The genus Prototheca, a unicellular, non-photosynthetic, yeast-like microalgae, is a pathogen of concern for the dairy industry. It causes bovine mastitis that currently cannot be cured, and hence generates significant economic losses in milk production. In this study, for the first time in Ecuador, we identify Prototheca bovis as the etiologic agent of chronic mastitis in dairy cattle. Milk samples (n = 458) of cows with chronic mastitis were cultured on Sabouraud Dextrose Agar (SDA). Microscopy and cytB gene sequencing were used to identify Prototheca, whereby Prototheca bovis was isolated from 15.1% (n = 69) of the milk samples, one of the highest infection rates that can be found in the literature in a “non-outbreak” situation. No other Prototheca species were found. We were unable to isolate the alga from environmental samples. We showed that P. bovis was relatively resistant to disinfectants used to sterilize milking equipment on the cattle farms where it was isolated. We discuss how to avoid future infection and also hypothesize that the real prevalence of Prototheca infection in bovine mastitis is probably much higher than what was detected. We recommend a protocol to increase the diagnostic yield in the bacteriology laboratory.
The genus Prototheca, unicellular, non-photosynthetic, yeast-like microalgae, is a pathogen of concern for the dairy industry causing bovine mastitis that currently cannot be cured and hence generates significant economic losses in milk production. In this study, for the first time in Ecuador, we identify Prototheca bovis as the etiologic agent of chronic mastitis in dairy cattle. Milk samples (n=458) of cows with chronic mastitis were cultured on Sabouraud Dextrose Agar (SDA). Microscopy and cytB gene sequencing were used to identify Prototheca, whereby Prototheca bovis was isolated from 15.1% (n=69) of the milk samples, one of the highest infection rates that can be found in the literature in a “non-outbreak” situation. No other Prototheca species were found. We were unable to isolate the alga from environmental samples. We showed that P. bovis was relatively resistant to disinfectants used to sterilize milking equipment on the cattle farms where it was isolated. We discuss how to avoid future infection and also hypothesize that the real prevalence of Prototheca infection in bovine mastitis is probably much higher than what was detected. We recommend a protocol to increase the diagnostic yield in the bacteriology laboratory.
Non-tuberculous mycobacteria that cannot be identified at the species level represent a challenge for clinical laboratories, as proper species assignment is key to implementing successful treatments or epidemiological studies. We re-identified forty-eight isolates of Ziehl–Neelsen (ZN)-staining-positive “acid-fast bacilli” (AFB), which were isolated in a clinical laboratory and previously identified as Mycobacterium species but were unidentifiable at the species level with the hsp65 PCR restriction fragment length polymorphism analysis (PRA). As most isolates also could not be identified confidently via 16S, hsp65, or rpoB DNA sequencing and a nBLAST search analysis, we employed a phylogenetic method for their identification using the sequences of the 16S rDNA, which resulted in the identification of most AFB and a Mycobacterium species diversity not found before in our laboratory. Most were rare species with only a few clinical reports. Moreover, although selected with the ZN staining as AFB, not all isolates belonged to the genus Mycobacterium, and we report for the first time in Latin America the isolation of Nocardia puris, Tsukamurella pulmosis, and Gordonia sputi from sputum samples of symptomatic patients. We conclude that ZN staining does not differentiate between the genus Mycobacterium and other genera of AFB. Moreover, there is a need for a simple and more accurate tree-based identification method for mycobacterial species. For this purpose, and in development in our lab, is a web-based identification system using a phylogenetic analysis (including all AFB genera) based on 16S rDNA sequences (and in the future multigene datasets) and the closest relatives.
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