The Application of Imaging Flow Cytometry for Characterisation and Quantification of Bacterial Phenotypes

Abstract

Bacteria modify their morphology in response to various factors including growth stage, nutrient availability, predation, motility and long-term survival strategies. Morphological changes may also be associated with specific physiological phenotypes such as the formation of dormant or persister cells in a “viable but non-culturable” (VBNC) state which frequently display different shapes and size compared to their active counterparts. Such dormancy phenotypes can display various degrees of tolerance to antibiotics and therefore a detailed understanding of these phenotypes is crucial for combatting chronic infections and associated diseases. Cell shape and size are therefore more than simple phenotypic characteristics; they are important physiological properties for understanding bacterial life-strategies and pathologies. However, quantitative studies on the changes to cell morphologies during bacterial growth, persister cell formation and the VBNC state are few and severely constrained by current limitations in the most used investigative techniques of flow cytometry (FC) and light or electron microscopy. In this study, we applied high-throughput Imaging Flow Cytometry (IFC) to characterise and quantify, at single-cell level and over time, the phenotypic heterogeneity and morphological changes in cultured populations of four bacterial species, Bacillus subtilis, Lactiplantibacillus plantarum, Pediococcus acidilactici and Escherichia coli. Morphologies in relation to growth stage and stress responses, cell integrity and metabolic activity were analysed. Additionally, we were able to identify and morphologically classify dormant cell phenotypes such as VBNC cells and monitor the resuscitation of persister cells in Escherichia coli following antibiotic treatment. We therefore demonstrate that IFC, with its high-throughput data collection and image capture capabilities, provides a platform by which a detailed understanding of changes in bacterial phenotypes and their physiological implications may be accurately monitored and quantified, leading to a better understanding of the role of phenotypic heterogeneity in the dynamic microbiome.

Imaging Flow Cytometry to Study Biofilm-Associated Microbial Aggregates

“…The developed tool, being a combination of imaging flow cytometry and a machine learning module-based interpretation protocol, significantly improved the analytic potential of conventional flow cytometry. The IFC instrument (a unique combination of a conventional flow cytometer with a fluorescence microscope), together with advanced software for an in-depth analysis of the cytometric results, provides the ability to image large numbers of cells in high resolution and improves the cytometric analysis of cells even in complex cell populations/consortia [ 42 , 43 ].…”

“…The ML-based software-assisted IFC analysis provided: (i) a precise “look” into the heterogeneity of the microbial population while increasing the range of information obtained about cells (direct correlation of the fluorescence intensity with cell morphology) [ 43 ] and (ii) allowed for comprehensive monitoring of the dynamics of complex processes, such as biofilm formation [ 43 , 46 ].…”

Developing whole cell standards for the microbiome field

“…To combine the 20 strains in equal ratios, the number of fixed cells for each bacterial strain was enumerated using flow cytometry, the gold standard method for such purposes [26][27][28][29][30][31][32]. Strains were quantified using the Bacteria Counting Kit for flow cytometry (Invitrogen, UK) in accordance with the manufacturer's instructions.…”

Single-Cell Technologies to Study Phenotypic Heterogeneity and Bacterial Persisters

“…IFC differs from traditional flow cytometry in the way that it can provide fluorescently indicated morphological and physiological information in the context of a single cell image [62]. For example, bacterial length and granularity data measured through IFC have been used in a model to predict persistence based on a cell's morphological features [63,64]. Additionally, through continual improvements to IFC, virtual-freezing fluorescence imaging flow cytometry (VIFFI-FC) has been developed.…”