Heterologous expression and optimization of the antimicrobial peptide acidocin 4356 in Komagataella phaffii to target Pseudomonas aeruginosa
Bibliographic record
Abstract
The increasing incidence of antibiotic-resistant bacteria signifies a major worldwide health concern, requiring the immediate exploration of new antimicrobial strategies (Chinemerem Nwobodo et al. 2022 ). Multidrug-resistant (MDR) pathogens, especially those belonging to the ESKAPE group ( Enterococcus faecium , Staphylococcus aureus , Klebsiella pneumoniae , Acinetobacter baumannii , Pseudomonas aeruginosa , and Enterobacter species), represent a substantial threat to public health due to their role in hospital-acquired infections that exhibit escalating resistance to multiple antibiotics (de Oliveira et al. 2020 ). P. aeruginosa has garnered significant attention due to its inherent resistance mechanisms, prominent biofilm development, and capacity to induce serious infections in immunocompromised individuals and patients using medical devices such as intravenous or urethral catheters (Ishizaki et al. 2023 ; Ostapska et al. 2022 ). These infections are notoriously challenging to treat and are associated with elevated morbidity and mortality rates. The worldwide ramifications of antimicrobial resistance (AMR) are significant, with projections indicating that by 2050, AMR may lead to 10 million fatalities per year (Angst et al. 2025 ; Diaz Caballero et al. 2023 ; Luo et al. 2022 ). This alarming trend highlights the urgent need to discover and develop novel antimicrobial agents (Xu et al. 2021 ). Antimicrobial peptides (AMPs) have emerged as promising alternatives in this context (Cao et al. 2018 ; Xuan et al. 2023 ). AMPs are naturally occurring molecules that form part of the innate immune systems of various organisms. They have broad-spectrum antibacterial activity, target bacterial membranes, and are less likely to induce resistance (Cao et al. 2018 ; Li et al. 2022 ). Their amphipathic and cationic characteristics enable significant contact with negatively charged bacterial membranes, frequently resulting in fast bactericidal activity (Chen et al. 2023 ; Hoelscher et al. 2022 ). Despite their therapeutic potential, AMPs present considerable barriers to widespread clinical application, owing to high manufacturing costs and the technical complexity involved in large-scale synthesis (Cao et al. 2018 ; Chaudhary et al. 2023 ). Conventional chemical synthesis methods, such as solid-phase peptide synthesis, can be prohibitively expensive, ranging from $100 to $600 per gram, and often face limitations with longer peptides and hydrophobic peptides (Chaudhary et al. 2023 ). Recombinant DNA (rDNA) technology offers a practical alternative, allowing for cost-effective, scalable production of AMPs in heterologous expression systems while preserving or even improving their biological properties via molecular engineering (Roca-Pinilla et al. 2022 ; Unver and Dagci 2024 ). Selecting an appropriate host system is critical to achieving high yields and functional integrity of rAMPs (Roca-Pinilla et al. 2022 ). Recombinant proteins have been produced using a variety of biological systems, including bacteria, yeast, and mammalian hosts (Berlec and Štrukelj 2013 ; Zhang et al. 2021 ). Escherichia coli has historically been the most commonly employed bacterial host due to its fast growth and well-defined genetics (Berlec and Strukelj 2013 ). However, AMPs’ intrinsic lethality to bacterial hosts and susceptibility to proteolytic degradation pose considerable hurdles (Berlec and Štrukelj 2013 ; Cao et al. 2018 ; Du et al. 2022 ). Although fusion protein techniques have been developed to mitigate toxicity and degradation, these efforts frequently produce inadequate yields, ranging from 1 to 30 mg/L (Cao et al. 2018 ). Yeast hosts, notably Komagataella phaffii (formerly Pichia pastoris ), have significant benefits over bacterial systems for rAMP generation. Furthermore, K. phaffii is resistant to AMP-mediated toxicity, allows for high cell-density fermentation, and has strong genetic stability (Unver and Dagci 2024 ). It is appealing for industrial-scale applications due to its effective secretion routes, which make downstream processing easier, and the FDA’s Generally Recognized as Safe (GRAS) designation (Unver and Dagci 2024 ). Additionally, K. phaffii can be grown in low-cost, nearly protein-free substrates, which lowers production costs and lowers the possibility of contamination (Unver and Dagci 2024 ). Crucially, the carbon supply tightly regulates the induction of the methanol-inducible alcohol oxidase 1 (AOX1) promoter in K. phaffii , which enables the high-level production of heterologous proteins. Protein production can be tailored to fulfill specific industrial needs based on the methanol utilization phenotype, which can be Mut + (methanol utilization plus), MutS (methanol utilization slow), or Mut − (methanol utilization minus) (Unver and Dagci 2024 ). Furthermore, the generation of functionally active recombinant peptides is guaranteed by the system’s ability to undergo post-translational changes (such as glycosylation and acylation) (Unver and Dagci 2024 ). In our prior research, we identified and characterized acidocin 4356 (ACD), an antimicrobial peptide isolated from Lactobacillus acidophilus ATCC 4356 (Modiri et al. 2020 ). ACD displayed potent activity against P. aeruginosa through membrane disruption, reduction of virulence factors, and effective biofilm degradation. Moreover, its stability under physiological conditions and minimal hemolytic activity underscore its potential as a therapeutic agent. However, the high cost and complexities of traditional AMP extraction motivate the pursuit of alternative production strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".