Predicting antibacterial activity from snake venom proteomes

被引:8
作者
Rheubert, Justin L. [1 ]
Meyer, Michael F. [2 ]
Strobel, Raeshelle M. [1 ]
Pasternak, Megan A. [1 ]
Charvat, Robert A. [1 ]
机构
[1] Univ Findlay, Dept Biol, Findlay, OH 45840 USA
[2] Washington State Univ, Sch Environm, Pullman, WA 99164 USA
来源
PLOS ONE | 2020年 / 15卷 / 01期
基金
美国国家科学基金会;
关键词
AMINO-ACID OXIDASE; ANTIMICROBIAL ACTIVITY; VIPER VENOM; SAMPLE-SIZE; NAJA-ATRA; PURIFICATION; RATTLESNAKE; ANTIVENOM; EVOLUTION; PROTEINS;
D O I
10.1371/journal.pone.0226807
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The continued evolution of antibiotic resistance has increased the urgency for new antibiotic development, leading to exploration of non-traditional sources. In particular, snake venom has garnered attention for its potent antibacterial properties. Numerous studies describing snake venom proteomic composition as well as antibiotic efficacy have created an opportunity to synthesize relationships between venom proteomes and their antibacterial properties. Using literature reported values from peer-reviewed studies, our study generated models to predict efficacy given venom protein family composition, snake taxonomic family, bacterial Gram stain, bacterial morphology, and bacterial respiration strategy. We then applied our predictive models to untested snake species with known venom proteomic compositions. Overall, our results provide potential protein families that serve as accurate predictors of efficacy as well as promising organisms in terms of antibacterial properties of venom. The results from this study suggest potential future research trajectories for antibacterial properties in snake venom by offering hypotheses for a variety of taxa.
引用
收藏
页数:18
相关论文
共 64 条
[1]   Interaction of a snake venom L-amino acid oxidase with different cell types membrane [J].
Abdelkafi-Koubaa, Zaineb ;
Aissa, Imen ;
Morjen, Maram ;
Kharrat, Nadia ;
El Ayeb, Mohamed ;
Gargouri, Youssef ;
Srairi-Abid, Najet ;
Marrakchi, Naziha .
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES, 2016, 82 :757-764
[2]  
[Anonymous], 2017, R LANG ENV STAT COMP
[3]  
[Anonymous], 2002, MODEL SEL MULTIMODEL, DOI 10.1007/978-0-387-22456-5_5
[4]  
[Anonymous], 2012, BIOMETRY PRINCIPLES, DOI DOI 10.2307/2343822
[5]  
[Anonymous], 1973, 1973 2 INT S INFORM, DOI [10.1007/978-1-4612-1694-0, 10.1007/978-1-4612-0919-5_38]
[6]  
[Anonymous], 2007, APPL MULTIVARIATE ST
[7]  
Antao EM, 2018, BUNDESGESUNDHEITSBLA, V61, P499, DOI 10.1007/s00103-018-2726-y
[8]   The effects of small sample size and sample bias on threshold selection and accuracy assessment of species distribution models [J].
Bean, William T. ;
Stafford, Robert ;
Brashares, Justin S. .
ECOGRAPHY, 2012, 35 (03) :250-258
[9]   Antibacterial activity of selected snake venoms on pathogenic bacterial strains [J].
Boda, Francisc Andrei ;
Mare, Anca ;
Szabo, Zoltan Istvan ;
Berta, Lavinia ;
Curticapean, Augustin ;
Dogaru, Maria ;
Man, Adrian .
REVISTA ROMANA DE MEDICINA DE LABORATOR, 2019, 27 (03) :305-317
[10]   Snake Venomics of Crotalus tigris: The Minimalist Toxin Arsenal of the Deadliest Neartic Rattlesnake Venom. Evolutionary Clues for Generating a Pan-Specific Antivenom against Crotalid Type II Venoms [J].
Calvete, Juan J. ;
Perez, Alicia ;
Lomonte, Bruno ;
Sanchez, Elda E. ;
Sanz, Libia .
JOURNAL OF PROTEOME RESEARCH, 2012, 11 (02) :1382-1390