Differences in Physical and Biochemical Properties of Thermus scotoductus SA-01 Cultured with Dielectric or Convection Heating

Towards image-based cancer cell lines authentication using deep neural networks

Although short tandem repeat (STR) analysis is available as a reliable method for the determination of the genetic origin of cell lines, the occurrence of misauthenticated cell lines remains an important issue. Reasons include the cost, effort and time associated with STR analysis. Moreover, there are currently no methods for the discrimination between isogenic cell lines (cell lines of the same genetic origin, e.g. different cell lines derived from the same organism, clonal sublines, sublines adapted to grow under certain conditions). Hence, additional complementary, ideally low-cost and low-effort methods are required that enable (1) the monitoring of cell line identity as part of the daily laboratory routine and 2) the authentication of isogenic cell lines. In this research, we automate the process of cell line identification by image-based analysis using deep convolutional neural networks. Two different convolutional neural networks models (MobileNet and InceptionResNet V2) were trained to automatically identify four parental cancer cell line (COLO 704, EFO-21, EFO-27 and UKF-NB-3) and their sublines adapted to the anti-cancer drugs cisplatin (COLO-704rCDDP1000, EFO-21rCDDP2000, EFO-27rCDDP2000) or oxaliplatin (UKF-NB-3rOXALI2000), hence resulting in an eight-class problem. Our best performing model, InceptionResNet V2, achieved an average of 0.91 F1-score on tenfold cross validation with an average area under the curve (AUC) of 0.95, for the 8-class problem. Our best model also achieved an average F1-score of 0.94 and 0.96 on the authentication through a classification process of the four parental cell lines and the respective drug-adapted cells, respectively, on a four-class problem separately. These findings provide the basis for further development of the application of deep learning for the automation of cell line authentication into a readily available easy-to-use methodology that enables routine monitoring of the identity of cell lines including isogenic cell lines. It should be noted that, this is just a proof of principal that, images can also be used as a method for authentication of cancer cell lines and not a replacement for the STR method.

Molecular Mechanisms Contributing to the Growth and Physiology of an Extremophile Cultured with Dielectric Heating

The effect of microwave frequency electromagnetic fields on living microorganisms is an active and highly contested area of research. One of the major drawbacks to using mesophilic organisms to study microwave radiation effects is the unavoidable heating of the organism, which has limited the scale (<5 ml) and duration (<1 h) of experiments. However, the negative effects of heating a mesophile can be mitigated by employing thermophiles (organisms able to grow at temperatures of >60°C). This study identified changes in global gene expression profiles during the growth of Thermus scotoductus SA-01 at 65°C using dielectric (2.45 GHz, i.e., microwave) heating. RNA sequencing was performed on cultures at 8, 14, and 24 h after inoculation to determine the molecular mechanisms contributing to long-term cellular growth and survival under microwave heating conditions. Over the course of growth, genes associated with amino acid metabolism, carbohydrate metabolism, and defense mechanisms were upregulated; the number of repressed genes with unknown function increased; and at all time points, transposases were upregulated. Genes involved in cell wall biogenesis and elongation were also upregulated, consistent with the distinct elongated cell morphology observed after 24 h using microwave heating. Analysis of the global differential gene expression data enabled the identification of molecular processes specific to the response of T. scotoductus SA-01 to dielectric heating during growth.

IMPORTANCE

The residual heating of living organisms in the microwave region of the electromagnetic spectrum has complicated the identification of radiation-only effects using microorganisms for 50 years. A majority of the previous experiments used either mature cells or short exposure times with low-energy high-frequency radiation. Using global differential gene expression data, we identified molecular processes unique to dielectric heating using Thermus scotoductus SA-01 cultured over 30 h in a commercial microwave digestor. Genes associated with amino acid metabolism, carbohydrate metabolism, and defense mechanisms were upregulated; the number of repressed genes with unknown function increased; and at all time points, transposases were upregulated. These findings serve as a platform for future studies with mesophiles in order to better understand the response of microorganisms to microwave radiation.