CATH-2-derived antimicrobial peptide inhibits multidrug-resistant Escherichia coli infection in chickens

Frontiers in Cellular and Infection Microbiology, Journal Year: 2024, Volume and Issue: 14

Published: May 15, 2024

Avian colibacillosis (AC), caused by infection with Escherichia coli ( E. ), is a major threat to poultry health, food safety and public results in high mortality significant economic losses. Currently, new drugs are urgently needed replace antibiotics due the continuous emergence increasing resistance of multidrug-resistant (MDR) strains irrational use agriculture animal husbandry. In recent years, antimicrobial peptides (AMPs), which uniquely evolved protect host, have emerged as leading alternative clinical settings. CATH-2, member cathelicidin peptide family, has been reported antibacterial activity. To enhance potency reduce adverse effects on animals, we designed five novel AMPs, named C2-1, C2-2, C2-3, C2-4 C2-5, based chicken secondary structures these AMPs were consistently α-helical had an altered net charge hydrophobicity compared those CATH-2 (1-15) sequences. Subsequently, activities against MDR evaluated vitro . Specifically, C2-2 showed excellent activity either ATCC standard strain or veterinary isolates , concentrations ranging from 2-8 μ g/mL. Furthermore, maintained its strong efficacy under temperature saline conditions, demonstrating stability. Similarly, retained level no hemolytic mature red blood cells cytotoxicity kidney over concentration range 0-64 Moreover, administration improved survival rate reduced bacterial load heart, liver spleen during chickens. Additionally, pathological damage intestine was prevented when infected chickens treated C2-2. Together, our study that may be promising therapeutic agent for treatment infections AC.

Language: Английский

---

Green algae-produced multimer cathelicidin-RC1 disrupts membrane integrity for inhibiting bacterial growth

Process Biochemistry, Journal Year: 2024, Volume and Issue: 146, P. 1 - 12

Published: July 3, 2024

Language: Английский

---

Evaluation of the Antibacterial Potential of Two Short Linear Peptides YI12 and FK13 against Multidrug-Resistant Bacteria

Pathogens, Journal Year: 2024, Volume and Issue: 13(9), P. 797 - 797

Published: Sept. 14, 2024

The accelerating spread of antibiotic resistance has significantly weakened the clinical efficacy existing antibiotics, posing a severe threat to public health. There is an urgent need develop novel antimicrobial alternatives that can bypass mechanisms and effectively kill multidrug-resistant (MDR) pathogens. Antimicrobial peptides (AMPs) are one most promising candidates treat MDR pathogenic infections since they display broad-spectrum activities less prone achieve drug resistance. In this study, we investigated antibacterial capability two machine learning-driven linear peptide compounds termed YI12 FK13. We reveal FK13 exhibit properties against clinically significant bacterial pathogens, inducing no or minimal hemolysis in mammalian red blood cells. further ascertain resilient heat acid-base conditions, susceptibility hydrolytic enzymes divalent cations under physiological conditions. Initial mechanistic investigations compromise membrane integrity, leading potential dissipation excessive reactive oxygen species (ROS) generation. Collectively, our findings highlight prospective utility these cationic amphiphilic as agents.

Language: Английский

---

APPLICATION OF ANTIMICROBIAL PEPTIDES IN THE POULTRY INDUSTRY

Veterinary Microbiology, Journal Year: 2024, Volume and Issue: 298, P. 110267 - 110267

Published: Sept. 27, 2024

Language: Английский

---

Multi-Objective Optimization Accelerates the De Novo Design of Antimicrobial Peptide for Staphylococcus aureus

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(24), P. 13688 - 13688

Published: Dec. 21, 2024

Humans have long used antibiotics to fight bacteria, but increasing drug resistance has reduced their effectiveness. Antimicrobial peptides (AMPs) are a promising alternative with natural broad-spectrum activity against bacteria and viruses. However, instability hemolysis limit medical use, making the design improvement of AMPs key research focus. Designing antimicrobial multiple desired properties using machine learning is still challenging, especially limited data. This study utilized multi-objective optimization method, non-dominated sorting genetic algorithm II (NSGA-II), enhance physicochemical peptide sequences identify those improved activity. Combining NSGA-II neural networks, approach efficiently identified AMP candidates accurately predicted antibacterial method significantly advances by optimizing factors like hydrophobicity, index, aliphatic index improve stability. It offers more efficient way address limitations AMPs, paving for development safer effective treatments.

Language: Английский

---