Nasal Resistome Development in Infants With Cystic Fibrosis in the First Year of Life

The antibiotic resistance reservoir of the lung microbiome expands with age in a population of critically ill patients

Antimicrobial resistant lower respiratory tract infections are an increasing public health threat and an important cause of global mortality. The lung microbiome can influence susceptibility of respiratory tract infections and represents an important reservoir for exchange of antimicrobial resistance genes. Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene burden, however, corollary studies in the lung microbiome remain absent. We performed an observational study of children and adults with acute respiratory failure admitted to the intensive care unit. From tracheal aspirate RNA sequencing data, we evaluated age-related differences in detectable antimicrobial resistance gene expression in the lung microbiome. Using a multivariable logistic regression model, we find that detection of antimicrobial resistance gene expression was significantly higher in adults compared with children after adjusting for demographic and clinical characteristics. This association remained significant after additionally adjusting for lung bacterial microbiome characteristics, and when modeling age as a continuous variable. The proportion of adults expressing beta-lactam, aminoglycoside, and tetracycline antimicrobial resistance genes was higher compared to children. Together, these findings shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Differential airway resistome and its correlations with clinical characteristics in Haemophilus- or Pseudomonas-predominant microbial subtypes of bronchiectasis

The prevalence and clinical correlates of antibiotic resistance genes (ARGs) in bronchiectasis are not entirely clear. We aimed to profile the ARGs in sputum from adults with bronchiectasis, and explore the association with airway microbiome and disease severity and subtypes. In this longitudinal study, we prospectively collected 118 sputum samples from stable and exacerbation visits of 82 bronchiectasis patients and 19 healthy subjects. We profiled ARGs with shotgun metagenomic sequencing, and linked these to sputum microbiome and clinical characteristics, followed by validation in an international cohort. We compared ARG profiles in bronchiectasis according to disease severity, blood and sputum inflammatory subtypes. Unsupervised clustering revealed a Pseudomonas predominant subgroup (n = 16), Haemophilus predominant subgroup (n = 48), and balanced microbiome subgroup (N = 54). ARGs of multi-drug resistance were over-dominant in the Pseudomonas-predominant subgroup, while ARGs of beta-lactam resistance were most abundant in the Haemophilus-predominant subgroup. Pseudomonas-predominant subgroup yielded the highest ARG diversity and total abundance, while Haemophilus-predominant subgroup and balanced microbiota subgroup were lowest in ARG diversity and total abundance. PBP-1A, ksgA and emrB (multidrug) were most significantly enriched in Haemophilus-predominant subtype. ARGs generally correlated positively with Bronchiectasis Severity Index, fluoroquinolone use, and modified Reiff score. 68.6% of the ARG-clinical correlations could be validated in an independent international cohort. In conclusion, ARGs are differentially associated with the dominant microbiome and clinical characteristics in bronchiectasis.

The antibiotic resistance reservoir of the lung microbiome expands with age

Antimicrobial resistant lower respiratory tract infections (LRTI) are an increasing public health threat, and an important cause of global mortality. The lung microbiome influences LRTI susceptibility and represents an important reservoir for exchange of antimicrobial resistance genes (ARGs). Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene (ARG) burden, however corollary studies in the lung microbiome remain absent, despite the respiratory tract representing one of the most clinically significant sites for drug resistant infections. We performed a prospective, multicenter observational study of 261 children and 88 adults with acute respiratory failure, ranging in age from 31 days to ≥ 89 years, admitted to intensive care units in the United States. We performed RNA sequencing on tracheal aspirates collected within 72 hours of intubation, and evaluated age-related differences in detectable ARG expression in the lung microbiome as a primary outcome. Secondary outcomes included number and classes of ARGs detected, proportion of patients with an ARG class, and composition of the lung microbiome. Multivariable logistic regression models (adults vs children) or continuous age (years) were adjusted for sex, race/ethnicity, LRTI status, and days from intubation to specimen collection. Detection of ARGs was significantly higher in adults compared with children after adjusting for sex, race/ethnicity, LRTI diagnosis, and days from intubation to specimen collection (adjusted odds ratio (aOR): 2.16, 95% confidence interval (CI): 1.10-4.22). A greater proportion of adults compared with children had beta-lactam ARGs (31% (CI: 21-41%) vs 13% (CI: 10-18%)), aminoglycoside ARGs (20% (CI: 13-30%) vs 2% (CI: 0.6-4%)), and tetracycline ARGs (14% (CI: 7-23%) vs 3% (CI: 1-5%)). Adults ≥70 years old had the highest proportion of these three ARG classes. The total bacterial abundance of the lung microbiome increased with age, and microbiome alpha diversity varied with age. Taxonomic composition of the lung microbiome, measured by Bray Curtis dissimilarity index, differed between adults and children (p = 0.003). The association between age and increased ARG detection remained significant after additionally including lung microbiome total bacterial abundance and alpha diversity in the multivariable logistic regression model (aOR: 2.38, (CI: 1.25-4.54)). Furthermore, this association remained robust when modeling age as a continuous variable (aOR: 1.02, (CI: 1.01-1.03) per year of age). Taken together, our results demonstrate that age is an independent risk factor for ARG detection in the lower respiratory tract microbiome. These data shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Antibiotic resistance in chronic respiratory diseases: from susceptibility testing to the resistome

The development of resistome analysis, i.e. the comprehensive analysis of antibiotic-resistance genes (ARGs), is enabling a better understanding of the mechanisms of antibiotic-resistance emergence. The respiratory microbiome is a dynamic and interactive network of bacteria, with a set of ARGs that could influence the response to antibiotics. Viruses such as bacteriophages, potential carriers of ARGs, may also form part of this respiratory resistome. Chronic respiratory diseases (CRDs) such as cystic fibrosis, severe asthma, chronic obstructive pulmonary disease and bronchiectasis, managed with long-term antibiotic therapies, lead to multidrug resistance. Antibiotic susceptibility testing provides a partial view of the bacterial response to antibiotics in the complex lung environment. Assessing the ARG network would allow personalised, targeted therapeutic strategies and suitable antibiotic stewardship in CRDs, depending on individual resistome and microbiome signatures. This review summarises the influence of pulmonary antibiotic protocols on the respiratory microbiome, detailing the variable consequences according to antibiotic class and duration of treatment. The different resistome-profiling methods are explained to clarify their respective place in antibiotic-resistance analysis in the lungs. Finally, this review details current knowledge on the respiratory resistome related to therapeutic strategies and provides insight into the application of resistome analysis to counter the emergence of multidrug-resistant respiratory pathogens.

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.

Mosaic Ends Tagmentation (METa) Assembly for Highly Efficient Construction of Functional Metagenomic Libraries

Functional metagenomic libraries, physical bacterial libraries which allow the high-throughput capture and expression of microbiome genes, have been instrumental in the sequence-naive and cultivation-independent exploration of metagenomes. However, preparation of these libraries is often limited by their high DNA input requirement and their low cloning efficiency. Here, we describe a new method, mosaic ends tagmentation (METa) assembly, for highly efficient functional metagenomic library preparation. We applied tagmentation to metagenomic DNA from soil and gut microbiomes to prepare DNA inserts for high-throughput cloning into functional metagenomic libraries. The presence of mosaic end sequences in the resulting DNA fragments synergized with homology-based assembly cloning to result in a 300-fold increase in cloning efficiency compared to traditional blunt-cloning-based protocols. We show that compared to published libraries prepared by state-of-the-art protocols, METa assembly is on average ca. 20- to 200-fold more efficient and can prepare gigabase-sized libraries with as little as 200 ng of input DNA. We show the usefulness of METa assembly first by using a normative 5-μg mass of soil metagenomic DNA to prepare a 700-Gb library that allowed us to discover novel nourseothricin resistance genes and a potentially new mode of resistance to this antibiotic and second by using only 300 ng of goose fecal metagenomic DNA to prepare a 27-Gb library that captured numerous tetracycline and colistin resistance genes. METa assembly provides a streamlined, flexible, and efficient method for preparing functional metagenomic libraries, enabling new avenues of genetic and biochemical research into low-biomass or scarce microbiomes. IMPORTANCE Medically and industrially important genes can be recovered from microbial communities by high-throughput sequencing, but precise annotation is often limited to characterized genes and their relatives. Cloning a metagenome en masse into an expression host to produce a functional metagenomic library, directly connecting genes to functions, is a sequence-naive and cultivation-independent method to discover novel genes. The process of preparing these libraries is DNA greedy and inefficient, however. Here, we describe a library preparation method that is an order of magnitude more efficient and less DNA greedy. This method is consistently efficient across libraries prepared from cultures, a soil microbiome, and a goose fecal microbiome and allowed us to discover new antibiotic resistance genes and mechanisms. This library preparation method will potentially allow the functional metagenomic exploration of microbiomes that were previously off limits due to their rarity or low microbial biomass, such as biomedical swabs or exotic samples.

Changes in the Cystic Fibrosis Airway Microbiome in Response to CFTR Modulator Therapy

The development of CFTR modulator therapies significantly changed the treatment scheme of people with cystic fibrosis. However, CFTR modulator therapy is still a life-long treatment, which is not able to correct the genetic defect and cure the disease. Therefore, it becomes crucial to understand the effects of such modulation of CFTR function on the airway physiology, especially on airway infections and inflammation that are currently the major life-limiting factors in people with cystic fibrosis. In this context, understanding the dynamics of airway microbiome changes in response to modulator therapy plays an essential role in developing strategies for managing airway infections. Whether and how the newly available therapies affect the airway microbiome is still at the beginning of being deciphered. We present here a brief review summarizing the latest information about microbiome alterations in light of modern cystic fibrosis modulator therapy.

Untargeted Metagenomic Investigation of the Airway Microbiome of Cystic Fibrosis Patients with Moderate-Severe Lung Disease

Although the cystic fibrosis (CF) lung microbiota has been characterized in several studies, little is still known about the temporal changes occurring at the whole microbiome level using untargeted metagenomic analysis. The aim of this study was to investigate the taxonomic and functional temporal dynamics of the lower airway microbiome in a cohort of CF patients. Multiple sputum samples were collected over 15 months from 22 patients with advanced lung disease regularly attending three Italian CF Centers, given a total of 79 samples. DNA extracted from samples was subjected to shotgun metagenomic sequencing allowing both strain-level taxonomic profiling and assessment of the functional metagenomic repertoire. High inter-patient taxonomic heterogeneity was found with short-term compositional changes across clinical status. Each patient exhibited distinct sputum microbial communities at the taxonomic level, and strain-specific colonization of both traditional and atypical CF pathogens. A large core set of genes, including antibiotic resistance genes, were shared across patients despite observed differences in clinical status, and consistently detected in the lung microbiome of all subjects independently from known antibiotic exposure. In conclusion, an overall stability in the microbiome-associated genes was found despite taxonomic fluctuations of the communities.