Mutant phenotypes often vary across genetically distinct individuals. To identify the causes of such genetic background effects, we studied differences in gene essentiality across 18 genetically diverse natural yeast strains. We identified 39 genes that were essential in the laboratory reference strain but not in at least one other genetic background, and we mapped and validated the genetic variants that were responsible for the differences in gene essentiality. These variants typically occurred in single modifier genes that tended to differ between genetic backgrounds. The affected genes often indirectly compensated for the loss of the essential gene and identified naturally occurring evolutionary trajectories. Overall, our results highlight the prevalence of changes in gene essentiality in natural populations, as well as the underlying mechanisms. A thorough understanding of the causes of genetic background effects is crucial for the interpretation of genotype-to-phenotype relationships, including those associated with human disease.

Metabolite concentration changes can have broad consequences on the function and robustness of metabolic networks. Here, we measured the metabolome response of 1,515 CRISPR interference (CRISPRi) E. coli strains targeting all genes in the iML1515 metabolic model. Metabolites that are hardly measurable in wild-type E. coli accumulated in specific CRISPRi strains, indicating that they are normally maintained at low levels. We confirmed metabolite accumulation using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and generated putative reference spectra for 102 metabolites for which no MS2 data had previously been available. We show that minimal metabolite levels are beneficial because they (1) enable substrate level regulation of enzyme activity, (2) prevent competitive inhibition, and (3) suppress side reactions. However, minimal metabolite pools also limit flux through engineered pathways. For example, low levels of farnesyl diphosphate (frdp) constrained a synthetic carotenoid pathway, and we show that the knockdown of octaprenyl diphosphate synthase (IspB) increased frdp levels and carotenoid production. A record of this paper's transparent peer review process is included in the supplemental information.

The engineering of genetic circuits to perform predefined computations is central to synthetic biology, enabling living cells with new functionalities applicable across various domains. However, these circuits are often specifically tailored to particular cellular hosts, with Escherichia coli being the most popular. Consequently, their intended functions may not translate well to other organisms, limiting their scope. Understanding circuit dynamics in less familiar organisms is crucial, especially for niche-specific applications requiring cellular chassis different from model organisms generally used in synthetic biology. Here, we develop a combined experimental and theoretical pipeline to evaluate the performance of NOT logic circuits, also called inverters, in the soil bacterium Pseudomonas protegens Pf-5—a host renowned for its unique environmental functions and a newcomer to genetic circuitry. Inverters were experimentally tested to characterize input-output functionality, and mathematical modelling was used to infer the dynamic principles of circuit modules. The model quantified the individual impacts of key parameters—such as translation efficiency, repressor performance, and promoter activity—on output levels, enabling predictions about inter-host circuit portability. This parameter calibration revealed unique properties of the chassis, including steeper transitions between on and off circuit states compared to the synthetic biology workhorse Pseudomonas putida. Moreover, model parameters guided the successful serial connection of two NOT gates, enabling YES logic function. As a result, our work provides DNA parts, circuits and mathematical characterizations to establish P. protegens Pf-5 as a viable chassis for environmental synthetic biology.

SUMMARYThe native microbiome influences numerous host processes, including neurological function. However, its impacts on diverse brain cell types remain poorly understood. Here, we performed single-nucleus RNA sequencing on the hippocampus of wild-type, germ-free mice, revealing the microbiome-dependent transcriptional landscape across all major neural cell types. We found conserved impacts on key adaptive immune and neurodegenerative transcriptional pathways. Mono-colonization with select indigenous microbes identified organism-specific effects on brain myeloid cell transcriptional state. Escherichia coli colonization induced a distinct myeloid cell activation state, increased brain-resident CD8+ T cells, and shaped amyloid phagocytic capacity, suggesting heightened disease susceptibility. Finally, E. coli-exposed 5xFAD mice displayed exacerbated cognitive decline and amyloid pathology, demonstrating the sufficiency of intestinal E. coli to worsen Alzheimer’s disease-relevant outcomes. Together, these results emphasize the broad, species-specific, microbiome-dependent consequences on neural cell states and highlight the capacity of specific microbes to modulate disease susceptibility.