Waseem Hassan, Williams Maggie R, Stedtfeld Tiffany, Chai Benli, Stedtfeld Robert D, Cole James R, Tiedje James M, Hashsham Syed A
Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, USA.
Center for Microbial Ecology, Michigan State University, East Lansing, MI 48824, USA.
Environ Sci Process Impacts. 2017 Mar 22;19(3):247-260. doi: 10.1039/c6em00689b.
Virulence factor activity relationships (VFARs) - a concept loosely based on quantitative structure-activity relationships (QSARs) for chemicals was proposed as a predictive tool for ranking risks due to microorganisms relevant to water safety. A rapid increase in sequencing capabilities and bioinformatics tools has significantly increased the potential for VFAR-based analyses. This review summarizes more than 20 bioinformatics databases and tools, developed over the last decade, along with their virulence and antimicrobial resistance prediction capabilities. With the number of bacterial whole genome sequences exceeding 241 000 and metagenomic analysis projects exceeding 13 000 and the ability to add additional genome sequences for few hundred dollars, it is evident that further development of VFARs is not limited by the availability of information at least at the genomic level. However, additional information related to co-occurrence, treatment response, modulation of virulence due to environmental and other factors, and economic impact must be gathered and incorporated in a manner that also addresses the associated uncertainties. Of the bioinformatics tools, a majority are either designed exclusively for virulence/resistance determination or equipped with a dedicated module. The remaining have the potential to be employed for evaluating virulence. This review focusing broadly on omics technologies and tools supports the notion that these tools are now sufficiently developed to allow the application of VFAR approaches combined with additional engineering and economic analyses to rank and prioritize organisms important to a given niche. Knowledge gaps do exist but can be filled with focused experimental and theoretical analyses that were unimaginable a decade ago. Further developments should consider the integration of the measurement of activity, risk, and uncertainty to improve the current capabilities.
毒力因子活性关系(VFARs)——一个大致基于化学物质定量构效关系(QSARs)的概念,被提议作为一种预测工具,用于对与水安全相关的微生物所带来的风险进行排序。测序能力和生物信息学工具的迅速发展显著增加了基于VFAR分析的潜力。本综述总结了过去十年间开发出的20多个生物信息学数据库和工具,以及它们的毒力和抗微生物耐药性预测能力。随着细菌全基因组序列数量超过241,000个,宏基因组分析项目超过13,000个,并且只需花费几百美元就能添加更多基因组序列,显然,至少在基因组层面,VFARs的进一步发展不受信息可用性的限制。然而,必须收集与共现、治疗反应、环境和其他因素导致的毒力调节以及经济影响相关的额外信息,并以一种能够解决相关不确定性的方式将其纳入。在生物信息学工具中,大多数要么专门设计用于毒力/耐药性测定,要么配备了专用模块。其余的则有用于评估毒力的潜力。本综述广泛关注组学技术和工具,支持了这样一种观点,即这些工具现在已经足够成熟,可以应用VFAR方法并结合额外的工程和经济分析,对特定生态位中重要的生物体进行排序和优先级划分。知识差距确实存在,但可以通过十年前难以想象的有针对性的实验和理论分析来填补。进一步的发展应考虑将活性测量、风险和不确定性进行整合,以提高当前的能力。