Contact lens-related Pseudomonas aeruginosa keratitis in a 49-year-old woman

Complete genome sequence of Pseudomonas aeruginosa YK01, a sequence type 16 isolated from a patient with keratitis

OBJECTIVES

Pseudomonas aeruginosa, a Gram-negative opportunistic pathogen, is frequently associated with multidrug resistance and global epidemic outbreaks, contributing significantly to morbidity and mortality in hospitalized patients. However, P. aeruginosa belonging to the sequence type (ST) 16 was rarely reported. Here, this report presents the complete genome sequence of YK01, a ST16 P. aeruginosa isolate from a patient with keratitis. The complete reference genome of P. aeruginosa YK01 is expected to provide valuable data for investigating its genomic population, enhancing understanding of genetic basis of P. aeruginosa species complex.

DATA DESCRIPTION

A complete genome of 6.3 Mb was obtained for P. aeruginosa YK01 by combining Illumina 150-bp short reads and Nanopore long reads. The assembly is fully complete with chromosomal genome size of 6,183,266 bp, presenting a GC content of 66.7%, and a plasmid with the size of 46,067 bp, presenting GC content of 59.0%. Predicted chromosomal genomic features include 5,709 CDS, 12 rRNAs, 63 tRNAs, 4 ncRNAs, and 5,788 genes. To our knowledge, this genome data represents the first complete genome of P. aeruginosa ST16, providing crucial information for further comparative genome analysis.

Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp images

Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their diagnostic accuracy is low even for experienced ophthalmologists. To characterize the “face” of an infected cornea, we have adapted a deep learning architecture used for facial recognition and applied it to determine a probability score for a specific pathogen causing keratitis. To record the diverse features and mitigate the uncertainty, batches of probability scores of 4 serial images taken from many angles or fluorescence staining were learned for score and decision level fusion using a gradient boosting decision tree. A total of 4306 slit-lamp images including 312 images obtained by internet publications on keratitis by bacteria, fungi, acanthamoeba, and herpes simplex virus (HSV) were studied. The created algorithm had a high overall accuracy of diagnosis, e.g., the accuracy/area under the curve for acanthamoeba was 97.9%/0.995, bacteria was 90.7%/0.963, fungi was 95.0%/0.975, and HSV was 92.3%/0.946, by group K-fold validation, and it was robust to even the low resolution web images. We suggest that our hybrid deep learning-based algorithm be used as a simple and accurate method for computer-assisted diagnosis of infectious keratitis.

Pseudomonas aeruginosa-induced nociceptor activation increases susceptibility to infection

We report a rapid reduction in blink reflexes during in vivo ocular Pseudomonas aeruginosa infection, which is commonly attributed and indicative of functional neuronal damage. Sensory neurons derived in vitro from trigeminal ganglia (TG) were able to directly respond to P. aeruginosa but reacted significantly less to strains of P. aeruginosa that lacked virulence factors such as pili, flagella, or a type III secretion system. These observations led us to explore the impact of neurons on the host's susceptibility to P. aeruginosa keratitis. Mice were treated with Resiniferatoxin (RTX), a potent activator of Transient Receptor Potential Vanilloid 1 (TRPV1) channels, which significantly ablated corneal sensory neurons, exhibited delayed disease progression that was exemplified with decreased bacterial corneal burdens and altered neutrophil trafficking. Sensitization to disease was due to the increased frequencies of CGRP-induced ICAM-1+ neutrophils in the infected corneas and reduced neutrophil bactericidal activities. These data showed that sensory neurons regulate corneal neutrophil responses in a tissue-specific matter affecting disease progression during P. aeruginosa keratitis. Hence, therapeutic modalities that control nociception could beneficially impact anti-infective therapy.

Destruction of Pseudomonas aeruginosa pre-formed biofilms by cationic polymer micelles bearing silver nanoparticles

Pseudomonas aeruginosa is an opportunistic Gram-negative pathogen often associated with biofilm infections. This study evaluated the capacity for biofilm destruction of a novel combination of cationic polymer micelles formed from poly(2-(dimethylamino)ethyl methacrylate)-b-poly(ε-caprolactone)-b-poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA-PCL-PDMAEMA) triblock copolymer either alone, or loaded with silver nanoparticles (M_AgNPs). Pre-formed P. aeruginosa biofilms were incubated with either blank micelles, AgNO₃, or M_AgNPs. Biofilm biomass (crystal violet assay), metabolic activity (Alamar blue reduction), structure (SEM) and viability (CLSM after Live/Dead staining, or plating for CFU) were checked. The results showed that the micelles alone loosened the biofilm matrix, and caused some alterations in the bacterial surface. AgNO₃ killed the bacteria in situ leaving dead biofilm bacteria on the surface. M_AgNPs combined the two types of activities causing significant biofilm reduction, and alteration and death of biofilm bacteria. Therefore, the applied PDMAEMA-based micelles appear to be a successful candidate for the treatment of P. aeruginosa biofilm infections.