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UNLABELLED: Microorganisms with simplified genomes represent interesting cell chassis for systems and synthetic biology. However, genome reduction can lead to undesired traits, such as decreased growth rate and metabolic imbalances. To investigate the impact of genome reduction on Escherichia coli strain DGF-298, a strain in which ~ 36% of the genome has been removed, we reconstructed a strain-specific metabolic model (iAC1061), investigated the regulation of gene expression using iModulon-based transcriptome analysis, and performed adaptive laboratory evolution to let the strain correct potential imbalances that arose during its simplification. The model notably predicted that the removal of all three key pathways for glycolaldehyde disposal in this microorganism would lead to a metabolic bottleneck through folate starvation. Glycolaldehyde is also known to cause self-generation of reactive oxygen species, as evidenced by the increased expression of oxidative stress resistance genes in the SoxS iModulon. The reintroduction of the aldA gene, responsible for one native glycolaldehyde disposal route, alleviated the constitutive oxidative stress response. Our results suggest that systems-level approaches and adaptive laboratory evolution have additive benefits when trying to repair and optimize genome-engineered strains. IMPORTANCE: Genomic streamlining can be employed in model organisms to reduce complexity and enhance strain predictability. One of the most striking examples is the bacterial strain Escherichia coli DGF-298, notable for having over one-third of its genome deleted. However, such extensive genome modifications raise the question of how similar this simplified cell remains when compared with its parent, and what are the possible unintended consequences of this simplification. In this study, we used metabolic modeling along with iModulon-based transcriptomic analysis in different growth conditions to assess the impact of genome reduction on metabolism and gene regulation. We observed little impact of genomic reduction on the regulatory network of E. coli DGF-298 and identified a potential metabolic bottleneck leading to the constitutive activity of the SoxS iModulon. We then leveraged the models predictions to successfully restore SoxS activity to the basal level.

Mesoplasma florum, a fast-growing near-minimal organism, is a compelling model to explore rational genome designs. Using sequence and structural homology, the set of metabolic functions its genome encodes was identified, allowing the reconstruction of a metabolic network representing ˜ 30% of its protein-coding genes. Growth medium simplification enabled substrate uptake and product secretion rate quantification which, along with experimental biomass composition, were integrated as species-specific constraints to produce the functional iJL208 genome-scale model (GEM) of metabolism. Genome-wide expression and essentiality datasets as well as growth data on various carbohydrates were used to validate and refine iJL208. Discrepancies between model predictions and observations were mechanistically explained using protein structures and network analysis. iJL208 was also used to propose an in silico reduced genome. Comparing this prediction to the minimal cell JCVI-syn3.0 and its parent JCVI-syn1.0 revealed key features of a minimal gene set. iJL208 is a stepping-stone toward model-driven whole-genome engineering.

Cloning and transplantation of bacterial genomes is a powerful method for the creation of engineered microorganisms. However, much remains to be understood about the molecular mechanisms and limitations of this approach. We report the whole-genome cloning of Mesoplasma florum in Saccharomyces cerevisiae, and use this model to investigate the impact of a bacterial chromosome in yeast cells. Our results indicate that the cloned M. florum genome is subjected to weak transcriptional activity, and causes no significant impact on yeast growth. We also report that the M. florum genome can be transplanted into Mycoplasma capricolum without any negative impact from the putative restriction enzyme encoding gene mfl307. Using whole-genome sequencing, we observed that a small number of mutations appeared in all M. florum transplants. Mutations also arose, albeit at a lower frequency, when the M. capricolum genome was transplanted into M. capricolum recipient cells. These observations suggest that genome transplantation is mutagenic, and that this phenomenon is magnified by the use of genome donor and recipient cell belonging to different species. No difference in efficiency was detected after three successive rounds of genome transplantation, suggesting that the observed mutations were not selected during the procedure. Taken together, our results provide a more accurate picture of the events taking place during bacterial genome cloning and transplantation.

DNA-binding proteins play a crucial role in all living organisms by interacting with various DNA sequences across the genome. While several methods have been used to study the interaction between DNA and proteins in vitro, chromatin immunoprecipitation followed by sequencing (ChIP-seq) has become the standard technique for identifying the genome-wide location of DNA-binding proteins in vivo. However, the resolution of standard ChIP-seq methodology is limited by the DNA fragmentation process and presence of contaminating DNA. A significant improvement of the ChIP-seq technique results from the addition of an exonuclease treatment during the immunoprecipitation step (ChIP-exo) that lowers background noise and more importantly increases the identification of binding sites to a level near to single-base resolution by effectively footprinting DNA-bound proteins. By doing so, ChIP-exo offers new opportunities for a better characterization of the complex and fascinating architecture that resides in DNA-proteins interactions and provides new insights for the comprehension of important molecular mechanisms.

Transcription start sites are commonly used to locate promoter elements in bacterial genomes. TSS were previously studied one gene at a time, often through 5'-rapid amplification of cDNA ends (5'-RACE). This technique has now been adapted for high-throughput sequencing and can be used to precisely identify TSS in a genome-wide fashion for practically any bacterium, which greatly contributes to our understanding of gene regulatory networks in microorganisms.