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Airway microbiota signals anabolic and catabolic remodeling in the transplanted lung

Background: Homeostatic turnover of the extracellular matrix conditions the structure and function of the healthy lung. In lung transplantation, long‐term management remains limited by chronic lung allograft dysfunction, an umbrella term used for a heterogeneous entity ultimately associated with pathological airway and/or parenchyma remodeling. Objective: This study assessed whether the local cross‐talk between the pulmonary microbiota and host cells is a key determinant in the control of lower airway remodeling posttransplantation. Methods: Microbiota DNA and host total RNA were isolated from 189 bronchoalveolar lavages obtained from 116 patients post lung transplantation. Expression of a set of 11 genes encoding either matrix components or factors involved in matrix synthesis or degradation (anabolic and catabolic remodeling, respectively) was quantified by real‐time quantitative PCR. Microbiota composition was characterized using 16S ribosomal RNA gene sequencing and culture. Results: We identified 4 host gene expression profiles, among which catabolic remodeling, associated with high expression of metallopeptidase‐7, ‐9, and ‐12, diverged from anabolic remodeling linked to maximal thrombospondin and platelet‐derived growth factor D expression. While catabolic remodeling aligned with a microbiota dominated by proinflammatory bacteria (eg, Staphylococcus, Pseudomonas, and Corynebacterium), anabolic remodeling was linked to typical members of the healthy steady state (eg, Prevotella, Streptococcus, and Veillonella). Mechanistic assays provided direct evidence that these bacteria can impact host macrophage‐fibroblast activation and matrix deposition. Conclusions: Host‐microbes interplay potentially determines remodeling activities in the transplanted lung, highlighting new therapeutic opportunities to ultimately improve long‐term lung transplant outcome. Graphical abstract Figure. No caption available.

determinant in the control of lower airway remodeling posttransplantation. Methods: Microbiota DNA and host total RNA were isolated from 189 bronchoalveolar lavages obtained from 116 patients post lung transplantation. Expression of a set of 11 genes encoding either matrix components or factors involved in matrix synthesis or degradation (anabolic and catabolic remodeling, respectively) was quantified by real-time quantitative PCR. Microbiota composition was characterized using 16S ribosomal RNA gene sequencing and culture. Results: We identified 4 host gene expression profiles, among which catabolic remodeling, associated with high expression of metallopeptidase-7, -9, and -12, diverged from anabolic remodeling linked to maximal thrombospondin and plateletderived growth factor D expression. While catabolic remodeling aligned with a microbiota dominated by proinflammatory bacteria (eg, Staphylococcus, Pseudomonas, and Corynebacterium), anabolic remodeling was linked to typical members of the healthy steady state (eg, Prevotella, Streptococcus, and Veillonella). Mechanistic assays provided direct evidence that these bacteria can impact host macrophage-fibroblast activation and matrix deposition. Conclusions: Host-microbes interplay potentially determines remodeling activities in the transplanted lung, highlighting new therapeutic opportunities to ultimately improve long-term lung transplant outcome. (J Allergy Clin Immunol 2018;141:718-29.) Key words: Airway remodeling, fibroblasts, macrophages, matrix, microbiota Despite a marked improvement over the last 2 decades, lung transplantation remains associated with a lower survival rate (54% at 5 years posttransplantation in 2013), 1 compared with the rates for heart, kidney, liver, and pancreas transplantations. In fact, long-term management of the lung allograft faces a major, as yet incompletely characterized condition: chronic lung allograft dysfunction (CLAD), an umbrella term used to describe different phenotypes of chronic lung allograft rejection, for which a general consensus on the precise clinical definition is still lacking. The heterogeneity of CLAD phenotypes reflects the complexity of the underlying mechanisms, whereby inflammation combined with aberrant airway and/or parenchyma remodeling progressively impairs lung function, ultimately leading to retransplantation or death. 2 Consequently, there is an urgent need for increasing our understanding of CLAD pathophysiology and identifying biomarkers that are specific for the different CLAD phenotypes.
A rich and balanced airway microbiota has been linked with the maintenance of local tissue homeostasis. Perturbation in the composition of this microbial community, known as dysbiosis, has been reported in a variety of respiratory conditions, including lung transplantation. [3][4][5][6] We recently showed that there is a predominance of proinflammatory (eg, Staphylococcus and Pseudomonas) or low stimulatory (eg, Prevotella and Streptococcus) bacteria aligned with inflammatory or tissue remodeling gene expression profiles, respectively, in bronchoalveolar lavage (BAL) cells following transplantation, which suggests that the pulmonary microbiota may impact long-term graft survival. 7 In the present study, we sought to dissect host-microbe interactions in the context of the complex remodeling processes taking place following lung transplantation. We show that the transplanted lung presents distinct remodeling profiles, characterized by the expression of genes differentially involved in matrix synthesis or degradation. In addition, we provide evidence that the constituents of microbial communities dominated by these bacterial taxa fine-tune gene expression profiles in macrophages and fibroblasts-2 key cell types in the regulation of remodeling processes.

Patient sample collection and ethics statement
BAL samples were collected during surveillance bronchoscopies carried out during the first 14 months posttransplantation, from October 2012 to July 2014 in 6 Swiss and French transplantation centers, within the framework of the European project System prediction of Chronic Lung Allograft Dysfunction (SysCLAD). 8 The national and local ethics committees approved the study, and all subjects, whose details are provided in Table I, 9 gave written informed consent.
Detail on BAL fluid collection and processing is provided in the Methods in this article's Online Repository (available at www.jacionline.org). BAL fluid was submitted to cell differential determination, culture-dependent bacterial and fungal detection, and PCR-based detection of viral infection, according to routine clinical procedures. Negative control samples obtained on washing a ready-to-use endoscope with sterile saline were prepared following the same procedure.

RNA-seq and data analysis
Total BAL cellular RNA converted into cDNA libraries using the Illumina TruSeq RNA Sample Preparation Kit (Illumina, San Diego, Calif) was submitted to high throughput sequencing using the Illumina HiSeq 2500 System. Gene expression quantification was based on reads per kilobase of exon model per million mapped reads.
Real-time quantitative PCR for characterizing gene expression profiles BAL cellular RNA was extracted, cDNA synthesized, and amplification performed using custom oligonucleotide primers and probes (Microsynth, Balgach, Switzerland; see details in the Methods and Table E1 in this article's Online Repository at www.jacionline.org).
Bacterial 16S ribosomal RNA gene amplification, sequencing, and metagenome prediction The 16S content of BAL fluid DNAwas characterized either by quantitative PCR using previously reported primers specific to pan bacteria or by major phyla (Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, and Fusobacteria), or Illumina MiSeq sequencing using primers targeting the V1-V2 region, as previously described. 11 Sequences were processed and the resulting table of operational taxonomic units was used for metagenome prediction, using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) software 12 (see detail in the Methods in this article's Online Repository).
In vitro macrophage-fibroblast coculture model of matrix deposition Conditions for maintenance of human THP-1 monocytic cell line (ATCC TIB-202) and MRC-5 fibroblasts (ATCC CCL-171), and macrophage colony-stimulating factor 1-driven generation of THP-1-derived macrophages (THP-DM) are provided in the Methods in this article's Online Repository. Stimulation using the bacterial suspensions described above, at a density of 5 CFUs per eukaryotic cell at day 0, was performed for 30 hours (gene expression analysis) or 6 days (quantification of matrix deposition) in minimum essential medium (Thermo Fisher Scientific, Rochester, NY), supplemented with 70-and 400-kDa Ficoll (37.5 and 25 mg/mL, respectively; GE Healthcare, Little Chalfont, UK) and transforming growth factor-b1 ([TGF-b1], 5 ng/mL; eBioscience, San Diego, Calif) for optimal matrix deposition, along with a mixture of prednisolone (500 nmol/L; Sigma, St Louis, Mo)/FK506 (tacrolimus, 25 nmol/L; Enzo Life Sciences, Lausen, Switzerland)/mycophenolic acid (10 mmol/L; Tocris Bioscience, Ellisville, Mo). Penicillin and streptomycin (1000 U/mL and 100 mg/mL, respectively; Thermo Fisher Scientific) were used to prevent bacterial growth, and cell viability was assessed using a dedicated colorimetric assay (Cell Counting Kit-8, Dojindo Molecular Technologies, Rockville, Md). Immunostaining for collagen type 1 and fibronectin and automated image acquisition are detailed in the Methods in this article's Online Repository.

Principal component and statistical analysis
To analyze the distribution of BAL cell gene expression profiles, the target gene/reference gene copy number ratio was log-transformed and principal component analysis was performed using prcomp (scaled) routine in R (R Foundation, Vienna, Austria). 13 Multiple-group comparisons were performed using Kruskal-Wallis test with Dunn post hoc analysis and BAL positive fungal culture* Aspergillus sp (n 5 4), Penicillium sp (n 5 3), Candida sp (n 5 4) 13 (6.9) BAL positive viral PCR*à CMV (n 5 11), EBV (n 5 2), metapneumovirus (n 5 1), parainfluenza (n 5 1) 14 (13.2) posttransplantation differences in the relative abundance of the remodeling gene expression profiles were compared using chi-square test (R package PMCMR).

Experimental toolkit for determining remodeling gene expression profiles in BAL cells
In a previous study, we showed that a majority of BAL samples obtained from lung transplant recipients up to 14 months posttransplantation can be distinguished on the basis of the expression levels of a set of genes involved in inflammation and remodeling. 7 However, a substantial group representing 43% of total samples showed an intermediate profile and remained poorly characterized. Moreover, we noted an overlap across the whole sample set in the expression of the selected remodeling markersplatelet-derived growth factor D (PDGFD) and the tissue inhibitor of metallopeptidase 1/matrix metallopeptidase 12 (MMP12) ratio. These data highlighted the need to develop an analytical toolkit able to further dissect the complexity of remodeling gene expression profiles posttransplantation.
To this end, we employed 2 complementary approaches (experimental scheme detailed in Fig 1, A). A subset of 9 BAL samples, that represented an inflammatory, remodeling, or intermediate gene expression profile in our first-round real-time PCR, was analyzed by RNA sequencing. Data were filtered on the basis of adjusted P value (.05 threshold) and ranked by fold-change. In parallel, we selected 6 GO terms linked to remodeling (see Fig 1, B for details) and interrogated the GO database using the application AmiGO version 2.3, 10 generating a list of 627 candidate genes. Table II presents the restricted list of 11 remodeling genes obtained after combining the 2 approaches, and further assessing potential candidates on the basis of a literature survey on the remodeling-fibrosis axis, in the context of various respiratory conditions. Real-time PCR validation analysis indicated that expression of the selected genes in our initial set of 9 BAL samples was associated with a widespread distribution of corresponding eigenvectors, as obtained by principal component analysis, consistent with implications in diverse remodeling-related activities (Fig 1, C). Indeed, the corresponding encoded proteins have been linked to multiple aspects of remodeling, including matrix composition, accumulation and degradation. [14][15][16][17][18][19][20][21] Four host remodeling gene expression profiles prevail in the transplanted lung To gain further insight into remodeling gene expression profiles posttransplantation, we analyzed by real-time PCR 189 BAL samples obtained from 116 patients between 0.5 and 24 months posttransplantation (see Table I for details) 9 using our new analytical toolkit. Principal component analysis (Fig 2, A) and hierarchical clustering (Fig 2, B) Table II for details) in the initial subset of 9 BAL samples (dots). tested (Fig 2, C). Anabolic remodeling was characterized by maximal expression of thrombospondin 1 (THBS1) and PDGFD, 2 factors previously linked to TGF-b-mediated repair in different experimental and clinical settings (Fig 2, C). 20,22 In contrast, expression of several metallopeptidases (MMP7, MMP9, and MMP12), typically associated with inflammation and matrix degradation, distinguished the catabolic remodeling group. This latter profile was also linked to a high expression of additional remodeling markers, including the matrix constituents collagen type VI a-2 and fibronectin 1, the growth-promoting insulin-like growth factor 1 (IGF1), and the matricellular proteins osteopontin (secreted phosphoprotein 1 [SPP1]), chitinase 3like 1 (CHI3L1), and IGF binding protein 2, all involved in the regulation of matrix turnover (Fig 2, C). Spearman correlation analysis confirmed these associations, with a coefficient (r) ranging from -0.27 (PDGFD vs SPP1) to 0.78 (MMP9 vs CHI3L1) indicating negative and positive correlation, respectively (see Fig E1 in this article's Online Repository at www.jacionline.org). We next observed that the different remodeling gene expression profiles identified were linked to distinct kinetics following transplantation (P < .05 by chi-square test) (Fig 2, D). Specifically, low remodeling was almost limited to the first 12 months posttransplantation, while the intermediate profile predominated in each of the 4 time windows considered (Fig 2,  D). We further observed that catabolic remodeling peaked between 3 and 6 months, clearly preceding the maximal relative frequency of anabolic remodeling, from 12 months onward (Fig 2, D). This latter divergence in the kinetics of catabolic versus anabolic remodeling was confirmed when we considered 87 combinations of paired samples obtained from 34 patients, who were lavaged multiple times (median: 3, range: 2-6) (  Table E2 in this article's Online Repository). A schematic representation of these longitudinal transitions between 2 different remodeling profiles further highlighted the marked difference between the catabolic and anabolic profiles, testified by a single direct transition (Fig 2, F). In contrast, the intermediate remodeling profile was often connected to either the low, anabolic, or catabolic remodeling profile, which is consistent with a central position (Fig 2, F). Furthermore, we observed a substantial degree of stability in remodeling gene expression over time. Indeed, 34 paired samples (39%) were linked to a stable profile, while 52 others (61%) showed a profile transition. Moreover, when further focusing on 14 patients who provided from 4 to 6 BAL samples (median: 4.5, interquartile range [IQR]: 4, 5) over a range of 5.5 to 21 months (see details in Table E2 in this article's Online Repository at www.jacionline.org), we found a median number of 2 profiles (IQR: 2.0, 2.3). Here, the relative frequency of paired samples with a stable profile decreased from the intermediate, anabolic, catabolic, to low remodeling background (50%, 23%, 15%, and 12%, respectively). Overall, these observations support the existence in the transplanted lung of distinct remodeling activities, differentially interconnected, and regulated in a time-dependent manner.

Relation between airway microbiota composition and host remodeling gene profiling
We previously reported that the airway microbiota composition varies in concert with BAL cell gene profiling posttransplantation. 7 In particular, we showed that dysbiosis, defined by a strong predominance of a single phylum exceeding 70% of relative abundance, was associated with a high expression of 2 contrasting sets of genes, linked to either inflammation or remodeling, depending on the predominant phylum, while more balanced bacterial communities aligned with a neutral gene expression profile. We therefore investigated whether the airway microbiota composition aligned with the 4 host remodeling gene expression profiles identified in the present study, with a special interest in the contrasting catabolic and anabolic profiles. For this purpose, we relied on a combination of molecular analysis and culture, which proved complementary in distinguishing the composition of the airway microbiota associated with a catabolic remodeling gene expression profile, versus that linked to a low, intermediate, or anabolic profile. Specifically, PCR amplification of the 16S ribosomal RNA (rRNA) gene using phylum-specific primers indicated that dysbiosis observed in 37% of total BAL samples was increased when driven by Firmicutes or Actinobacteria, and decreased when Bacteroidetes predominated, on a catabolic remodeling background (Fig 3, A). Moreover, sequence analysis at genus level underscored the association of catabolic remodeling with Staphylococcus, Corynebacterium, Stenotrophomonas, and Haemophilus (Fig 3, B). In contrast, a microbial community comprising Prevotella, Streptococcus, Veillonella, and Neisseria was poorly represented in this catabolic remodeling context, while strongly predominating in association with low, intermediate, or anabolic remodeling (Fig 3, B). These specificities in the airway microbiota composition linked to host catabolic remodeling gene expression profiling were also accompanied by a reduced diversity compared with the 3 other remodeling profiles (Fig 3, C). Assessment of positive cultures confirmed Staphylococcus spp and Corynebacterium spp, and additionally included Pseudomonas spp, as part of the bacteria primarily linked to a catabolic remodeling profile (Fig 3, D). In contrast, BAL samples tested positive for oropharyngeal flora, which typically includes bacteria of the genera Prevotella, Streptococcus, Veillonella, and Neisseria, 3 predominated in association with an anabolic remodeling gene expression profile (Fig 3, D).
To explore further the links between the airway microbiota composition and host gene expression, and given the early onset of the catabolic remodeling profile, versus the late onset of the anabolic remodeling profile, we next determined the relative abundance of the different microbiota states within 4 time windows posttransplantation (Fig 3, E). Here, we found that microbiota dysbiosis was more likely to occur during the first 6 months posttransplantation when driven by Firmicutes, while becoming more frequent over time when driven by Bacteroidetes, Log10 gene expression Log10 gene expression J ALLERGY CLIN IMMUNOL VOLUME 141, NUMBER 2 thus aligning with the kinetics of catabolic and anabolic remodeling, respectively. Furthermore, we applied PICRUSt analysis to gain insight on the predictive metagenome functions of the bacterial communities linked to the 4 remodeling profiles. 13 PICRUSt links operational taxonomic units, as identified by 16S rRNA gene sequencing, to Kyoto Encyclopedia of Genes and Genomes (KEGG) genes, their corresponding KEGG orthologs (KOs) and, ultimately, functions. Global analysis of the predicted metagenome indicated a segregation of the microbial communities found on a catabolic remodeling background, which especially differed from the communities associated with an anabolic remodeling profile (Fig 3, F). To investigate potential differences with respect to host remodeling more specifically, we next considered a subset of 159 KOs related to bacteriamatrix interaction and/or protein degradation. We found that 24 genes were significantly differentially represented (threshold set to log 2 fold-change >2) within the communities associated with a catabolic, compared with an anabolic, remodeling profile (Fig 3, G). Of note, 23 of those genetic markers, which included, however not exclusively, virulence factors linked to infections of various etiology, including S aureus and P aeruginosa, were enriched (median log 2 fold-change: 6.1, IQR: 2.3, 10.3; adjusted P value < _ .01) in the communities associated with a catabolic remodeling profile (Fig 3, G).

Host-microbe associations and the underlying clinical situation
The relatively limited follow-up time in our study did not allow us to look for associations between the observed features in host remodeling gene expression or microbiota composition and the onset of chronic rejection. Moreover, we found no link with the   Table E3 in the Online Repository at www.jacionline.org). In addition, when considering samples with a histologic diagnosis of airway inflammation (lymphocytic bronchiolitis, B grade), we found only a slight increase between the percentage of samples with a catabolic remodeling signature versus those of samples with a low, intermediate, or anabolic profile (21.4% vs 11.4%, 10.9%, and 15.4%, respectively) (see Table E3 in the Online Repository). However, confirming our previous findings, 7 Firmicutes-, Proteobacteria-, and Actinobacteria-driven dysbiosis, rather than the absence of dysbiosis or Bacteroidetes-driven dysbiosis, was found to be linked to histologically determined airway inflammation (27.8%, 15.9%, and 4.8%, respectively) (see Table E3 in the Online Repository).
To assess potential links among host remodeling, microbiota states, and inflammation directly in the BAL, we next looked at the cell differential and found a marked enrichment in neutrophils, a hallmark of acute inflammation, accompanied by a corresponding relative decrease in macrophage and lymphocyte counts, on a catabolic remodeling background (Fig 4, A). Consistently, we also observed a stronger expression of the inflammation marker genes COX2 and TNF-a (Fig 4, B) in this setting. These observations suggested that the microbial communities linked to catabolic remodeling exhibit increased inflammatory properties in comparison to the principal members of the community dominated by Prevotella, 7,23 as previously reported.
Given that the bacterial genera associated with catabolic remodeling comprise common respiratory pathogens, we next aimed to evaluate the links between host remodeling-microbe associations and the diagnosis of infection. For this purpose, we focused our attention on a subset of 29 BAL samples obtained from patients who presented with clinical evidence of infection and had a positive result in BAL culture by routine microbiological examination and/or microbiota dysbiosis detected by 16S rRNA gene amplification. BAL samples with catabolic and anabolic remodeling gene expression profiles aligned with maximal and minimal rates of clinical infection, respectively (Fig 4, C). Moreover, when considering all of those samples associated with a clinical suspicion of infection, we found a striking difference in the bacteria identified by culture and/or type of detected dysbiosis, depending on the remodeling context (Fig 4, D). Hence, combined with the information we obtained on the kinetics of gene expression profiles (Fig 2, D and E) and microbiota states (Fig 3, E and F), this dataset indicated that the early acquisition of a catabolic remodeling profile and dysbiosis driven by highly stimulatory bacteria, is linked to inflammation and a more frequent association with clinical infection. In contrast, the clinical implications of the coincident anabolic remodeling profile and dysbiosis driven by low stimulatory bacteria, which are likely to be expressed later following lung transplantation, remain to be defined.

The constituents of airway microbial communities set the balance between anabolic and catabolic remodeling
The identification of anabolic and catabolic gene expression profiles linked to different airway microbiota compositions raised the possibility that the extracellular matrix turnover in the transplanted lung is differentially influenced by the constituents of local bacterial communities. To address this, we used an in vitro model system that exploits the microbial sensing and proremodeling capacities of THP-DM and MRC-5 fibroblasts to compare the direct effects of bacterial mixes on remodeling   Fig E2 in the Online Repository). In this setting, bacteria identified in lung transplant recipients on a catabolic remodeling background (a mix of S aureus and P aeruginosa) induced a globally distinct remodeling gene expression profile in macrophage-fibroblast cocultures, as compared to the representatives of the community linked to anabolic remodeling (P melaninogenica and S pneumoniae) (Fig 5, A). Specifically, Staphylococcus and Pseudomonas induced maximal expression of MMP7, -9, and -12, while Prevotella and Streptococcus were linked to higher THBS1 expression, 2 features aligning with catabolic and anabolic gene expression profiling in BAL cells of lung transplant recipients, respectively (Fig 5, B). Staphylococcus and Pseudomonas were more potent in repressing expression of the  marker of fibroblast to myofibroblast differentiation, a-smooth muscle actin, along with that of the matrix components collagen type 1 a1and fibronectin 1 (Fig 5, B). These divergent gene expression profiles were ultimately reflected by a marked decrease in matrix deposition linked to Staphylococcus and Pseudomonas versus Prevotella and Streptococcus exposure, as determined by collagen type 1 and fibronectin immunostaining (Fig 5, C and D).
Consequently, this dataset underscored the critical role of bacterial stimulation in the maintenance of homeostatic matrix turnover, suggesting that the detrimental impact of airway microbiota dysbiosis following transplantation may consist of exaggerated anabolic or catabolic remodeling processes.

DISCUSSION
The view of the lower airways representing an ecosystem implies that host cells and the constituents of the microbiota vary in a coordinated manner, particularly in the case of a breakdown in local homeostasis. Accordingly, different microbial communities have been observed in association with lung diseases such as asthma, chronic obstructive pulmonary disease (COPD), and idiopathic pulmonary fibrosis, versus the healthy state, with further changes prior, during, or following exacerbations. [4][5][6]23,24 The ecosystem associated with the transplanted lung is shaped by the early and continuous implementation of immunosuppression and the preventive or therapeutic use of antibiotics. We have previously reported that this lung habitat is linked to distinct microbial communities, which can influence macrophage gene expression. 7 The present study aimed to discriminate between anabolic and catabolic remodeling following lung transplantation, given the contrasting implications for graft fate these mechanisms may have. In addition, we investigated the composition of lower airway microbial communities on the different remodeling backgrounds and addressed the impact of bacterial stimulation on remodeling using an in vitro system of matrix deposition.
Beside their implication in homeostatic matrix turnover, all of these factors are involved in the control of lung injury, where they function to ensure a time-dependent sequence of inflammatory and remodeling processes, which ultimately lead to tissue repair. Likewise, they have been linked to different respiratory conditions, where their production varies with disease progression. Hence, both the physiological and pathophysiological functions of these factors appear to be orchestrated in a time-dependent manner. In this respect, our study, supported by longitudinal data, shows marked differences in the kinetics of the 4 remodeling profiles identified following transplantation. Of particular interest, the frequency of the catabolic remodeling profile was maximal between 3 and 6 months, while the anabolic remodeling profile peaked between 12 and 24 months posttransplantation. Several factors associated with the catabolic remodeling profile have been linked to inflammatory and/or acute conditions, such as acute lung injury (SPP1), 30 severe asthma (CHI3L1), 31 or COPD exacerbation (CHI3L1). 25 Moreover, the upregulated production of MMPs by inflammatory, epithelial, and stromal cells, and the associated release in the lung and circulation of matrix degradation products, have been observed in a large panel of respiratory conditions, including CLAD versus stable lung transplant recipients. [32][33][34][35] In contrast, THBS1 and PDGFD, 2 factors linked to the anabolic remodeling profile, have been reported to be part of a positive feedback loop with the prototypical profibrogenic factor TGF-b1, during tissue repair, 20,36 promoting fibroblast proliferation and myofibroblast differentiation. 36,37 Collectively, these observations suggest that the factors linked to the catabolic and anabolic remodeling profiles identified are active in distinct remodeling processes and/or stages.
The lower airway microbiota composition also varies over time posttransplantation. We observed that a maximal frequency of communities, strongly dominated by highly stimulatory bacteria (from 3 to 6 months), coincided both with the peak of bacterial infection and that of the catabolic remodeling profile. In marked contrast, the maximal frequency of communities dominated by low stimulatory bacteria (from 12 months onward), aligned with the kinetics of the anabolic remodeling profile, suggesting that the interplay among host cells, microbes, and the matrix represents a key determinant of the lower airway microenvironment. In this respect, data suggest that increases in BAL and/or circulating matrix degradation products coincide with shifts in airway microbiota composition during exacerbations in COPD and idiopathic pulmonary fibrosis. 5,6,34,38 Furthermore, matricellular proteins play important roles in innate immune mechanisms linked to both physiological bacterial colonization and infection, such as the regulation of bioactive antibacterial peptide release. 39,40 Our in vitro dataset indicates that S aureus and P aeruginosa, typically associated with proinflammatory microbial communities, trigger a stronger catabolic remodeling profile, in comparison to P melaninogenica and S pneumoniae. This is consistent with recent observations linking the 2 former bacterial species to increased BAL levels of matrix glycosaminoglycans, as compared to those associated with S pneumoniae, in acute exacerbation and stable COPD, respectively. 41 There are different ways bacteria could modulate matrix production in our in vitro system. Fig 5, A-D indicates that this occurred through stimulation of fibroblasts and macrophages, by shifting the gene expression balance between matrix components and metalloproteinases. In addition, bacteria could have impacted remodeling through direct degradation of the matrix. However, given the presence of antibiotics in the culture medium, which efficiently prevented bacterial metabolic activities, this second mode of action is likely to be insignificant in this setting. Consequently, we propose that the observed effects are linked to the higher stimulatory potential of the microbe-associated molecular patterns, such as peptidoglycan and lipopolysaccharide, which contribute to the structural properties of bacterial cells in Staphylococcus and Pseudomonas versus those in Prevotella and Streptococcus. Regardless of the mechanisms involved, these observations suggest that the net effect of host-microbe interactions on matrix regulation closely depends on the microbiota constituents. We propose that in the healthy state, the lower airway microenvironmental conditions are linked to low-grade matrix turnover and a balanced microbiota, which contribute to local homeostasis. However, in respiratory diseases associated with acute inflammation or fibrogenesis, local conditions linked to a catabolic and anabolic remodeling profile, respectively, promote the growth of specific bacteria, which in turn differentially impact matrix regulation.
There were limitations to this study. First, although our in vitro dataset revealed a link between remodeling gene expression levels and activities, we acknowledge that remodeling in the transplanted lung cannot be inferred solely from the identification of BAL cell gene expression profiles, given the importance of posttranscriptional regulation in this process. Nonetheless, the different remodeling gene expression profiles we identified correspond to distinct microenvironmental conditions, as corroborated by specific features in the lung microbiota composition and the underlying clinical state. Second, while the anabolic and catabolic remodeling profiles distinguished 2 well-delineated sample groups, as further confirmed by their association with contrasting bacterial communities, we found no such associations for the low and intermediate remodeling profiles. A possible underlying reason is that these 2 latter profiles reflect local conditions that are convergent enough to accommodate similar microbial communities. Alternatively, the analytical tools we used to characterize gene expression profiling and the composition of the airway microbiota might not have reached the power required to further dissect existing associations. Third, given that remodeling gene expression was measured from unsorted BAL cells, we could not ascertain the cellular source of gene transcripts, which would provide information about the underlying pathophysiological processes. Fourth, the posttransplantation follow-up period was not long enough to enable us to assess any distinction between stable transplant recipients and patients with CLAD. Given the progressive nature and prevalence of this major obstacle to long-term graft survival, further studies with a minimal 3-year longitudinal follow-up are required to elucidate a link between pulmonary bacterial dysbiosis, host gene expression profiling, and eventually pathophysiological tissue remodeling. Fifth, a direct assessment of the impact of antibiotics and immunosuppressive drugs was precluded by the broad use, large variability, and partly overlapping effects of the applied regimens, within the context of lung transplantation. Sixth, a full picture of the airway ecosystem should include an in-depth characterization of the viral and fungal microbiota constituents. Notwithstanding these shortcomings, our collective findings shed light on the role of host-microbe interactions in the control of matrix turnover after lung transplantation. Further increasing our understanding of the mechanisms implicated may help decipher the pathophysiology of CLAD and, by inference, that of other respiratory conditions associated with lower airway remodeling. Key messages d Four host remodeling gene expression profiles that align with different bacterial communities prevail in the transplanted lung.
d Typical bacterial pathogens that occasionally bloom during the first months posttransplantation appear to promote the degradation of the extracellular matrix, while bacteria belonging to a healthy steady-state microbiota permit fibroblast to myofibroblast differentiation and matrix deposition.
Patients underwent transoral or transnasal bronchoscopy. For BAL fluid (BALF) collection, the bronchoscope was wedged either in the middle lobe or lingula of the allograft and 100 to 150 mL of normal saline were instilled. Different fractions of collected samples were submitted to cell differential determination, culture-dependent bacterial and fungal detection, and PCR-based detection of viral infection, according to routine clinical procedures. Two fractions of 3 mL were stored at 48C and centrifuged within 3 hours at either 2,000g or 14,000g for 10 minutes, for future isolation of BALF cellular RNA and total DNA, respectively. Pellets were snap frozen, either after cell lysis in RLT buffer (Qiagen, Hilden, Germany) to preserve RNA integrity, or directly, and were stored at 2808C until further processing. Samples obtained on washing the endoscope with sterile saline prior an examination were prepared following the same procedure and were used as negative control samples.
BALF cellular RNA extraction and real-time quantitative PCR for gene expression analysis BALF cell lysates were transferred into a QIAshredder column (Qiagen) for homogenization and total RNA was extracted using RNeasy Mini Kit (Qiagen) according to the manufacturer's instructions. RNA concentration was determined using a Nanodrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, Mass) and reverse transcription was performed using iScript cDNA Synthesis Kit (Bio-Rad, Hercules, Calif). Characterization of BALF cell remodeling profiles was based on multiplex real-time PCR analysis of expression of a set of 11 genes (Table II). We used guanine nucleotide-binding protein, b-polypeptide 2-like 1 gene as a reference gene, given its high expression stability in BALF cells in both health and disease. E1 Custom oligonucleotide primers and probes (Table E1) were designed using National Center for Biotechnology Information (Bethesda, Md) primer blast software and were purchased from Microsynth (Balgach, Switzerland). Amplification was carried out using iQ Multiplex Powermix and a CFX96 Real-Time detection system. Absolute quantification was performed using the CFX Manager software 2.1 (all from Bio-Rad) based on values obtained with a set of purified amplicons used as standards.

Bacterial metagenome prediction
The operational taxonomic units table obtained from 16S rRNA gene sequencing data was normalized relative to the 16S rRNA gene copy number, and the metagenomic content was predicted using PICRUSt software. The predicted metagenome was exported as KOs for principal coordinate analysis on Bray-Curtis distance, using the cmdscale function in R. To investigate the potential functional capacity of the bacterial metagenome in respect to host remodeling, a subset of 159 KOs related to matrix interactions (search terms chondroitin*, collagen*, fibrinogen, fibronectin, hyaluron*) or protein/peptide degradation (search terms protease, proteinase, peptidase, *lysin, *pain, *staphin) were selected. All of these KOs were previously reported to be linked to bacterial genomes.

Bacterial cultures
Staphylococcus aureus (ATCC 25904) and P aeruginosa (ATCC BAA-47) were cultured on tryptic soy agar or in tryptic soy broth at 378C with 130 and 200 revolutions/min agitation, respectively (all media were obtained from Becton-Dickinson, Franklin Lakes, NJ, unless otherwise specified). Streptococcus pneumoniae (NCTC 7466) was grown on Mueller Hinton agar with 5% sheep blood or in tryptic soy broth at 378C, in absence of agitation in a 5% CO2 incubator. Prevotella melaninogenica (ATCC 25845) was cultured on Columbia agar with 5% sheep blood or in chopped meat broth (Remel Laboratories, Lenexa, Kan) at 378C under anaerobic conditions. For stimulation experiments, bacteria were grown for 16 hours, washed twice in PBS (BioConcept, Allschwil, Switzerland) at 3000g for 10 minutes at 48C, and resuspended in X-VIVO 15 medium (Lonza, Basel, Switzerland). Suspensions were finally diluted to reach a concentration of 4 3 10 23 (P aeruginosa and S pneumoniae) or 2 3 10 23 (S aureus and P melaninogenica) optical density at 600 nm corresponding to 10 6 CFU/mL.

In vitro macrophage-fibroblast maintenance and stimulation experiments
The MRC-5 (ATCC CCL-171) human fibroblast cell line was maintained in minimum essential medium with Earle's salts, supplemented with nonessential amino acids, sodium pyruvate, 10% (vol/vol) heat inactivated FBS and 100 U/mL penicillin and 100 mg/mL streptomycin (all from Thermo Fisher Scientific). The THP-1 (ATCC TIB-202) human monocytic cell line was maintained in RPMI 1640 medium supplemented with 10% (vol/vol) heat inactivated FBS, 20 mmol/L 2-mercaptoethanol, 100 U/mL penicillin, and 100 mg/mL streptomycin (all from Thermo Fisher Scientific). Incubation was at 378C in a humidified 5% CO 2 atmosphere. For generating THP-DM, 24-well plates were precoated with FBS for 60 minutes. THP1 cells were centrifuged at 300g for 10 minutes, resuspended in differentiation medium, which corresponded to maintenance medium supplemented with human recombinant Macrophage-Colony Stimulating Factor (Peprotech, Rocky Hill, NJ), FBS (20% final concentration) and 10 mmol/L HEPES, and were seeded into precoated 24-well plates at a density of 10 5 cells per well. Incubation was for 7 days, without medium change. To assess gene expression levels in macrophage-fibroblast cocultures in the presence or absence of bacteria, fibroblasts and THP-DM were seeded at a density of 40,000 and 20,000 cells/cm 2 , respectively, in serum-free minimum essential medium with Earle's salts containing TGF-b1 (5 ng/mL; eBioscience, San Diego, Calif), a mixture of prednisolone (500 nmol/L; Sigma, St. Louis, Mo)/FK506 (tacrolimus, 25 nmol/L; Enzo Life Sciences, Lausen, Switzerland)/mycophenolic acid (10 mmol/L; Tocris Bioscience, Ellisville, Mo), and penicillin and streptomycin (1000 U/mL and 100 mg/mL, respectively; Thermo Fisher Scientific). Bacterial suspensions were added 16 hours postseeding, at a total density of 3 3 10 5 CFU/cm 2 , which corresponded to 5 CFU per eukaryotic cell at day 0, and the effects of stimulation were assessed 30 hours later, when supernatants were removed and cells were lyzed in RLT buffer (Qiagen) to preserve RNA integrity. Cell viability was assessed 30 hours following the addition of bacterial mixtures into macrophage-fibroblast cocultures, using a WST-1-based colorimetric assay (Cell Counting Kit-8, Dojindo Molecular Technologies, Rockville, Md), according to the manufacturer's instructions.

In vitro assessment of matrix deposition
To optimize for maximal matrix deposition, macrophage-fibroblast coculture medium was supplemented with 70-and 400-kDa Ficoll (37.5 and 25 mg/mL, respectively; GE Healthcare, Little Chalfont, UK). E2 Cocultures were seeded at a density of 25,000 and 12,500 cells/cm 2 , respectively, in m-Slide 8-well ibi-Treat slides (Ibidi, Martinsried, Germany), and were incubated for 6 days without medium change, in the presence or absence of bacteria, and thereafter supernatants were removed and cells were fixed in 4% paraformaldehyde in PBS for 20 minutes, for subsequent immunostaining analysis.