Carbon source-dependent growth heterogeneity across Streptococcus pneumoniae serotypes revealed through interactive data visualization

Bacteria at the host-pathogen interface must continuously adapt their metabolism to the nutrient landscape of the host environment. More than 30% of the Streptococcus pneumoniae genome is dedicated to carbohydrate transport and metabolism, thus underscoring the importance of central carbon metabolism in host adaptation and survival. Despite this, comprehensive comparisons of carbon source-dependent growth dynamics across diverse pneumococcal serotypes remain limited. In this study, we used Biolog phenotype microarray plates together with a physiologically relevant defined medium, RPMI 1640, to characterize carbon source utilization and growth phenotypes across encapsulated serotypes and non-encapsulated strains. While several carbon sources supported conserved growth patterns across serotypes or strains, substantial serotype-specific variation was observed in carbon source utilization, maximal growth achieved, growth kinetics, and the timing of the death phase or the extent of autolysis. To address limitations in conventional data presentation, we present an interactive visualization framework for bacterial growth analysis. In the web version of this article, readers can dynamically explore carbon source-dependent phenotypes through interactive heatmaps linked to full growth curves, enabling detailed examination of growth phases, kinetic transitions, and autolysis events, alongside Venn diagrams that highlight serotype- and carbon source-specific phenotypic differences. The underlying code is publicly available via GitHub, providing a template for interactive data exploration. Together, these findings provide a valuable resource for investigating pneumococcal metabolic adaptation in host-relevant nutrient environments and demonstrate how interactive publication can enhance exploration and interpretation of complex bacterial growth data sets. IMPORTANCE As bacteria adapt their metabolism to nutritional environments, comprehensive comparisons across experimental data sets are often limited by their scale and complexity. Here, we characterize carbon source utilization across Streptococcus pneumoniae serotypes and strains, revealing both conserved and strain-specific growth dynamics that likely contribute to colonization and disease potential. We also address a broader challenge: how large, high-dimensional data sets are presented and interpreted in peer-reviewed publications. Current figures compress multidimensional kinetic data into single, static representations, limiting a reader's ability to independently evaluate the underlying dynamics. To overcome this limitation, we developed an interactive data visualization platform directly into the web-based article, enabling readers to explore the data while maintaining full data transparency. This approach advances data presentation in peer-reviewed research by providing a generalizable framework to improve the accessibility, interpretability, and evaluation of complex biological data sets.