Abstract：
University students predominantly spend their time indoors, where prolonged exposure raises the risk of contact with microorganisms of concern. However, our knowledge about the microbial community characteristics on university campus and their underpinnings is limited. To address it, we characterized bacterial communities from the surfaces of various built environments typical of a university campus, including cafeterias, classrooms, dormitories, offices, meeting rooms, and restrooms, in addition to human skin. The classrooms harbored the highest α-diversity, while the cafeterias had the lowest α-diversity. The bacterial community composition varied significantly across different building types. Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, and Cyanobacteria were common phyla in university buildings, accounting for more than 90 % of total abundance. Staphylococcus aureus was the most abundant potential pathogen in classrooms, dormitories, offices, restrooms, and on human skin, indicating a potential risk for skin disease infections in these buildings. We further developed a new quantitative pathogenic risk assessment method according to the threat of pathogens to humans and found that classrooms exhibited the highest potential risk. The fast expectation-maximization algorithm identified 59 %-86 % of bacterial sources in buildings, with the human skin as the largest bacterial source for most buildings. As the sources of bacteria were highly traceable, we showed that homogeneous selection, dispersal limitation, and ecological drift were major ecological forces that drove community assembly. Our findings have important implications for predicting the distribution and sources of indoor dust bacterial communities on university campus.
摘要：
大学生主要花时间在室内，长期接触会增加与相关微生物接触的风险。然而,我们对大学校园微生物群落特征及其基础的了解有限。为了解决这个问题，我们从大学校园典型的各种建筑环境的表面表征了细菌群落，包括自助餐厅,教室,宿舍,offices,会议室,还有洗手间,除了人类皮肤。教室拥有最高的α多样性，而自助餐厅的α多样性最低。不同建筑物类型的细菌群落组成差异很大。变形杆菌,放线菌,Firmicutes,拟杆菌,蓝细菌是大学建筑中常见的门，占总丰度的90%以上。金黄色葡萄球菌是教室中最丰富的潜在病原体，宿舍,offices,洗手间,在人类皮肤上，表明这些建筑物存在皮肤病感染的潜在风险。根据病原体对人类的威胁，我们进一步开发了一种新的定量致病风险评估方法，发现教室表现出最高的潜在风险。快速期望最大化算法确定了建筑物中59％-86％的细菌来源，人类皮肤是大多数建筑物最大的细菌来源。由于细菌的来源是高度可追溯的，我们证明了同质选择，扩散限制，生态漂移是推动社区集会的主要生态力量。我们的发现对预测大学校园室内粉尘细菌群落的分布和来源具有重要意义。
