Porphyromonas, a potential predictive biomarker ofPseudomonas aeruginosapulmonary infection in cystic fibrosis

Abstract

IntroductionPseudomonas aeruginosa pulmonary infections are the primary cause of morbi-mortality in patients with cystic fibrosis (CF). In this cohort study, the objective was to identify candidate biomarkers of P. aeruginosa infection within the airway microbiota.MethodsA 3-year prospective multicentre study (PYOMUCO study) was conducted in Western France and included patients initially P. aeruginosa free for at least 1 year. A 16S-targeted metagenomics approach was applied on iterative sputum samples of a first set of patients (n=33). The composition of airway microbiota was compared according to their P. aeruginosa status at the end of the follow-up (colonised vs non-colonised), and biomarkers associated with P. aeruginosa were screened. In a second step, the distribution of a candidate biomarker according to the two groups of patients was verified by qPCR on a second set of patients (n=52) coming from the same cohort and its load quantified throughout the follow-up.ResultsPorphyromonas (mainly P. catoniae) was found to be an enriched phylotype in patients uninfected by P. aeruginosa (p<0.001). This result was confirmed by quantitative PCR. Conversely, in patients who became P. aeruginosa-positive, P. catoniae significantly decreased before P. aeruginosa acquisition (p=0.014).DiscussionFurther studies on replication cohorts are needed to validate this potential predictive biomarker, which may be relevant for the follow-up in the early years of patients with CF. The identification of infection candidate biomarkers may offer new strategies for CF precision medicine.

Analysis of airway microbiota in adults from a Brazilian cystic fibrosis center

“…We highlight the presence of anaerobes in the microbiota of four of the five patients (occurring in most of the samples from patients A, B, D and E), being represented by the genera Veillonella, Prevotella, and Fusobacterium. Although the role of anaerobes in pulmonary disease in CF remains unclear, some studies showed that this group contributes to the transf e r e n c e o f a n t i b i o t i c r e s i s t a n c e g e n e s b e t w e e n microrganisms-while producing quorum sensing molecules that regulate the interspecies mediation pathways [34], and also attributed anaerobes to influence virulence characteristics in pathogens such as P. aeruginosa [35] or as potential predictive biomarkers in CF pulmonary infections such as for Porphyromonas catoniae [1].…”

“…Chronic infection of the lower airways is the major cause of morbidity and reduced survival in cystic fibrosis (CF) patients. The progression of pulmonary disease is associated with a complex respiratory microbiota that experiences an increased worsening and succession of the infecting microorganisms [1]. Bacterial infections in the airways of these patients should be monitored not only to follow disease progression but also for therapeutic interventions that may improve the quality of life and life expectancy of the patient [2,3].…”

The Microbiome in Cystic Fibrosis Pulmonary Disease

“…The CF pulmonary microbiome shows overrepresentation of Proteobacteria and Actinobacteria [72]. The core microbiome comprises Streptococcus, Prevotella, Veillonella, Rothia, Actinomyces, Gemella, Granulicatella, Fusobacterium, Neisseria, Atopobium, and Porphyromonas [23,[76][77][78], with variations in other taxa [22]. Notably, anaerobics are fewer than in non-CF lung microbiomes, which may be significant for CF pulmonary physiopathology [44].…”

“…Risk of P. aeruginosa early colonization may be assessed on predictive biomarkers within the microbiome. Porphyromonas is a candidate biomarker in the lungs (BEACH study; ClinicalTrials.gov Identifier: NCT03947957) [78], and Parabacteroides in the gut [8]. The predictive potential of the microbiome for exacerbation was studied to adapt antibiotic therapeutic strategies.…”

Multi-Omics Approaches: The Key to Improving Respiratory Health in People With Cystic Fibrosis?

“…Comparing it to an idealized healthy benchmark may give advanced warning of unfavorable alterations in the composition of the microbiota, or potential "blooms" of pathogens, allowing for earlier intervention, especially if the patient is harboring slow growing pathogens or strains resistant to standard clinical culture (Harris et al, 2007;Woo et al, 2008). Recently Keravec et al (2019) used a 16S MGA approach to identify prognostic biomarkers of P. aeruginosa infection in patients with CF and proposed representatives of the genus Porphyromonas as possible predictive markers.…”