HighlightsSynthetic peptide display screen identifies a macrocyclic b-hairpin peptide antibiotic Symbah-1 kills through disrupting bacterial membranes, yet is not very hemolytic Symbah-1 loses activity in human serum, likely due to structural instability Structural optimization improves its serum activity by reducing its protease lability

Desiccation tolerance has been implicated as an important characteristic that potentiates the spread of the bacterial pathogen Acinetobacter baumannii on dry surfaces. Here we explore several factors influencing desiccation survival of A. baumannii. At the macroscale level, we find that desiccation tolerance is influenced by cell density and growth phase. A transcriptome analysis indicates that desiccation represents a unique state for A. baumannii compared to commonly studied growth phases and strongly influences pathways responsible for proteostasis. Remarkably, we find that an increase in total cellular protein aggregates, which is often considered deleterious, correlates positively with the ability of A. baumannii to survive desiccation. We show that inducing protein aggregate formation prior to desiccation increases survival and, importantly, that proteins incorporated into cellular aggregates can retain activity. Our results suggest that protein aggregates may promote desiccation tolerance in A. baumannii through preserving and protecting proteins from damage during desiccation until rehydration occurs.

The beta hairpin motif is a ubiquitous protein structural motif that can be found in molecules across the tree of life. This motif, which is also popular in synthetically designed proteins and peptides, is known for its stability and adaptability to broad functions. Here, we systematically probe all 49,000 unique beta hairpin substructures contained within the Protein Data Bank (PDB) to uncover key characteristics correlated with stable beta hairpin structure, including amino acid biases and enriched interstrand contacts. We find that position specific amino acid preferences, while seen throughout the beta hairpin structure, are most evident within the turn region, where they depend on subtle turn dynamics associated with turn length and secondary structure. We also establish a set of broad design principles, such as the inclusion of aspartic acid residues at a specific position and the careful consideration of desired secondary structure when selecting residues for the turn region, that can be applied to the generation of libraries encoding proteins or peptides containing beta hairpin structures.

Peptide macrocycles are a rapidly emerging class of therapeutic, yet the design of their structure and activity remains challenging. This is especially true for those with β-hairpin structure due to weak folding properties and a propensity for aggregation. Here, we use proteomic analysis and common antimicrobial features to design a large peptide library with macrocyclic β-hairpin structure. Using an activity-driven high-throughput screen, we identify dozens of peptides killing bacteria through selective membrane disruption and analyze their biochemical features via machine learning. Active peptides contain a unique constrained structure and are highly enriched for cationic charge with arginine in their turn region. Our results provide a synthetic strategy for structured macrocyclic peptide design and discovery while also elucidating characteristics important for β-hairpin antimicrobial peptide activity.

Influenza databases now contain over 100,000 worldwide sequence records for strains influenza A(H3N2) and A(H1N1). Although these data facilitate global research efforts and vaccine development practices, they also represent a stumbling block for researchers because of their confusing and heterogeneous annotation. Unclear passaging annotations are particularly concerning given the recent work highlighting the presence and risk of false adaptation signals introduced by cell passaging of viral isolates. With this in mind, we aim to provide a concise outline of why viruses are passaged, a clear overview of passaging annotation nomenclature currently in use, and suggestions for a standardized nomenclature going forward. Our hope is that this summary will empower researchers and clinicians alike to more easily understand a virus sample’s passage history when analyzing influenza sequences.