Title Rapid MALDI biotyper-based identification and cluster analysis of Streptococcus iniae
Author Si Won Kim1, Seong Won Nho2, Se Pyeong Im1, Jung Seok Lee1, Jae Wook Jung1, Jassy Mary S. Lazarte1, Jaesung Kim1, Woo-Jai Lee3, Jeong-Ho Lee4, and Tae Sung Jung1*
Address 1Laboratory of Aquatic Animal Diseases, Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 52828, Republic of Korea, 2Division of Microbiology, National Center for Toxicological Research/FDA, Jefferson, Arkansas, USA, 3BluGen Korea, Busan 48071, Republic of Korea, 4Inland Aquaculture Research Center, NIFS, Changwon 51695, Republic of Korea
Bibliography Journal of Microbiology, 55(4),260-266, 2017,
DOI 10.1007/s12275-017-6472-x
Key Words MALDI TOF MS, Streptococcus iniae, olive floun-der, Paralichthys olivaceus, database
Abstract Streptococcus iniae causes severe mortalities among cultured marine species, especially in the olive flounder (Paralichthys olivaceus), which is economically important in Korea and Japan. Recently, there has been growing concern regarding the emergence of S. iniae as a zoonotic pathogen. Here, 89 S. iniae isolates obtained from diseased olive flounders collected from 2003 to 2008 in Jeju Island, South Korea, were charac-terized using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). The results were aligned both with the available Bruker Daltonics data-base and with a new set of S. iniae data entries developed in our laboratory, and the results were compared. When we used the Bruker Daltonics database, the 89 isolates yielded either “no reliable identification” or were incorrectly iden-tified as Streptococcus pyogenes at the genus level. When we used the new data entries from our laboratory, in contrast, all of the isolates were correctly identified as S. iniae at the genus (100%) and species (96.6%) levels. We performed pro-teomic analysis, divided the 89 isolates into cluster I (51.7%), cluster II (20.2%), and cluster III (28.1%), and then used the MALDI Biotyper software to identify specific mass peaks that enabled discrimination between clusters and between Strep-tococcus species. Our results suggest that the use of MALDI TOF MS could outperform the conventional methods, prov-ing easier, faster, cheaper and more efficient in properly identifying S. iniae. This strategy could facilitate the epide-miological and taxonomical study of this important fish pathogen.