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Supporting data for "High-throughput proteomics and <i>in vitro</i> functional characterization of the 26 medically most important elapids and vipers from sub-Saharan Africa"

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DataCite Commons2025-05-26 更新2025-04-15 收录
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http://gigadb.org/dataset/102333
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资源简介:
Venomous snakes are important parts of the ecosystem, and their behavior and evolution have been shaped by their surrounding environments over the eons. This is reflected in their venoms, which are typically highly adapted for their biological niche, including their diet and defense mechanisms for deterring predators. Sub-Saharan Africa is rich in venomous snake species, of which many are dangerous to humans due to the high toxicity of their venoms and their ability to effectively deliver large amounts of venom into their victims via their bite. In this study, the venoms of 26 of sub-Saharan Africas medically most relevant elapid and viper species were subjected to parallelized toxicovenomics analysis. The analysis included venom proteomics and <i>in vitro</i> functional characterization of whole venom toxicities and enables a robust comparison of venom profiles between species. The data presented here corroborates previous studies and provides biochemical details for the clinical manifestations observed in envenomings by the 26 snake species. Moreover, two new venom proteomes (<i>N. anchietae</i> and <i>E. leucogaster</i>) are presented here for the first time. Combined, the presented data can help shine light on snake venom evolutionary trends and possibly be used to further improve or develop novel antivenoms.

有毒蛇类是生态系统的重要组成部分,其行为与演化历经亿万年均由周遭环境塑造。这一特征在蛇毒中得以体现:蛇毒通常高度适配其生存生态位,包括匹配自身食性与抵御捕食者的防御机制。撒哈拉以南非洲拥有丰富的有毒蛇类物种,其中诸多物种因蛇毒毒性剧烈,且可通过咬伤向受害者有效注入大量毒液,因而对人类具有较高危险性。本研究针对撒哈拉以南非洲26种临床相关性最高的眼镜蛇科(elapid)与蝰科(viper)蛇类的蛇毒,开展了并行化蛇毒毒组学(toxicovenomics)分析。该分析涵盖蛇毒蛋白质组学与全蛇毒毒性的体外(in vitro)功能表征,可实现不同物种间蛇毒特征的可靠比较。本研究提交的数据不仅佐证了既往相关研究,还为这26种蛇类咬伤中毒时观察到的临床表现提供了生化细节。此外,本研究首次报道了两种全新的蛇毒蛋白质组:<i>N. anchietae</i>与<i>E. leucogaster</i>。综上,本研究提交的数据可助力阐明蛇毒的演化规律,或可用于进一步优化或开发新型抗蛇毒血清。
提供机构:
GigaScience Database
创建时间:
2022-11-08
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