Deep mutational scanning of essential bacterial proteins can guide antibiotic development.

Deep mutational scanning is a powerful approach to investigate a wide variety of research questions including protein function and stability. Here, we perform deep mutational scanning on three essential E. coli proteins (FabZ, LpxC and MurA) involved in cell envelope synthesis using high-throughput CRISPR genome editing, and study the effect of the mutations in their original genomic context. We use more than 17,000 variants of the proteins to interrogate protein function and the importance of individual amino acids in supporting viability. Additionally, we exploit these libraries to study resistance development against antimicrobial compounds that target the selected proteins. Among the three proteins studied, MurA seems to be the superior antimicrobial target due to its low mutational flexibility, which decreases the chance of acquiring resistance-conferring mutations that simultaneously preserve MurA function. Additionally, we rank anti-LpxC lead compounds for further development, guided by the number of resistance-conferring mutations against each compound. Our results show that deep mutational scanning studies can be used to guide drug development, which we hope will contribute towards the development of novel antimicrobial therapies.

Increasing Solvent Tolerance to Improve Microbial Production of Alcohols, Terpenoids and Aromatics.

Fuels and polymer precursors are widely used in daily life and in many industrial processes. Although these compounds are mainly derived from petrol, bacteria and yeast can produce them in an environment-friendly way. However, these molecules exhibit toxic solvent properties and reduce cell viability of the microbial producer which inevitably impedes high product titers. Hence, studying how product accumulation affects microbes and understanding how microbial adaptive responses counteract these harmful defects helps to maximize yields. Here, we specifically focus on the mode of toxicity of industry-relevant alcohols, terpenoids and aromatics and the associated stress-response mechanisms, encountered in several relevant bacterial and yeast producers. In practice, integrating heterologous defense mechanisms, overexpressing native stress responses or triggering multiple protection pathways by modifying the transcription machinery or small RNAs (sRNAs) are suitable strategies to improve solvent tolerance. Therefore, tolerance engineering, in combination with metabolic pathway optimization, shows high potential in developing superior microbial producers.

'Drc', a structurally novel ssDNA-binding transcription regulator of N4-related bacterial viruses.

Bacterial viruses encode a vast number of ORFan genes that lack similarity to any other known proteins. Here, we present a 2.20 Å crystal structure of N4-related Pseudomonas virus LUZ7 ORFan gp14, and elucidate its function. We demonstrate that gp14, termed here as Drc (ssDNA-binding RNA Polymerase Cofactor), preferentially binds single-stranded DNA, yet contains a structural fold distinct from other ssDNA-binding proteins (SSBs). By comparison with other SSB folds and creation of truncation and amino acid substitution mutants, we provide the first evidence for the binding mechanism of this unique fold. From a biological perspective, Drc interacts with the phage-encoded RNA Polymerase complex (RNAPII), implying a functional role as an SSB required for the transition from early to middle gene transcription during phage infection. Similar to the coliphage N4 gp2 protein, Drc likely binds locally unwound middle promoters and recruits the phage RNA polymerase. However, unlike gp2, Drc does not seem to need an additional cofactor for promoter melting. A comparison among N4-related phage genera highlights the evolutionary diversity of SSB proteins in an otherwise conserved transcription regulation mechanism.

CRISPR-FRT targets shared sites in a knock-out collection for off-the-shelf genome editing.

CRISPR advances genome engineering by directing endonuclease sequence specificity with a guide RNA molecule (gRNA). For precisely targeting a gene for modification, each genetic construct requires a unique gRNA. By generating a gRNA against the flippase recognition target (FRT) site, a common genetic element shared by multiple genetic collections, CRISPR-FRT circumvents this design constraint to provide a broad platform for fast, scarless, off-the-shelf genome engineering.

Network-Based Identification of Adaptive Pathways in Evolved Ethanol-Tolerant Bacterial Populations.

Efficient production of ethanol for use as a renewable fuel requires organisms with a high level of ethanol tolerance. However, this trait is complex and increased tolerance therefore requires mutations in multiple genes and pathways. Here, we use experimental evolution for a system-level analysis of adaptation of Escherichia coli to high ethanol stress. As adaptation to extreme stress often results in complex mutational data sets consisting of both causal and noncausal passenger mutations, identifying the true adaptive mutations in these settings is not trivial. Therefore, we developed a novel method named IAMBEE (Identification of Adaptive Mutations in Bacterial Evolution Experiments). IAMBEE exploits the temporal profile of the acquisition of mutations during evolution in combination with the functional implications of each mutation at the protein level. These data are mapped to a genome-wide interaction network to search for adaptive mutations at the level of pathways. The 16 evolved populations in our data set together harbored 2,286 mutated genes with 4,470 unique mutations. Analysis by IAMBEE significantly reduced this number and resulted in identification of 90 mutated genes and 345 unique mutations that are most likely to be adaptive. Moreover, IAMBEE not only enabled the identification of previously known pathways involved in ethanol tolerance, but also identified novel systems such as the AcrAB-TolC efflux pump and fatty acids biosynthesis and even allowed to gain insight into the temporal profile of adaptation to ethanol stress. Furthermore, this method offers a solid framework for identifying the molecular underpinnings of other complex traits as well.