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Acinetobacter baumannii is a gram-negative bacterium that causes hospital-acquired and opportunistic infections, resulting in pneumonia, sepsis, and severe wound infections that can be difficult to treat due to antimicrobial resistance and the formation of biofilms. There is an urgent need to develop novel antimicrobials to tackle the rapid increase in antimicrobial resistance, and antimicrobial peptides (AMPs) represent an additional class of potential agents with direct antimicrobial and/or host-defense activating activities. In this study, we present GATR-3, a synthetic, designed AMP that was modified from a cryptic peptide discovered in American alligator, as our lead peptide to target multidrug-resistant (MDR) A. baumannii. Antimicrobial susceptibility testing and antibiofilm assays were performed to assess GATR-3 against a panel of 8 MDR A. baumannii strains, including AB5075 and some clinical strains. The GATR-3 mechanism of action was determined to be via loss of membrane integrity as measured by DiSC3(5) and ethidium bromide assays. GATR-3 exhibited potent antimicrobial activity against all tested multidrug-resistant A. baumannii strains with rapid killing. Biofilms are difficult to treat and eradicate. Excitingly, GATR-3 inhibited biofilm formation and, more importantly, eradicated preformed biofilms of MDR A. baumannii AB5075, as evidenced by MBEC assays and scanning electron micrographs. GATR3 did not induce resistance in MDR A. baumannii, unlike colistin. Additionally, the toxicity of GATR-3 was evaluated using human red blood cells, HepG2 cells, and waxworms using hemolysis and MTT assays. GATR-3 demonstrated little to no cytotoxicity against HepG2 and red blood cells, even at 100 μg/mL. GATR-3 injection showed little toxicity in the waxworm model, resulting in a 90% survival rate. The therapeutic index of GATR-3 was estimated (based on the HC50/MIC against human RBCs) to be 1250. Overall, GATR-3 is a promising candidate to advance to preclinical testing to potentially treat MDR A. baumannii infections. [ABSTRACT FROM AUTHOR]

The discovery of new antimicrobials is necessary to combat multidrug-resistant (MDR) bacteria, especially those that infect wounds and form prodigious biofilms, such as Acinetobacter baumannii. Antimicrobial peptides (AMPs) are a promising class of new therapeutics against drug-resistant bacteria, including gram-negatives. Here, we utilized a computational AMP design strategy combining database filtering technology plus positional analysis to design a series of novel peptides, named HRZN, designed to be active against A. baumannii. All of the HRZN peptides we synthesized exhibited antimicrobial activity against three MDR A. baumannii strains with HRZN-15 being the most active (MIC 4 µg/mL). This peptide also inhibited and eradicated biofilm of A. baumannii strain AB5075 at 8 and 16 µg/mL, which is highly effective. HRZN-15 permeabilized and depolarized the membrane of AB5075 rapidly, as demonstrated by the killing kinetics. HRZN 13 and 14 peptides had little to no hemolysis activity against human red blood cells, whereas HRZN-15, -16, and -17 peptides demonstrated more significant hemolytic activity. HRZN-15 also demonstrated toxicity to waxworms. Further modification of HRZN-15 could result in a new peptide with an improved toxicity profile. Overall, we successfully designed a set of new AMPs that demonstrated activity against MDR A. baumannii using a computational approach. [ABSTRACT FROM AUTHOR]

Antimicrobial peptides (AMPs) are ubiquitous amongst living organisms and are part of the innate immune system with the ability to kill pathogens directly or indirectly by modulating the immune system. AMPs have potential as a novel therapeutic against bacteria due to their quick-acting mechanism of action that prevents bacteria from developing resistance. Additionally, there is a dire need for therapeutics with activity specifically against Gram-negative bacterial infections that are intrinsically difficult to treat, with or without acquired drug resistance. Development of new antibiotics has slowed in recent years and novel therapeutics (like AMPs) with a focus against Gram-negative bacteria are needed. We designed eight novel AMPs, termed PHNX peptides, using ab initio computational design (database filtering technology combined with the novel positional analysis on APD3 dataset of AMPs with activity against Gram-negative bacteria) and assessed their theoretical function using published machine learning algorithms, and finally, validated their activity in our laboratory. These AMPs were tested to establish their minimum inhibitory concentration (MIC) and half-maximal effective concentration (EC50) under CLSI methodology against antibiotic resistant and antibiotic susceptible Escherichia coli and Staphylococcus aureus. Laboratory-based experimental results were compared to computationally predicted activities for each of the peptides to ascertain the accuracy of the computational tools used. PHNX-1 demonstrated antibacterial activity (under high and low-salt conditions) against antibiotic resistant and susceptible strains of Gram-positive and Gram-negative bacteria and PHNX-4 to -8 demonstrated low-salt antibacterial activity only. The AMPs were then evaluated for cytotoxicity using hemolysis against human red blood cells and demonstrated some hemolysis which needs to be further evaluated. In this study, we successfully developed a design methodology to create synthetic AMPs with a narrow spectrum of activity where the PHNX AMPs demonstrated higher antibacterial activity against Gram-negative bacteria compared to Gram-positive bacteria. Thus, these peptides present novel synthetic peptides with a potential for therapeutic use. Based on our findings, we propose upfront selection of the peptide dataset for analysis, an additional step of positional analysis to add to the ab initio database filtering technology (DFT) method, and we present laboratory data on the novel, synthetically designed AMPs to validate the results of the computational approach. We aim to conduct future in vivo studies which could establish these AMPs for clinical use. [ABSTRACT FROM AUTHOR]

Acinetobacter baumannii is a gram-negative bacterium that causes hospital-acquired and opportunistic infections, resulting in pneumonia, sepsis, and severe wound infections that can be difficult to treat due to antimicrobial resistance and the formation of biofilms. There is an urgent need to develop novel antimicrobials to tackle the rapid increase in antimicrobial resistance, and antimicrobial peptides (AMPs) represent an additional class of potential agents with direct antimicrobial and/or host-defense activating activities. In this study, we present GATR-3, a synthetic, designed AMP that was modified from a cryptic peptide discovered in American alligator, as our lead peptide to target multidrug-resistant (MDR) A. baumannii . Antimicrobial susceptibility testing and antibiofilm assays were performed to assess GATR-3 against a panel of 8 MDR A. baumannii strains, including AB5075 and some clinical strains. The GATR-3 mechanism of action was determined to be via loss of membrane integrity as measured by DiSC 3 (5) and ethidium bromide assays. GATR-3 exhibited potent antimicrobial activity against all tested multidrug-resistant A. baumannii strains with rapid killing. Biofilms are difficult to treat and eradicate. Excitingly, GATR-3 inhibited biofilm formation and, more importantly, eradicated preformed biofilms of MDR A. baumannii AB5075, as evidenced by MBEC assays and scanning electron micrographs. GATR3 did not induce resistance in MDR A. baumannii , unlike colistin. Additionally, the toxicity of GATR-3 was evaluated using human red blood cells, HepG2 cells, and waxworms using hemolysis and MTT assays. GATR-3 demonstrated little to no cytotoxicity against HepG2 and red blood cells, even at 100 μg/mL. GATR-3 injection showed little toxicity in the waxworm model, resulting in a 90% survival rate. The therapeutic index of GATR-3 was estimated (based on the HC 50 /MIC against human RBCs) to be 1250. Overall, GATR-3 is a promising candidate to advance to preclinical testing to potentially treat MDR A. baumannii infections.

Low-molecular weight (LMW) thiols, encompassing peptides and small proteins with active cysteine residue(s), are important to bacteria as they are involved in a wide range of redox reactions. They include the tripeptide glutathione (GSH) and the small redox proteins, thioredoxins and glutaredoxins. We review the low MW thiols and related molecules in Francisella species and what role they may play in growth and virulence. Genes for GSH biosynthesis, metabolism and thioredoxins are present in all strains of Francisella , including the fully human-virulent strains. GSH and cysteine (CSH) are the major LMW thiols in Francisella extracts. We explore the potential role of the LMW thiols to overcome the nutritional challenges of intracellular growth (high GSH conditions) as well as the nutritional challenges of planktonic growth (low GSH conditions), and their contribution to Francisella' s sensing its environmental location. Francisella may also use GSH as a source of CSH, for which it is auxotrophic. "Glutathione stealing" from the host may be an important part of Francisella 's success strategy as a facultative intracellular pathogen both to detect its location and obtain CSH. An understanding of GSH metabolism in Francisella provides insights into the interaction of this pathogen with its host and may reveal additional targets for therapeutic intervention for tularemia infections., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Antibiotic resistance constitutes a global threat and could lead to a future pandemic. One strategy is to develop a new generation of antimicrobials. Naturally occurring antimicrobial peptides (AMPs) are recognized templates and some are already in clinical use. To accelerate the discovery of new antibiotics, it is useful to predict novel AMPs from the sequenced genomes of various organisms. The antimicrobial peptide database (APD) provided the first empirical peptide prediction program. It also facilitated the testing of the first machine-learning algorithms. This chapter provides an overview of machine-learning predictions of AMPs. Most of the predictors, such as AntiBP, CAMP, and iAMPpred, involve a single-label prediction of antimicrobial activity. This type of prediction has been expanded to antifungal, antiviral, antibiofilm, anti-TB, hemolytic, and anti-inflammatory peptides. The multiple functional roles of AMPs annotated in the APD also enabled multi-label predictions (iAMP-2L, MLAMP, and AMAP), which include antibacterial, antiviral, antifungal, antiparasitic, antibiofilm, anticancer, anti-HIV, antimalarial, insecticidal, antioxidant, chemotactic, spermicidal activities, and protease inhibiting activities. Also considered in predictions are peptide posttranslational modification, 3D structure, and microbial species-specific information. We compare important amino acids of AMPs implied from machine learning with the frequently occurring residues of the major classes of natural peptides. Finally, we discuss advances, limitations, and future directions of machine-learning predictions of antimicrobial peptides. Ultimately, we may assemble a pipeline of such predictions beyond antimicrobial activity to accelerate the discovery of novel AMP-based antimicrobials., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)