The 16s ribosomal ribonucleic acid microorganisms’ detection in mesenteric lymph nodes by a polymerase chain reaction in view of colorectal cancer

Alina Ogizbayeva 1 * , Yermek Turgunov 1, Irina Kadyrova 2, Kayrat Shakeyev 1, Svetlana Kolesnichenko 2, Miras Mugazov 3, Ilshat Moldozhanov 3
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1 Department of Surgical Diseases, Karaganda Medical University, Karaganda, Kazakhstan
2 Collective Use Laboratory of the Research Centre, Karaganda Medical University, Karaganda, Kazakhstan
3 Department of Anesthesiology, Resuscitation and Emergency Medical Care, Karaganda, Kazakhstan
* Corresponding Author
J CLIN MED KAZ, Volume 19, Issue 2, pp. 38-42.
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Objective: This study proposes a method to detect 16s rRNA microorganisms in mesenteric lymph nodes (MLN) using a polymerase chain reaction (PCR) in patients with colorectal cancer (CRC).
Material and methods:  To quantify the presence of microorganisms in MLN, it is proposed to determine the dependence of the accumulated amplification products on the number of colony-forming units of bacteria (CFU/ml). The pure culture of Escherichia coli, GFP 6 serotype of biotype 1 (ATCC® 25922GFP™) with the CFU values from 102 to 108 (group 1) as well as the mixtures of E.coli with CFU/ml from 102 to 108 with the MLN tissues (group 2) were calibrated. The third group consisted of the MLN patients (60 people) with CRC without bowel obstruction. The 16s rRNA bacteria in MLN was detected by using real-time PCR by the BIO-RAD CFX96 amplifier.
Results: To assess the dependence of the bacteria’s CFU/ml logarithm on the value of the threshold cycle amplification, a model was developed in the form of an equation. The amplification curves, threshold cycle values, and PCR efficiency differ from the first two groups. This can be due to the presence of DNA amplification-inhibiting compounds as well as the non-specific binding of MLN primers to DNA. Therefore, a mathematical model of the second group (suspension of E.Coli and MLN) was used to study the translocation of microorganisms in MLN. According to the developed mathematical model, depending on the values of the threshold amplification cycles, the positive PCR result in the study group (patients with CRC) was detected in 15 patients (25%).  At the same time, the level of CFU/ml with bacterial translocation in MLN does not exceed 104.
Conclusion: The developed method allows to determine the microbial DNA in MLN quantitatively in a wide range of its concentrations (102 to 108 CFU).


Ogizbayeva A, Turgunov Y, Kadyrova I, Shakeyev K, Kolesnichenko S, Mugazov M, et al. The 16s ribosomal ribonucleic acid microorganisms’ detection in mesenteric lymph nodes by a polymerase chain reaction in view of colorectal cancer. J CLIN MED KAZ. 2022;19(2):38-42.


  • Pisano M, Zorcolo L, Merli C, et al. 2017 WSES guidelines on colon and rectal cancer emergencies: obstruction and perforation. World J Emerg Surg. 2018; 13(1):36.
  • Nurshabaeva AE, Dauletkalieva ZA. Analysis of population coverage by screening studies for the early detection of colorectal cancer. Astana medicine journal. 2018; 4(98):154-159.
  • Catena F, De Simone B, Coccolini F, et al Bowel obstruction: a narrative review for all physicians. World J Emerg Surg. 2019; 14(1):20.
  • Zembower TR. Epidemiology of infections in cancer patients. Cancer Treat.Res. 2014; 161:43–89.
  • Galloway-Peña J, Brumlow C, Shelburne S. Impact of the Microbiota on Bacterial Infections during Cancer Treatment. Trends Microbiol 2017; 25(12):992–1004.
  • Schietroma M, Pessia B, Colozzi S, et al. Septic complications after resection for middle or low rectal cancer: role of gut barrier function and inflammatory serum markers. Dig Surg. 2017; 34(6):507–517.
  • Oliver JD. The viable but nonculturable state in bacteria. J Microbiol. 2005; 43:93–100. PMID: 15765062.
  • Ames NJ, Ranucci A, Moriyama B, Wallen, GR. The Human Microbiome and Understanding the 16S rRNA Gene in Translational Nursing Science. Nurs Res. 2017; 66(2):184–197.
  • Ritz C, Spiess A-N. qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis. Bioinformatics. 2008; 24(13):1549–1551.
  • Walker SP, Barrett M, Hogan G et al. Non‑specific amplification of human DNA is a major challenge for 16S rRNA gene sequence analysis. Sci Rep. 2020; 10(1).
  • Earl JP, Adappa ND, Krol J, et al. Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes. Microbiome. 2018; 6(1):190.
  • Kiely CJ, Pavli P, O’Brien CL. The microbiome of translocated bacterial populations in patients with and without inflammatory bowel disease. Intern Med J. 2018; 10:44.
  • Deitch EA. Bacterial translocation or lymphatic drainage of toxic products from the gut: what is important in human beings? Surgery. 2002; 131(3):241– 244.
  • Gatt M, Reddy BS, MacFie J. Review article: bacterial translocation in the critically ill—evidence and methods of prevention. Aliment Pharmacol Ther. 2007; 25(7):741–57.
  • Mizuno T, Yokoyama Y, Nishio H. Intraoperative Bacterial Translocation Detected by Bacterium-Specific Ribosomal RNA-Targeted Reverse-Transcriptase Polymerase Chain Reaction for the Mesenteric Lymph Node Strongly Predicts Postoperative Infectious Complications After Major Hepatectomy for Biliary Malignancies. Annals of Surgery. 2010; 252(6):1013-1019.
  • O'Brien CL, Pavli P, Gordon DM, Allison GE. Detection of bacterial DNA in lymph nodes of Crohn's disease patients using high throughput sequencing. Gut. 2014; 63:1596-606.
  • Nishigaki E, Abe T, Yokoyama Y. The Detection of Intraoperative Bacterial Translocation in the Mesenteric Lymph Nodes Is Useful in Predicting Patients at High Risk for Postoperative Infectious Complications After Esophagectomy. Annals of Surgery. 2014; 259(3).
  • Yu G, Fadrosh D, Goedert JJ et al. Nested PCR Biases in Interpreting Microbial Community Structure in 16S rRNA Gene Sequence Data sets. PlosOne. 2015; 10(7):e0132253.
  • Villette R, Autaa G, Hind S, et al. Refinement of 16S rRNA gene analysis for low biomass biospecimens. Sci Rep. 2021; 11:1074.