Profiling toxin genes and antibiotic resistance in Bacillus cereus isolated from pre-launch spacecraft

被引:2
作者
Mohammadi, Barakatullah [1 ]
Gorkina, Natalia [1 ]
Perez-Reyes, Marco Esteban [1 ]
Smith, Stephanie A. [1 ]
机构
[1] Washington State Univ, Sch Food Sci, Consumer Food Safety Lab, Pullman, WA 99163 USA
关键词
Bacillus cereus; toxin gene; antibiotic resistance; spacecraft; spacecraft assembly facilities; ANTIMICROBIAL RESISTANCE; PREVALENCE; SUSCEPTIBILITY; MECHANISMS; STATION;
D O I
10.3389/fmicb.2023.1231726
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Characterization of the microbiomes of pre-launch spacecraft in spacecraft assembly facilities is an important step in keeping crews healthy during journeys that can last several hundred days in small artificial environments in space. Bacillus cereus, a foodborne pathogenic bacterium, has the potential to be a significant source of food contamination in such environments. This bacterium is a spore-forming bacteria that resists different antimicrobial treatments in cleanrooms where spacecraft are assembled. This study evaluated 41 B. cereus isolates from four pre-launch spacecraft in spacecraft assembly facilities for their toxin gene profile and antibiotic resistance. Four enterotoxin genes (hlbC, cytK, nheA, and entFM) and two emetic toxin genes (ces and CER) were targeted for chromosomal DNA and plasmid DNA. Results showed 31.7, 7.3, 85, and 41.5% of isolates contained hblC, cytK, nheA, and entFM, respectively, in chromosomal or plasmid DNA. Overall, 37 isolates (90.2%) showed at least one enterotoxin gene. The emetic toxin gene, ces, was detected in the plasmid DNA of three isolates (7.3%). The antibiotic resistance of isolates was evaluated by the Kirby-Bauer disk diffusion procedure. All the isolates exhibited 100% susceptibility to gentamicin, 97% were susceptible to clindamycin, and 95% to chloramphenicol, imipenem, tetracycline, and vancomycin. The overall susceptibility average is 51%. However, 98% of the isolates were resistant to beta-lactam antibiotics, 97.5% were resistant to sulfamethoxazole/trimethoprim, and 80% were resistant to rifampin. This study provides important information on B. cereus isolates from spacecraft assembly facilities for use in microbial monitoring programs of spacecraft.
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相关论文
共 33 条
[1]   Gapped BLAST and PSI-BLAST: a new generation of protein database search programs [J].
Altschul, SF ;
Madden, TL ;
Schaffer, AA ;
Zhang, JH ;
Zhang, Z ;
Miller, W ;
Lipman, DJ .
NUCLEIC ACIDS RESEARCH, 1997, 25 (17) :3389-3402
[2]   Detection of toxigenic Bacillus cereus and Bacillus thuringiensis spores in US rice [J].
Ankolekar, Chandrakant ;
Rahmati, Talat ;
Labbe, Ronald G. .
INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, 2009, 128 (03) :460-466
[3]   Toxin profile, antibiotic resistance, and phenotypic and molecular characterization of Bacillus cereus in Sunsik [J].
Chon, Jung-Whan ;
Kim, Jong-Hyun ;
Lee, Sun-Jin ;
Hyeon, Ji-Yeon ;
Seo, Kun-Ho .
FOOD MICROBIOLOGY, 2012, 32 (01) :217-222
[4]   MECHANISMS OF BACTERIAL-RESISTANCE TO ANTIBIOTICS [J].
DEVER, LA ;
DERMODY, TS .
ARCHIVES OF INTERNAL MEDICINE, 1991, 151 (05) :886-895
[5]  
Hudzicki J., 2009, Kirby-Bauer disk diffusion susceptibility test protocol, DOI DOI 10.1371/JOURNAL.PONE.0222911
[6]  
Kemnic T. R., 2022, StatPearls, V25, P375, DOI [10.1542/pir.25.11.375, DOI 10.1542/PIR.25.11.375]
[7]   Improved multiplex PCR assay for simultaneous detection of Bacillus cereus emetic and enterotoxic strains [J].
Kim, Jae-Myung ;
Forghani, Fereidoun ;
Kim, Jung-Beom ;
Park, Yong-Bae ;
Park, Myoung-Su ;
Wang, Jun ;
Park, Joong Hyun ;
Oh, Deog-Hwan .
FOOD SCIENCE AND BIOTECHNOLOGY, 2012, 21 (05) :1439-1444
[8]   How antibiotics kill bacteria: from targets to networks [J].
Kohanski, Michael A. ;
Dwyer, Daniel J. ;
Collins, James J. .
NATURE REVIEWS MICROBIOLOGY, 2010, 8 (06) :423-435
[9]   Microbial characterization of the Mars Odyssey spacecraft and its encapsulation facility [J].
La Duc, MT ;
Nicholson, W ;
Kern, R ;
Venkateswaran, K .
ENVIRONMENTAL MICROBIOLOGY, 2003, 5 (10) :977-985
[10]   Machine learning algorithm to characterize antimicrobial resistance associated with the International Space Station surface microbiome [J].
Madrigal, Pedro ;
Singh, Nitin K. ;
Wood, Jason M. ;
Gaudioso, Elena ;
Hernandez-Del-Olmo, Felix ;
Mason, Christopher E. ;
Venkateswaran, Kasthuri ;
Beheshti, Afshin .
MICROBIOME, 2022, 10 (01)