A simplified strategy for titrating gene expression reveals new relationships between genotype, environment, and bacterial growth.

A lack of high-throughput techniques for making titrated, gene-specific changes in expression limits our understanding of the relationship between gene expression and cell phenotype. Here, we present a generalizable approach for quantifying growth rate as a function of titrated changes in gene expression level. The approach works by performing CRISPRi with a series of mutated single guide RNAs (sgRNAs) that modulate gene expression. To evaluate sgRNA mutation strategies, we constructed a library of 5927 sgRNAs targeting 88 genes in Escherichia coli MG1655 and measured the effects on growth rate. We found that a compounding mutational strategy, through which mutations are incrementally added to the sgRNA, presented a straightforward way to generate a monotonic and gradated relationship between mutation number and growth rate effect. We also implemented molecular barcoding to detect and correct for mutations that 'escape' the CRISPRi targeting machinery; this strategy unmasked deleterious growth rate effects obscured by the standard approach of ignoring escapers. Finally, we performed controlled environmental variations and observed that many gene-by-environment interactions go completely undetected at the limit of maximum knockdown, but instead manifest at intermediate expression perturbation strengths. Overall, our work provides an experimental platform for quantifying the phenotypic response to gene expression variation.

A DNA-Binding Protein Tunes Septum Placement during Bacillus subtilis Sporulation.

Bacillus subtilis is a bacterium capable of differentiating into a spore form more resistant to environmental stress. Early in sporulation, each cell possesses two copies of a circular chromosome. A polar FtsZ ring (Z ring) directs septation over one of the chromosomes, generating two cell compartments. The smaller "forespore" compartment initially contains only 25 to 30% of one chromosome, and this transient genetic asymmetry is required for differentiation. Timely assembly of polar Z rings and precise capture of the chromosome in the forespore both require the DNA-binding protein RefZ. To mediate its role in chromosome capture, RefZ must bind to specific DNA motifs (RBMs) that localize near the poles at the time of septation. Cells artificially induced to express RefZ during vegetative growth cannot assemble Z rings, an effect that also requires DNA binding. We hypothesized that RefZ-RBM complexes mediate precise chromosome capture by modulating FtsZ function. To investigate, we isolated 10 RefZ loss-of-function (rLOF) variants unable to inhibit cell division yet still capable of binding RBMs. Sporulating cells expressing the rLOF variants in place of wild-type RefZ phenocopied a ΔrefZ mutant, suggesting that RefZ acts through an FtsZ-dependent mechanism. The crystal structure of RefZ was solved, and wild-type RefZ and the rLOF variants were further characterized. Our data suggest that RefZ's oligomerization state and specificity for the RBMs are critical determinants influencing RefZ's ability to affect FtsZ dynamics. We propose that RBM-bound RefZ complexes function as a developmentally regulated nucleoid occlusion system for fine-tuning the position of the septum relative to the chromosome during sporulation.IMPORTANCE The bacterial nucleoid forms a large, highly organized structure. Thus, in addition to storing the genetic code, the nucleoid harbors positional information that can be leveraged by DNA-binding proteins to spatially constrain cellular activities. During B. subtilis sporulation, the nucleoid undergoes reorganization, and the cell division protein FtsZ assembles polarly to direct septation over one chromosome. The TetR family protein RefZ binds DNA motifs (RBMs) localized near the poles at the time of division and is required for both timely FtsZ assembly and precise capture of DNA in the future spore compartment. Our data suggest that RefZ exploits nucleoid organization by associating with polarly localized RBMs to modulate the positioning of FtsZ relative to the chromosome during sporulation.

A continuous epistasis model for predicting growth rate given combinatorial variation in gene expression and environment.

Quantifying and predicting growth rate phenotype given variation in gene expression and environment is complicated by epistatic interactions and the vast combinatorial space of possible perturbations. We developed an approach for mapping expression-growth rate landscapes that integrates sparsely sampled experimental measurements with an interpretable machine learning model. We used mismatch CRISPRi across pairs and triples of genes to create over 8,000 titrated changes in E. coli gene expression under varied environmental contexts, exploring epistasis in up to 22 distinct environments. Our results show that a pairwise model previously used to describe drug interactions well-described these data. The model yielded interpretable parameters related to pathway architecture and generalized to predict the combined effect of up to four perturbations when trained solely on pairwise perturbation data. We anticipate this approach will be broadly applicable in optimizing bacterial growth conditions, generating pharmacogenomic models, and understanding the fundamental constraints on bacterial gene expression. A record of this paper's transparent peer review process is included in the supplemental information.