Phage-encoded cationic antimicrobial peptide used for outer membrane disruption in lysis

Abstract

Spanins are required for the last step in bacteriophage lysis: the disruption of the outer membrane. Bioinformatic analysis has shown that ~15% of phages lack a spanin gene, which suggests an alternate mechanism of outer membrane disruption. To address this, we selected virulent podophage ϕKT as a spaninless exemplar and tested ϕKT genes for outer membrane disruption during lysis. Hypothetical novel gene 28 causes outer membrane disruption when coexpressed with ϕKT lysis genes and complements the lysis defect of a λ spanin mutant. Gp28 is a 56 aa cationic peptide with predicted amphipathic helical structure and is associated with the particulate fraction after lysis. Urea and KCl washes did not release gp28 from the particulate, suggesting a strong hydrophobic interaction with the membrane. Super high-resolution microscopy supports a primarily outer membrane localization for the peptide. Additionally, holin function is not required for gp28-mediated lysis. Gp28 is similar in size, charge, predicted fold, and membrane association to the human cathelicidin antimicrobial peptide LL-37. In standard assays to measure bactericidal and inhibitory effects of antimicrobial peptides on bacterial cells, synthesized gp28 performed equivalently to LL-37. The studies presented here suggest that ϕKT gp28 disrupts bacterial outer membranes during lysis in a manner akin to antimicrobial peptides. SignificanceHere we provide evidence that ϕKT produces an antimicrobial peptide for outer membrane disruption during lysis. The disruptin is a new paradigm for phage lysis, and has no similarities to other known lysis genes. Many mechanisms have been proposed for the function of antimicrobial peptides, however there is not a consensus on the molecular basis of membrane disruption. Additionally, there is no established genetic selection system to support such studies. Therefore, the ϕKT disruptin may represent the first genetically tractable antimicrobial peptide.

Sequence-Function Relationships in Phage-Encoded Bacterial Cell Wall Lytic Enzymes and Their Implications for Phage-Derived Product Design

“…It was recently suggested that phages lacking spanins (spaninless phages) need additional gene products that behave similarly to AMPs to induce efficient host cell lysis ( 67 ). This hypothesis could also be extrapolated to the presence of AMP-like membrane-permeabilizing subdomains, which could then compensate for a missing spanin system.…”

“…There are indeed abundant examples in on May 2, 2021 by guest http://jvi.asm.org/ Downloaded from literature on the ability of G-lysins to interact with bacterial membranes and permeabilize them (33,38,39,69), a trait that, it is plausible to say both from our own analysis and the experimental results of many works, would reside in such AMP-like elements. It has been recently suggested that phages lacking spanins ('spaninless phages') need additional gene products that behave in a similar way to AMPs to induce efficient host cell lysis (70). This hypothesis could also be extrapolated to the presence of AMP-like, membrane permeabilizing subdomains, which could then compensate for a lacking spanin system.…”

VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

“…Viruses harbor vast potential for diverse genetic content, arrangement, and encoded functions [14][15][16][17]. Recognizing their genetic diversity, there has been substantial interest in "mining" these viral sequences for novel anti-microbial drug candidates, enzymes for biotechnological applications, and for bioremediation [18][19][20][21][22]. Recently, it has been appreciated that viruses may directly link biogeochemical cycling of nutrients by specifically driving metabolic processes [23][24][25][26][27].…”

VIBRANT: Automated recovery, annotation and curation of microbial viruses, and evaluation of virome function from genomic sequences

“…Annotations from all three databases are used to assemble 27 metrics for the neural network classifier. Briefly the metrics are as follows: [1] total proteins, [2] total KEGG annotations, [3] sum of KEGG v-scores, [4] total Pfam annotations, [5] sum of Pfam v-scores, [6] total VOG annotations, [7] sum of VOG v-scores, [8] total KEGG integration related annotations (e.g., integrase), [9] total KEGG annotations with a v-score of zero, [10] total KEGG integration related annotations (e.g., integrase), [11] total Pfam annotations with a v-score of zero, [12] total VOG redoxin (e.g., glutaredoxin) related annotations, [13] total VOG non-integrase integration related annotations, [14] total VOG integrase annotations, [15] total VOG ribonucleotide reductase related annotations, [16] total VOG nucleotide replication (e.g., DNA polymerase) related annotations, [17] total KEGG nuclease (e.g., restriction endonuclease) related annotations, [18] total KEGG toxin/anti-toxin related annotations, [19] total VOG hallmark protein (e.g., capsid) annotations, [20] total proteins annotated by KEGG, Pfam and VOG, [21] total proteins annotated by Pfam and VOG only, [22] total proteins annotated by Pfam and KEGG only, [23] total proteins annotated by KEGG and VOG only, [24] total proteins annotated by KEGG only, [25] total proteins annotated by Pfam only, [26] total proteins annotated by VOG only, and [27] total unannotated proteins. Non-annotation features such as gene density, average gene length and strand switching were not used because they were found to decrease performance of the neural network classifier despite being differentiating features between bacteria/archaea and viruses; viruses tend to have shorter genes, less intergenic space and strand switch less frequently.…”