Antimicrobial and antibiofilm activity and machine learning classification analysis of essential oils from different mediterranean plants against pseudomonas aeruginosa

Pseudomonas aeruginosa is a ubiquitous organism and opportunistic pathogen that can cause persistent infections due to its peculiar antibiotic resistance mechanisms and to its ability to adhere and form biofilm. The interest in the development of new approaches for the prevention and treatment of biofilm formation has recently increased. The aim of this study was to seek new non-biocidal agents able to inhibit biofilm formation, in order to counteract virulence rather than bacterial growth and avoid the selection of escape mutants. Herein, different essential oils extracted from Mediterranean plants were analyzed for their activity againstP. aeruginosa. Results show that they were able to destabilize biofilm at very low concentration without impairing bacterial viability. Since the action is not related to a bacteriostatic/bactericidal activity onP. aeruginosa, the biofilm change of growth in presence of the essential oils was possibly due to a modulation of the phenotype. To this aim, application of machine learning algorithms led to the development of quantitative activity-composition relationships classification models that allowed to direct point out those essential oil chemical components more involved in the inhibition of biofilm production. The action of selected essential oils on sessile phenotype make them particularly interesting for possible applications such as prevention of bacterial contamination in the community and in healthcare environments in order to prevent human infections. We assayed 89 samples of different essential oils asP. aeruginosaanti-biofilm. Many samples inhibitedP. aeruginosabiofilm at concentrations as low as 48.8 µg/mL. Classification of the models was developed through machine learning algorithms

Essential oils against bacterial isolates from cystic fibrosis patients by means of antimicrobial and unsupervised machine learning approaches

Recurrent and chronic respiratory tract infections in cystic fibrosis (CF) patients result in progressive lung damage and represent the primary cause of morbidity and mortality. Staphylococcus aureus (S. aureus) is one of the earliest bacteria in CF infants and children. Starting from early adolescence, patients become chronically infected with Gram-negative non-fermenting bacteria, and Pseudomonas aeruginosa (P. aeruginosa) is the most relevant and recurring. Intensive use of antimicrobial drugs to fight lung infections inevitably leads to the onset of antibiotic resistant bacterial strains. New antimicrobial compounds should be identified to overcome antibiotic resistance in these patients. Recently interesting data were reported in literature on the use of natural derived compounds that inhibited in vitro S. aureus and P. aeruginosa bacterial growth. Essential oils, among these, seemed to be the most promising. In this work is reported an extensive study on 61 essential oils (EOs) against a panel of 40 clinical strains isolated from CF patients. To reduce the in vitro procedure and render the investigation as convergent as possible, machine learning clusterization algorithms were firstly applied to pick-up a fewer number of representative strains among the panel of 40. This approach allowed us to easily identify three EOs able to strongly inhibit bacterial growth of all bacterial strains. Interestingly, the EOs antibacterial activity is completely unrelated to the antibiotic resistance profile of each strain. Taking into account the results obtained, a clinical use of EOs could be suggested

Antarctic Marine Bacteria as a Source of Anti-Biofilm Molecules to Combat ESKAPE Pathogens

: The ESKAPE pathogens, including bacteria such as Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species, pose a global health threat due to their ability to resist antimicrobial drugs and evade the immune system. These pathogens are responsible for hospital-acquired infections, especially in intensive care units, and contribute to the growing problem of multi-drug resistance. In this study, researchers focused on exploring the potential of Antarctic marine bacteria as a source of anti-biofilm molecules to combat ESKAPE pathogens. Four Antarctic bacterial strains were selected, and their cell-free supernatants were tested against 60 clinical ESKAPE isolates. The results showed that the supernatants did not exhibit antimicrobial activity but effectively prevented biofilm formation and dispersed mature biofilms. This research highlights the promising potential of Antarctic bacteria in producing compounds that can counteract biofilms formed by clinically significant bacterial species. These findings contribute to the development of new strategies for preventing and controlling infections caused by ESKAPE pathogens

Essential oils biofilm modulation activity, chemical and machine learning analysis. Application on staphylococcus aureus isolates from cystic fibrosis patients

Bacterial biofilm plays a pivotal role in chronic Staphylococcus aureus (S. aureus) infection and its inhibition may represent an important strategy to develop novel therapeutic agents. The scientific community is continuously searching for natural and “green alternatives” to chemotherapeutic drugs, including essential oils (EOs), assuming the latter not able to select resistant strains, likely due to their multicomponent nature and, hence, multitarget action. Here it is reported the biofilm production modulation exerted by 61 EOs, also investigated for their antibacterial activity on S. aureus strains, including reference and cystic fibrosis patients’ isolated strains. The EOs biofilm modulation was assessed by Christensen method on five S. aureus strains. Chemical composition, investigated by GC/MS analysis, of the tested EOs allowed a correlation between biofilm modulation potency and putative active components by means of machine learning algorithms application. Some EOs inhibited biofilm growth at 1.00% concentration, although lower concentrations revealed dierent biological profile. Experimental data led to select antibiofilm EOs based on their ability to inhibit S. aureus biofilm growth, which were characterized for their ability to alter the biofilm organization by means of SEM studies

Characterization of Scardovia wiggsiae biofilm by original scanning electron microscopy protocol

Early childhood caries (ECC) is a severe manifestation of carious pathology with rapid and disruptive progression. The ECC microbiota includes a wide variety of bacterial species, among which is an anaerobic newly named species, Scardovia wiggsiae, a previously unidentified Bifidobacterium. Our aim was to provide the first ultrastructural characterization of S. wiggsiae and its biofilm by scanning electron microscopy (SEM) using a protocol that faithfully preserved the biofilm architecture and allowed an investigation at very high magnifications (order of nanometers) and with the appropriate resolution. To accomplish this task, we analyzed Streptococcus mutans’ biofilm by conventional SEM and VP-SEM protocols, in addition, we developed an original procedure, named OsO4-RR-TA-IL, which avoids dehydration, drying and sputter coating. This innovative protocol allowed high-resolution and high-magnification imaging (from 10000× to 35000×) in high-vacuum and high-voltage conditions. After comparing three methods, we chose OsO4-RR-TA-IL to investigate S. wiggsiae. It appeared as a fusiform elongated bacterium, without surface specialization, arranged in clusters and submerged in a rich biofilm matrix, which showed a well-developed micro-canalicular system. Our results provide the basis for the development of innovative strategies to quantify the effects of different treatments, in order to establish the best option to counteract ECC in pediatric patients

Serratiopeptidase affects the physiology of pseudomonas aeruginosa isolates from cystic fibrosis patients

Pseudomonas aeruginosa is frequently involved in cystic fibrosis (CF) airway infections. Biofilm, motility, production of toxins and the invasion of host cells are different factors that increase P. aeruginosa's virulence. The sessile phenotype offers protection to bacterial cells and resistance to antimicrobials and host immune attacks. Motility also contributes to bacterial colonization of surfaces and, consequently, to biofilm formation. Furthermore, the ability to adhere is the prelude for the internalization into lung cells, a common immune evasion mechanism used by most intracellular bacteria, such as P. aeruginosa. In previous studies we evaluated the activity of metalloprotease serratiopeptidase (SPEP) in impairing virulence-related properties in Gram-positive bacteria. This work aimed to investigate SPEP's effects on different physiological aspects related to the virulence of P. aeruginosa isolated from CF patients, such as biofilm production, pyoverdine and pyocyanin production and invasion in alveolar epithelial cells. Obtained results showed that SPEP was able to impair the attachment to inert surfaces as well as adhesion/invasion of eukaryotic cells. Conversely, SPEP's effect on pyocyanin and pyoverdine production was strongly strain-dependent, with an increase and/or a decrease of their production. Moreover, SPEP seemed to increase swarming motility and staphylolytic protease production. Our results suggest that a large number of clinical strains should be studied in-depth before drawing definitive conclusions. Why different strains sometimes react in opposing ways to a specific treatment is of great interest and will be the object of future studies. Therefore, SPEP affects P. aeruginosa's physiology by differently acting on several bacterial factors related to its virulence

Anti-Virulence Properties of Coridothymus capitatus Essential Oil against Pseudomonas aeruginosa Clinical Isolates from Cystic Fibrosis Patients

Pseudomonas aeruginosa is an opportunistic pathogen responsible for nosocomial infections, and is often involved in airway infections of cystic fibrosis (CF) patients. P. aeruginosa virulence is related to its ability to form biofilm, trigger different types of motilities, and produce toxins (for example, bacterial pigments). In this scenario, essential oils (EOs) have gained notoriety for their role in phenotype modulation, including virulence modulation. Among different EOs previously analyzed, herein we investigated the activity of Coridothymus capitatus EO (CCEO) against specific virulence factors produced by P. aeruginosa isolated from CF patients. CCEO showed inhibition of new biofilm formation and reduction in mature biofilm in about half of the tested strains. On selected strains, SEM analysis provided interesting information regarding CCEO action in a pre-adhesion assay. CCEO treatment showed a dramatic modification of the extracellular matrix (ECM) structure. Our results clearly showed a drastic reduction in pyocyanin production (between 84% and 100%) for all tested strains in the presence of CCEO. Finally, CCEO was also able to strongly affect P. aeruginosa swarming and swimming motility for almost all tested strains. In consideration of the novel results obtained on clinical strains isolated from CF patients, CCEO may be a potential candidate to limit P. aeruginosa virulence

Cold-adapted bacterial extracts as source of anti-infective and antimicrobial compounds against Staphylococcus aureus

Aim: The dramatic emergence of antibiotic resistance has directed the interest of research toward the discovery of novel antimicrobial molecules. In this context, cold-adapted marine bacteria living in polar regions represent an untapped reservoir of biodiversity endowed with an interesting chemical repertoire. The aim of this work was to identify new antimicrobials and/or antibiofilm molecules produced by cold-adapted bacteria. Materials & methods: Organic extracts obtained from polar marine bacteria were tested against Staphylococcus aureus. Most promising samples were subjected to suitable purification strategies. Results: Results obtained led to the identification of a novel lipopeptide able to effectively inhibit the biofilm formation of S. aureus. Conclusion: New lipopeptide may be potentially useful in a wide variety of biotechnological and medical applications

Machine Learning Analyses on Data including Essential Oil Chemical Composition and In Vitro Experimental Antibiofilm Activities against Staphylococcus Species

Biofilm resistance to antimicrobials is a complex phenomenon, driven not only by genetic mutation induced resistance, but also by means of increased microbial cell density that supports horizontal gene transfer across cells. The prevention of biofilm formation and the treatment of existing biofilms is currently a difficult challenge; therefore, the discovery of new multi-targeted or combinatorial therapies is growing. The development of anti-biofilm agents is considered of major interest and represents a key strategy as non-biocidal molecules are highly valuable to avoid the rapid appearance of escape mutants. Among bacteria, staphylococci are predominant causes of biofilm-associated infections. Staphylococci, especially Staphylococcus aureus (S. aureus) is an extraordinarily versatile pathogen that can survive in hostile environmental conditions, colonize mucous membranes and skin, and can cause severe, non-purulent, toxin-mediated diseases or invasive pyogenic infections in humans. Staphylococcus epidermidis (S. epidermidis) has also emerged as an important opportunistic pathogen in infections associated with medical devices (such as urinary and intravascular catheters, orthopaedic implants, etc.), causing approximately from 30% to 43% of joint prosthesis infections. The scientific community is continuously looking for new agents endowed of anti-biofilm capabilities to fight S. aureus and S epidermidis infections. Interestingly, several reports indicated in vitro efficacy of non-biocidal essential oils (EOs) as promising treatment to reduce bacterial biofilm production and prevent the inducing of drug resistance. In this report were analyzed 89 EOs with the objective of investigating their ability to modulate bacterial biofilm production of different S. aureus and S. epidermidis strains. Results showed the assayed EOs to modulated the biofilm production with unpredictable results for each strain. In particular, many EOs acted mainly as biofilm inhibitors in the case of S. epidermidis strains, while for S. aureus strains, EOs induced either no effect or stimulate biofilm production. In order to elucidate the obtained experimental results, machine learning (ML) algorithms were applied to the EOs’ chemical compositions and the determined associated anti-biofilm potencies. Statistically robust ML models were developed, and their analysis in term of feature importance and partial dependence plots led to indicating those chemical components mainly responsible for biofilm production, inhibition or stimulation for each studied strain, respectively

Essential Oils Biofilm Modulation Activity and Machine Learning Analysis on <i>Pseudomonas aeruginosa</i> Isolates from Cystic Fibrosis Patients

The opportunistic pathogen Pseudomonas aeruginosa is often involved in airway infections of cystic fibrosis (CF) patients. It persists in the hostile CF lung environment, inducing chronic infections due to the production of several virulence factors. In this regard, the ability to form a biofilm plays a pivotal role in CF airway colonization by P. aeruginosa. Bacterial virulence mitigation and bacterial cell adhesion hampering and/or biofilm reduced formation could represent a major target for the development of new therapeutic treatments for infection control. Essential oils (EOs) are being considered as a potential alternative in clinical settings for the prevention, treatment, and control of infections sustained by microbial biofilms. EOs are complex mixtures of different classes of organic compounds, usually used for the treatment of upper respiratory tract infections in traditional medicine. Recently, a wide series of EOs were investigated for their ability to modulate biofilm production by different pathogens comprising S. aureus, S. epidermidis, and P. aeruginosa strains. Machine learning (ML) algorithms were applied to develop classification models in order to suggest a possible antibiofilm action for each chemical component of the studied EOs. In the present study, we assessed the biofilm growth modulation exerted by 61 commercial EOs on a selected number of P. aeruginosa strains isolated from CF patients. Furthermore, ML has been used to shed light on the EO chemical components likely responsible for the positive or negative modulation of bacterial biofilm formation