Spatial Correlations and Distribution of Competence Gene Expression in Biofilms of Streptococcus mutans

Abstract

Streptococcus mutans is an important pathogen in the human oral biofilm. It expresses virulent behaviors that are linked to its genetic competence regulon, which is controlled by comX. Expression of comX is modulated by two diffusible signaling peptides, denoted CSP and XIP, and by other environmental cues such as pH and oxidative stress. The sensitivity of S. mutans competence to environmental inputs that may vary on microscopic length scales raises the question of whether the biofilm environment creates microniches where competence and related phenotypes are concentrated, leading to spatial clustering of S. mutans virulence behaviors. We have used two-photon microscopy to characterize the spatial distribution of comX expression among individual S. mutans cells in biofilms. By analyzing correlations in comX activity, we test for spatial clustering that may suggest localized competence microenvironments. Our data indicate that both competence-signaling peptides diffuse efficiently through the biofilm. XIP elicits a population-wide response. CSP triggers a Poisson-like, spatially random comX response from a subpopulation of cells that is homogeneously dispersed. Our data indicate that competence microenvironments if they exist are small enough that the phenotypes of individual cells are not clustered or correlated to any greater extent than occurs in planktonic cultures.

Responses of Salmonella biofilms to oxidizing biocides: Evidence of spatial clustering

“…Spatial point pattern analysis allows us to classify spatial distributions of the green channel particles in Figure 6A. A powerful tool for examining spatial independence across scales is Ripley's K ‐function which has been applied to quantify the spatial distribution of bacteria within the biofilm in several studies (Hart et al, 2019; Ishkov et al, 2021; Marchal et al, 2017). The univariate form of Ripley's K‐function (where only one type of point is considered) is. where n is the number of points inside a region of area A , is the edge effect correction factor.…”

“…Biofilms are inherently resilient to stress (Rode et al, 2020 ) in part due to the heterogeneity of cells and structures within the community, cells can be spatially organized into clusters and this has been linked to antimicrobial survival (Wong et al, 2021 ). To characterize the spatial distribution of cells, digital image analysis (Dazzo & Yanni, 2017 ; Schillinger et al, 2012 ), spatial analysis methods such as Ripley's K (Hart et al, 2019 ; Ishkov et al, 2021 ; Marchal et al, 2017 ) and methods for determining spatial randomness such as the Hopkins statistic (Drury et al, 1993 ; Espinoza et al, 2012 ) have been used. However, methods for evaluating clusterability can vary significantly and a comprehensive comparison of statistical tests in the biofilm context is currently lacking.…”