Lower airway microbiota and decreasing lung function in young Brazilian cystic fibrosis patients with pulmonary Staphylococcus and Pseudomonas infection.

Cystic fibrosis (CF) is a genetic disease caused by mutations in the cystic fibrosis transmembrane conductance regulator gene that leads to respiratory complications and mortality. Studies have shown shifts in the respiratory microbiota during disease progression in individuals with CF. In addition, CF patients experience short cycles of acute intermittent aggravations of symptoms called pulmonary exacerbations, which may be characterized by a decrease in lung function and weight loss. The resident microbiota become imbalanced, promoting biofilm formation, and reducing the effectiveness of therapy. The aim of this study was to monitor patients aged 8-23 years with CF to evaluate their lower respiratory microbiota using 16S rRNA sequencing. The most predominant pathogens observed in microbiota, Staphylococcus (Staph) and Pseudomonas (Pseud) were correlated with clinical variables, and the in vitro capacity of biofilm formation for these pathogens was tested. A group of 34 patients was followed up for 84 days, and 306 sputum samples were collected and sequenced. Clustering of microbiota by predominant pathogen showed that children with more Staph had reduced forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) compared to children with Pseud. Furthermore, the patients' clinical condition was consistent with the results of pulmonary function. More patients with pulmonary exacerbation were observed in the Staph group than in the Pseud group, as confirmed by lower body mass index and pulmonary function. Additionally, prediction of bacterial functional profiles identified genes encoding key enzymes involved in virulence pathways in the Pseud group. Importantly, this study is the first Brazilian study to assess the lower respiratory microbiota in a significant group of young CF patients. In this sense, the data collected for this study on the microbiota of children in Brazil with CF provide a valuable contribution to the knowledge in the field.

Introduction

Cystic fibrosis (CF) is the most common life-shortening rare disease with an estimated incidence of 1 in every 6000 live births in Euro-Brazilians and 1/14000 in Afro-Brazilians [1]. The disease is caused by mutations in the CF transmembrane conductance regulator gene (CFTR), and the homozygous F508del is present in approximately 48% of all CF alleles [2]. Complications of CF disease begin in early life and over time, a combination of impaired mucociliary clearance, innate immune responses, inflammatory pulmonary process, chronic infection leads to bronchiectasis and respiratory failure [3].

The microbiota of the respiratory tract is recognized as an essential factor in the homeostasis of the respiratory system [4]. The respiratory microbiota is linked to progressive CF lung disease depending on many factors such as the time of diagnosis, patient age, chronic use of antibiotics, and mutation type of the CFTR gene [5]. Thus, the establishment of a community composed mainly of typical CF pathogens with other agents such as anaerobic bacteria, fungi, and viruses may cause dysbiosis of the respiratory system [5]. In addition, the pathophysiology of CF affects the respiratory microbiota, with the formation of biofilm and mucus plugging, making the pulmonary distal airways inaccessible by treatment agents [6].

A wide variety of bacterial species can be identified from patients with CF; the most frequently observed include Staphylococcus aureus, Pseudomonas aeruginosa, Haemophilus influenzae, and Burkholderia cepacia complex [7, 8]. Other opportunistic bacterial species that are less frequently detected in CF patients include Stenotrophomonas maltophilia, Achromobacter xylosoxidans, Ralstonia spp., Pandoraea spp., Cupriavidus spp., and non-tuberculosis mycobacteria [9, 10]. In addition, CF patients experience short cycles of acute intermittent aggravations of symptoms called pulmonary exacerbations, characterized by a decrease in lung function and weight loss, generally caused by opportunistic pathogens which can promote biofilm formation and reduce the effectiveness of therapy [11].

Nevertheless, the composition of respiratory microbiota varies noticeably among individuals; some patients show marked changes in the bacterial community with alternating infectious agents, and others show community resilience [3]. We analyzed the microbiota of 306 sputum samples of patients with CF and evaluated correlations with clinical variables (mutation type and patient’s clinical status). In addition, we grouped CF patients in two groups by the dominant respiratory microbiota pathogens, Staph and Pseud, and analyzed these groups by their clinical variables using Pearson’s correlation analysis and non-metric multidimensional scaling. Furthermore, bacterial functional profiles were predicted for both pathogen groups.

Material and methods

Study setting

This study was performed at the Pequeno Príncipe Hospital, the largest pediatric hospital in Brazil. Currently, 390 pediatric beds are available in 32 pediatric specializations. The CF unit includes 80 pediatric patients who are followed until they are transferred to an adult unit.

Study population and clinical data

In this study, a group of 34 CF patients aged between 8 and 23 years was followed for 84 d (). Patients were diagnosed by a sweat test and CFTR gene screening. After each regularly scheduled clinic visit or hospital admission, clinical data including the use of broad- and narrow-spectrum antibiotics, body mass index (BMI), and lung function parameters such as forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were collected. Lung function was assessed using a JAEGER MasterScope® Spirometer (VIASYS Healthcare GmbH, Hoechberg, Germany) following the standardization of pulmonary function test (PFT) by ATS/ERS Task Force [12]. Patients with O2 saturation ≥88% in room air and capacity to perform PFT were included. The clinical conditions were categorized as baseline, exacerbation, treatment, and recovery [10]. Baseline condition: no acute respiratory symptoms and no systemic antibiotic use for >30 d; patients may or may not be on maintenance antibiotics such as azithromycin or inhaled antibiotics. Exacerbation condition: the initiation of acute respiratory symptoms and use of antibiotics (oral or intravenous). Treatment condition: the use of intravenous or oral antibiotics for more than 7 d for pulmonary exacerbation treatment. Recovery: no systemic antibiotic use for >7 d; patients may or may not be on maintenance antibiotics and may or may not be back to the baseline clinical condition.

Ethics statement

The Institutional Review Board (IRB) of the participating center (IRB #2.405.167) approved this study, and informed consent was obtained from the parents or guardians of all participants. Research was conducted in a manner to ensure the confidentiality for each patient.

Sample collection, processing, bacterial culture, and identification

A triplicate of sputum samples of the patients were collected on days 0, 42, and 84 (a total of 306 samples). Inhalation of hypertonic sterile saline solution (7%) by nebulization was used for sputum collection, followed by coughing and expectoration of airway secretions. Sputum characteristics ranged from salivary to purulent. The collected sputum samples were transported to the microbiology laboratory for processing within 2 h. Sputum samples were transferred to 15 mL graduated Falcon tubes, free of DNase and RNase, and sterile phosphate-buffered saline was added to bring the total volume to 8 mL. After homogenization, 2 mL of purulent sputum was transferred to new tubes and treated with β-mercaptoethanol and DNase I (Sigma-Aldrich, St. Louis, United States) to remove proteins and other soluble DNA, such as mitochondrial DNA [13]. The obtained pellet after treatment of all purulent samples and 1 mL aliquots of saliva samples were stored in a freezer at -80°C until DNA extraction. The remaining volume in the initial Falcon tubes was sent to the microbiology laboratory for bacterial culture identification [14]. S. aureus and P. aeruginosa isolated from sputum samples and identified by matrix-assisted laser desorption ionization mass spectrometry (MALDI-TOF MS) using a MicroflexTM LT instrument (Bruker Daltonics, Billerica, MA, USA) were stored at -80°C in brain heart infusion broth (HIMEDIA, Mumbai, Maharashtra, India) with 20% (v/v) glycerol for further analysis [15].

Phenotypic biofilm production detection

Qualitative biofilm production was performed using the tube method previously described [16]. A loop of microorganisms collected from tryptone soya agar (OXOID, Basingstoke, Hampshire, England) was inoculated into a polystyrene tube (15 mL Falcon tube) containing 10 mL of tryptone soy broth (OXOID, Basingstoke, Hampshire, England) supplemented with glucose (final concentration of 8%). Tubes were incubated at 35 ± 2°C for 24 h, and the broth was gently aspirated. The tubes were washed thoroughly with phosphate-buffered saline (pH 7.2) and dried. Cells in the dried tubes were stained with 0.1% crystal violet for 7 min, and excess dye was removed by washing the cells with distilled water [16]. After drying, the tubes were visually evaluated for biofilm formation (presence or absence). Biofilm formation was considered positive when a visible film coated the wall and bottom of the tube. The experiments were performed in duplicate, and biofilm production was evaluated independently by two different observers. The sterile tryptone soy broth supplemented with glucose and the non-biofilm producer Candida albicans were used as a negative control and the biofilm producer Candida tropicalis was used as a positive control in the assay.

DNA extraction and 16S rRNA amplicon sequencing

All samples (frozen pellet and saliva) were kept on ice until they were completely thawed when subjected to genomic DNA extraction. A volume of 750 μL of lysis buffer was added to the pellet of each purulent sample and homogenized until the pellet was dissolved. The same volume of lysis buffer (750 μL) was added to 250 μL of each saliva sample. The total volume of each mixture was transferred to a ZR BashingBead® Lysis tube (Zymo Research, CA, USA) for DNA extraction. DNA extraction was performed using the ZymoBIOMICS® DNA Miniprep Kit (Zymo Research, CA, USA), according to the manufacturer’s recommendations. The purity and quality of the DNA were verified using a NanoVue Plus spectrophotometer (GE Healthcare, Life Sciences, Marlborough, MA, USA). Subsequently, DNA was stored at -80°C.

Polymerase chain reaction (PCR) and universal primers (F515/R806) were used to amplify the V4 region of the 16S rRNA gene [17]. PCR consisted of 2.5 μL bovine serum albumin (3 mg/mL), 2.5 μL high-fidelity buffer (10x), 0.63 μL MgCl2 (50 mM), 0.50 μL of dNTPs (10 mM), 0.625 μL primer mix (10 mM), 0.125 μL high-fidelity Taq polymerase (5 U/μL), 10 ng of template DNA, and 16.12 μL ultrapure water added to obtain a volume of 25 μL. The reaction conditions were as follows: 5 min at 95°C, 25 cycles of 40 s at 95°C, 2 min at 64°C, 1 min at 72°C, and 10 min at 72°C. The amplicons were quantified with Qubit using an HS dsDNA kit (Invitrogen, Carlsbad, CA, USA), diluted to 500 pM, and pooled. Next, 16 pM of pooled DNA was sequenced using the MiSeq reagent 600V3 (Illumina, San Diego, CA, USA). Sequencing was performed using a MiSeq® sequencer (Illumina) to obtain paired reads of 250 bp [18]. A negative control for sequencing was used to check contamination.

Sequencing data and statistical analysis

Sequencing data were analyzed using the QIIME2 Core 2021.8 pipeline [19]. Triplicate paired reads of the same collection of patients were joined in a single file (total of 102 samples). Next, the merged samples were filtered by quality, chimeras were removed and clustered into amplicon sequence variants using the DADA2 algorithm [20] in the QIIME2 program. Subsequently, taxonomic assignment was performed using the SILVA database, release 138 [21]. The reads output was normalized to 51,000 per sample, allowing a comparison of alpha and beta diversity between the groups.

Analysis of microbiota by the time of collection and clinical and genetic variables was compared using Welch’s t-test (P <0.05) and Bonferroni correction in STAMP software. Next, the abundance of bacterial taxa was compared for different pathogen groups using Welch’s t-test (P <0.05) and Bonferroni correction in STAMP software [22]. Clinical variables were analyzed using the Kruskal–Wallis and Mann-Whitney test (P <0.05). Pearson’s correlation coefficients and non-metric multidimensional scaling (NMDS) plots were calculated using the psych and vegan packages included in R software [23], and functional profiles of Staph and Pseud were obtained using the Tax4Fun program [24]. Only statistically significant results were reported (P <0.05).

Data accessibility

The dataset was submitted to the National Center for Biotechnology Information (NCBI) database under the BioSample accession code SAMN19760689.

Results

Of the 34 study participants, sputum samples were collected on days 0, 42, and 84 (a total of 102 samples), 17 were male, with a mean age of 15.3 years (range of 8–23 years), and 31 had an early diagnosis before age 2. All the patients underwent PFT (spirometry) with a wide range of the impaired pulmonary function with FVC ranging from 31% to 152% (mean = 84.3%) and FEV1 from 26% to 157% (mean = 75.9%). As for the nutritional status (BMI and Z score), the most repeated value in three collections was sought: 10 patients were considered eutrophic [25], 16 patients had grade I malnutrition, 8 patients had grade II malnutrition, and 2 patients had grade III malnutrition [26]; however, 12 individuals had score differences between collections for a higher or lower standard deviation according to their clinical condition at the time. Of the 34 patients, 26 had a negative Z-score (mean = -0.59), and 32 patients had pancreatic insufficiency. S. aureus was the most frequent microorganism (47%) identified by the culture-based methods, followed by P. aeruginosa (16%); both microorganisms were present in association from different culture media (25%), and in negative culture (14%). The metadata content of the clinical variables of the patients enrolled in this study is shown in supporting information (.

Sputum samples that showed Staph and Pseud with relative abundance >50% in the 16S rRNA sequencing were stored in -80°C for further biofilm production (total 40 samples, 20 samples of each pathogen). Therefore, a total of 13 S. aureus and 10 P. aeruginosa strains were evaluated for their biofilm production capacity. All of these were in vitro biofilm producers. Only the dichotomous analysis, presence or absence, was used, considering that by visual analysis the interpretation of intensity (+/++ and +++) can be subjective, especially without specific controls for each of these categories.

Taxonomic classification of sputum microbiota

This section presents the results of the analysis carried out at the genera and species levels. The analysis of the bacterial community at different collection times (days 0, 42, and 84) revealed 226 taxa, distributed among 178 genera and 48 species. The most abundant genera in the community were Veillonella, Prevotella, Haemophilus, Pseudomonas, Staphylococcus, Streptococcus, Serratia, Neisseria, and Porphyromonas (). A total of 155 taxa represented the core microbiota of the community on days 0, 42, and 84; these taxa were identified at all sampling periods and in all samples ().

Analyses of microbiota considering the time of collection, clinical variables or mutation did not identify any specific pattern in the lower respiratory microbiota of CF patients associated with the different clinical conditions. Thus, considering this result, the samples were clustered into two main groups Staph and Pseud, based on culture results and the most abundant pathogens identified in 16S rRNA sequencing (abundance >50%). Few samples with great abundance for other genera such as Veillonella and Haemophilus, among others were observed. Owing to the low number of samples, other microorganisms were not analyzed. The clinical variables of the patients were correlated with these two pathogen groups. Beta diversity analysis showed an adequate clustering of groups by pathogen type, which was reflected in the results of the principal component analysis (PCA), which highlighted that each group had a dominant organism, Staph or Pseud ().

Beta diversity of bacterial community, represented by PCA plot.

Dots with the same color mean samples of the same group, n = 20 per group.

Correlations among clinical variables and microbiota

We analyzed the clinical data by grouping patients according to the type of predominant pathogen in the sputum microbiota (the selection criterion was patients with pathogen abundance >50% in microbiota). We identified two dominant groups, Staph and Pseud, with a genetic mutation frequency of F508del in 67% of alleles, followed by G542x in 20%, 1078delT in 6%, and others (R334W and 2184delA) in 7% of alleles. The analyses revealed the following results:

The BMI was obtained by comparing patients of the same age; the BMI values were 18.09 and 19.41 for the Staph and Pseud groups, respectively. In other words, the patients in the Staph group were underweight (BMI <18.5 kg/m2 is considered underweight). On the other hand, the patients in the Pseud group had normal weight (BMI = 18.5–25.0). All patients in the Pseud group (except one patient) received antimicrobial treatment against Pseudomonas spp., in other words, chronically inhaled antibiotic to reduce bacterial growth and the frequency of exacerbations. In addition, we chose BMI values because this parameter had positive values. Besides, BMI Z-scores had negative values, which made it difficult to use Pearson’s correlation analysis or any other statistical analysis.

The clinical condition of the patients was as follows: in the Staph group, nine patients were classified in the baseline clinical condition, five in the exacerbated, six in the treatment, and one in the recovery group. In the Pseud group, 11 patients were classified in the baseline clinical condition, one in exacerbated, and five in the treatment group. Due to chronic lung infection, most CF patients had reduced lung function with significant differences (P <0.05) between the two groups; in general, the Staph group had reduced FEV1 and FVC compared to the Pseud group ().

Comparison between pathogens showing decreased forced vital capacity and forced expiratory volume in patients in the Staph group.

Forced vital capacity = FVC; forced expiratory volume in one second = FVE. Bars represent the average of the air volume, (**) means significant difference among treatments by Mann-Whitney test (P <0.05), n = 20 per group.

Pearson’s correlation analysis between clinical variables and microbiota

Pearson’s correlation coefficient showed significant relationship (P <0.05) between microbiota and clinical variables. In the Staph group, there were significant negative correlations between the variables (FVC and FEV) and prevalence of Staph and S. aureus (). In contrast, positive correlations were observed between clinical variables (BMI and age; FVC and FEV). Similarly, positive correlations were observed between the pathogens Staph and S. aureus. These results highlight the veracity of the correlation matrix. On the other hand, in the Pseud group, there was no significant positive or negative relationship between microbiota and clinical variables.

Pearson’s correlation showing significant correlations (P < 0.05) between microbiota and clinical variables in the Staph group.

Asterisks represent significant correlations. The bar in the right shows the correlation type, with positive in blue and negative in red. A positive correlation means that two variables in the matrix increased, n = 20.

Non-metric multidimensional scaling (NMDS)

To represent the behavior of the variables in a multivariate system, we used an NMDS plot. This analysis reveals the pairwise dissimilarity between objects in a two-dimensional space, in this case, microbiota and clinical variables (plotted as vectors). NMDS results confirmed the clustering of the pathogens in two groups with different taxonomic compositions. The first group, the Staph group, had higher abundance of Staph and S. aureus, and the second group, the Pseud group, had higher abundance of Pseud and P. aeruginosa (). In addition, vectors in the plot representing the clinical variables of patients were in the opposite direction to the Staph group, showing an inverse correlation of these parameters with bacteria present in high quantities in this group (Figs and ).

Non-metric Multidimensional Scaling (NMDS) plot showing significant correlations (P < 0.05) between microbiota and clinical variables in the Staph group.

The ellipses encompass different groups, with the Staph group in green and Pseud group in orange. Taxa are shown in black and clinical variables in red and blue vectors (red means significant). The direction of the vectors FEV and FVC indicates an inverse relationship with bacteria present in high quantities in the Staph group, n = 20 per group.

Prediction of bacterial functional profiles

Functional profiles were predicted from the 16S rRNA data obtained using the software package Tax4Fun. The aim of this analysis was to highlight the different profiles among pathogens groups in an unbiased manner. The complete profiles are shown in the Supporting Information (). Genes encoding key enzymes involved in virulence pathways were identified in the resulting profiles using their KEGG orthologs (). Thus, key genes related to antibiotic resistance were identified in the Staph group, such as: K01467, beta-lactamase; K03327, multidrug resistance protein, MATE family; K08218, MFS transporter-PAT family, beta-lactamase induction signal transducer AmpG, and genes related to horizontal gene transfer, such as: K07481, transposase, IS5 family; K07485, transposase; and K07489, transposase. In the Pseud group, key genes related to secretion systems were: K02456, general secretion pathway protein G; K02459, general secretion pathway protein J; K03195, type IV secretion system protein VirB10; K07344, type IV secretion system protein TrbL; K11891, type VI secretion system protein ImpL; K11896, type VI secretion system protein ImpG; and a gene related to biofilm synthesis: K11937, biofilm PGA synthesis protein PgaD ().

Table 1

Prediction of bacterial functional profiles.

KEGG functions
Staphylococcus group
K01467; beta-lactamase
K02028; polar amino acid transport system ATP-binding protein
K02029; polar amino acid transport system permease protein
K02030; polar amino acid transport system substrate-binding protein
K03327; multidrug resistance protein, MATE family
K06994; putative drug exporter of the RND superfamily
K07481; transposase, IS5 family
K07485; transposase
K07489; transposase
K07668; two-component system, OmpR family, response regulator VicR
K08138; MFS transporter, SP family, xylose: H+ symportor
K08191; MFS transporter, ACS family, hexuronate transporter
K08218; MFS transporter, PAT family, beta-lactamase induction signal transducer AmpG
K11068; hemolysin III
K11070; spermidine/putrescine transport system permease protein
K11071; spermidine/putrescine transport system permease protein
K15342; CRISP-associated protein Cas1
Pseudomonas group
K02456; general secretion pathway protein G
K02459; general secretion pathway protein J
K02657; twitching motility two-component system response regulator PilG
K03195; type IV secretion system protein VirB10
K03808; paraquat-inducible protein A
K07344; type IV secretion system protein TrbL
K11891; type VI secretion system protein ImpL
K11896; type VI secretion system protein ImpG
K11937; biofilm PGA synthesis protein PgaD
K12516; putative surface-exposed virulence protein
K13735; adhesin/invasin

Discussion

The bacterial taxa detected in the present study are in agreement with previous studies [27, 28]. Khanolkar et al. [29] and Raghuvanshi et al. [30] showed shifts in the composition of respiratory microbiota in patients with CF, such as the enrichment of Staphylococcus spp., Haemophilus spp., Pseudomonas spp., Streptococcus spp., Serratia spp., Neisseria spp., and Porphyromonas spp. We classified patients into two groups based on the dominant pathogens observed in the respiratory microbiota: the Staph and Pseud groups. These taxa are consistent with the results obtained from microbiological cultures, clinical practice, and scientific articles on CF, especially in our target age range [31]. In older patients, other bacteria, such as Burkholderia spp., and some emerging bacteria, such as Stenotrophomonas spp. and Acinetobacter spp. are observed [32].

In Brazil, the diagnosis of CF follows the Brazilian guidelines for the diagnosis and treatment of cystic fibrosis [33]. Thus, the algorithm of newborn screening for cystic fibrosis used in Brazil is based on two tests of immunoreactive trypsinogen levels, the second of which is performed within 30 days of life. If screening is positive (i.e., two positive tests), sweat testing is performed to confirm or rule out cystic fibrosis. Sweat chloride concentrations ≥ 60 mmol/L, as measured by quantitative methods, in two samples, confirm the diagnosis. Diagnostic alternatives are detection of two cystic fibrosis-related mutations and CFTR functional tests.

Children in the Staph group showed lower BMI than the Pseud group (18.09 versus 19.41); that is, children in the Staph group were underweight. Overall, children and young patients infected with Pseudomonas usually have a lower BMI than children infected with genus Staphylococcus, but this does not occur when the patient is already being monitored and receiving medication; in Pseud patients, treatment includes chronic use of inhaled antibiotics, such as tobramicyn (TOBI®) and azithromycin, which have immunomodulatory and antiviral effects [34]. However, it is not common to use prophylactic treatment in patients with chronic infection by Staphylococcus spp.; those patients use “off label” antibiotics [35]. This could explain the decreased BMI in patients with Staphylococcus spp.; however, this information should be used with caution because S. aureus is more prevalent at an earlier age and there are no reliable tools to measure lung function in children under six years of age.

Our results showed that patients’ clinical condition agreed with the results of pulmonary function (FVC and FEV1). In clinical practice, this observation reflects the definition of disease exacerbation, which means worsening of symptoms, changes in sputum color, loss or cessation of weight gain, and worsening of lung function [10]. Greater patient numbers were observed in the Staph exacerbation group than in the Pseud group, a finding that was confirmed by the lower values of BMI and pulmonary function. Limoli et al. [36] observed that co-infection with S. aureus and P. aeruginosa was associated with decreased lung function and increased numbers of pulmonary exacerbations. Polymicrobial dynamics may be a better indicator of CF patient outcomes, as opposed to the presence of a single pathogen [37, 38]. Pearson’s correlation analysis revealed significant relationships between the Staph group and parameters of pulmonary function (FVC and FEV).

In this study, biofilm formation capacity was observed in S. aureus and P. aeruginosa isolates. Thus, there is increasing evidence that biofilm-mediated infections facilitate the development of chronic infectious diseases and recurrent infections [39]. Biofilms are often considered a survival strategy for bacteria, which are facilitated by numerous factors in CF lungs, including mucus accumulation [11]. Previous studies have suggested that antibiotic resistance of bacteria in CF lungs is due to biofilm formation [40]. In addition, multiple species of lung biofilm producers such as Pseud in CF patients are affected by specific treatments; thus, competitiveness among different species is harmful, promoting the survival of the most abundant pathogen [41]. However, the clinical significance of in vitro biofilm production remains unclear and biofilm detection by laboratory techniques does not necessarily indicate in vivo production because biofilms are a community of multiple bacterial species that coexist in a specific environment [42].

Functional inference of communities showed that the presence of key genes in each pathogen group was possible because of the low biodiversity of each group, which was dominated by a single bacterial genus (Staph or Pseud). Thus, in the Staph group, a functional profile determined by antimicrobial resistance genes was observed. In the case of our isolates, this resistance profile was not identified, and all S. aureus isolates were sensitive to oxacillin and vancomycin. As in Voronina et al. [32], the presence of the mecA gene in sputum samples from pediatric patients with CF was not identified in this study; the mecA gene confers resistance to methicillin in S. aureus strains. The in silico inference profile is based on genomes deposited in the database; thus, these genomes may represent strains that carry genes of antibiotic resistance, and the result will depend on the database used as a comparison [43]. In the Pseud group, a dominant profile by secretion systems was identified which is expected because gram-negative bacteria carry several of these systems [44].

There are some limitations in this study. First, the cohort size is too small and heterogeneous. However, it represents the largest pediatric hospital in Brazil, and thus is an interesting clinical cohort from Brazil. In addition, this work is novel, as the only published work on the respiratory microbiota of Brazilian CF patients was recently published by Vasco et al. [45], where the authors evaluated the microbiota of 10 children under 6 years old with pancreatic insufficiency who underwent pancreatic enzyme replacement therapy with Creon®. In this sense, this preliminary work is totally different from ours.

The second limitation is regarding the over-simplification of the microbiota data. Initially, we used longitudinal data and triplicates, but this information was not used at all in the manuscript. This information would be relevant to answer important questions such as the longitudinal relationship between microbiome and lung function or the heterogeneity of sputum at a single timepoint. However, analyses of microbiota by the time of collection or by related clinical variables did not identify any specific microbiota pattern from the respiratory tract of the patients. Thus, considering this result, the microbiota was clustered into two main groups, Staph and Pseud. Microbiota samples with abundance >50% of either Staphylococcus or Pseudomonas were further analyzed. This grouping parameter may seem to skew the data to the expected result. However, this approach, using a cutoff in the data, yielded results that had not been observed in previous studies. Using a cutoff in the data allows the creation of a reference for future studies, and, importantly, this approach helped us to better understand the relationship between opportunistic microbiota pathogens and lung function.

Finally, in patients with CF, the composition of respiratory microbiota varies noticeably between individuals; some patients show marked changes in the bacterial community with alternating infectious agents. Besides, different types of CF mutation did not show unique microbiota. Thus, some points require further research: (i) How can we promptly identify the agent in patients with acute exacerbation with negative classical culture? (ii) How can we make better use of next-generation sequencing and other techniques to identify low-abundance microorganisms that are likely to be responsible for exacerbation in patients?

Clinical variables of the patients enrolled in this study.

(XLSX)

Click here for additional data file.

Complete prediction profiles.

(XLSX)

Click here for additional data file.

Relative frequency of the most abundant genera of the bacterial community by data collection.

(A) day 0; (B) day 42; and (C) day 84 of collection.

(EPS)

Click here for additional data file.

Venn diagram representing the core microbiota of the community by sampling time.

155 taxa were identified as the core microbiota.

(EPS)

Click here for additional data file.

24 Mar 2022

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Mesa et al present a longitudinal prospective study of predominantly pediatric CF patients to evaluate their microbiome and correlate it to clinical findings. While this is certainly an area of interest, a number of significant issues preclude my recommendation for publication as noted in detail below.

Title: I am very unclear why it states upper airway microbiota when the authors clearly describe induced sputum which samples mainly the lower respiratory tract. While there have been numerous studies evaluating the presence of upper airway oropharyngeal microbiota contamination in saliva samples--to label this as primarily upper airway (i.e. oropharynx and proximal anatomy) is incorrect and atypical in CF literature.

Abstract:

Line 26: "Long periods"--this is vague--are they referring to clinical progression? Baseline?

Line 29-30: This is inaccurate to say PEx are caused by those classic pathogens--while that has been the traditional viewpoint, the authors should be redirected to numerous studies failing to demonstrate molecular (i.e. increased relative abundance) or culture-based (i.e. CFU) evidence that classic pathogens increase at times of PEx--hence this is the cornerstone of microbiome studies in CF.

Line 32: Need a space between "time to".

Line 33: Again not upper respiratory tract..

Line 33: Unclear what "more abundant" pathogens refers to--by prevalence or relative abundance in samples?

Line 37: Had should be lower case.

Line 39: Unclear what the patients clinical condition were consistent with results of pulmonary function?

Introduction:

Line 52: This is incorrect, delF508 is present in >90% of CF patients in one copy--unless the authors are describing homozygous delF508 which then should be included in the sentence.

Line 54: "A marked inflammatory process" suggests only one process which is inaccurate.

Line 55: I am unclear what "pulmonary lesions" are. ?Bronchiectasis? These are not lesions.

Line 57: This needs a reference as up until a decade ago the respiratory tract was considered sterile.

Line 67-68: Disagree. In fact numerous taxa have been implicated in CF as both pathogenic or protective--if the authors are going to make such a sweeping statement a reference is required.

Lines 76-78: Again refer to the same statement in the abstract which is inaccurate.

Lines 83-84: Poor sentence structure, they describe their study but also present conclusions.

Methods:

Lines 108-115: The authors should reference where they obtained these definitions of baseline, exacerbation, recovery and treatment.

Lines 119: Fragment sentence.

Lines 120: More discussion around the control group in the study by Hahn et al is required in the methods briefly--including what defined "healthy" and if any exclusion criteria were applied.

Line 132: This is unclear--where sputum collected in triplicate on each of those days (0, 42, 84) OR was it one sample on each of these days?

Results:

Line 216: Can the authors comment more (perhaps in the methods) on CF diagnosis in Brazil? In North America this done by newborn screening but the authors imply that 31 had an early diagnosis before age 2. More clarity would be helpful to international audiences.

Lines 220: Define eutrophic, unclear what this and grades of malnutrition are.

Line 224: Should put percentage of patients next to number.

Lines 226: Are "both organisms in association" on the SAME culture or just a history of both?

Line 233: I am assuming the authors mean relative abundance but this should be clarified.

Lines 235: The authors need to expand on these results--was there assay a dichotomous yes/no or were there grades of biofilm development that could be scored?

Lines 238-239: This is very well known in the literature and not required in the results.

Lines 243: Are these ASV's since the authors used the dada2 protocol? If so they should consider presenting their data at the collapsed genera level such to not split ASV (i.e. two Prevotella are listed).

Lines 247-249: This is very much lacking in detail. How was this analysis done? Was it a multivariate model? Where are the statistics or statistical methodology?

Lines 250-252: Again, unclear is. Is it they had to be BOTH culture AND most abundant or either or? I also find it suspect that each had 20 samples per group--more clarity is required. Why did the authors pick Pseudomonas and Staphylococcus? They stated that the most abundant genera were mostly anaerobic--so what is the rationale for this? If it is to evaluate classic pathogens, why exclude Haemophilus which appears to be prevalent and abundant? I do not see a clear hypothesis.

Lines 265: The authors need to expand how they got to the species level, again by ASV?

Lines 281-285: This is absolutely incorrect. The authors have not shown any statistical analysis to evaluate for confounders before concluding that Staphylococcus is contributing to underweight status. There is lacking of evidence to back up such a sweeping conclusion.

Lines 286-287: Is this nebulizer chronic therapy?? Again more details.

Lines 296-298: I find it unusual their Pseudomonas group had BETTER clinical outcome when multiple studies over years clearly show worse outcomes upon acquisition of Pseudomonas. The authors need to postulate in the discussion why their results differ from multiple well-conducted studies.

Lines 316-332: Again I am unclear what this data is meant to show. It is clear the dominant groups would differ--what is the hypothesis?

Discussion:

Overall, I found the discussion weak and unable to support many of their conclusions for the reasons cited in the results. Specific examples include: lines 377-388 with no discussion around confounding variables.

Many of the references are not appropriate or up to date to support the conclusions stated--such as reference 32. Overall, I do not see a clear hypothesis or understanding of how the data contributes to the literature. It was also extremely unclear why the authors described a longitudinal prospective study but then did no work on this and rather became cross-sectional.

Overall significant issues are present and needs careful attention.

Reviewer #2: In the study presented here, authors Kussek et al. show data on the respiratory microbiota of children with cystic fibrosis in Brazil. 34 children with CF are included in the study, and samples are collected at 3 different time points for comparison. Relationships between clinical variables (lung function scores, BMI, etc.) and abundance of dominant CF respiratory pathogens, namely S. aureus and P. aeruginosa, are investigated. The authors conclude that S. aureus correlates with worse clinical outcomes in their pediatric CF population, and they identify potential virulence genes in S. aureus and P. aeruginosa metagenomic data.

The data presented on this population of children with CF is valuable and addresses important questions about how presence of CF bacterial pathogens relates to patient exacerbations and clinical outcomes. The manuscript is overall well-written, and the strengths and weaknesses of this work is well described in the discussion section. This would be a valuable dataset to publish, if concerns raised below are addressed:

Major concerns:

A major issue with this work is that healthy control data used for comparison is from a previous publication by a different group who conducted their study in the US (lines 115-121). Samples from healthy children in the Hahn et al. study were collected from a different site in the respiratory tract (oropharynx) than used in this manuscript, and data were obtained by sequencing samples from oropharyngeal swabs, not induced sputum samples. OP swabs have not been reported to accurately reflect the lower respiratory microbiome, and there may also be regional differences in respiratory microbiota in healthy controls in distinct geographic locations like the US and Brazil. For these reasons, making direct comparisons between these datasets is not possible, and healthy control data should be removed from figures and tables presented here. The new data collected for this study on the microbiome of children in Brazil with CF is valuable on its own. It would be appropriate compare and contrast how these findings relate to previous studies with healthy control groups of a similar age in the discussion section, but not in the results.

It would be informative to compare the S. aureus- and P. aeruginosa-dominant groups to samples where neither of these organisms was the abundant species in Fig. 2 and Fig. 3, rather than making the healthy control comparisons using data from the Hahn et al. study.

For analyses in Fig. 2, 20 samples per group with greater than 50% relative abundance of S. aureus and P. aeruginosa were selected. If not all samples meeting this criteria were compared, how were representative samples chosen? Are samples evaluated here from the same patients whose clinical variables (FEV and FVC) are compared in Figure 4?

The NMDS plot in Fig. 6 does not show individual data points for samples, so interpreting how ellipses relate to clustering of the different groups is not possible. It is confusing how four clinical variables can be included here in a plot with only two axes. It would seem correct to instead separate the clinical variables into different plots where 3 variables are compared in each and show multiple plots to make comparisons.

Minor concerns:

Lines 29-30 and 74-77, There is not a concrete link between either P. aeruginosa or S. aureus and exacerbation in CF, although many groups have looked at this and presence of bacteria has been positively correlated with other outcomes (i.e. P. aeruginosa infection and end-stage lung disease). Would consider walking back language in these statements.

Lines 32-33, The data presented is from induced sputum samples obtained by inhalation of nebulized hypertonic saline, which would provide information about lower respiratory tract infections and microbiota. However, the abstract states that upper respiratory microbiota are evaluated, which is not tested here. This should be changed to “lower respiratory microbiota.”

Line 53, Rather than stating “CF beings early in life…” it may be more accurate to say “Complications of CF disease begin early in life…”

Line 60, Does “its mutation class” refer to CFTR mutations?

Line 64, Would remove the word “all” from statement that “… all pulmonary distal airways are inaccessible.”

Lines 244-245, How is the “core community” defined? Based on Figure S3, would this be taxa identified at all sampling periods, and/or in all samples?

Figure 4, It would be helpful to include individual data points for comparison of sample groups in bar graphs.

Lines 286-287, Was it evaluated if receiving antimicrobial treatment led to significant changes in P. aeruginosa relative abundance at subjects’ next visits post-treatment? This would be a very interesting relationship to investigate.

Lines 440-453, It’s discussed that other comparisons were made with longitudinal samples, but data was not included because a pattern was not identified. I would consider revising or removing some of this language; not all data is going to result in a pattern, and stating that a particular outcome is sought indicates potential bias in data interpretation. Variability in patient clinical data is common and expected. These findings actually echo much of what has been observed in other CF patient studies, and presenting results even if a specific correlation isn’t observed is still valuable.

Reviewer #3: The manuscript describes a study undertaken to assess the upper respiratory tract microbiota of young patients suffering from cystic fibrosis (CF). Sputum samples collected from 34 CF patients were characterised and further used for isolating microbial cultures. Parallelly, the samples were also used to extract the DNA and perform 16SrRNA gene sequencing to analyse the entire microbial community present. Functional profiles of genes encoding virulence factors or antibiotic resistance were analysed and used for correlation with microbial data.

The manuscript is well written and the authors have rightly described the few limitations of the study also highlighting the need to use next generation sequencing and other techniques to better assess the data.

After thoroughly reading the article, I would like to make the following comments and suggestions.

1] Abstract: appears a bit general. It would be appropriate to include specific results obtained and conclusions drawn. Correct the typographical errors on Line 32 and Line 37.

2] Introduction is well written and identifies the need to carry out this study. Full name (Genus and species) of organism may be written on first appearance followed by genus (initial) and species full name.

3] Materials and Methods-

i. Line 161-162- It would have been more appropriate to measure the absorbance to quantify the biofilm synthesised. Visual (Qualitative data) interpretations are less reliable.

ii. Line 163-164 – Please mention the strain numbers or source of Candida isolates used.

4] Results-

i. Line 233- How was the abundance of a particular pathogen determined?

ii. Line 243- Prevotella 7? Appears to be a typographical error

iii. Line 300- Figure 4A and 4B can be merged

iv. Line 341- How reliable is to predict the bacterial functional profiles on the basis of 16SrRNA gene sequence data alone? Justify.

v. Were only 23 (13 S. aureus and 10 P. aeruginosa) isolates obtained on culturing sputum samples? Or was that the number tested for biofilm formation? Did you isolate both S. aureus and P. aeruginosa both from a single sputum sample?

vi. The term Staphylococcus aureus and Staphylococcus spp. appears to be used quite interchangeably. Please correct the same. Same for Pseudomonas aeruginosa and Pseudomonas spp.

5] Discussion is well written.

6] There are few grammatical and typographical mistakes in the manuscript which need to be carefully identified and corrected.

Reviewer #4: General Comments:

It is an important non-interventional clinical trial in which sputum samples of young patients were evaluated for the relative prevalence of bacteria in their sputum. There are a lot if information collected however the way the data are presented makes the study findings and conclusions not clear and the significance of the findings not convincing. In fact, discussion of the results is stressing that the data generated simply confirms previously published studies.

The analysis of the results needs a major revision after the patients are properly grouped according to their mutation status, sex and baseline FeV1. The results generated should be re-evaluated once the patients are properly divided according to their mutation status and their exacerbation status at the onset of the trial. The exacerbating patients can not be analyzed in the same group as stable patients.

The authors state that FEV1 of 26% for some patients. It is unclear if this is a baseline FeV1 typical for the patients or recorded at the peak of exacerbation. If is a baseline FeV1 it would be exceptionally severe CF lung disease for so young patient (s). If this only happened for few days at the peak of exacerbation when patient experienced severe pneumonia it is completely different story. The FEV1 at onset should be measured when the patient is stable for 30 days.

FeV1 can be measured also during the exacerbation of course to evaluate how severe impairment in lung function occurred during the exacerbation but the analyses of the findings should be done by separating the patients into different subgroups groups and interpretation of these findings should to be different when the stable patients are evaluated vs. when the exacerbating patients are evaluated.

The exacerbating patients’ microbiota in the sputum should be evaluated separately than microbiota typical for steady state baseline microbiota typical for chronically infected patient on azithromycin and inhaled antibiotics.

The way the data are presented does not brings much useful information. It is not clear what is a typical the microbiome at steady-state level in each patient and which microbiome changes occur during exacerbation .

Is there observed during exacerbations an increase in the CFUs of specific pathogens that were already present at baseline (with the relative composition of bacteria remaining the same), or during the exacerbation the relative composition of bacteria changes dramatically?

Major specific comments:

1. Patients ages ranges 8-23 contain both pediatric cases and adult cases so should not be classified broadly as pediatric. Table containing characteristics of each patient should be included that would provide information about each patient’s age, sex, the class of the mutations that each patient had should also be stated, specific CFTR gene mutations should be stated for each patient, CRP at the time of the initiation of the trial ( for stable patients with no exacerbation for 30 days), amount of exacerbation in the year prior to the study at the initiation of the study. Steady-state FeV1 recorded when there is no exacerbation.

2. FEV1 is only informative as a characteristic of the patient when is recorded at baseline (30 days with no exacerbation and with not major increase in CRP level compared to the previous periods without exacerbation). The patients with active exacerbation at the onset of the study should be studied separately and once they get stabilized their baseline Fev1 should be recorded. At the exacerbation the FeV1 is very volatile and can drop dramatically but it does not represent the overall FeV1 characteristics of the patient. It is affected primarily by the sudden raise in the bacterial counts and sometimes also type of combination of infections

3. The biggest drop in the stable FEV1 usually occurs between age 18 and 30. It is not clear how many patients were in this age bracket? Did the authors seen a difference in baseline FeV1 and between 8–17-year-old patients compared to 18–23-year-old patients?

4. The number of patients positive for PA, SA and both should be stated, not only the percentage of the cohort L225-L228. How many patients experienced dual infection with PA and SA? (Table S1…. check if the information is there….)

5. Is the relative higher abundance PA vs SA in both age group similar?

6. Methodology mentioned in 146-149 needs to be properly described in detail (buffers, duration of run, columns used, temperature, elution parameters, etc … ). The methodology should be written in a way that the method can be reproduced by other investigators just based on the descriptions provided. The protocol used should be included as a supplementary material. If there as space restrictions imposed by the journal, detailed protocols, including details, buffers, parameters of runs, how many times repeated, standards used should be appended as supplemental data. The way it is written is not informative at all and can not be even properly evaluated.

7. Primers sequences should be included 5’-3’ in addition to their positions that has been mentioned in L178.

8. The information about CFTR gene mutation presented as percentages should be at least referred to the Table in the supplement that contains specific information regarding CFTR mutations each patient included in the study had, so not only percentages would be presented but the number of patients for each mutation type combination should be clear

9. The description of BMI does not take into consideration if the patients were males or females the range of BMI changes with age and sex, some children grow faster than other children so the way the BMI is presented in not informative at all.

10. In the discussion, the authors state that the Staphylococcal infections are not usually treated because there is not good treatment protocol. Authors findings suggest that the Staphylococcus species tested during this study were sensitive to oxacillin and vancomycin. It is not clear if these laboratory findings were used in the study to select proper treatment for Staphylococcal exacerbation or not. This should be at least mentioned.

11. The way the authors group the data into two groups over 50% Staphylococcus spp. or Pseudomonas spp. made the analysis of the data and resulting conclusions predictable and expected and diminished clinical significance of presented findings.

12. Lack of identification of specific microbe associated with apparent exacerbation is not well discussed; possibility of viral infections (frequently not diagnosed because there is no specific diagnostic test established, or/and the physician does not asks for more sophisticated tests to be done) and very slow growing or difficult to propagate in vitro bacterial infections (e.g mycobacterial species, such as M. abscessus complex)

Minor editing errors:

Abstract: Sentence starting from Clustering…. and the sentence starting from “Had reduced….” Should be all one sentence

L52: Authors state the 48% patients were delF508 – this is not clear – 48% had one allele of delF508 or both alleles with the same delF508 mutation?

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Reviewer #2: No

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Reviewer #4: No

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5 Aug 2022

June 23, 2022

Abdelwahab Omri, Pharm B, Ph.D

Academic Editor

PLOS ONE

Dear Editor:

I, along with my coauthors, wish to submit the revised manuscript entitled “Lower airway microbiota and decreasing lung function in young cystic fibrosis Brazilian patients with pulmonary Staphylococcus and Pseudomonas infection.” The paper was coauthored by Paulo Kussek, Dany Mesa, Luiza Souza Rodrigues, Thaís Muniz Vasconcelos, Damaris Krul, Helisson Faoro, Humberto Ibanez, and Jussara Kasuko Palmeiro.

We would like to thank you and the reviewers for your thoughtful suggestions and insights which have significantly helped us to improve our manuscript. We have carefully revised the manuscript (the revisions are highlighted in yellow for your convenience) to address the major concerns raised and hope that our revised manuscript meets your standards and will be reconsidered for publication in PLOS ONE.

We have also provided our point-by-point response (in red color) to all comments raised and hope that our replay addressed all your concerns.

Should you have any further questions, please contact us.

Thank you for your consideration. I look forward to hearing from you.

Sincerely,

Libera Maria Dalla Costa

Faculdades Pequeno Príncipe (FPP), Curitiba, Paraná, Brazil

Instituto de Pesquisa Pelé Pequeno Príncipe (IPPPP), Curitiba, Paraná, Brazil

Av. Silva Jardim, 1632, Curitiba, PR, Brazil

Fax: +55 41 33101035

lmdallacosta@gmail.com

libera.costa@professor.edu.br

Specific comments

Reviewer #1:

Mesa et al present a longitudinal prospective study of predominantly pediatric CF patients to evaluate their microbiome and correlate it to clinical findings. While this is certainly an area of interest, a number of significant issues preclude my recommendation for publication as noted in detail below.

Thank you for your constructive suggestions. We modified the structure to make the text clearer from the introduction to the discussion. In addition, each question was answered in red color.

Title: I am very unclear why it states upper airway microbiota when the authors clearly describe induced sputum which samples mainly the lower respiratory tract. While there have been numerous studies evaluating the presence of upper airway oropharyngeal microbiota contamination in saliva samples--to label this as primarily upper airway (i.e. oropharynx and proximal anatomy) is incorrect and atypical in CF literature.

Thank you for your observation. The title was corrected. Sorry for the mistake.

Abstract:

Line 26: "Long periods"--this is vague--are they referring to clinical progression? Baseline?

Yes, this refers to the clinical progression of the disease. The text was modified to make the statement clearer.

Line 29-30: This is inaccurate to say PEx are caused by those classic pathogens--while that has been the traditional viewpoint, the authors should be redirected to numerous studies failing to demonstrate molecular (i.e. increased relative abundance) or culture-based (i.e. CFU) evidence that classic pathogens increase at times of PEx--hence this is the cornerstone of microbiome studies in CF.

Thanks for your observation. The sentence has been reworded.

Line 32: Need a space between "time to". Thank you, space added.

Line 33: Again not upper respiratory tract. Thank you. The sentence was corrected.

Line 33: Unclear what "more abundant" pathogens refers to--by prevalence or relative abundance in samples? Thank you, the sentence was adjusted.

Line 37: Had should be lower case. Thank you, capital letter replaced.

Line 39: Unclear what the patients clinical condition were consistent with results of pulmonary function? Thank you, the patient's clinical condition was to make the sentence clearer.

Introduction:

Line 52: This is incorrect, delF508 is present in >90% of CF patients in one copy--unless the authors are describing homozygous delF508 which then should be included in the sentence. Thanks you, the statement was corrected in line 53.

Line 54: "A marked inflammatory process" suggests only one process which is inaccurate. Thanks you, the statement was adjusted in lines 55 and 56.

Line 55: I am unclear what "pulmonary lesions" are. ?Bronchiectasis? These are not lesions. Thank you, the sentence was adjusted in line 56.

Line 57: This needs a reference as up until a decade ago the respiratory tract was considered sterile. Thank you, a reference was included in line 59.

Line 67-68: Disagree. In fact numerous taxa have been implicated in CF as both pathogenic or protective--if the authors are going to make such a sweeping statement a reference is required. Thank you, the sentence was adjusted in lines 68 and 69.

Lines 76-78: Again refer to the same statement in the abstract which is inaccurate. Thank you, the sentence was adjusted in line 76.

Lines 83-84: Poor sentence structure, they describe their study but also present conclusions. Thank you, the sentence was adjusted.

Methods:

Lines 108-115: The authors should reference where they obtained these definitions of baseline, exacerbation, recovery and treatment. Thank you, a reference was included in line 107.

Lines 119: Fragment sentence. Thank you, the sentence was excluded.

Lines 120: More discussion around the control group in the study by Hahn et al is required in the methods briefly--including what defined "healthy" and if any exclusion criteria were applied. Thank you for the suggestion, however the control group was excluded.

Line 132: This is unclear--where sputum collected in triplicate on each of those days (0, 42, 84) OR was it one sample on each of these days? Thank you, the sentence was adjusted in line 124.

Results:

Line 216: Can the authors comment more (perhaps in the methods) on CF diagnosis in Brazil? In North America this done by newborn screening, but the authors imply that 31 had an early diagnosis before age 2. More clarity would be helpful to international audiences. Patients were confirmed with CF by a sweat test and CFTR gene screening (lines 98-99 of methods). In addition, one sentence regarding diagnosis in Brazil was added in discussion section (Line 360-367).

Lines 220: Define eutrophic, unclear what this and grades of malnutrition are. Anthropometry is a useful tool for grading malnutrition (reference 1) and dates demonstration of the correlation between severity of underweight for age and risk of death (more pulmonary exacerbations and major risk of hospitalization (reference 2). The publication by WHO opened the way to validation of different indicators in terms of their ability to predict risk of death in different geographical or emergency situations with reference to a globally accepted database (reference 3). References were added to the text in lines 216 and 217.

1. Duggan MB. Anthropometry as a tool for measuring malnutrition: impact of the new WHO growth standards and reference. Ann Trop Paediatr. 2010;30(1):1-17. doi: 10.1179/146532810X12637745451834. PMID: 20196929.

2. Smyth AR, Bell SC, Bojcin S, Bryon M, Duff A, Flume P, Kashirskaya N, Munck A, Ratjen F, Schwarzenberg SJ, Sermet-Gaudelus I, Southern KW, Taccetti G, Ullrich G, Wolfe S; European Cystic Fibrosis Society. European Cystic Fibrosis Society Standards of Care: Best Practice guidelines. J Cyst Fibros. 2014 May;13 Suppl 1:S23-42. doi: 10.1016/j.jcf.2014.03.010. PMID: 24856775.

3. Weir CB, Jan A. BMI Classification Percentile And Cut Off Points. 2021 Jun 29. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan–. PMID: 31082114.

Line 224: Should put percentage of patients next to number. Thank you for your suggestion. Percentage was added in lines 221-223.

Lines 226: Are "both organisms in association" on the SAME culture or just a history of both? Both organisms were isolated from the same culture sample but in different culture media.

Line 233: I am assuming the authors mean relative abundance but this should be clarified. Thank you, the sentence was corrected.

Lines 235: The authors need to expand on these results--was there assay a dichotomous yes/no or were there grades of biofilm development that could be scored? Only the dichotomous analysis, presence or absence, was used, considering that by visual analysis the interpretation of intensity (+/++ and +++) can be subjective, especially without specific controls for each of these categories. Lines 232-234.

Lines 238-239: This is very well known in the literature and not required in the results. Thank you for your suggestion, the sentence was excluded.

Lines 243: Are these ASV's since the authors used the dada2 protocol? If so they should consider presenting their data at the collapsed genera level such to not split ASV (i.e. two Prevotella are listed) Thank you for your suggestion, the sentence was adjusted and only genera was listed.

Lines 247-249: This is very much lacking in detail. How was this analysis done? Was it a multivariate model? Where are the statistics or statistical methodology? Thank you for your suggestion, the sentence was adjusted, and details were included in the section of material and methods.

Lines 250-252: Again, unclear is. Is it they had to be BOTH culture AND most abundant or either or? I also find it suspect that each had 20 samples per group--more clarity is required. Why did the authors pick Pseudomonas and Staphylococcus? They stated that the most abundant genera were mostly anaerobic--so what is the rationale for this? If it is to evaluate classic pathogens, why exclude Haemophilus which appears to be prevalent and abundant? I do not see a clear hypothesis. Thank you, the sentence was adjusted, and details were included in line 249-252.

Lines 265: The authors need to expand how they got to the species level, again by ASV? According to your recommendation we have removed the control group, so, the figure 3 was removed.

Lines 281-285: This is absolutely incorrect. The authors have not shown any statistical analysis to evaluate for confounders before concluding that Staphylococcus is contributing to underweight status. There is lacking of evidence to back up such a sweeping conclusion. Thank you, the sentence was adjusted in line 269-272.

Lines 286-287: Is this nebulizer chronic therapy?? Again more details. The treatment of lung disease in cystic fibrosis includes nebulization of various medications that are key to improve lung health, and an inhaler system is essential for all patients with cystic fibrosis. All patients in the Pseudomonas group (except one patient) received antimicrobial treatment against Pseudomonas spp, in other words, chronically inhaled antibiotic to reduce bacterial growth and the frequency of exacerbations. Lines 274-275.

Lines 296-298: I find it unusual their Pseudomonas group had BETTER clinical outcome when multiple studies over years clearly show worse outcomes upon acquisition of Pseudomonas. The authors need to postulate in the discussion why their results differ from multiple well-conducted studies. Thank you for suggestion, some points were addressed in discussion section.

Lines 316-332: Again I am unclear what this data is meant to show. It is clear the dominant groups would differ--what is the hypothesis? Our data mean to analyze the clinical variables in function of these two groups. A different approach to traditional works.

Discussion:

Overall, I found the discussion weak and unable to support many of their conclusions for the reasons cited in the results. Specific examples include: lines 377-388 with no discussion around confounding variables.

Many of the references are not appropriate or up to date to support the conclusions stated--such as reference 32. Overall, I do not see a clear hypothesis or understanding of how the data contributes to the literature. It was also extremely unclear why the authors described a longitudinal prospective study but then did no work on this and rather became cross-sectional.

Overall significant issues are present and needs careful attention.

Thank you for your considerations. Some points were addressed in discussion section. The objective was to carry out a longitudinal prospective study, however the microbiota data were very different between patients. We performed various statistical analyses without any significant result. Therefore, we opted for a different approach, to group patients by the dominant pathogen observed in the microbiota and compare the clinical variables among these two pathogen groups, Staph and Pseud. We agree that the approach is not common in this area; however it was the only option left to take advantage of this data. Thus, this work in not a “longitudinal prospective study”.

Reviewer #2:

In the study presented here, authors Kussek et al. show data on the respiratory microbiota of children with cystic fibrosis in Brazil. 34 children with CF are included in the study, and samples are collected at 3 different time points for comparison. Relationships between clinical variables (lung function scores, BMI, etc.) and abundance of dominant CF respiratory pathogens, namely S. aureus and P. aeruginosa, are investigated. The authors conclude that S. aureus correlates with worse clinical outcomes in their pediatric CF population, and they identify potential virulence genes in S. aureus and P. aeruginosa metagenomic data.

The data presented on this population of children with CF is valuable and addresses important questions about how presence of CF bacterial pathogens relates to patient exacerbations and clinical outcomes. The manuscript is overall well-written, and the strengths and weaknesses of this work is well described in the discussion section. This would be a valuable dataset to publish, if concerns raised below are addressed:

Thanks you for your constructive suggestions. Each question was answered in red color.

Major concerns:

A major issue with this work is that healthy control data used for comparison is from a previous publication by a different group who conducted their study in the US (lines 115-121). Samples from healthy children in the Hahn et al. study were collected from a different site in the respiratory tract (oropharynx) than used in this manuscript, and data were obtained by sequencing samples from oropharyngeal swabs, not induced sputum samples. OP swabs have not been reported to accurately reflect the lower respiratory microbiome, and there may also be regional differences in respiratory microbiota in healthy controls in distinct geographic locations like the US and Brazil. For these reasons, making direct comparisons between these datasets is not possible, and healthy control data should be removed from figures and tables presented here. According to your recommendation we have removed the control group, so, the figure 3 was excluded from the manuscript.

The new data collected for this study on the microbiome of children in Brazil with CF is valuable on its own. It would be appropriate compare and contrast how these findings relate to previous studies with healthy control groups of a similar age in the discussion section, but not in the results. It would be informative to compare the S. aureus- and P. aeruginosa-dominant groups to samples where neither of these organisms was the abundant species in Fig. 2 and Fig. 3, rather than making the healthy control comparisons using data from the Hahn et al. study. According to your recommendation we have modified the figure 2, the healthy control was excluded from the manuscript.

For analyses in Fig. 2, 20 samples per group with greater than 50% relative abundance of S. aureus and P. aeruginosa were selected. If not all samples meeting this criteria were compared, The selection criterion was the minimal number of identified samples by culture (20) in both groups (Staphylococcus and Pseudomonas), how were representative samples chosen? Are samples evaluated here from the same patients whose clinical variables (FEV and FVC) are compared in Figure 4? Yes, they are the same samples compared in figure 4, now figure 3. The value from these variables is shown in Table S1.

The NMDS plot in Fig. 6 does not show individual data points for samples, so interpreting how ellipses relate to clustering of the different groups is not possible. It is confusing how four clinical variables can be included here in a plot with only two axes. It would seem correct to instead separate the clinical variables into different plots where 3 variables are compared in each and show multiple plots to make comparisons. Non-metric Multi-dimensional Scaling (NMDS) is a way to condense information from multidimensional data (multiple variables/species/OTUs), into a 2D representation or ordination. In this ordination, the closer two points are, the more similar the corresponding samples are with respect to the variables that went into making the NMDS plot. In addition, several works used this approach, for example, the work of Tassi et al, 2018 “The biogeochemical vertical structure renders a meromictic volcanic lake a trap for geogenic CO2 (Lake Averno, Italy)” plotted more than 10 variables in a unique figure. Thus, this approach is scientifically validated.

Minor concerns:

Lines 29-30 and 74-77, There is not a concrete link between either P. aeruginosa or S. aureus and exacerbation in CF, although many groups have looked at this and presence of bacteria has been positively correlated with other outcomes (i.e. P. aeruginosa infection and end-stage lung disease). Would consider walking back language in these statements. Lines 32-33, The data presented is from induced sputum samples obtained by inhalation of nebulized hypertonic saline, which would provide information about lower respiratory tract infections and microbiota. However, the abstract states that upper respiratory microbiota are evaluated, which is not tested here. This should be changed to “lower respiratory microbiota.” According to your recommendation we have rewrote this sentence.

Line 53, Rather than stating “CF beings early in life…” it may be more accurate to say “Complications of CF disease begin early in life According to your recommendation we have rewrote this sentence in line 54.

”Line 60, Does “its mutation class” refer to CFTR mutations? Line 64, Would remove the word “all” from statement that “… all pulmonary distal airways are inaccessible.” According to your recommendation we have rewrote this sentence, the word “all” was also removed.

Lines 244-245, How is the “core community” defined? Based on Figure S3, would this be taxa identified at all sampling periods, and/or in all samples? Yes, all sampling periods, and/or in all samples, according to your recommendation we have rewrote this sentence.

Figure 4, It would be helpful to include individual data points for comparison of sample groups in bar graphs. Considering that standard deviation inclusion in the respective bars of each group, we believe that the figure is adequately informative. In addition, the figure was chance a new figure (Figure 3).

Lines 286-287, Was it evaluated if receiving antimicrobial treatment led to significant changes in P. aeruginosa relative abundance at subjects’ next visits post-treatment? This would be a very interesting relationship to investigate. We only have data from three visits, we haven´t got following up post-treatment data.

Lines 440-453, It’s discussed that other comparisons were made with longitudinal samples, but data was not included because a pattern was not identified. I would consider revising or removing some of this language; not all data is going to result in a pattern, and stating that a particular outcome is sought indicates potential bias in data interpretation. Variability in patient clinical data is common and expected. These findings actually echo much of what has been observed in other CF patient studies, and presenting results even if a specific correlation isn’t observed is still valuable. Thank very much for your positive considerations of this data.

Reviewer #3:

The manuscript describes a study undertaken to assess the upper respiratory tract microbiota of young patients suffering from cystic fibrosis (CF). Sputum samples collected from 34 CF patients were characterised and further used for isolating microbial cultures. Parallelly, the samples were also used to extract the DNA and perform 16SrRNA gene sequencing to analyze the entire microbial community present. Functional profiles of genes encoding virulence factors or antibiotic resistance were analysed and used for correlation with microbial data. The manuscript is well written and the authors have rightly described the few limitations of the study also highlighting the need to use next generation sequencing and other techniques to better assess the data. After thoroughly reading the article, I would like to make the following comments and suggestions. 1] Abstract: appears a bit general. It would be appropriate to include specific results obtained and conclusions drawn. Correct the typographical errors on Line 32 and Line 37.

Thanks you for your constructive suggestions. We have modified the text to clarity the manuscript from the introduction until discussion. In addition, each question was answered in red color.

The typographical errors were corrected.

2] Introduction is well written and identifies the need to carry out this study. Full name (Genus and species) of organism may be written on first appearance followed by genus (initial) and species full name.

Thank you, Genus and species nomenclature were corrected as your recommendation.

3] Materials and Methods-

i. Line 161-162- It would have been more appropriate to measure the absorbance to quantify the biofilm synthesised. Visual (Qualitative data) interpretations are less reliable.

We agree that the sensitivity of detection by absorbance is higher and that it would allow its quantification, however, the tube method is validated and here, we had a concordant result in controls, duplicate analyses and in the results between different observers.

ii. Line 163-164 – Please mention the strain numbers or source of Candida isolates used.

We used clinical isolates of Candida spp. belonging to the collection of microorganisms of our institution, previously characterized as biofilm producers by quantitative and qualitative assessment methods for biofilm growth (microtiter plate assay and tube method).

4] Results-

i. Line 233- How was the abundance of a particular pathogen determined?

Please see the rephrased sentence in the manuscript.

ii. Line 243- Prevotella 7? Appears to be a typographical error.

Thank you, the names were corrected as your recommendation.

iii. Line 300- Figure 4A and 4B can be merged.

Thank you, the figure was merged in a new figure 3.

iv. Line 341- How reliable is to predict the bacterial functional profiles on the basis of 16SrRNA gene sequence data alone? Justify. Thank you. We agree with you, it seems to be very superficial. However, the inference is based on the genomic bank of the microorganism identified in the 16S rRNA. Thus, metabolic pathways of each organism are raised from the database. We included this analysis because Staph and Pseud are very different microorganisms.

v. Were only 23 (13 S. aureus and 10 P. aeruginosa) isolates obtained on culturing sputum samples? Or was that the number tested for biofilm formation? Did you isolate both S. aureus and P. aeruginosa both from a single sputum sample? Thank you, the sentence was rephrased.

vi. The term Staphylococcus aureus and Staphylococcus spp. appears to be used quite interchangeably. Please correct the same. Same for Pseudomonas aeruginosa and Pseudomonas spp.

When we use Staphylococcus spp in the text, it is because in the analysis of 16S to cannot identify levels other than genera. However, the Group’s names were change to Staph and Pseud in the manuscript to avoid confusion.

5] Discussion is well written.

6] There are few grammatical and typographical mistakes in the manuscript which need to be carefully identified and corrected.

Reviewer #4:

General: Comments:It is an important non-interventional clinical trial in which sputum samples of young patients were evaluated for the relative prevalence of bacteria in their sputum. There are a lot if information collected however the way the data are presented makes the study findings and conclusions not clear and the significance of the findings not convincing. In fact, discussion of the results is stressing that the data generated simply confirms previously published studies. The analysis of the results needs a major revision after the patients are properly grouped according to their mutation status, sex and baseline FeV1. The results generated should be re-evaluated once the patients are properly divided according to their mutation status and their exacerbation status at the onset of the trial. The exacerbating patients can not be analyzed in the same group as stable patients. The authors state that FEV1 of 26% for some patients. It is unclear if this is a baseline FeV1 typical for the patients or recorded at the peak of exacerbation. If is a baseline FeV1 it would be exceptionally severe CF lung disease for so young patient (s). If this only happened for few days at the peak of exacerbation when patient experienced severe pneumonia it is completely different story. The FEV1 at onset should be measured when the patient is stable for 30 days. FeV1 can be measured also during the exacerbation of course to evaluate how severe impairment in lung function occurred during the exacerbation but the analyses of the findings should be done by separating the patients into different subgroups groups and interpretation of these findings should to be different when the stable patients are evaluated vs. when the exacerbating patients are evaluated. The exacerbating patients’ microbiota in the sputum should be evaluated separately than microbiota typical for steady state baseline microbiota typical for chronically infected patient on azithromycin and inhaled antibiotics. The way the data are presented does not brings much useful information. It is not clear what is a typical the microbiome at steady-state level in each patient and which microbiome changes occur during exacerbation.

Thanks for your constructive suggestions. We have modified the structure to clarity the text from the introduction until discussion. In addition, each question was answered in red color. Our objective was to carry out longitudinal prospective study, however the microbiota data were very different between patients. We performed various statistical analyses, without any significant result. Therefore, we opted for a different approach, try to group patients by the dominant pathogen observed in the microbiota and compare the clinical variables among these two pathogen groups, Staph and Pseud. We agree that the approach, is not common in the clinical area, however it was the only option left to take advantage of this data. Thus, this work in not a “longitudinal prospective study”.

Is there observed during exacerbations an increase in the CFUs of specific pathogens that were already present at baseline (with the relative composition of bacteria remaining the same), or during the exacerbation the relative composition of bacteria changes dramatically?

The analyzes performed by mutation type were not carried out due to the heterogenicity of the groups, in some cases, one mutation type was observed twice. It was also not possible due to the clinical condition because statistical analyzes would not have a significant “n”.

Considering the large number of patient variables and their subclassifications, the detailed description of all these particularities results unproductive. Therefore, we chose to describe in a generic way and submit the raw data in the supplementary material.

Major specific comments:

1. Patients ages ranges 8-23 contain both pediatric cases and adult cases so should not be classified broadly as pediatric. Table containing characteristics of each patient should be included that would provide information about each patient’s age, sex, the class of the mutations that each patient had should also be stated, specific CFTR gene mutations should be stated for each patient. The table was added as supplemental material in the original submission (S1 Table), data of sex was added too. Because the information is very large to include in the main text. CRP at the time of the initiation of the trial (for stable patients with no exacerbation for 30 days), amount of exacerbation in the year prior to the study at the initiation of the study. Steady-state FeV1 recorded when there is no exacerbation. Additional data prior to the trial initiation were not collected.

2. FEV1 is only informative as a characteristic of the patient when is recorded at baseline (30 days with no exacerbation and with not major increase in CRP level compared to the previous periods without exacerbation). The patients with active exacerbation at the onset of the study should be studied separately and once they get stabilized their baseline Fev1 should be recorded. At the exacerbation the FeV1 is very volatile and can drop dramatically but it does not represent the overall FeV1 characteristics of the patient. It is affected primarily by the sudden raise in the bacterial counts and sometimes also type of combination of infections.

This study was carried out in one of the largest cystic fibrosis centers in the state of Paraná and some patients have to travel for long distance to attend medical appointment, therefore we include as many patients as possible in the study. It would not be possible to carry out the study if we consider all the suggestions raised here. For this reason, we try to make the most of patient visits to the clinical center.

3. The biggest drop in the stable FEV1 usually occurs between age 18 and 30. It is not clear how many patients were in this age bracket? Did the authors seen a difference in baseline FeV1 and between 8–17-year-old patients compared to 18–23-year-old patients? When compared patients in this suggested cohort, the result was the following: FVC of 91 to patients among 8-17 years and FVC of 60 to patients among 18-23 years.

4. The number of patients positive for PA, SA and both should be stated, not only the percentage of the cohort L225-L228. How many patients experienced dual infection with PA and SA? (Table S1…. check if the information is there….). We chose to describe in a generic way and submit the raw data in the supplementary material. In addition, due to the type of our study, we do not have this information.

5. Is the relative higher abundance PA vs SA in both age group similar? According to your recommendation we have added this information in supplementary material. However, in the patients among 8-17 years the abundance was similar, on the other hand, in the patients among 18-23 years the abundance was great to Staphylococcus.

6. Methodology mentioned in 146-149 needs to be properly described in detail (buffers, duration of run, columns used, temperature, elution parameters, etc … ). The methodology should be written in a way that the method can be reproduced by other investigators just based on the descriptions provided. The protocol used should be included as a supplementary material. If there as space restrictions imposed by the journal, detailed protocols, including details, buffers, parameters of runs, how many times repeated, standards used should be appended as supplemental data. The way it is written is not informative at all and can not be even properly evaluated.

MALDI-TOF mass spectrometry is an equipment adapted for the diagnosis of microorganisms in the clinical routine. Samples are processed with a matrix that allows disruption and ionization of microbial proteins. Subsequently, the sample is placed on a plate with a small spot containing the isolated microorganism and placed on a plate that is then inserted by a laser into the equipment. but the equipment parameters are fixed

7. Primers sequences should be included 5’-3’ in addition to their positions that has been mentioned in L178. Name of these primers is a universal consensus. Nomenclature is related to a specific region in the gene and sense. Thus, the form of writing is correct.

8. The information about CFTR gene mutation presented as percentages should be at least referred to the Table in the supplement that contains specific information regarding CFTR mutations each patient included in the study had, so not only percentages would be presented but the number of patients for each mutation type combination should be clear. According to your recommendation we have added this information in the supplementary material.

9. The description of BMI does not take into consideration if the patients were males or females the range of BMI changes with age and sex, some children grow faster than other children so the way the BMI is presented in not informative at all. The BMI was obtained by comparing patients of the same age. In addition, when compared patients by sex, the result was the following: BMI of 18,34 in female and BMI of 18,55 in male.

10. In the discussion, the authors state that the Staphylococcal infections are not usually treated because there is not good treatment protocol. Authors findings suggest that the Staphylococcus species tested during this study were sensitive to oxacillin and vancomycin. It is not clear if these laboratory findings were used in the study to select proper treatment for Staphylococcal exacerbation or not. This should be at least mentioned.

Thank you for your suggestion. The sentence was rephrased to make it clearer. On the other hand, all S. aureus isolates were sensitive to oxacillin and vancomycin, lines 412. Our study did not aim to make interventions in the treatment and clinical management of patients, so the results of classical microbiology were not used to guide treatment.

11. The way the authors group the data into two groups over 50% Staphylococcus spp. or Pseudomonas spp. made the analysis of the data and resulting conclusions predictable and expected and diminished clinical significance of presented findings. Thank you very much for the observation, because of this, the limitations of our study were included in the discussion.

12. Lack of identification of specific microbe associated with apparent exacerbation is not well discussed; possibility of viral infections (frequently not diagnosed because there is no specific diagnostic test established, or/and the physician does not asks for more sophisticated tests to be done) and very slow growing or difficult to propagate in vitro bacterial infections (e.g mycobacterial species, such as M. abscessus complex). We agree that there are several other microorganisms related to the pulmonary exacerbation of patients. However, the methodology of our study does not allow specific identification of these pathogens, therefore we suggest in lines 448-452 further studies with a more specific methodology.

Minor editing errors:

Abstract: Sentence starting from Clustering…. and the sentence starting from “Had reduced….” Should be all one sentence L52: Authors state the 48% patients were delF508 – this is not clear – 48% had one allele of delF508 or both alleles with the same delF508 mutation? Thank you, the sentence was rephrased.

Submitted filename: Response to Reviewers.docx

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9 Aug 2022

Lower airway microbiota and decreasing lung function in young Brazilian cystic fibrosis patients with pulmonary Staphylococcus and Pseudomonas infection

PONE-D-22-04509R1

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11 Aug 2022

PONE-D-22-04509R1

Lower airway microbiota and decreasing lung function in young Brazilian cystic fibrosis patients with pulmonary Staphylococcus and Pseudomonas infection

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