Department of Microbiology, University of Stellenbosch, Stellenbosch, Western Cape 7600, South Africa.
Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States.
Water Res. 2023 Mar 1;231:119599. doi: 10.1016/j.watres.2023.119599. Epub 2023 Jan 11.
River water is an essential human resource that may be contaminated with hazardous microorganisms. However, the risk of yeast infection through river water exposure is unclear because it is highly dependant on individual susceptibility and has therefore not been well-studied, to date. To evaluate this undefined risk, we analysed the fungal communities in less polluted (LP) and highly polluted (HP) river water, as determined using principal coordinate analysis of pollution indicators. We enumerated culturable yeasts using a thermally selective isolation procedure (37 °C) and thus promoted the growth of potentially opportunistic species. Yeast species identified as clinically relevant were then tested for antifungal resistance. In addition, we propose a quantitative microbial risk assessment (QMRA) framework to quantitatively assess the potential risk of yeast infection. Our results indicated that pollution levels significantly altered fungal communities (p = 0.007) and that genera representing opportunistic and pathogenic members were significantly more abundant in HP waters (p = 0.038). Additionally, the yeast species Candida glabrata and Clavispora lusitaniae positively correlated with other pollution indicators, demonstrating the species' indicator potential. Our QMRA results further indicate that higher risk of infection is associated with increased water pollution levels (considering both physicochemical and bacterial indicators). Furthermore, yeast species with higher pathogenic potential present an increased risk of infection despite lower observed concentrations in the river water. Interestingly, the bloom of Meyerozyma guilliermondii during the wet season suggests that other environmental factors, such as dissolved oxygen levels and water turbulence, might affect growth characteristics of yeasts in river water, which consequently affects the distribution of annual infection risks. The presence of antifungal resistant yeasts, observed in this study, could further contribute to variation in risk distribution. Research on the ecophysiology of yeasts in these environments is therefore necessary to ameliorate the uncertainty and sensitivity of the proposed QMRA model. In addition to the vital knowledge on opportunistic and pathogenic yeast occurrence in river water and their observed association with pollution, this study provides valuable methods and insights to initiate future QMRAs of yeast infections.
河水是一种重要的人类资源,但可能受到有害微生物的污染。然而,通过河水暴露感染酵母的风险尚不清楚,因为它高度依赖于个体易感性,迄今为止尚未得到充分研究。为了评估这种未定义的风险,我们分析了使用污染指标主坐标分析确定的污染程度较低(LP)和污染程度较高(HP)河水中的真菌群落。我们使用热选择性分离程序(37°C)对可培养酵母进行计数,从而促进了潜在机会性物种的生长。然后对被鉴定为临床相关的酵母物种进行抗真菌药物耐药性测试。此外,我们提出了一种定量微生物风险评估(QMRA)框架,以定量评估酵母感染的潜在风险。我们的结果表明,污染水平显著改变了真菌群落(p=0.007),并且代表机会性和致病性成员的属在 HP 水中更为丰富(p=0.038)。此外,酵母物种 Candida glabrata 和 Clavispora lusitaniae 与其他污染指标呈正相关,表明这些物种具有指示潜力。我们的 QMRA 结果进一步表明,感染风险与水污染水平的增加呈正相关(同时考虑理化和细菌指标)。此外,尽管河水中观察到的浓度较低,但具有更高致病性潜力的酵母物种会增加感染风险。有趣的是,在潮湿季节梅耶罗氏酵母的大量繁殖表明,其他环境因素,如溶解氧水平和水湍流,可能会影响河水中酵母的生长特性,从而影响年度感染风险的分布。本研究中观察到的抗真菌耐药酵母的存在可能进一步导致风险分布的变化。因此,研究这些环境中的酵母生态生理学对于改善所提出的 QMRA 模型的不确定性和敏感性是必要的。除了关于河水机会性和致病性酵母发生的重要知识及其与污染的观察到的关联外,本研究还提供了有价值的方法和见解,以启动未来的酵母感染 QMRA。