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J AOAC Int. 2017 Nov 1;100(6):1836-1847. doi: 10.5740/jaoacint.17-0097. Epub 2017 Jun 23.

Cellular Light Scattering for the Identification of Bacteria and Its Application to the Identification of Staphylococcus.

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Micro Identification Technologies, 970 Calle Amanecer, Suite F, San Clemente, CA 92673.
Northern Michigan University, Biology Department, 1401 Presque Isle Ave, Marquette, MI 49855.
Northern Michigan University, Clinical Life Sciences Department, 1401 Presque Isle Ave, Marquette, MI 49855.


Rapid identification of bacteria is critical in clinical and food safety applications. This paper describes a novel instrument and data analysis method for identifying bacteria based on the measurement of laser light scattering as the beam interacts with bacterial cells suspended in water. A description of the technology is followed by an identification performance study for a set of strains from the genus Staphylococcus (the inclusive target organisms) and a set of non-Staphylococcus strains (the exclusive organisms). Staphylococcus and non-Staphylococcus cells were grown on sheep blood agar (SBA), tryptic soy agar, brain heart infusion (BHI) agar, or Luria-Bertani (LB) agar and identified based on how cells scattered light. Bacteria from the genus Staphylococcus grown on solid media were correctly identified more than 92% of the time. To determine whether the system could also identify bacteria grown in liquid culture, six different Staphylococcus strains and six different non-Staphylococcus strains were grown in tryptic soy broth, BHI broth, or LB broth. This system accurately identified all targeted Staphylococcus samples tested, and no misidentifications occurred. A single-blind identification experiment was also performed on human clinical isolates obtained from the Upper Peninsula Health System. Ninety blind-coded clinical bacterial isolates on SBA were tested to determine whether they were from the genus Staphylococcus. All Staphylococcus were accurately identified, and no misidentifications occurred. This study demonstrated the proof of concept of a novel system that can rapidly and accurately identify bacteria from pure culture based on cellular light-scattering properties.

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