Improving genomically recoded Escherichia coli for the production of proteins containing non-canonical amino acids

A genomically recoded Escherichia coli strain that lacks all amber codons and release factor 1 (C321.ΔA) enables efficient genetic encoding of chemically diverse, non-canonical amino acids (ncAAs) into proteins. While C321.ΔA has opened new opportunities in chemical and synthetic biology, this strain has not been optimized for protein production, limiting its utility in widespread industrial and academic applications. To address this limitation, we describe the construction of a series of genomically recoded organisms that are optimized for cellular protein production. We demonstrate that the functional deactivation of nucleases (e.g., rne, endA) and proteases (e.g., lon) increases production of wild-type superfolder green fluorescent protein (sfGFP) and sfGFP containing two ncAAs up to ∼5-fold. Additionally, we introduce a genomic IPTG-inducible T7 RNA polymerase (T7RNAP) cassette into these strains. Using an optimized platform, we demonstrated the ability to introduce 2 identical N6-(propargyloxycarbonyl)-L-Lysine residues site specifically into sfGFP with a 17-fold improvement in production relative to the parent. We envision that our library of organisms will provide the community with multiple options for increased expression of proteins with new and diverse chemistries.

Convenient Genetic Encoding of Phenylalanine Derivatives through Their α-Keto Acid Precursors

The activity and function of proteins can be improved by incorporation of non-canonical amino acids (ncAAs). To avoid the tedious synthesis of a large number of chiral phenylalanine derivatives, we synthesized the corresponding phenylpyruvic acid precursors. Escherichia coli strain DH10B and strain C321.ΔA.expΔPBAD were selected as hosts for phenylpyruvic acid bioconversion and genetic code expansion using the MmPylRS/pyltRNACUA system. The concentrations of keto acids, PLP and amino donors were optimized in the process. Eight keto acids that can be biotransformed and their coupled genetic code expansions were identified. Finally, the genetic encoded ncAAs were tested for incorporation into fluorescent proteins with keto acids.

The Way forward for the Origin of Life: Prions and Prion-Like Molecules First Hypothesis

In this paper the hypothesis that prions and prion-like molecules could have initiated the chemical evolutionary process which led to the eventual emergence of life is reappraised. The prions first hypothesis is a specific application of the protein-first hypothesis which asserts that protein-based chemical evolution preceded the evolution of genetic encoding processes. This genetics-first hypothesis asserts that an “RNA-world era” came before protein-based chemical evolution and rests on a singular premise that molecules such as RNA, acetyl-CoA, and NAD are relics of a long line of chemical evolutionary processes preceding the Last Universal Common Ancestor (LUCA). Nevertheless, we assert that prions and prion-like molecules may also be relics of chemical evolutionary processes preceding LUCA. To support this assertion is the observation that prions and prion-like molecules are involved in a plethora of activities in contemporary biology in both complex (eukaryotes) and primitive life forms. Furthermore, a literature survey reveals that small RNA virus genomes harbor information about prions (and amyloids). If, as has been presumed by proponents of the genetics-first hypotheses, small viruses were present during an RNA world era and were involved in some of the earliest evolutionary processes, this places prions and prion-like molecules potentially at the heart of the chemical evolutionary process whose eventual outcome was life. We deliberate on the case for prions and prion-like molecules as the frontier molecules at the dawn of evolution of living systems.

Novel EDGE encoding method enhances ability to identify genetic interactions

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)–rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.