fibrobacter isolates: towards a phylogenetic classification. Syst Appl Microbiol, 15, 23–31.
  • Amaral-Zettler LA, McCliment EA, Ducklow HW, & Huse SM. (2009). A method for studying protistan diversity using massively parallel sequencing of V9 hypervariable regions of small-subunit ribosomal RNA Genes. PLoS ONE, 4, e6372.
  • Birbir M, Sesal C. (2003). Extremely halophilic bacterial communities in Şereflikoçhisar Salt Lake in Turkey. Turk J Biol, 27, 7-22.
  • Bolhuis H, Palm P, Wende A, Falb M, Rampp M, Rodriguez-Valera F, Pfeiffer F, Oesterhelt D. (2006). The genome of the square archaeon Haloquadratum walsbyi: life at the limits of water activity. BMC Genomics, 7, 169.
  • Brown DS, Jarman SN, Symondson WO. (2012). Pyrosequencing of prey DNA in reptile faeces: analysis of earthworm consumption by slow worms. Mol Ecol Res, 12, 259-266.
  • Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes S. (2016). DADA2: High resolutionsample inference from Illumina amplicon data. Nat Methods, 13, 581-583.
  • Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, et al. (2010). QIIME allows analysis of high throughput community sequencing data. Nat Methods, 7, 335-336.
  • Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, Noah Fierer N, & Knight R. (2011). Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA, 108, 4516–4522.
  • Caporaso JG, Lauber C L, Walters W A, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, & Knight R. (2012). Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J, 6, 1621–1624.
  • Collins MD, Rodrigues U, Ash C, Aguirre M, Farrow JAE, Martinez-Murcia A, Phillips BA, Williams AM and Wallbanks S. (1991). Phylogenetic analysis of the genus Lactobacillus and related lactic acid bacteria as determined by reverse transcriptase sequencing of 16S rRNA. FEMS Microbiol Lett, 77, 5–12.
  • Çınar S, Mutlu MB. (2016). Comparative analysis of prokaryotic diversity in solar salterns in eastern Anatolia (Turkey). Exteremophiles, 20, 589-601.
  • DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. (2006). Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol, 72, 5069-5072.
  • Edgar RC. (2013). UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nature Methods, 10, 996–998.
  • Elevi Bardavid R, Ionescu D, Oren A, Rainey FA, Hollen BJ, Bagaley DR, Small AM, McKay C. (2007). Selective enrichment, isolation and molecular detection of Salinibacter and related extremely halophilic Bacteria from hypersaline environments. Hydrobiologica, 576, 3-13.
  • Emerson JB, Thomas BC, Andrade K, Allen EE, Heidelberg KB, Banfield JF. (2012). Dynamic viral populations in hypersaline systems as revealed by metagenomic assembly. Appl. Environ. Microbiol, 78, 6309–6320.
  • Emerson JB, Andrade K, Thomas BC, Norman A, Allen EE, Heidelberg KB, Banfield JF. (2013). Virus–host and CRISPR dynamics in archaea-dominated hypersaline Lake Tyrrell, Victoria, Australia. Archaea, 370871.
  • Federhen S. The NCBI taxonomy database. (2012). Nucleic Acids Res, 40, 136–143.
  • Fernandez AB, Ghai R, Martin-Cuadrado AB, Sanchez-Porro C, Rodriguez-Valera F, Ventosa A. (2014). Prokaryotic taxonomic and metabolic diversity of an intermediate salinity hypersaline habitat assessed by metagenomics. FEMS Microbiol Ecol, 88, 623–635.
  • Fouts DE, Szpakowski S, Purushe J, Torralba M, Waterman RC, et al. (2012). Next generation sequencing to define prokaryotic and fungal diversity in the bovine rumen. PLoS ONE, 7, e48289.
  • Fox GE, Wisotzkey JD and Jurtshuk P. (1992). How close is close: 16S rRNA sequence identity may not be sufficient to guarantee species identity. Int J Syst Bacteriol, 42, 166–170.
  • Ghai R, Pašić L, Fernández AB, Martin-Cuadrado AB, Mizuno CM, McMahon KD, Papke RT, Stepanauskas R, Rodriguez-Brito B, Rohwer F, Sánchez-Porro C, Ventosa A, Rodríguez-Valera F. (2011). New abundant microbial groups in aquatic hypersaline environments. Scientific Reports, 1, 135.
  • Harris JK, Caporaso JG, Walker JJ, Spear JR, Gold NJ, Robertson CE, Hugenholtz P, Goodrich J, McDonald D, Knights D, Marshall P, Tufo H, Knight R, Pace NR. (2013). Phylogenetic stratigraphy in the Guerrero Negro hypersaline microbial mat. ISME J, 7, 50-60.
  • Hiiesalu I, Opik M, Metsis M, Lilje L, Davison J, et al. (2012). Plant species richness belowground: higher richness and new patterns revealed by next- generation sequencing. Mol Ecol, 21, 2004-2016.
  • Koday S. (1999). Tuz Gölü tuzlaları. Marmara Coğrafya Dergisi, 2, 128-149.
  • Kowalczyk R, Taberlet P, Coissac E, Valentini A, Mique C et al. (2011). Influence of management practices on large herbivore diet—Case of European bison in Białowieza Primeval Forest (Poland). F Ecology and Management, 261, 821-828.
  • Martinez-Murcia AJ and Collins MD. A phylogenetic analysis of the genus Leuconostoc based on reverse transcriptase sequencing of 16 S rRNA. FEMS Microbiol Lett 1990; 70: 73–83.
  • Martinez-Murcia AJ, Benlloch S and Collins MD. (1992). Phylogenetic interrelationships of members of the genera Aeromonas and Pleisiomonas as determined by 16S ribosomal DNA sequencing: lack of congruence with results of DNA-DNA hybridizations. Int J Syst Bacteriol, 42, 412–421.
  • McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P. (2012). An improved greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J, 6, 610–618.
  • Mutlu MB, Martinez-Garcia M, Santos F, Pena A, Guven K & Anton J. (2008). Prokaryotic diversity in Tuz Lake, a hypersaline environment in inland Turkey. FEMS Microbiol Ecol, 65, 474-483.
  • Oren A. (2005). A hundred years of Dunaliella research: 1905–2005. Saline Systems, 1, 2.
  • Oren A. (2014). Halophilic archaea on earth and in space: growth and survival under extreme conditions. Philos Trans R Soc A, 372, 20140194.
  • Pace NR. (1997). A molecular view of microbial diversity and the biosphere. Science, 276, 734-740.
  • Parada AE, Needham DM, & Fuhrman JA. (2016). Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol, 18, 1403–1414.
  • Pavan-Kumar A, Gireesh-Babu P and Lakra WS. (2015). DNA Metabarcoding: A new approach for rapid biodiversity assessment. J Cell Sci Mol Biol, 2, 111.
  • Pike LJ, Viciani E, Kumar N. (2018). Microbial diversity knows no borders. Nat Rev Microbiol, 16, 66.
  • Porazinska DL, Giblin-Davis RM, Esquivel A, Powers TO, Sung W, et al. (2010). Ecometagenetics confirms high tropical nematode diversity. Mol Ecol, 19, 5521-5530.
  • Ramette A. (2009). Quantitative community fingerprinting methods for estimating the abundance of operational taxonomic units in natural microbial communities. Appl Environ Microbiol, 75, 2495-2505.
  • Raye G, Miquel C, Coissac E, Redjadj C, Loison A, et al. (2011). New insights on diet variability revealed by DNA barcoding and high-throughput pyrosequencing: chamois diet in autumn as a case study. Eco Res, 26, 265- 276.
  • Simachew A, Lanzén A, Gessesse A, Øvreås L. (2016). Prokaryotic community diversity along an increasing salt gradient in a soda ash concentration pond. Microb Ecol, 71, 326-338.
  • Sogin ML, Morrison HG, Huber JA, Welch DM, Huse SM, et al. (2006). Microbial diversity in the deep sea and the underexplored “rare biosphere.” Proc Natl Acad Sci USA, 103, 12115-12120.
  • Taberlet P, Coissac E, Pompanon F, Brochmann C, Willerslev E. (2012). Towards next-generation biodiversity assessment using DNA metabarcoding. Mol Ecol, 21, 2045-2050.
  • Tazi L, Breakwell DP, Harker AR, Crandall KA. (2014). Life in extreme environments: microbial diversity in Great Salt Lake, Utah. Extremophiles, 18, 525-535.
  • Tindall BJ, Rossello-Mora R, Busse, H-J, Ludwig W, Kampfer P. (2010). Notes on the characterization of prokaryote strains for taxonomic purposes. Int J Sys Evo Microbiol, 60, 249-266.
  • Ventosa A, Fernández AB, León MJ, Sánchez-Porro C, Rodriguez-Valera F. (2014). The Santa Pola saltern as a model for studying the microbiota of hypersaline environments. Extremophiles, 18, 811-824.
  • Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, Gilbert JA, Jansson JK, Caporaso JG, Fuhrman JA, Apprill A, & Knight R. (2016). Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems, 1: e00009–15.
  • Wang Q, Garrity GM, Tiedje JM, Cole JR. (2007). Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol, 73, 5261–5267.
  • 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. Nucleic Acids Res, 42, 643–648.

A pilot study for determining microorganisms in Lake Tuz, Turkey by metabarcoding approach

Year 2020, Issue: 19, 366 - 374, 31.08.2020
https://doi.org/10.31590/ejosat.682557

Abstract

Although traditional microbial methods based on microscopy and culture techniques are highly effective, they are sometimes inadequate to identify the high diversity of microbial species found in environmental samples. In the past two decades, molecular techniques have improved significantly, and genomic approaches have been used to provide a more comprehensive and quantitative description of the distribution of microorganisms. In this pilot study, prokaryotic and eukaryotic microbial diversity of the samples from Lake Tuz was investigated by metabarcoding approach. According to the 16S / 18S rDNA sequencing results, an average of 29 Archaea, 23 Bacteria and 61 Eukaryotic OTUs were determined in the samples and the ratio of prokaryotic OTUs was 65.3%. In all examples, the most detected archaeal OTU belongs to Haloquadratum walsbyi from the Euryarchaeota branch, and the most common bacterial OTUs belong to the members of the genus Salinibacter. In accordance with the 18S rDNA sequencing results, the most abundant eukaryotic OTU is Dunaliella salina. In this study, many prokaryotic and eukaryotic OTUs that could not be cultured in vitro were detected and an OTU with less than 97% similarity ( 92%) to 16S rDNA sequences in their databases was determined. The results obtained have the potential to contribute to the clarification of the structure and composition of microbial communities in Lake Tuz.

Project Number

FHD-2017-16050

References

  • Abdallah MB, Karray F, Mhiri N, Mei N, Quéméneur M, Cayol JL, et al. (2016). Prokaryotic diversity in a Tunisian hypersaline lake, Chott El Jerid. Extremophiles, 20, 125-138.
  • Abdelfattah A, Malacrinò A, Wisniewski M, Cacciola SO & Schena L. (2017). Metabarcoding: a powerful tool to investigate microbial communities and shape future plant protection strategies. Biol Control, 120, 1–10.
  • Amann RI, Lin C, Key R, Montgomery L and Stahl DA. (1992). Diversity among Fibrobacter isolates: towards a phylogenetic classification. Syst Appl Microbiol, 15, 23–31.
  • Amaral-Zettler LA, McCliment EA, Ducklow HW, & Huse SM. (2009). A method for studying protistan diversity using massively parallel sequencing of V9 hypervariable regions of small-subunit ribosomal RNA Genes. PLoS ONE, 4, e6372.
  • Birbir M, Sesal C. (2003). Extremely halophilic bacterial communities in Şereflikoçhisar Salt Lake in Turkey. Turk J Biol, 27, 7-22.
  • Bolhuis H, Palm P, Wende A, Falb M, Rampp M, Rodriguez-Valera F, Pfeiffer F, Oesterhelt D. (2006). The genome of the square archaeon Haloquadratum walsbyi: life at the limits of water activity. BMC Genomics, 7, 169.
  • Brown DS, Jarman SN, Symondson WO. (2012). Pyrosequencing of prey DNA in reptile faeces: analysis of earthworm consumption by slow worms. Mol Ecol Res, 12, 259-266.
  • Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes S. (2016). DADA2: High resolutionsample inference from Illumina amplicon data. Nat Methods, 13, 581-583.
  • Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, et al. (2010). QIIME allows analysis of high throughput community sequencing data. Nat Methods, 7, 335-336.
  • Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, Noah Fierer N, & Knight R. (2011). Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA, 108, 4516–4522.
  • Caporaso JG, Lauber C L, Walters W A, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, & Knight R. (2012). Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J, 6, 1621–1624.
  • Collins MD, Rodrigues U, Ash C, Aguirre M, Farrow JAE, Martinez-Murcia A, Phillips BA, Williams AM and Wallbanks S. (1991). Phylogenetic analysis of the genus Lactobacillus and related lactic acid bacteria as determined by reverse transcriptase sequencing of 16S rRNA. FEMS Microbiol Lett, 77, 5–12.
  • Çınar S, Mutlu MB. (2016). Comparative analysis of prokaryotic diversity in solar salterns in eastern Anatolia (Turkey). Exteremophiles, 20, 589-601.
  • DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. (2006). Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol, 72, 5069-5072.
  • Edgar RC. (2013). UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nature Methods, 10, 996–998.
  • Elevi Bardavid R, Ionescu D, Oren A, Rainey FA, Hollen BJ, Bagaley DR, Small AM, McKay C. (2007). Selective enrichment, isolation and molecular detection of Salinibacter and related extremely halophilic Bacteria from hypersaline environments. Hydrobiologica, 576, 3-13.
  • Emerson JB, Thomas BC, Andrade K, Allen EE, Heidelberg KB, Banfield JF. (2012). Dynamic viral populations in hypersaline systems as revealed by metagenomic assembly. Appl. Environ. Microbiol, 78, 6309–6320.
  • Emerson JB, Andrade K, Thomas BC, Norman A, Allen EE, Heidelberg KB, Banfield JF. (2013). Virus–host and CRISPR dynamics in archaea-dominated hypersaline Lake Tyrrell, Victoria, Australia. Archaea, 370871.
  • Federhen S. The NCBI taxonomy database. (2012). Nucleic Acids Res, 40, 136–143.
  • Fernandez AB, Ghai R, Martin-Cuadrado AB, Sanchez-Porro C, Rodriguez-Valera F, Ventosa A. (2014). Prokaryotic taxonomic and metabolic diversity of an intermediate salinity hypersaline habitat assessed by metagenomics. FEMS Microbiol Ecol, 88, 623–635.
  • Fouts DE, Szpakowski S, Purushe J, Torralba M, Waterman RC, et al. (2012). Next generation sequencing to define prokaryotic and fungal diversity in the bovine rumen. PLoS ONE, 7, e48289.
  • Fox GE, Wisotzkey JD and Jurtshuk P. (1992). How close is close: 16S rRNA sequence identity may not be sufficient to guarantee species identity. Int J Syst Bacteriol, 42, 166–170.
  • Ghai R, Pašić L, Fernández AB, Martin-Cuadrado AB, Mizuno CM, McMahon KD, Papke RT, Stepanauskas R, Rodriguez-Brito B, Rohwer F, Sánchez-Porro C, Ventosa A, Rodríguez-Valera F. (2011). New abundant microbial groups in aquatic hypersaline environments. Scientific Reports, 1, 135.
  • Harris JK, Caporaso JG, Walker JJ, Spear JR, Gold NJ, Robertson CE, Hugenholtz P, Goodrich J, McDonald D, Knights D, Marshall P, Tufo H, Knight R, Pace NR. (2013). Phylogenetic stratigraphy in the Guerrero Negro hypersaline microbial mat. ISME J, 7, 50-60.
  • Hiiesalu I, Opik M, Metsis M, Lilje L, Davison J, et al. (2012). Plant species richness belowground: higher richness and new patterns revealed by next- generation sequencing. Mol Ecol, 21, 2004-2016.
  • Koday S. (1999). Tuz Gölü tuzlaları. Marmara Coğrafya Dergisi, 2, 128-149.
  • Kowalczyk R, Taberlet P, Coissac E, Valentini A, Mique C et al. (2011). Influence of management practices on large herbivore diet—Case of European bison in Białowieza Primeval Forest (Poland). F Ecology and Management, 261, 821-828.
  • Martinez-Murcia AJ and Collins MD. A phylogenetic analysis of the genus Leuconostoc based on reverse transcriptase sequencing of 16 S rRNA. FEMS Microbiol Lett 1990; 70: 73–83.
  • Martinez-Murcia AJ, Benlloch S and Collins MD. (1992). Phylogenetic interrelationships of members of the genera Aeromonas and Pleisiomonas as determined by 16S ribosomal DNA sequencing: lack of congruence with results of DNA-DNA hybridizations. Int J Syst Bacteriol, 42, 412–421.
  • McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P. (2012). An improved greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J, 6, 610–618.
  • Mutlu MB, Martinez-Garcia M, Santos F, Pena A, Guven K & Anton J. (2008). Prokaryotic diversity in Tuz Lake, a hypersaline environment in inland Turkey. FEMS Microbiol Ecol, 65, 474-483.
  • Oren A. (2005). A hundred years of Dunaliella research: 1905–2005. Saline Systems, 1, 2.
  • Oren A. (2014). Halophilic archaea on earth and in space: growth and survival under extreme conditions. Philos Trans R Soc A, 372, 20140194.
  • Pace NR. (1997). A molecular view of microbial diversity and the biosphere. Science, 276, 734-740.
  • Parada AE, Needham DM, & Fuhrman JA. (2016). Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol, 18, 1403–1414.
  • Pavan-Kumar A, Gireesh-Babu P and Lakra WS. (2015). DNA Metabarcoding: A new approach for rapid biodiversity assessment. J Cell Sci Mol Biol, 2, 111.
  • Pike LJ, Viciani E, Kumar N. (2018). Microbial diversity knows no borders. Nat Rev Microbiol, 16, 66.
  • Porazinska DL, Giblin-Davis RM, Esquivel A, Powers TO, Sung W, et al. (2010). Ecometagenetics confirms high tropical nematode diversity. Mol Ecol, 19, 5521-5530.
  • Ramette A. (2009). Quantitative community fingerprinting methods for estimating the abundance of operational taxonomic units in natural microbial communities. Appl Environ Microbiol, 75, 2495-2505.
  • Raye G, Miquel C, Coissac E, Redjadj C, Loison A, et al. (2011). New insights on diet variability revealed by DNA barcoding and high-throughput pyrosequencing: chamois diet in autumn as a case study. Eco Res, 26, 265- 276.
  • Simachew A, Lanzén A, Gessesse A, Øvreås L. (2016). Prokaryotic community diversity along an increasing salt gradient in a soda ash concentration pond. Microb Ecol, 71, 326-338.
  • Sogin ML, Morrison HG, Huber JA, Welch DM, Huse SM, et al. (2006). Microbial diversity in the deep sea and the underexplored “rare biosphere.” Proc Natl Acad Sci USA, 103, 12115-12120.
  • Taberlet P, Coissac E, Pompanon F, Brochmann C, Willerslev E. (2012). Towards next-generation biodiversity assessment using DNA metabarcoding. Mol Ecol, 21, 2045-2050.
  • Tazi L, Breakwell DP, Harker AR, Crandall KA. (2014). Life in extreme environments: microbial diversity in Great Salt Lake, Utah. Extremophiles, 18, 525-535.
  • Tindall BJ, Rossello-Mora R, Busse, H-J, Ludwig W, Kampfer P. (2010). Notes on the characterization of prokaryote strains for taxonomic purposes. Int J Sys Evo Microbiol, 60, 249-266.
  • Ventosa A, Fernández AB, León MJ, Sánchez-Porro C, Rodriguez-Valera F. (2014). The Santa Pola saltern as a model for studying the microbiota of hypersaline environments. Extremophiles, 18, 811-824.
  • Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, Gilbert JA, Jansson JK, Caporaso JG, Fuhrman JA, Apprill A, & Knight R. (2016). Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems, 1: e00009–15.
  • Wang Q, Garrity GM, Tiedje JM, Cole JR. (2007). Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol, 73, 5261–5267.
  • 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. Nucleic Acids Res, 42, 643–648.
There are 49 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Sibel Kucukyildirim Celik 0000-0003-2241-3060

Hasan Ünal 0000-0003-3492-0326

Project Number FHD-2017-16050
Publication Date August 31, 2020
Published in Issue Year 2020 Issue: 19

Cite

APA Kucukyildirim Celik, S., & Ünal, H. (2020). Metabarkodlama yaklaşımıyla Tuz Gölü, Türkiye mikroorganizmalarının belirlenmesi için bir pilot çalışma. Avrupa Bilim Ve Teknoloji Dergisi(19), 366-374. https://doi.org/10.31590/ejosat.682557