Evaluation of multidrug resistance patterns in siderophore-producing Pseudomonas aeruginosa from clinical and environmental samples in Gorgan, Iran

Unravelling the Distinctive Virulence Traits and Clonal Relationship among the Pseudomonas aeruginosa Isolates from Diabetic Patients

Infections with P. aeruginosa are three times more common in people with diabetes than in non-diabetic individuals. Investigations disclosing the distinguishing traits of P. aeruginosa strains to cause respiratory and wound infection in diabetics is limited. Wound swab and sputum from infected diabetic patients were used for the isolation of P. aeruginosa. The confirmed isolates were evaluated for their virulence factor production, antibiotic susceptibility, and clonal relationship. The study confirmed the increased virulence of sputum isolates characterized by their multidrug resistant nature, strong biofilm formation at 72h [(p<0.05) =0.003)] and 96h [(p<0.05) =0.002)] and elaboration of proteolytic enzymes (40.0%). Albeit the fact that wound isolates were less virulent than the sputum isolates, there was an increased siderophore production (77.0%). Nearly 90.0% of the isolates including sputum and wound were resistant to colistin. Random Amplified Polymorphic DNA analysis showed no distinct lineages of wound and sputum isolates. The study disclosed the higher prevalence of virulent P. aeruginosa in causing infection in the diabetics. No distinct lineages of the wound and sputum isolates indicated their ability to adapt to different host environments. To the best of our knowledge, this is the first study to show the difference in virulence traits among the P. aeruginosa strains isolated from sputum and wound of diabetic patients. Our study distinctly reveals the significance of periodic examination of antibiotic resistance and virulence factors of P. aeruginosa in order to recognize the possible co-regulatory mechanism involved in their expression.

Can We Arrest the Evolution of Antibiotic Resistance? The Differences between the Effects of Silver Nanoparticles and Silver Ions

Silver nanoparticles (AgNPs) are effective antimicrobial substances that show promise in combatting multidrug resistance. The potential application and release of AgNPs into the environment may neutralize the selective advantage of antibiotic resistance. Systemic knowledge regarding the effect of NPs on the evolution of antibiotic resistance is lacking. Our results showed that bacteria slowly developed adaptive tolerance to ciprofloxacin (CIP) under cyclic CIP and silver ion (Ag⁺) cotreatment, and no resistance/tolerance was discernible when CIP and AgNP exposure was alternated. In contrast, rapid CIP resistance was induced under continuous selection by treatment with only CIP. To combat the effects of CIP and Ag⁺, bacteria developed convergent evolutionary strategies with similar adaptive mechanisms, including anaerobic respiration transitioning (to reduce oxidative stress) and stringent response (to survive harsh environments). Alternating AgNP exposure impeded evolutionary resistance by accelerating B12-dependent folate and methionine cycles, which reestablished DNA synthesis and partially offset high oxidative stress levels, in contrast with the effect of CIP-directed evolutionary pressure. Nevertheless, CIP/AgNP treatment was ineffective in attenuating virulence, and CIP/Ag⁺ exposure even induced the virulence-critical type III secretion system. Our results increase the basic understanding of the impacts of NPs on evolutionary biology and suggest prospective nanotechnology applications for arresting evolutionary antibiotic resistance.

Polymicrobial Interactions in the Cystic Fibrosis Airway Microbiome Impact the Antimicrobial Susceptibility of Pseudomonas aeruginosa

Pseudomonas aeruginosa is one of the most dominant pathogens in cystic fibrosis (CF) airway disease and contributes to significant inflammation, airway damage, and poorer disease outcomes. The CF airway is now known to be host to a complex community of microorganisms, and polymicrobial interactions have been shown to play an important role in shaping P. aeruginosa pathogenicity and resistance. P. aeruginosa can cause chronic infections that once established are almost impossible to eradicate with antibiotics. CF patients that develop chronic P. aeruginosa infection have poorer lung function, higher morbidity, and a reduced life expectancy. P. aeruginosa adapts to the CF airway and quickly develops resistance to several antibiotics. A perplexing phenomenon is the disparity between in vitro antimicrobial sensitivity testing and clinical response. Considering the CF airway is host to a diverse community of microorganisms or 'microbiome' and that these microorganisms are known to interact, the antimicrobial resistance and progression of P. aeruginosa infection is likely influenced by these microbial relationships. This review combines the literature to date on interactions between P. aeruginosa and other airway microorganisms and the influence of these interactions on P. aeruginosa tolerance to antimicrobials.

SELfies and CELLfies: Whole Genome Sequencing and Annotation of Five Antibiotic Resistant Bacteria Isolated from the Surfaces of Smartphones, An Inquiry Based Laboratory Exercise in a Genomics Undergraduate Course at the Rochester Institute of Technology

Are touchscreen devices a public health risk for the transmission of pathogenic bacteria, especially those that are resistant to antibiotics? To investigate this, we embarked on a project aimed at isolating and identifying bacteria that are resistant to antibiotics from the screens of smartphones. Touchscreen devices have become ubiquitous in society, and it is important to evaluate the potential risks they pose towards public health, especially as it pertains to the harboring and transmission of pathogenic bacteria that are resistant to antibiotics. Sixteen bacteria were initially isolated of which five were unique (four Staphylococcus species and one Micrococcus species). The genomes of the five unique isolates were subsequently sequenced and annotated. The genomes were analyzed using in silico tools to predict the synthesis of antibiotics and secondary metabolites using the antibiotics and Secondary Metabolite Analysis SHell (antiSMASH) tool in addition to the presence of gene clusters that denote resistance to antibiotics using the Resistance Gene Identifier (RGI) tool. In vivo analysis was also done to assess resistance/susceptibility to four antibiotics that are commonly used in a research laboratory setting. The data presented in this manuscript is the result of a semester-long inquiry based laboratory exercise in the genomics course (BIOL340) in the Thomas H. Gosnell School of Life Sciences/College of Science at the Rochester Institute of Technology.