Evaluating flow cytometric metrics for enhancing microbial monitoring in drinking water treatment processes

Flow cytometry (FCM) offers a rapid method for bacterial detection in drinking water but faces challenges in terms of data analysis, particularly gating subjectivity. This study evaluates three metrics derived from the Intact Cell Count (ICC): High/Low Nucleic Acid (HNA/LNA) ratios, Bray–Curtis Dissimilarity Index (BCDI), and FCM fingerprints—to enhance microbial monitoring approaches across different water treatment and distribution stages. ICC provided a direct assessment of microbial load in high cell count scenarios, while HNA/LNA ratios were valuable during low microbial levels. BCDI effectively tracked microbial population changes throughout treatment processes. A lead–lag analysis revealed that ICC changes often precede or coincide with BCDI changes and lead changes in HNA/LNA ratios. FCM fingerprinting visualized spatial and temporal variations in microbial communities. Combining these FCM metrics improved microbial water quality assessment and supports approaches to optimise water treatment strategies from a microbial perspective.