Synthetic genomes unveil the effects of synonymous recoding.

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers 1-4 . Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

Discovery of a structural class of antibiotics with explainable deep learning.

The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis1-9. Deep learning approaches have aided in exploring chemical spaces1,10-15; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of 39,312 compounds and applied ensembles of graph neural networks to predict antibiotic activity and cytotoxicity for 12,076,365 compounds. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.

Correction to "An Iterative Approach Guides Discovery of the FabI Inhibitor Fabimycin, a Late-Stage Antibiotic Candidate with In Vivo Efficacy against Drug-Resistant Gram-Negative Infections".

[This corrects the article DOI: 10.1021/acscentsci.2c00598.].

An Iterative Approach Guides Discovery of the FabI Inhibitor Fabimycin, a Late-Stage Antibiotic Candidate with In Vivo Efficacy against Drug-Resistant Gram-Negative Infections.

Genomic studies and experiments with permeability-deficient strains have revealed a variety of biological targets that can be engaged to kill Gram-negative bacteria. However, the formidable outer membrane and promiscuous efflux pumps of these pathogens prevent many candidate antibiotics from reaching these targets. One such promising target is the enzyme FabI, which catalyzes the rate-determining step in bacterial fatty acid biosynthesis. Notably, FabI inhibitors have advanced to clinical trials for Staphylococcus aureus infections but not for infections caused by Gram-negative bacteria. Here, we synthesize a suite of FabI inhibitors whose structures fit permeation rules for Gram-negative bacteria and leverage activity against a challenging panel of Gram-negative clinical isolates as a filter for advancement. The compound to emerge, called fabimycin, has impressive activity against >200 clinical isolates of Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii, and does not kill commensal bacteria. X-ray structures of fabimycin in complex with FabI provide molecular insights into the inhibition. Fabimycin demonstrates activity in multiple mouse models of infection caused by Gram-negative bacteria, including a challenging urinary tract infection model. Fabimycin has translational promise, and its discovery provides additional evidence that antibiotics can be systematically modified to accumulate in Gram-negative bacteria and kill these problematic pathogens.

Structure-function analysis of the SHOC2-MRAS-PP1C holophosphatase complex.

Receptor tyrosine kinase (RTK)-RAS signalling through the downstream mitogen-activated protein kinase (MAPK) cascade regulates cell proliferation and survival. The SHOC2-MRAS-PP1C holophosphatase complex functions as a key regulator of RTK-RAS signalling by removing an inhibitory phosphorylation event on the RAF family of proteins to potentiate MAPK signalling1. SHOC2 forms a ternary complex with MRAS and PP1C, and human germline gain-of-function mutations in this complex result in congenital RASopathy syndromes2-5. However, the structure and assembly of this complex are poorly understood. Here we use cryo-electron microscopy to resolve the structure of the SHOC2-MRAS-PP1C complex. We define the biophysical principles of holoenzyme interactions, elucidate the assembly order of the complex, and systematically interrogate the functional consequence of nearly all of the possible missense variants of SHOC2 through deep mutational scanning. We show that SHOC2 binds PP1C and MRAS through the concave surface of the leucine-rich repeat region and further engages PP1C through the N-terminal disordered region that contains a cryptic RVXF motif. Complex formation is initially mediated by interactions between SHOC2 and PP1C and is stabilized by the binding of GTP-loaded MRAS. These observations explain how mutant versions of SHOC2 in RASopathies and cancer stabilize the interactions of complex members to enhance holophosphatase activity. Together, this integrative structure-function model comprehensively defines key binding interactions within the SHOC2-MRAS-PP1C holophosphatase complex and will inform therapeutic development .

Drugging the Folate Pathway in Mycobacterium tuberculosis: The Role of Multi-targeting Agents.

The folate biosynthetic pathway offers many druggable targets that have yet to be exploited in tuberculosis therapy. Herein, we have identified a series of small molecules that interrupt Mycobacterium tuberculosis (Mtb) folate metabolism by dual targeting of dihydrofolate reductase (DHFR), a key enzyme in the folate pathway, and its functional analog, Rv2671. We have also compared the antifolate activity of these compounds with that of para-aminosalicylic acid (PAS). We found that the bioactive metabolite of PAS, in addition to previously reported activity against DHFR, inhibits flavin-dependent thymidylate synthase in Mtb, suggesting a multi-targeted mechanism of action for this drug. Finally, we have shown that antifolate treatment in Mtb decreases the production of mycolic acids, most likely due to perturbation of the activated methyl cycle. We conclude that multi-targeting of the folate pathway in Mtb is associated with highly potent anti-mycobacterial activity.

MRSA Isolates from United States Hospitals Carry dfrG and dfrK Resistance Genes and Succumb to Propargyl-Linked Antifolates.

Antibiotic resistance is a rapidly evolving health concern that requires a sustained effort to understand mechanisms of resistance and to develop new agents that overcome those mechanisms. The dihydrofolate reductase (DHFR) inhibitor, trimethoprim (TMP), remains one of the most important orally administered antibiotics. However, resistance through chromosomal mutations and mobile, plasmid-encoded insensitive DHFRs threatens the continued use of this agent. We are pursuing the development of new propargyl-linked antifolate (PLA) DHFR inhibitors designed to evade these mechanisms. While analyzing contemporary TMP-resistant clinical isolates of methicillin-resistant and sensitive Staphylococcus aureus, we discovered two mobile resistance elements, dfrG and dfrK. This is the first identification of these resistance mechanisms in the United States. These resistant organisms were isolated from a variety of infection sites, show clonal diversity, and each contain distinct resistance genotypes for common antibiotics. Several PLAs showed significant activity against these resistant strains by direct inhibition of the TMP resistance elements.

Propargyl-Linked Antifolates Are Potent Inhibitors of Drug-Sensitive and Drug-Resistant Mycobacterium tuberculosis.

Mycobacterium tuberculosis continues to cause widespread, life-threatening disease. In the last decade, this threat has grown dramatically as multi- and extensively-drug resistant (MDR and XDR) bacteria have spread globally and the number of agents that effectively treat these infections is significantly reduced. We have been developing the propargyl-linked antifolates (PLAs) as potent inhibitors of the essential enzyme dihydrofolate reductase (DHFR) from bacteria and recently found that charged PLAs with partial zwitterionic character showed improved mycobacterial cell permeability. Building on a hypothesis that these PLAs may penetrate the outer membrane of M. tuberculosis and inhibit the essential cytoplasmic DHFR, we screened a group of PLAs for antitubercular activity. In this work, we identified several PLAs as potent inhibitors of the growth of M. tuberculosis with several of the compounds exhibiting minimum inhibition concentrations equal to or less than 1 µg/mL. Furthermore, two of the compounds were very potent inhibitors of MDR and XDR strains. A high resolution crystal structure of one PLA bound to DHFR from M. tuberculosis reveals the interactions of the ligands with the target enzyme.

Charged Nonclassical Antifolates with Activity Against Gram-Positive and Gram-Negative Pathogens.

Although classical, negatively charged antifolates such as methotrexate possess high affinity for the dihydrofolate reductase (DHFR) enzyme, they are unable to penetrate the bacterial cell wall, rendering them poor antibacterial agents. Herein, we report a new class of charged propargyl-linked antifolates that capture some of the key contacts common to the classical antifolates while maintaining the ability to passively diffuse across the bacterial cell wall. Eight synthesized compounds exhibit extraordinary potency against Gram-positive S. aureus with limited toxicity against mammalian cells and good metabolic profile. High resolution crystal structures of two of the compounds reveal extensive interactions between the carboxylate and active site residues through a highly organized water network.