Eskhan Asma O, Abu-Lail Nehal I
The Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, Pullman, Washington 99164, United States.
Department of Biomedical Engineering and Chemical Engineering, The University of Texas at San Antonio, San Antonio, Texas, 78249, United States.
Langmuir. 2020 Aug 4;36(30):8947-8964. doi: 10.1021/acs.langmuir.0c01500. Epub 2020 Jul 24.
The roles of the bacterial surface biopolymers of pathogenic EGDe grown under variable pH conditions in governing their adhesion to a model surface of silicon nitride were investigated using atomic force microscopy under water. Our results indicated that the adhesion forces were the highest for cells cultured in media adjusted to pH 7 followed by 1.39, 1.49, 1.57, and 2.18-fold reductions at pH 6, 8, 9, and 5, respectively. Adhesion energies followed the same trends with 1.35, 1.67, 2.20, and 2.79-fold reductions in energies at pH 6, 8, 9, and 5, respectively, compared to the energy measured at pH 7. Furthermore, the structural properties of the bacterial surface biopolymer brush represented by the biopolymer brush thickness () and the molecular density (Γ) were determined by fitting a steric model of repulsion to the approach force-distance data. The values followed the same trends as adhesion forces and energies, with thickness being highest at pH 7 followed by 1.82, 2.99, 3.11, and 4.66-fold reductions at pH 6, 8, 9, and 5, respectively. Γ was the highest at pH 5 and was followed by 1.26, 1.27, 1.70, and 2.82-fold reductions at pH 8, 9, 6, and 7, respectively. Our results indicated that bacterial adhesion forces and energies increased linearly with the product of and Γ representing the number of biopolymers per unit length of the bacterial surface. To predict the adhesion forces and energies measured, a force-averaging model of the soft-particle analysis of the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory was used. In addition to the standard parameters accounted for in the soft-particle analysis of the DLVO theory such as surface potential, hydrophobicity, and size, this averaging model incorporates in it structural bacterial parameters such as and Γ as well as a surface coverage factor (ϕ) that represents the fraction of the bacterial surface covered by biopolymers. When the soft-particle analysis of DLVO was considered, repulsive hydrogen bond strengths were predicted at close distances of approach (<0.3 nm). In comparison, the force-averaging model predicted that attractive hydrogen bonds dominate the bacterial adhesion strengths quantified. The highest adhesion quantified for cells grown at pH 7 was related to longer and more spaced biopolymers, higher contents of cellular carbohydrates, and more hydrophilic biopolymers, each of which contributes to higher possibilities for hydrogen bonding formation. These results are significant in designing new strategies that aim at controlling bacterial adhesion to surfaces.
在水环境下,利用原子力显微镜研究了在不同pH条件下生长的致病性伊氏李斯特菌(EGDe)的细菌表面生物聚合物在其与氮化硅模型表面黏附中的作用。我们的结果表明,在pH 7条件下培养的细胞的黏附力最高,而在pH 6、8、9和5条件下,黏附力分别降低了1.39倍、1.49倍、1.57倍和2.18倍。黏附能也呈现相同趋势,与pH 7时测得的能量相比,在pH 6、8、9和5条件下,黏附能分别降低了1.35倍、1.67倍、2.20倍和2.79倍。此外,通过将空间排斥模型拟合到接近力-距离数据来确定由生物聚合物刷厚度()和分子密度(Γ)表示的细菌表面生物聚合物刷的结构特性。值与黏附力和能量呈现相同趋势,厚度在pH 7时最高,在pH 6、8、9和5条件下分别降低了1.82倍、2.99倍、3.11倍和4.66倍。Γ在pH 5时最高,在pH 8、9、6和7条件下分别降低了1.26倍、1.27倍、1.70倍和2.82倍。我们的结果表明,细菌的黏附力和能量与和Γ的乘积呈线性增加,和Γ代表细菌表面单位长度的生物聚合物数量。为了预测所测得的黏附力和能量,使用了德亚金-朗道-韦弗-奥弗比克(DLVO)理论的软颗粒分析的力平均模型。除了DLVO理论的软颗粒分析中考虑的标准参数,如表面电势、疏水性和尺寸外,该平均模型还纳入了细菌结构参数,如和Γ以及表示生物聚合物覆盖的细菌表面部分的表面覆盖因子(ϕ)。当考虑DLVO的软颗粒分析时,预测在接近距离(<0.3 nm)时存在排斥性氢键强度。相比之下,力平均模型预测吸引力氢键主导了量化的细菌黏附强度。在pH 7条件下生长的细胞的最高黏附量化与更长且间隔更大的生物聚合物、更高的细胞碳水化合物含量以及更亲水的生物聚合物有关,其中每一项都有助于形成氢键的更高可能性。这些结果对于设计旨在控制细菌与表面黏附的新策略具有重要意义。