Isolation of Intact Microbial Populations by Preparative Capillary Zone Electrophoresis

Poster Presentation

Prepared by B. Huge, S. Lum, M. Champion, N. Dovichi
University of Notre Dame, University of Notre Dame, Chemistry & Biochem, 431B Stepan, Notre Dame, IN, 46556, United States

Contact Information:; 574-631-7380


Microbes often grow in complex communities, called microbiomes. Communal properties such as robustness and division of labor are among the benefits to the organisms within a microbiome. Their interactions have been known to promote survival in otherwise unfavorable environments, but present obstacles to researchers across several fields. The greatest obstacles are identification of the individual organisms and their specific contribution to the microbiome.

Estimates are that 99% of microbial species cannot be cultured. Therefore, culture-independent methods are used to assess microbial diversity. Analysis of 16S rRNA genes is a well-established method to generate a community profile for a given environmental sample. Metagenomic analysis of extracted microbial DNA can be used to reassemble genomes and assign population-specific functions based on matching known genes and genomes, but rarer organisms are easily lost within a metagenome. Single-cell or single-population genomics are necessary for complete sequence coverage and facilitate the discovery of novel organisms, but require high-resolution separations of microbial populations within a microbiome prior to analysis.

We are developing a method for the isolation of microbial populations within a mixture using capillary zone electrophoresis (CZE), which separates based on size-charge ratio, coupled to an automated fraction collector for sample recovery and purification. Standard laboratory strains Escherichia coli and Bacillus subtilis were used in preliminary experiments. First, we demonstrated the ability to recover viable cells after electrophoretic deposition, which will aid in complete sequence coverage and function assignment. Next, we evaluated separation efficiency with binary mixtures and simulated a complex environment with a large dynamic range. With confirmed viable conditions and sufficient resolution, this work forms a model for future analysis of complex environmental and clinical microbiomes.