Charting the sequence-activity landscape of peptide inhibitors of translation termination

Sequence diversity of apidaecin-like peptides arresting the terminating ribosome

The Proline-rich Antimicrobial Peptide (PrAMP) apidaecin (Api) inhibits translation by binding in the ribosomal nascent peptide exit tunnel, trapping release factors RF1 or RF2, and arresting ribosomes at stop codons. To explore the extent of sequence variations of the native 18-amino acid Api that allows it to preserve its activity, we screened a library of synthetic mutant Api genes expressed in bacterial cells, resulting in nearly 350000 peptide variants with multiple substitutions. By applying orthogonal negative and positive selection strategies, we identified a number of multi-substituted Api variants capable of arresting ribosomes at stop codons. Our findings underscore the critical contribution of specific amino acid residues of the peptide for its on-target function while significantly expanding the variety of PrAMPs acting on the terminating ribosome. Additionally, some of the tested synthesized multi-substituted Api variants exhibit improved antibacterial activity compared to that of the wild type PrAMP and may constitute the starting point to develop clinically useful antimicrobials.

Multimodal binding and inhibition of bacterial ribosomes by the antimicrobial peptides Api137 and Api88

Proline-rich antimicrobial peptides (PrAMPs) inhibit bacterial protein biosynthesis by binding to the polypeptide exit tunnel (PET) near the peptidyl transferase center. Api137, an optimized derivative of honeybee PrAMP apidaecin, inhibits protein expression by trapping release factors (RFs), which interact with stop codons on ribosomes to terminate translation. This study uses cryo-EM, functional assays and molecular dynamic (MD) simulations to show that Api137 additionally occupies a second binding site near the exit of the PET and can repress translation independently of RF-trapping. Api88, a C-terminally amidated (-CONH2) analog of Api137 (-COOH), binds to the same sites, occupies a third binding pocket and interferes with the translation process presumably without RF-trapping. In conclusion, apidaecin-derived PrAMPs inhibit bacterial ribosomes by multimodal mechanisms caused by minor structural changes and thus represent a promising pool for drug development efforts.

Structure-Activity Relationships of the Antimicrobial Peptide Natural Product Apidaecin

With the growing crisis of antimicrobial resistance, it is critical to continue to seek out new sources of novel antibiotics. This need has led to renewed interest in natural product antimicrobials, specifically antimicrobial peptides. Nonlytic antimicrobial peptides are highly promising due to their unique mechanisms of action. One such peptide is apidaecin (Api), which inhibits translation termination through stabilization of the quaternary complex of the ribosome-apidaecin-tRNA-release factor. Synthetic derivatives of apidaecin have been developed, but structure-guided modifications have yet to be considered. In this work, we have focused on modifying key residues in the Api sequence that are responsible for the interactions that stabilize the quaternary complex. We present one of the first examples of a highly modified Api peptide that maintains its antimicrobial activity and interaction with the translation complex. These findings establish a starting point for further structure-guided optimization of Api peptides.

Inhibition of translation termination by the antimicrobial peptide Drosocin

The proline-rich antimicrobial peptide (PrAMP) Drosocin (Dro) from fruit flies shows sequence similarity to other PrAMPs that bind to the ribosome and inhibit protein synthesis by varying mechanisms. The target and mechanism of action of Dro, however, remain unknown. Here we show that Dro arrests ribosomes at stop codons, probably sequestering class 1 release factors associated with the ribosome. This mode of action is comparable to that of apidaecin (Api) from honeybees, making Dro the second member of the type II PrAMP class. Nonetheless, analysis of a comprehensive library of endogenously expressed Dro mutants shows that the interactions of Dro and Api with the target are markedly distinct. While only a few C-terminal amino acids of Api are critical for binding, the interaction of Dro with the ribosome relies on multiple amino acid residues distributed throughout the PrAMP. Single-residue substitutions can substantially enhance the on-target activity of Dro.

Optimization of the antimicrobial peptide Bac7 by deep mutational scanning

BACKGROUND

Intracellularly active antimicrobial peptides are promising candidates for the development of antibiotics for human applications. However, drug development using peptides is challenging as, owing to their large size, an enormous sequence space is spanned. We built a high-throughput platform that incorporates rapid investigation of the sequence-activity relationship of peptides and enables rational optimization of their antimicrobial activity. The platform is based on deep mutational scanning of DNA-encoded peptides and employs highly parallelized bacterial self-screening coupled to next-generation sequencing as a readout for their antimicrobial activity. As a target, we used Bac71-23, a 23 amino acid residues long variant of bactenecin-7, a potent translational inhibitor and one of the best researched proline-rich antimicrobial peptides.

RESULTS

Using the platform, we simultaneously determined the antimicrobial activity of >600,000 Bac71-23 variants and explored their sequence-activity relationship. This dataset guided the design of a focused library of ~160,000 variants and the identification of a lead candidate Bac7PS. Bac7PS showed high activity against multidrug-resistant clinical isolates of E. coli, and its activity was less dependent on SbmA, a transporter commonly used by proline-rich antimicrobial peptides to reach the cytosol and then inhibit translation. Furthermore, Bac7PS displayed strong ribosomal inhibition and low toxicity against eukaryotic cells and demonstrated good efficacy in a murine septicemia model induced by E. coli.

CONCLUSION

We demonstrated that the presented platform can be used to establish the sequence-activity relationship of antimicrobial peptides, and showed its usefulness for hit-to-lead identification and optimization of antimicrobial drug candidates.

Identifying Small Open Reading Frames in Prokaryotes with Ribosome Profiling

Small proteins encoded by open reading frames (ORFs) shorter than 50 codons (small ORFs [sORFs]) are often overlooked by annotation engines and are difficult to characterize using traditional biochemical techniques. Ribosome profiling has tremendous potential to empirically improve the annotations of prokaryotic genomes. Recent improvements in ribosome profiling methods for bacterial model organisms have revealed many new sORFs in well-characterized genomes. Antibiotics that trap ribosomes just after initiation have played a key role in these developments by allowing the unambiguous identification of the start codons (and, hence, the reading frame) for novel ORFs. Here, we describe these new methods and highlight critical controls and considerations for adapting ribosome profiling to different prokaryotic species.

A Platform for Deep Sequence-Activity Mapping and Engineering Antimicrobial Peptides

Developing potent antimicrobials, and platforms for their study and engineering, is critical as antibiotic resistance grows. A high-throughput method to quantify antimicrobial peptide and protein (AMP) activity across a broad continuum would be powerful to elucidate sequence-activity landscapes and identify potent mutants. Yet the complexity of antimicrobial activity has largely constrained the scope and mechanistic bandwidth of AMP variant analysis. We developed a platform to efficiently perform sequence-activity mapping of AMPs via depletion (SAMP-Dep): a bacterial host culture is transformed with an AMP mutant library, induced to intracellularly express AMPs, grown under selective pressure, and deep sequenced to quantify mutant depletion. The slope of mutant growth rate versus induction level indicates potency. Using SAMP-Dep, we mapped the sequence-activity landscape of 170 000 mutants of oncocin, a proline-rich AMP, for intracellular activity against Escherichia coli. Clonal validation supported the platform's sensitivity and accuracy. The mapped landscape revealed an extended oncocin pharmacophore contrary to earlier structural studies, clarified the C-terminus role in internalization, identified functional epistasis, and guided focused, successful synthetic peptide library design, yielding a mutant with 2-fold enhancement in both intracellular and extracellular activity. The efficiency of SAMP-Dep poises the platform to transform AMP engineering, characterization, and discovery.

The Multifaceted Roles of Proline in Cell Behavior

Herein, we review the multifaceted roles of proline in cell biology. This peculiar cyclic imino acid is: (i) A main precursor of extracellular collagens (the most abundant human proteins), antimicrobial peptides (involved in innate immunity), salivary proteins (astringency, teeth health) and cornifins (skin permeability); (ii) an energy source for pathogenic bacteria, protozoan parasites, and metastatic cancer cells, which engage in extracellular-protein degradation to invade their host; (iii) an antistress molecule (an osmolyte and chemical chaperone) helpful against various potential harms (UV radiation, drought/salinity, heavy metals, reactive oxygen species); (iv) a neural metabotoxin associated with schizophrenia; (v) a modulator of cell signaling pathways such as the amino acid stress response and extracellular signal-related kinase pathway; (vi) an epigenetic modifier able to promote DNA and histone hypermethylation; (vii) an inducer of proliferation of stem and tumor cells; and (viii) a modulator of cell morphology and migration/invasiveness. We highlight how proline metabolism impacts beneficial tissue regeneration, but also contributes to the progression of devastating pathologies such as fibrosis and metastatic cancer.

Identification of novel translated small ORFs in Escherichia coli using complementary ribosome profiling approaches

Small proteins of <51 amino acids are abundant across all domains of life but are often overlooked because their small size makes them difficult to predict computationally, and they are refractory to standard proteomic approaches. Ribosome profiling has been used to infer the existence of small proteins by detecting the translation of the corresponding open reading frames (ORFs). Detection of translated short ORFs by ribosome profiling can be improved by treating cells with drugs that stall ribosomes at specific codons. Here, we combine the analysis of ribosome profiling data for Escherichia coli cells treated with antibiotics that stall ribosomes at either start or stop codons. Thus, we identify ribosome-occupied start and stop codons with high sensitivity for ∼400 novel putative ORFs. The newly discovered ORFs are mostly short, with 365 encoding proteins of <51 amino acids. We validate translation of several selected short ORFs, and show that many likely encode unstable proteins. Moreover, we present evidence that most of the newly identified short ORFs are not under purifying selection, suggesting they do not impact cell fitness, although a small subset have the hallmarks of functional ORFs. IMPORTANCE Small proteins of <51 amino acids are abundant across all domains of life but are often overlooked because their small size makes them difficult to predict computationally, and they are refractory to standard proteomic approaches. Recent studies have discovered small proteins by mapping the location of translating ribosomes on RNA using a technique known as ribosome profiling. Discovery of translated sORFs using ribosome profiling can be improved by treating cells with drugs that trap initiating ribosomes. Here, we show that combining these data with equivalent data for cells treated with a drug that stalls terminating ribosomes facilitates the discovery of small proteins. We use this approach to discover 365 putative genes that encode small proteins in Escherichia coli.