J Genomics 2019; 7:26-30. doi:10.7150/jgen.31911
SELfies and CELLfies: Whole Genome Sequencing and Annotation of Five Antibiotic Resistant Bacteria Isolated from the Surfaces of Smartphones, An Inquiry Based Laboratory Exercise in a Genomics Undergraduate Course at the Rochester Institute of Technology
The Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester NY, USA
Parthasarathy A, Wong NH, Weiss AN, Tian S, Ali SE, Cavanaugh NT, Chinsky TM, Cramer CE, Gupta A, Jha R, Johnson LK, Tuason ED, Klafehn LM, Krishnadas V, Musich RJ, Pfaff JM, Richman SC, Shumway AJ, Hudson AO. SELfies and CELLfies: Whole Genome Sequencing and Annotation of Five Antibiotic Resistant Bacteria Isolated from the Surfaces of Smartphones, An Inquiry Based Laboratory Exercise in a Genomics Undergraduate Course at the Rochester Institute of Technology. J Genomics 2019; 7:26-30. doi:10.7150/jgen.31911. Available from http://www.jgenomics.com/v07p0026.htm
Are touchscreen devices a public health risk for the transmission of pathogenic bacteria, especially those that are resistant to antibiotics? To investigate this, we embarked on a project aimed at isolating and identifying bacteria that are resistant to antibiotics from the screens of smartphones. Touchscreen devices have become ubiquitous in society, and it is important to evaluate the potential risks they pose towards public health, especially as it pertains to the harboring and transmission of pathogenic bacteria that are resistant to antibiotics. Sixteen bacteria were initially isolated of which five were unique (four Staphylococcus species and one Micrococcus species). The genomes of the five unique isolates were subsequently sequenced and annotated. The genomes were analyzed using in silico tools to predict the synthesis of antibiotics and secondary metabolites using the antibiotics and Secondary Metabolite Analysis SHell (antiSMASH) tool in addition to the presence of gene clusters that denote resistance to antibiotics using the Resistance Gene Identifier (RGI) tool. In vivo analysis was also done to assess resistance/susceptibility to four antibiotics that are commonly used in a research laboratory setting. The data presented in this manuscript is the result of a semester-long inquiry based laboratory exercise in the genomics course (BIOL340) in the Thomas H. Gosnell School of Life Sciences/College of Science at the Rochester Institute of Technology.
Keywords: smartphones, touchscreen, public health, antibiotic resistance, Staphylococcus, Micrococcus, secondary metabolites