Fig. 5: LytB affects gene expression and cell death in a confined space. | Nature Communications

Fig. 5: LytB affects gene expression and cell death in a confined space.

From: Droplet Tn-Seq combines microfluidics with Tn-Seq for identifying complex single-cell phenotypes

Fig. 5

a The volcano plot shows genome-wide fitness changes from a dTn-Seq experiment between batch and droplet growth with glucose. Fitness difference is shown on the x-axis along with the associated p-value on the y-axis (one sample t test with Bonferroni correction). All significant genes are highlighted with color, which represent each gene’s functional category shown in the “Gene Category” figure key. b The wild-type (orange) has shorter cell-chain lengths compared with ΔlytB (green) in batch culture, but in droplets chain lengths are similar (c). d Loss of lytB causes a reduced fitness in droplets compared with batch culture. The live cell (CFU) expansion between wt and ΔlytB is similar in batch culture, however, in droplets ΔlytB grows less well then wt (n= 6; p-value is based on a one-way ANOVA with Bonferroni correction for multiple testing, * < 0.05). Shorter-chain lengths and less growth of ΔlytB in droplets could either be caused by slower growth or a higher death rate. e The expression of each gene relative to the control gene SPT_2222. f The change in expression of each gene when comparing droplet to batch. The expression of competence genes comD, comE, comM, and comX are downregulated in wt when grown in droplets, while they become upregulated in ΔlytB. In addition, the cell wall hydrolases cbpD and lytA, which are associated with increased cell lysis and fratricide become highly upregulated in ΔlytB, while only cbpD becomes upregulated in wt. Collectively, this suggests a role for LytB in suppressing the expression of competence-related genes in a confined environment. Each expression experiment consists of at least three biological replicates and three technical replicates each, error bars are standard error of the mean. p-values are based on a one-way ANOVA with Bonferroni correction for multiple testing. ns = not significant, * < 0.05, ** < 0.005, *** < 0.0005, **** < 0.0001. Source data are available in the Source Data file.

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