1. DergiPark
  2. JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH
  3. Arşiv
  4. Cilt 1, Sayı
Yıl 2017, Cilt 1, Sayı , Sayfalar 56 - 67 2017-11-15

Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri
Molecular Diagnostic Tests in Microbiota Investigations

Nafia Canan Gürsoy [1] , Barış Otlu [2]

227 1195

Öz

Son yıllarda mikrobiyotanın insan sağlığı üzerine olan potansiyel etkileri hakkında çok daha fazla veri elde edilmekte ve bazı hastalıkların patofi zyolojisinde mikrobiyotanın rol oynadığına dair güçlü bulgulara ulaşılmaktadır. Bu durum, birçok farklı tıp branşının insan mikrobiyotomuna ilgi duymasına neden olmuş ve bu konudaki çalışmalar önemli düzeyde artmıştır. Böylelikle; günümüze kadar genellikle sadece patojen-odaklı olarak çalışan tıbbi mikrobiyoloji laboratuvarları için insan fl orasında bulunan ve patojen olmayan yüzlerce bakteri, mantar ve virüsün tanımlanması gerekliliği ortaya çıkmıştır. Sahip olduğumuz tanı yöntemleri içinde kültür ve moleküler temelli yöntemlerin bu alanda etkili olarak kullanılması ile mikrobiyotomun sırları açıklanmaya başlanmıştır. Bu derlemede, mikrobiyota çalışmalarında kullanılan laboratuvar tanı yöntemleri değerlendirilerek moleküler esaslı inceleme araçları hakkındaki güncel verilerin paylaşılması amaçlanmıştır.

In the recent years, a plenty of data has been acquired about the potential effects of the microbiota on the human health, and strong evidences have been appeared related to the roles of the microbiota on the pathophysiology of some diseases. This situation has led many medical disciplines to pay attention to the human microbiome, and the number of researches on this topic has signifi cantly increased. Therefore, a requirement has emerged for the medical microbiology laboratories that previously used to work on the pathogen-based identifi cations, to identify hundreds of non-pathogenic bacteria, fungi and viruses present in the human body fl oras. The secrets of microbiome have been expressed as we have effectively used the available techniques among the culture-based and molecular-based identifi - cation methods. In this review, it is aimed to share the recent knowledge about the molecular-based investigation tools with evaluating the available laboratory research methods that can be utilized in the microbiota studies.

Kaynakça

  • 1. Qin J, Li R, Raes J, et al. A human gut microbial gene catalog established by metagenomic sequencing. Nature. 2010; 464(7285): 59-65.
  • 2. The Human Microbiome Project Consortium 2012. Structure, function and diversity of the healthy human microbiome. Nature. 486: 207–214.
  • 3. Zoetendal EG, Vaughan EE, De Vos WM. A microbial world within us. Mol Microbiol. 2006; 59(6): 1639–50.
  • 4. Wade W. Unculturable bacteria—the uncharacterized organisms that cause oral infections. Journal of the Royal Society of Medicine. 2002; 95(2): 81-83.
  • 5. Zengler K, Toledo G, Rappe M, Elkins J, Mathur EJ, Short JM, et al. Cultivating the uncultured. Proc Natl Acad Sci USA. 2002; 99: 15681–6.
  • 6. Ingham CJ, Sprenkels A, Bomer J, Molenaar D, van den Berg A, Vlieg JETVH et al. The micro-Petri dish, a million-well growth chip for the culture and high-throughput screening of microorganisms. Proc Natl Acad Sci USA. 2007; 104: 18217–18222.
  • 7. Stewart EJ. Growing unculturable bacteria. J Bacteriol. 2012;194:4151–4160.
  • 8. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, et al. Diversity of the human intestinal microbial fl ora. Science. 2005; 308(5728):1635–8.
  • 9. Goodman AL, Kallstrom G, Faith JJ, Reyes A, Moore A, Dantas G, et al. Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice. Proc Natl Acad Sci U S A. 2011; 108(15): 6252–7.
  • 10. Hugenholtz P, Goebel BM, Pace NR. Impact of Culture-Independent Studies on the Emerging Phylogenetic View of Bacterial Diversity. Journal of Bacteriology. 1998;180(18):4765-4774.
  • 11. Morgan X, Huttenhower C. Chapter 12: human microbiome analysis.PLoS Comput Biol. 2012; 8:12.10.1371.
  • 12. Austin, B. The value of cultures to modern microbiology. Antonie van Leeuwenhoek. 2017; 110: 1247.
  • 13. Zuckerkandl E, Pauling L. Molecules as documents of evolutionary history. J Theor Biol. 1965; 8, 357-366.
  • 14. Fraher MH, O’Toole PW, Quigley EM. Techniques used to characterize the gut microbiota: a guide for the clinician. Nat Rev Gastroenterol Hepatol. 2012; 9: 312–22.
  • 15. Hayashi H, Sakamoto M, Benno Y. Phylogenetic analysis of the human gut microbiota using 16S rDNA clone libraries and strictly anaerobic culture-based methods. Microbiol. Immunol. 2002; 46, 535-548.
  • 16. Rajendhran J, Gunasekaran P. Microbial phylogeny and diversity: Small subunit ribosomal RNA sequence analysis and beyond. Microbial Res 2011; 166: 99–110.
  • 17. Clarridge JE. Impact of 16S rRNA Gene Sequence Analysis for Identifi cation of Bacteria on Clinical Microbiology and Infectious Diseases. Clinical Microbiology Reviews. 2004;17(4):840-862.
  • 18. Fox GE, Stackebrandt E, Hespell RB, Gibson J, Maniloff J, et al. The phylogeny of prokaryotes. Science. 1980; 209: 457–463.
  • 19. DeSantis TZ, Hugenholtz P, Larsen N, et al. Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB. Applied and Environmental Microbiology. 2006;72(7):5069-5072.
  • 20. Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, et al. The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Research. 2009;37(suppl 1):D141–D5
  • 21. Pruesse E, Quast C, Knittel K, et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Research. 2007;35(21):7188-7196.
  • 22. Devereux R, He S, Doyle C, Orkland S, Stahl D, et al. Diversity and origin of Desulfovibrio species: phylogenetic defi nition of a family. Journal of Bacteriology. 1990; 172: 3609–3619.
  • 23. Moore ERB, Mua M, Arnscheidt A, Böttger EC, Hutson RA, Collins MD, et al. The determination and comparison of the 16S rDNA gene sequences of species of the genus Pseudomonas (sensu stricto) and estimation of the natural intrageneric relationships. Syst. Appl. Microbiol. 1996; 19, 476–492.
  • 24. Amann RI, Ludwig W, Schleifer KH. Phylogenetic identifi cation and in situ detection of individual microbial cells without cultivation. Microbiological Reviews. 1995; 59(1):143-169.
  • 25. Giovannoni SJ, DeLong EF, Olsen GJ, Pace NR. Phylogenetic groupspecifi c oligodeoxynucleotide probes for identifi cation of single microbial cells. Journal of Bacteriology. 1988;170(2):720-726.
  • 26. Amann RI, Binder BJ, Olson RJ, Chisholm SW, Devereux R, Stahl DA. Combination of 16S rRNA-targeted oligonucleotide probes with fl ow cytometry for analyzing mixed microbial populations. Applied and Environmental Microbiology. 1990; 56(6): 1919–25.
  • 27. Moter A, Göbel UB. Fluorescence in situ hybridization (FISH) for direct visualization of microorganisms. J Microbiol Methods 2000; 41:85–112.
  • 28. Handelsman J. Metagenomics: application of genomics to uncultured microorganisms. Microbiology and molecular biology reviews. 2004;68(4):669–85.
  • 29. Alexander BD, Ashley ED, Reller LB, et al. Cost savings with implementation of PNA FISH testing for identifi cation of Candida albicans in blood cultures. Diagn Microbiol Infect Dis. 2006; 54: 277–82.
  • 30. Rochet V, Rigottier-Gois L, Rabot S, Doré J. Validation of fl uorescent in situ hybridization combined with fl ow cytometry for assessing interindividual variation in the composition of human fecal microfl ora during long-term storage of samples. J Microbiol Methods. 2004; 59: 263–270.
  • 31. Bartlett JM, Stirling D. A short history of the polymerase chain reaction. Methods Mol Biol. 2003; 226: 3– 6.
  • 32. Wintzingerode FV, Göbel UV, Stackebrandt E. Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis. FEMS Microbiol Rev. 1997; 21: 213–229.
  • 33. Grønseth R, Drengenes C, Wiker HG, et al. Protected sampling is preferable in bronchoscopic studies of the airway microbiome. ERJ Open Research. 2017;3(3):00019-02017.
  • 34. Deiner K, Walser J-C, Mächler E, Altermatt F. Choice of capture and extraction methods affect detection of freshwater biodiversity from environmental DNA. Biological Conservation. 2015; 183: 53–63.
  • 35. Acinas SG, Marcelino LA, Klepac-Ceraj V, Polz MF Divergence and redundancy of 16S rRNA sequences in genomes with multiple rrn operons. J. Bacteriol. 2004; 186, 2629–2635.
  • 36. Lee CM, Sieo CC, Abdullah N, Ho YW. Estimation of 16S rRNA gene copy number in several probiotic Lactobacillus strains isolated from the gastrointestinal tract of chicken. Kneifel W, ed. Fems Microbiology Letters. 2008; 287(1): 136-141.
  • 37. Klappenbach JA, Saxman PR, Cole JR, Schmidt TM. rrndb: the Ribosomal RNA Operon Copy Number Database. Nucleic Acids Research. 2001; 29(1): 181-184.
  • 38. Gilbride KA, Lee DY, Beaudette LA. Molecular techniques in wastewater: Understanding microbial communities, detecting pathogens, and real-time process control. J Microbiol Meth. 2006;66: 1–20.
  • 39. Kim J, Lim J, Lee C. Quantitative real-time PCR approaches for microbial community studies in wastewater treatment systems: applications and considerations. Biotechnol. Adv. 2013; 31, 1358–1373.
  • 40. Muyzer G, de Waal EC, Uitterlinden AG. Profi ling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplifi ed genes coding for 16S rRNA. Applied and Environmental Microbiology. 1993; 59(3): 695-700.
  • 41. Guo Y Qi Y, Yang X, Zhao L, Wen S, Liu Y, et al. Association between Polycystic Ovary Syndrome and Gut Microbiota. PLoS One. 2016; 11(4).
  • 42. Alioua S, Abdi A, Fhoula I, Bringel F, Boudabous A, Ouzari IH. Diversity of Vaginal Lactic Acid Bacterial Microbiota in 15 Algerian Pregnant Women with and without Bacterial Vaginosis by using Culture Independent Method. Journal of Clinical and Diagnostic Research : JCDR. 2016;10(9).
  • 43. Osborn AM, Moore ERB, Timmis KN. An evaluation of terminalrestriction fragment length polymorphism (T-RFLP) analysis for the study of microbial community structure and dynamics. Environ Microbiol. 2000; 2(1): 39–50.
  • 44. Hayashi H, Sakamoto M, Kitahara M, Benno Y. Molecular analysis of fecal microbiota in elderly individuals using 16S rDNA library and T-RFLP. Microbiol Immunol. 2003; 47: 557–570.
  • 45. Zakharkina T, Heinzel E, Koczulla RA, Greulich T, Rentz K, Pauling JK, et al. Analysis of the airway microbiota of healthy individuals and patients with chronic obstructive pulmonary disease by T-RFLP and clone sequencing. PLoS One. 2013; 8: e68302
  • 46. Mackay IM, Arden KE, Nitsche A. Real-time PCR in virology. Nucleic Acids Res 2002; 30: 1292–1305.
  • 47. Carey CM, Kirk JL, Ojha S, Kostrzynska M. Current and future uses of real time polymerase chain reaction and microarrays in the study of intestinal microbiota and probiotic use and effectiveness. Can. J. Microbiol. 2007; 53: 537–550.
  • 48. Shukla R, Ghoshal U, Dhole TN, Ghoshal UC. Fecal microbiota in patients with irritable bowel syndrome compared with healthy controls using real-time polymerase chain reaction: an evidence of dysbiosis. Dig Dis Sci. 2015;60:2953–2962.
  • 49. Murri M, Leiva I, Gomez-Zumaquero JM, Tinahones FJ, Cardona F, Soriguer F, et al. Gut microbiota in children with type 1 diabetes differs from that in healthy children: a case-control study. BMC Med. 2013; 11:46.
  • 50. Kuypers J, Jerome KR. Applications of Digital PCR for Clinical Microbiology. J Clin Microbiol. 2017; 55(6): 1621-1628.
  • 51. Low H, Chan SJ, Soo GH, Ling B, Tan EL. ClarityTM digital PCR system: a novel platform for absolute quantifi cation of nucleic acids. Anal Bioanal Chem. 2016; 409: 1869 –1875.
  • 52. Hall Sedlak R, Jerome KR. The potential advantages of digital PCR for clinical virology diagnostics. Expert Rev Mol Diagn 2014; 14: 501–507.
  • 53. Sedlak RH, Jerome KR. Viral diagnostics in the era of digital polymerase chain reaction. Diagn Microbiol Infect Dis 2013; 75:1– 4.
  • 54. Huggett JF, Cowen S, Foy CA. Considerations for digital PCR as an accurate molecular diagnostic tool. Clin Chem 2015; 61: 79 – 88.
  • 55. Paliy O, Agans R. Application of phylogenetic microarrays to interrogation of human microbiota. FEMS Microbiol Ecol. 2012; 79(1): 2–11.
  • 56. Zhou J. Microarrays for bacterial detection and microbial community analysis. Curr Opin Microbiol. 2003; 6: 288–294.
  • 57. Wu L, Thompson DK, Liu X, Fields MW, Bagwell CE, Tiedje JM, Zhou J. Development and evaluation of microarray-based whole-genome hybridization for detection of microorganisms within the context of environmental applications. Environ Sci Technol. 2004; 38(24): 6775-82.
  • 58. He Z, Gentry TJ, Schadt CW, Wu L, Liebich J, Chong SC, et al. GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes. The ISME journal. 2007;1(1):67–77.
  • 59. Zhou J, He Z, Van Nostrand J, Wu L, Deng Y. Applying GeoChip Analysis to Disparate Microbial Communities. Microbe. 2010;5:60–65.
  • 60. Zhou JZ, He ZL, Van Nostrand JD, Deng Y. Development and applications of functional gene microarrays in the analysis of the functional diversity, composition, and structure of microbial communities. Frontiers of Environmental Science & Engineering in China. 2011;5:1–20.
  • 61. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chainterminating inhibitors. Proceedings of the National Academy of Sciences of the United States of America. 1977; 74(12): 5463- 5467.
  • 62. Cox MJ, Cookson WO, Moffatt MF. Sequencing the human microbiome in health and disease. Hum Mol Genet. 2013; 22: R88–94.
  • 63. Belshaw R, Pereira V, Katzourakis A, Talbot G, Paces J, Burt A, et al. Long-term reinfection of the human genome by endogenous retroviruses. Proc Natl Acad Sci USA. 2004;101(14):4894–9.
  • 64. Koeth RA, Wang Z, Levison BS, et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nature medicine. 2013;19(5):576-585.
  • 65. Claesson MJ, Cusack S, O'Sullivan O, Greene-Diniz R, de Weerd H, Flannery E, et al. Composition, variability, and temporal stability of the intestinal microbiota of the elderly. Proceedings of the National Academy of Sciences of the United States of America. 2011;108 Suppl 1:4586–91.
  • 66. Achtman M, Wagner M. Microbial diversity and the genetic nature of microbial species. Nat Rev Microbiol. 2008; 6: 431–440.
  • 67. Schloss PD (2010) The effects of alignment quality, distance calculation method, sequence fi ltering, and region on the analysis of 16S rRNA gene-based studies. PLoS Comput Biol 6: e1000844.
  • 68. Ashelford, K.E., Chuzhanova, N.A., Fry, J.C., Jones, A.J. and Weightman, A.J. At least 1 in 20 16S rRNA sequence records currently held in public repositories is estimated to contain substantial anomalies. Appl. Environ. Microbiol. 2005; 71, 7724– 7736.
  • 69. Fleischmann, R.D., Adams, M.D., White, O., Clayton, R.A., Kirkness, E.F., Kerlavage, A.R., Bult, C.J., Tomb, J.F., Dougherty, B.A. and Merrick, J.M. Whole-genome random sequencing and assembly of Haemophilus infl uenzae Rd. Science, 1995; 269, 496–512.

Ayrıntılar

Konular Sağlık Bilimleri ve Hizmetleri
Dergi Bölümü Derleme
Yazarlar

Yazar: Nafia Canan Gürsoy
Kurum: İnönü Üniversitesi, Tıp Fakültesi, Tıbbi Mikrobiyoloji Anabilim Dalı, Malatya
Ülke: Turkey

Yazar: Barış Otlu (Sorumlu Yazar)
Kurum: İnönü Üniversitesi, Tıp Fakültesi, Tıbbi Mikrobiyoloji Anabilim Dalı, Malatya
Ülke: Turkey

Kaynak Göster

Bibtex @derleme { bshr363271, journal = {JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH}, issn = {}, eissn = {2587-1641}, address = {Deneysel, Biyoteknolojik, Klinik ve Stratejik Sağlık Araştırmaları Derneği}, year = {2017}, volume = {1}, pages = {56 - 67}, doi = {}, title = {Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri}, key = {cite}, author = {Gürsoy, Nafia Canan and Otlu, Barış} }
APA Gürsoy, N , Otlu, B . (2017). Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri. JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH, 1 (), 56-67. Retrieved from http://dergipark.gov.tr/bshr/issue/32641/363271
MLA Gürsoy, N , Otlu, B . "Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri". JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH 1 (2017): 56-67 <http://dergipark.gov.tr/bshr/issue/32641/363271>
Chicago Gürsoy, N , Otlu, B . "Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri". JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH 1 (2017): 56-67
RIS TY - JOUR T1 - Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri AU - Nafia Canan Gürsoy , Barış Otlu Y1 - 2017 PY - 2017 N1 - DO - T2 - JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH JF - Journal JO - JOR SP - 56 EP - 67 VL - 1 IS - SN - -2587-1641 M3 - UR - Y2 - 2017 ER -
EndNote %0 JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri %A Nafia Canan Gürsoy , Barış Otlu %T Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri %D 2017 %J JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH %P -2587-1641 %V 1 %N %R %U
ISNAD Gürsoy, Nafia Canan , Otlu, Barış . "Mikrobiyota Çalışmalarında Moleküler Tanı Yöntemleri". JOURNAL OF BIOTECHNOLOGY AND STRATEGIC HEALTH RESEARCH 1 / (Kasım 2017): 56-67.
Makale Gönder
Kabul Edilmiş Makaleler
Arşiv
Editör Kurulu
İletişim
Duyurular
Google Scholar
Google Scholar
SOBIAD
SOBIAD
ASOS Index
ASOS Index
JournalTOCs
JournalTOCs
TÜRK MEDLINE
TÜRK MEDLINE
TÜRKİYE ATIF DİZİNİ
TÜRKİYE ATIF DİZİNİ