Traceability Methods for Cell Line Authentication and Mycoplasma Detection

Many laboratories struggle with mycoplasma contamination and cell line misidentification when growing cells in culture. These well-documented issues affect the scientific research community and have detrimental downstream effects. Research published with suspect cultures can produce misleading results. There is increasing pressure to verify the integrity of experimental and established cell lines before publishing. Therefore, laboratories need to define how and when to perform these critical tests, analyze the results, and determine action plans if disparities exist. Our laboratory is committed to producing cell lines of the highest quality for use in experiments; thus, we created a surveillance strategy for these potential problems. We developed processes for both testing and tracing cell line authentication and mycoplasma detection data. Using these methods, we can protect the integrity of our patient and commercial cell lines, maintaining reliable cultures for our research.

Rapid and sensitive mycoplasma detection system using image-based deep learning

A major concern in the clinical application of cell therapy is the manufacturing cost of cell products, which mainly depends on quality control. The mycoplasma test, an important biological test in cell therapy, takes several weeks to detect a microorganism and is extremely expensive. Furthermore, the manual detection of mycoplasma from images requires high-level expertise. We hypothesized that a mycoplasma identification program using a convolutional neural network could reduce the test time and improve sensitivity. To this end, we developed a program comprising three parts (mycoplasma detection, prediction, and cell counting) that allows users to evaluate the sample and verify infected/non-infected cells identified by the program. In experiments conducted, stained DNA images of positive and negative control using mycoplasma-infected and non-infected Vero cells, respectively, were used as training data, and the program results were compared with those of conventional methods, such as manual counting based on visual observation. The minimum detectable mycoplasma contaminations for manual counting and the proposed program were 10 and 5 CFU (colony-forming unit), respectively, and the test time for manual counting was 20 times that for the proposed program. These results suggest that the proposed system can realize a low-cost and streamlined manufacturing process for cellular products in cell-based research and clinical applications.

Vaginal Bacterial Profile in Pregnant Women

Summary This study aimed to determine the bacterial profile of vaginal samples from pregnant women and the prevalence of identified microorganisms. Materials and methods: A prospective epidemiological study was conducted on 150 pregnant women admitted to the Clinic of Obstetrics and Gynecology at Dr. G. Stranski University Hospital in Pleven. Vaginal secretion samples were collected from all the 150 women. Direct microscopy of native smears prepared by the wet mount method to detect Trichomonas vaginalis and direct microscopy of Gram-stained smears was performed. Aerobic culture studies were conducted to identify pathogenic bacteria and Sabouraud glucose agar (SGA) to detect the presence of Candida spp. Samples were also collected from 107 of the women for PCR tests for mycoplasma detection. Results: The highest relative share in the study was women aged 21 to 35 years 104 (69.33%). Of all the hospitalized and examined pregnant women, 87 (57.99%) had medical problems during the current pregnancy and postpartum complications, and 63 women (42%) gave birth without accompanying complications. In 86 (57.32%) of the women, bacteria were detected by direct microscopy of Gram-stained smears. Of these, 24 (16%) had gram-negative rods, 28 (18.66%) had gram-positive cocci. In 34 (22.66%), we found gram-negative and gram-variable pleomorphic bacteria. The aerobic culture study revealed microbiological growth in 44 (29.33%) of the women investigated. Conclusions: Studies on the profile of the vaginal microbiota in pregnant women and the spread of pathogenic microorganisms are essential for make prognoses for pregnancy outcome, evaluating the risk of developing a maternal-fetal infection, and discussing options for timely treatment.

Aptamer Cocktail to Detect Multiple Species of Mycoplasma in Cell Culture

Mycoplasma contamination of cell line cultures is a common, yet often undetected problem in research laboratories. Many of the existing techniques to detect mycoplasma contamination of cultured cells are time-consuming, expensive, and have significant drawbacks. Here, we describe a mycoplasma detection system that is useful for detecting multiple species of mycoplasma in infected cell lines. The system contains three dye-labeled detection aptamers that can specifically bind to mycoplasma-infected cells and a dye-labeled control aptamer that minimally binds to cells. With this system, mycoplasma-contaminated cells can be detected within 30 min by using a flow cytometer, fluorescence microscope, or microplate reader. Further, this system may be used to detect mycoplasma-contaminated culture medium. This study presents an novel mycoplasma detection model that is simple, rapid, inexpensive, and sensitive.