Mucin-enriched environment shapes bacteriophage protection against Pseudomonas aeruginosa in airway epithelial cells

Mucin-enriched environment shapes bacteriophage protection against Pseudomonas aeruginosa in airway epithelial cells | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Mucin-enriched environment shapes bacteriophage protection against Pseudomonas aeruginosa in airway epithelial cells View ORCID Profile Daniel de Oliveira Patricio , Katri Niitti , View ORCID Profile Lucilene Wildner Granella , Valtteri Suokko , View ORCID Profile Gabriel Magno de Freitas Almeida , View ORCID Profile Lotta-Riina Sundberg doi: https://doi.org/10.1101/2025.10.17.683030 Daniel de Oliveira Patricio 1 Department of Biological and Environment Science, Nanoscience Center, University of Jyväskylä , Jyväskylä, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Daniel de Oliveira Patricio Katri Niitti 1 Department of Biological and Environment Science, Nanoscience Center, University of Jyväskylä , Jyväskylä, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lucilene Wildner Granella 1 Department of Biological and Environment Science, Nanoscience Center, University of Jyväskylä , Jyväskylä, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lucilene Wildner Granella Valtteri Suokko 1 Department of Biological and Environment Science, Nanoscience Center, University of Jyväskylä , Jyväskylä, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gabriel Magno de Freitas Almeida 2 The Norwegian College of Fishery Science, Faculty of Biosciences, Fisheries and Economics, UiT— The Arctic University of Norway , Tromsø, Norway Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Gabriel Magno de Freitas Almeida Lotta-Riina Sundberg 1 Department of Biological and Environment Science, Nanoscience Center, University of Jyväskylä , Jyväskylä, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lotta-Riina Sundberg For correspondence: lotta-riina.sundberg{at}jyu.fi Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Mucin hypersecretion, a hallmark of chronic respiratory diseases (CRD), creates a complex microenvironment that reshapes host immunity and microbial behavior. However, its impact on bacteriophage therapy remains poorly understood. Here, we demonstrate that, despite reducing Pseudomonas aeruginosa internalization, exogenous mucin increases bacterial-induced cytotoxicity and inflammation in airway epithelial cells, while driving CRD-like transcriptional changes, including hypoxia and stress responses. Under bacterial culture, mucin selectively downregulates bacterial virulence factors without impairing growth. P. aeruginosa -infecting bacteriophage DMS3vir retains full lytic activity in mucin-rich conditions and, in synergy with mucin, enhances protection against cytotoxicity in epithelial cells. DMS3vir also reduces IL-8 gene expression without triggering antiviral responses. Furthermore, mucin supplementation shapes phage-resistant P. aeruginosa phenotypes, altering colony pigmentation, pyocyanin production, and motility, influencing virulence trade-offs. These findings uncover the dual role of mucins as modulators of infection and sensitizers to phage protection, paving the way for optimized, mucosa-adapted phage therapies in chronic lung diseases. 1. Introduction Chronic respiratory diseases (CRD), including cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD) and asthma, are characterized by persistent inflammation, impaired mucociliary clearance, and recurrent airway infections 1 – 3 . A hallmark of these conditions is the hypersecretion of mucins, gel-forming glycoproteins such as MUC5AC and MUC5B, which structure the mucosal layer, trap pathogens, and help maintain epithelial integrity 1 – 5 . Increased mucin production by goblet cells can be influenced by various mediators such as pathogens, inflammatory responses, and xenobiotic exposure 2 . Mucin overproduction alters the physical and biochemical properties of the airway surface, creating a viscous, hypoxic, and oxidatively stressed microenvironment that disrupt immune balance and facilitates microbial colonization 2 , 6 – 10 . Pseudomonas aeruginosa , a key opportunistic pathogen found in chronic airway infections, thrives under hypoxic conditions. It contributes to epithelial injury and lung function decline through development of antimicrobial resistance, biofilm formation, and secretion of virulence factors regulated by quorum sensing (QS) 11 , 12 . The mucosal environment directly shapes P. aeruginosa behavior. For instance, mucin glycans have been shown to attenuate virulence by disrupting QS signaling and inhibiting biofilm formation 13 , 14 . Moreover, mucin hyper-concentration contributes to bacterial aggregation that increases antibiotic tolerance variability 15 , 16 . In addition to shaping microbial behavior, mucins are tightly linked to epithelial immune responses, particularly through the regulation of key pro-inflammatory cytokines 9 , 10 . Pro-inflammatory cytokines such as interleukin-6 (IL-6) and IL-8 (or CXCL8) play central roles during chronic respiratory diseases and are associated with mucin hypersecretion 1 , 17 . IL-8 is induced by pathogen-associated molecular patterns (PAMPs) in response to bacterial virulence factors and epithelial stress, acting as a chemoattractant for neutrophils and contributing to sustained inflammation and tissue damage by promoting excessive neutrophil infiltration into the airway lumen 18 , 19 . IL-6, in contrast, is a pleiotropic cytokine involved in acute-phase responses, often upregulated following inflammatory signals, recognition of PAMPs, and other secondary pathways 18 . Elevated levels of IL-6 and IL-8 have been consistently associated with disease severity, frequent exacerbations, and accelerated lung function decline in patients with chronic airway conditions 20 , 21 . The dual effects of mucin highlight a critical gap in our understanding of its influence on the outcome of bacterial infection and treatment. In particular, the effects of mucin-rich environments on modulating bacteriophage (phage), bacterial, and epithelial interactions remain largely undefined 22 – 24 . Phage therapy has re-emerged as a promising approach against multidrug-resistant bacteria due to its specificity, self-amplification, and minimal impact on commensal microbiota 25 , 26 . However, applying phages to mucus-dense tissues presents unique challenges, including limited diffusion, altered receptor accessibility, and potential immune interference 27 – 30 . The “Bacteriophage Adherence to Mucus” (BAM) model proposes that phages bind mucin glycans, increasing their concentration at mucosal surfaces and enhancing pathogen clearance 31 – 35 . Conversely, other studies suggest that mucins may act as a physical barrier, impeding phage diffusion and access to bacterial hosts 36 – 38 . In other bacterial models, such as Flavobacterium columnare , mucins have been shown to trigger bacterial protective stress responses or enhance adaptive mechanisms like CRISPR-Cas immunity 39 . These contrasting findings underscore the complexity of mucin-phage-bacteria interactions across different biological systems. Thus, the impact of mucins appears highly context-dependent, shaped by mucin type, microbial behavior, and infection dynamics 29 , 39 , 40 . In addition, little is known about how mucins influence bacterial evolution under phage pressure. Phage resistance commonly results in fitness costs or trade-offs in host bacteria, including altered motility, surface modifications, or reduced virulence 41 – 43 . Whether mucins mitigate or amplify these trade-offs, and how they shape the phenotypic and genotypic landscape of phage-resistant populations, remains to be determined. In this study, we used a cell culture model to investigate how a mucin-enriched microenvironment modulates epithelial responses, P. aeruginosa virulence, phage efficacy, and evolution of phage resistance. We show that exogenous mucin induces CRD-like transcriptional reprogramming in epithelial cells, enhances bacterial cytotoxicity and inflammation, and selectively represses bacterial virulence pathways. Despite this, mucin synergizes with bacteriophage DMS3vir to protect epithelial cells in a bacterial load-dependent manner without eliciting antiviral immune responses. Moreover, mucin shapes the phenotypic and genetic profiles of phage-resistant P. aeruginosa , affecting virulent traits and resistance trade-offs. These findings provide new insights into the tripartite interactions between epithelium, bacteria, and phages, in mucin-rich conditions, with implications for optimizing phage therapies in mucosal environments. 2. Results 2.1. Mucin enrichment induces CRD-like transcriptional remodeling in airway epithelial cells Mucus hypersecretion is a hallmark of chronic airway diseases such as COPD and CF 2 , 4 . To explore how a mucin-rich microenvironment influences epithelial gene expression, RNA sequencing was performed on A549 airway epithelial cells exposed to 0.2% porcine gastric mucin (PGM) for 18 h. Principal component analysis (PCA) revealed consistent intra-group clustering and clear separation between control and PGM-exposed groups, indicating a mucin-induced transcriptomic shift ( Fig. 1a ). Differential expression analysis identified 223 upregulated and 115 downregulated genes (log2 fold change > 0.5), and a stricter cutoff revealed 52 upregulated and 37 downregulated genes (log2 fold change > 1) in the PGM-exposed cells ( Fig. 1b ). The mucin-rich environment induced regulation of genes associated with stress and inflammation (response to hypoxia, unfolded protein, endoplasmic reticulum stress, tumor necrosis factor, oxidative stress), metabolic reprogramming (glycolytic process), cell adhesion, junction maintenance, epithelial to mesenchymal transition, and growth-factor signaling (EGF, TGF-β, and FGF) ( Fig. 1c, d ). These transcriptional changes are consistent with commonly observed in chronic lung disease 2 , 6 , 7 . Thus, exposure to exogenous mucin alone is sufficient to induce a CRD-like gene expression signature, offering a physiologically relevant platform to investigate epithelial responses and epithelial–pathogen interactions under mucosal conditions. Download figure Open in new tab Figure 1. Transcriptomic analysis of A549 cells exposed to mucin rich environment. (a) Principal component analysis (PCA) of global gene expression in A549 cells incubated with 0.2% porcine gastric mucin (PGM) or control medium for 18 h (n = 3 per group). Each point represents a biological replicate. (b) Volcano plot of differential gene expression between PGM-treated and control cells. Log2 fold change (x-axis) is plotted against the –log10 FDR-adjusted p-value (y-axis). Significantly regulated genes were defined by FDR > 0.5, with log2 fold change > 1 or > 0.5 (upregulated, red), and log2 fold change > -1 or > -0.5 (downregulated, blue). (c) Heatmap of significantly differentially expressed genes between conditions (FDR 1). Genes are hierarchically clustered and grouped into upregulated (top) and downregulated (bottom) sets. Columns represent biological replicates. Color scale indicates expression values. (d) Gene ontology of biological process enrichment analysis of upregulated (red) and downregulated (blue) genes. Bars represent significantly enriched biological processes, ranked by fold enrichment, with color intensity corresponding to statistical significance (–log10 FDR). 2.2. Mucin enriched environment enhances Pseudomonas aeruginosa cytotoxicity and amplifies epithelial inflammatory responses To investigate how mucin-rich environment alters bacterial virulence, the cytotoxicity of P. aeruginosa was assessed with infection in A549 epithelial cells using bacterial strains PA14 and 573. PA14 exhibited significant cytotoxicity at 10 4 CFUs, while strain 573 required a higher inoculum (10 6 CFUs) to elicit similar effects ( Fig. 2a ). Pre-exposure of A549 cells with 0.2% PGM significantly enhanced cytotoxicity induced by both strains at 4 h post infection, indicating that mucin enrichment sensitizes epithelial cells to bacterial attack ( Fig. 2b ). This effect was independent of exposure timing with mucins, as both pre-incubation and co-incubation with PGM led to similar increases of epithelial cell death ( Fig. 2c ). A similar trend was observed in HT-29 intestinal epithelial cells, where PGM exposure increased susceptibility to PA14-induced cytotoxicity ( Fig. 2d ), suggesting that this phenomenon is not limited to airway epithelial cells. Notably, PGM alone had no detectable cytotoxic effect on either cell line, underscoring its role in modulating epithelial-bacteria interactions rather than decreasing cell survival. To explore the underlying mechanisms, bacterial internalization was quantified in mucin-exposed cells. Surprisingly, PGM significantly reduced P. aeruginosa uptake in both A549 and HT-29 cells ( Fig. 2e, f ), revealing an inverse relationship between cytotoxicity and bacterial internalization. These findings suggest that mucin does not enhance bacterial invasion, but rather exacerbates epithelial cells susceptibility, possibly by amplifying the impact of secreted virulence factors. Download figure Open in new tab Figure 2. Mucin enrichment increases epithelial cytotoxicity and reduces bacterial internalization upon P. aeruginosa infection. (a) Bacterial cytotoxicity on A549 cells infected with P. aeruginosa PA14 and 573 strains for 4 h (n = 3). (b) Bacterial cytotoxicity on A549 cells pre-incubated with porcine gastric mucin (PGM) for 18 h prior to infection with PA14 or 573 (1 x 10 5 CFU). (c) Bacterial cytotoxicity on A549 cells pre-exposed (Pr) to PGM or co-exposed to PGM and PA14 for 4 h. (d) Bacterial cytotoxicity on HT-29 cells pre-incubated with PGM prior PA14 infection (1 x 10 5 CFU). 20% DMSO served as a positive control for cytotoxicity. (e) Bacterial internalization in A549 cells pre-incubated with PGM prior PA14 or 573 infections (1 x 10 5 CFU) for 1 h. (f) Bacterial internalization in HT-29 cells pre-incubated with 0.2% PGM prior PA14 infection (1 x 10 5 CFU) for 1 h. Quantitative data represent mean ± s.e.m. from at least two independent experiments. Statistical comparisons were performed using two-way ANOVA with multiple comparisons and Sidak’s post hoc test (a-e) , and unpaired two-tailed t-test (f) ; p-values and replicate numbers are indicated. Next, the impact of mucin-rich conditions on the expression of IL6 and IL8 , two key pro-inflammatory cytokines commonly elevated in CRD 9 , 10 , was assessed in A549 cells infected with P. aeruginosa . The IL8 expression was induced after 4 h of PA14 infection and further amplified in the presence of PGM, particularly at later time point ( Fig. 3a ). Both PA14 and 573 strains triggered IL8 and IL6 expression under mucin-enriched conditions ( Fig. 3b, c ), while PGM alone did not induce cytokine expression, indicating that the inflammatory amplification is infection-dependent. These trends were also observed in HT-29 cells, where PGM exposure enhanced IL8 expression during PA14 infection ( Fig. 3d ). The IL6 expression remained undetectable in HT-29 cells across all tested conditions (data not shown), consistent with previous findings 44 , 45 . Collectively, these results suggest that mucin-rich environments sensitize epithelial cells to bacterial virulence, amplifying both cytotoxic and inflammatory response without promoting bacterial invasion. Download figure Open in new tab Figure 3. Mucin rich environment enhances pro-inflammatory gene expression during P. aeruginosa infection. (a) Time-course analysis of relative IL8 mRNA expression in A549 cells pre-exposed to porcine gastric mucin (PGM) for 18 h prior P. aeruginosa PA14 infection (10 5 CFU). (b–c) Relative IL8 and IL6 mRNA levels in A549 cells pre-incubated with PGM and infected with PA14 or 573 (1 x 10 5 CFU) for 4 h. (d) IL8 mRNA expression in HT-29 cells pre-incubated with PGM and infected with PA14 (1 x 10 5 CFU) for 4 h. In all panels, cells were treated with 100 µg/mL TNF as a positive control. Quantitative data represent mean ± s.e.m. from at least two independent experiments. Statistical comparisons were performed using two-way ANOVA with multiple comparisons and Sidak’s post hoc test (a-d) ; p-values and replicate numbers are indicated. 2.3. Mucin enrichment selectively decreases quorum sensing and virulence gene expression in P. aeruginosa To evaluate whether mucin enrichment affects bacterial fitness, the growth of P. aeruginosa strains PA14 and 573 were monitored in the presence of 0.2% PGM. Growth curves showed no significant differences under PGM exposure ( Fig. 4a, b ). Additionally, neither strain was able to grow in nutrient-free condition supplemented PGM, confirming that PGM does not serve as a significant carbon or energy source ( Fig. 4c, d ). Although PGM did not influence bacterial growth, its impact on virulence gene regulation was notable. P. aeruginosa was exposed to PGM to determine whether mucin enriched condition alters bacterial virulence at the transcriptional level. Expression of quorum sensing (QS) and the virulence-associated gene algD , a key gene in alginate biosynthesis and biofilm formation, were quantified in both PA14 and 573 strains. Among QS genes, rhlI in PA14 and rhlR in 573 showed modest reductions, while expression of the other QS regulators remained unchanged ( Fig. 4e, f ). Notably, lasR and lasI transcripts were undetectable in strain 573 under all tested conditions, consistent with its reduced virulence phenotype ( Fig. 4f ). In both strains, exposure to PGM led to significant downregulation of algD , suggesting that mucin environment represses biofilm-associated pathways, rather than broadly suppressing QS. Pyocyanin production, a QS-regulated cytotoxin, was also evaluated. While overall levels varied over time, pyocyanin production by PA14 remained unaffected by PGM exposure ( Fig. 4g ). Taking together, these results indicate that while mucin-rich conditions do not impair bacterial proliferation, they can modulate transcriptional pathways associated with virulence. This underscores the complexity of epithelial-derived signals in modulating bacterial pathogenicity and highlights mucin as a context-dependent regulator of virulence gene expression. Download figure Open in new tab Figure 4. PGM does not serve as a nutrient source but modulates virulent gene expression in P. aeruginosa . (a–b) Bacterial growth curves of P. aeruginosa PA14 and 573 in LB medium supplemented with indicated porcine gastric mucin (PGM) concentration, measured by optical density at 600 nm (OD 600 ) over 24 h (n = 5). (c–d) Endpoint OD 600 readings of PA14 and 573 cultures incubated for 12 or 24 h in nutrient-free water (H 2 O) or LB media with increasing concentrations of PGM. (e–f) Relative expression of quorum sensing (QS) and virulence-associated genes in PA14 and 573 at 1 x 10 8 CFU following 4 h incubation in LB supplemented with PGM. ND = not detected. (g) Pyocyanin production by PA14 (1 x 10 8 CFU) in the presence of PGM. Values represent absorbance at 520 nm (OD 520 ). Quantitative data represent mean ± s.e.m. from at least two independent experiments. Statistical comparisons were performed using two-way ANOVA with multiple comparisons and Sidak’s post hoc test (a-g) ; p-values and replicate numbers are indicated. 2.4. Mucin-enriched environment enhances phage protection efficacy To evaluate how mucin enrichment influences phage–bacterium interactions, the ability of DMS3vir phage to suppress P. aeruginosa PA14 growth were tested. DMS3vir effectively inhibited bacterial proliferation in a concentration-dependent manner, although regrowth was observed after approximately 18 h, consistent with emergence of phage-resistant clones ( Fig. 5a ). Notably, the presence of 0.2% PGM was unable to interfere with phage-mediated bacterial suppression ( Fig. 5b ). Download figure Open in new tab Figure 5. Mucin enrichment enhances the protective activity of phage DMS3vir against P. aeruginosa infection. (a) Bacterial growth curves of P. aeruginosa PA14 (1 x 10 5 CFU) incubated with DMS3vir phage at different multiplicities of infection (MOIs) (n = 10). (b) Bacterial growth curves of PA14 (1 x 10 5 CFU) co-exposed with DMS3vir phage (MOI 1) and porcine gastric mucin (PGM) (n = 5). (c) Bacterial cytotoxicity on A549 cells pre-incubated with DMS3vir and PGM for 18 h, followed by infection with PA14 (1 x 10 5 CFU) for 4 h. (d) DMS3vir quantification of culture supernatants from the same experiment in (c) , collected after 4 h of infection. (e–f) Phage quantification from culture supernatants of A549 cells pre-exposed to PGM and DMS3vir prior PA14 infection at varying initial loads. (g–i) Bacterial cytotoxicity on A549 pre-exposed to PGM and DMS3vir, following PA14 infection at bacterial initial concentrations of (g) 1 x 10 5 , (h) 1 x 10 3 , or (i) 1 x 10 2 CFU for 24 h. Quantitative data represent mean ± s.e.m. from at least two independent experiments. Statistical comparisons were performed using two-way ANOVA with multiple comparisons and Sidak’s post hoc test (a-i) ; p-values and replicate numbers are indicated. To assess whether mucin enrichment affects phage protection in epithelial cells, A549 were co-exposured to 0.2% PGM and DMS3vir prior to P. aeruginosa PA14 infection. After 4 h, mucin-enhanced cytotoxicity was significantly reversed by phage pre-incubation, restoring epithelial cell viability to levels similar to non-mucin conditions ( Fig. 5c ). Quantification of viral particles by titration revealed that DMS3vir phage replicated significantly in the presence of bacteria, and this replication was unaffected by PGM ( Fig. 5d ). Extended incubation of 24 h confirmed that phage amplification remained stable regardless of mucin exposure or initial bacterial load ( Fig. 5e, f ). Interestingly, 24 h co-culture revealed that mucin enhanced the protective effects of DMS3vir on the epithelial cells in a manner that depended on the initial bacterial inoculum. At high bacteria density (10 5 CFUs), phage pre-incubation alone had limited impact, but when combined with PGM, epithelial cell viability improved modestly ( Fig. 5g ). In contrast, at lower bacterial inoculum (10 2 –10 3 CFUs), co-incubation with phage and PGM synergistically preserved epithelial viability, indicating a threshold-dependent enhancement of phage protection by mucin ( Fig. 5h, i ). Next, the influence of the phage on epithelial inflammatory responses in mucin-rich conditions was examined. As shown above, PGM alone amplified IL6 and IL8 expressions during PA14 infection ( Fig. 6a, b ). Interestingly, DMS3vir incubation selectively reduced IL8 expression regardless of PGM presence, while IL6 levels remained unaffected. Additionally, phage exposure did not trigger antiviral signaling pathways, as evidenced by unchanged IFNB expression (Fig. S1) and undetectable IFNL1 transcripts (data not shown). Download figure Open in new tab Figure 6. Phage DMS3vir selectively attenuates IL8 , but not IL6 , expression in P. aeruginosa -infected epithelial cells. (a-b) Relative expression of IL8 and IL6 mRNA of A549 cells pre-incubated with DMS3vir and porcine gastric mucin (PGM) for 18 h, followed by infection with P. aeruginosa PA14 (1 x 10 5 CFU) for 4 h. Quantitative data represent mean ± s.e.m. from at least two independent experiments. Statistical comparisons were performed using two-way ANOVA with multiple comparisons and Sidak’s post hoc test (a-b) ; p-values and replicate numbers are indicated. These results suggest that mucin-rich microenvironments enhance the protective efficacy of DMS3vir phage while not impairing its replication, especially at submaximal bacterial loads relevant for real life infections. Moreover, DMS3vir exerts pathway-specific immunomodulatory effects without triggering antiviral responses, highlighting its compatibility with mucosal environments. 2.5. Mucin-enriched environment modulates phenotypic trade-offs in phage-resistant P. aeruginosa To investigate how mucin exposure influences the evolution of phage-resistance, A549 cells were co-incubated with 0.2% PGM and DMS3vir phage prior P. aeruginosa PA14 infection. After 24 h, bacteriophage-insensitive mutants (BIMs) were isolated. Six independent clones were selected: three from standard conditions (BIM1-3) and three from mucin-enriched conditions (BIM(M)1-3). Control isolates not exposed to phage, including PA14(WT) (ancestral strain), PA14(C) (A549-exposed), and PA14(M) (A549 + PGM), retained their characteristic smooth, mucoid morphology with yellow-green pigmentation ( Fig. 7a ). By contrast, BIM clones developed smaller and rougher colonies with enhanced green pigmentation, suggestive of increased pyocyanin production ( Fig. 7b ). BIM(M) isolates displayed intermediate features, transitioning between rough and smooth morphologies with yellowish-green pigmentation, although BIM(M)1 isolate retained a rougher phenotype ( Fig. 7c ). Phage resistance was confirmed phenotypically, where DMS3vir effectively suppressed growth of control strains but failed to inhibit BIM or BIM(M) clones ( Fig. 7d, e, f ). Whole-genome sequencing revealed mutations across multiple functional categories, including virulence factors, surface modification, motility, surface attachment, metabolism, etc, ( Fig. 7g , S2a). Notably, BIM(M) isolates exhibited a broader mutational spectrum, suggesting additional selective pressures in the mucin-rich environment. CRISPR spacer analysis confirmed that resistance was not mediated by spacer acquisition but likely by surface modification (Fig. S2c). Download figure Open in new tab Figure 7. Isolation and genomic characterization of phage-resistant P. aeruginosa selected in the presence of epithelial cells and mucin rich environment. (a) Representative images of colony morphology of P. aeruginosa PA14 clones isolated after 24 h co-culture at 1 x 10 5 CFU with A549 cells pre-exposed to 0.2% porcine gastric mucin (PGM) and DMS3vir phage (10 7 PFU). (a) Control isolates: PA14(WT) (ancestral strain), PA14(C) (exposed to A549), PA14(M) (A549 + PGM). BIM isolates: (b) BIM1-2 (A549 + DMS3vir) and (c) BIM(M)1-3 (A549 + DMS3vir + PGM). Images show top-down views of individual (squared insert) and pool (circular insert) colonies. (d-f) Bacterial growth curves of (d) PA14 control clones, (e) BIM, and (f) BIM(M) exposed to DMS3vir (1 x 10 7 PFU). Growth curves represent four replicates. (g) Functional/pathway annotation of whole genome sequenced genes mutated in BIM1-2 and BIM(M)1-3 strains. Mutated genes shared with PA14(WT), PA14(C), or PA14(M) were excluded. Bars indicate the number of mutated gene hits per category. Quantitative data represent mean ± s.e.m. from at least two independent experiments. Statistical comparisons were performed using two-way ANOVA with multiple comparisons and Sidak’s post hoc test (d-f) ; p-values and replicate numbers are indicated. Phenotypical assays revealed distinct trade-off associated with phage resistance. After 6 h, BIM(M) strains maintained pyocyanin production comparable to controls, whereas BIM strains showed significantly reduced levels ( Fig. 8a ). At 48 h, however, BIM strains increased pyocyanin production, while BIM(M) levels remained stable ( Fig. 8b ). Despite these differences, both BIM and BIM(M) strains exhibited impaired biofilm formation compared to controls ( Fig. 8c ), indicating that phage resistance compromises biofilm capacity regardless of mucin exposure. Motility assays further distinguished the two phage-resistant groups. Swarming motility (flagella-dependent) was absent in BIM strains, while BIM(M)2 and BIM(M)3 retained intermediate activity, and BIM(M)1 remained non-motile, similar to the BIM group ( Fig. 8d ). Twitching motility (pilus-dependent) was lost in all BIM and BIM(M) isolates ( Fig. 8e ). Moreover, cytotoxicity assays in A549 cells revealed significantly reduced virulence in phage-resistant clones. At 4 h post-infection, both BIM and BIM(M) strains induced minimal epithelial cell death, in sharp contrast to the cytotoxicity of control strains ( Fig. 8f ). This trend persisted at 8 h, where phage-resistant strains remained significantly less cytotoxic ( Fig. 8g ). Download figure Open in new tab Figure 8. Phenotypic characterization of phage-resistant P. aeruginosa mutants reveals mucin-dependent modulation of virulence traits. (a–b) Pyocyanin production by PA14 clones (1 x 10 8 CFU) after (a) 6 h or (b) 48 h incubation in LB medium. (c) Biofilm formation measured by crystal violet staining (OD 595 ) after 24 h at 37 °C under static condition. (d) Swarming motility: representative images (upper panel) and motility diameters (lower panel) of PA14 clones spotted (2 µL, OD 600 = 0.1) after 24 h at 37 °C. (e) Twitching motility: representative images (upper panel) and motility diameters (lower panel) after 48 h at 37°C, stained with crystal violet. (f–g) Cytotoxicity in A549 cells infected with PA14 clones (1 x 10 5 CFU) for (f) 4 h or (g) 8 h. A 20% DMSO treatment served as a positive control for cytotoxicity. BIM and BIM(M) denote phage-resistant clones isolated in the absence or presence of porcine gastric mucin (PGM), respectively, as described in Figure 7 . Quantitative data represent mean ± s.e.m. from at least two independent experiments. Statistical comparisons were performed using one-way ANOVA with Turkey’s post hoc test (a-g) ; p-values and replicate numbers are indicated. Together, these findings demonstrate that a mucin-enriched microenvironment does not prevent the emergence of phage resistance but reshapes the phenotypic and genotypic landscape of resistant populations. The BIM(M) strains retained pyocyanin levels and partially preserved the swarming motility compared to wild-type strain, while exhibiting reduced cytotoxicity, biofilm formation, and loss of twitching motility. These underscore the complex interplay between mucosal environments, bacterial adaptation, and phage-mediated selection, and highlight the importance of epithelial-derived factors in shaping the evolutionary outcomes relevant to phage therapy. 3. Discussion Chronic respiratory diseases (CRD) such as COPD and CF are characterized by excessive mucin accumulation in the airways, profoundly reshaping host-pathogen dynamics 7 , 9 , 46 . Here we show that a mucin-enriched microenvironment reprograms epithelial responses, enhances P. aeruginosa cytotoxicity, and potentiates bacteriophage-mediated protection. Specifically, porcine gastric mucin (PGM) exposure induced CRD-like transcriptional remodeling in airway epithelial cells, sensitized them to bacterial damage, selectively modified P. aeruginosa virulence factor expression, and enhanced epithelial cell protection conferred by phage DMS3vir. These findings provide mechanistic insights into how mucin-rich conditions influence infection dynamics and therapy outcomes, with implications for mucosal-targeted interventions in chronic lung disease. First, we aimed to understand how exogenous mucins influence epithelial cells. Transcriptomic profiling revealed that exogenous mucin drives hypoxia-associated metabolic reprogramming in A549 cells, with increased glycolytic enzymes, hypoxia-response factors, and stress-associated regulators. These patterns mirror CRD airway epithelium 3 , 5 – 7 , and suggest that mucin-rich environments simulate inflamed mucosal conditions. Effects on growth factor signaling and epithelial-mesenchymal transition point to epithelial stress and remodeling, potentially weakening barrier function and promoting infection susceptibility. Next, we explored the interaction of bacterial and epithelial cells with and without exogenous mucins. Surprisingly, PGM increased P. aeruginosa cytotoxicity in airway and intestinal epithelial cells while reducing bacterial internalization. MUC1, a transmembrane mucin, is known to interact with P. aeruginosa flagellin, facilitating adhesion on epithelial cell 47 , 48 . It is possible that the mucin-rich environments block MUC1 receptors, decreasing bacterial adhesion but increasing epithelial vulnerability to secreted virulence factors. Elevated IL6 and IL8 expression under mucin exposure supports heightened epithelial sensitivity, consistent with inflammatory exacerbation during mucosal infections 17 , 20 , 49 . Notably, IL-8 upregulation may amplify neutrophil-driven tissue damage, fueling a detrimental cycle of inflammation and remodeling 50 . Moreover, recent study linking flagellar motility to aggregation-mediated antibiotic tolerance in mucin environments 16 further underscore the role of mucins in modulating bacterial access and epithelial host responses. When looking at the influence of mucins on bacterial cells alone, we observed that PGM selectively downregulated virulence-associated genes, including algD and specific quorum sensing regulators, without impairing growth or pyocyanin production. This suggests mucin functions as a signaling modulator, tuning bacterial programs rather than serving as a nutrient source 14 , 40 , 51 , consistent with earlier findings that neither PGM nor purified MUC5B support P. aeruginosa growth 32 , 51 . While PGM contains MUC5AC with human-like glycosylation, its composition differs from human airway mucins, which also include MUC5B and non-mucin proteins 39 , 52 – 54 . These compositional differences may engage distinct bacterial sensing pathways and explain differential regulatory effects. Reduced algD expression, despite sustained growth, could weaken biofilm integrity and persistence 55 , 56 . Since mucosal surfaces host a diverse community of bacteriophages, and phages could be used in treatment and prevention of mucosal infections, we looked into the tripartite interactions between phages, their bacterial host and epithelial cells. Strikingly, mucin-rich environment enhanced phage infection efficiency. Although PGM did not affect DMS3vir replication or lytic activity, the co-incubation significantly improved epithelial protection, particularly at lower bacterial loads. This threshold-dependent synergy suggests mucin alters the epithelial environment to favor phage-mediated defense. Such effects may define therapeutic windows during early infection or low-density colonization 35 , 38 . The possibility of combining mucin and phage for preventive strategies, such as mucosal colonization in high-risk individuals 30 , 57 , is reinforced by recent inhaled phage trials in CF patients that demonstrated reduced P. aeruginosa burden without adverse events 57 . Phage treatment also modulated epithelial immune responses. DMS3vir reduced IL8 expression during infection without affecting IL6 or triggering type I/III interferon responses. Both cytokines are regulated by NF-κB and MAPKs, but IL6 transcription is further controlled by cAMP and prostaglandin-responsive elements absent in IL8 19 , 58 , 59 . The selective IL-8 suppression may dampen neutrophil-driven inflammation while preserving other epithelial defenses, contributing to tissue protection in mucosal infections. Understanding the influence of environment on evolution of phage resistance is central for phage-bacterium interactions and phage therapy. Here, phage-resistant P. aeruginosa clones displayed distinct adaptation patterns under mucin influence. While resistance uniformly emerged without CRISPR spacer acquisition, implicating surface modification as the dominant mechanism 60 – 62 , mucin-exposed BIM(M) isolates retained pigment production and partial motility compared with BIMs. Whole-genome sequencing revealed mutations in surface structure, motility, and secretion pathways, with broader diversity in BIM(M) strains, underscoring mucin’s role in shaping resistance trajectories 31,32,39,55,56 . Swarming motility, driven by flagella, was completely lost in BIMs and in one BIM(M) isolate, whereas two BIM(M) clones retained partial swarming, suggesting that mucin preserves some motility functions under selective pressure. In contrast, twitching motility, dependent on type IV pili, was uniformly abolished across resistant clones, highlighting a broader fitness cost. Such motility impairments may restrict bacterial dissemination in mucosal niches and thereby enhance phage efficacy 15 . Despite differences in colony morphology and pigment production, all resistant clones showed reduced biofilm formation and attenuated cytotoxicity, consistent with a trade-off between resistance and virulence. However, BIM(M) isolates maintained pyocyanin and partial motility, suggesting that mucin tempers resistance costs and allows retention of virulence traits. Delayed pyocyanin accumulation in BIMs may reflect altered quorum sensing or metabolic adaptation 63 – 65 . Although based on limited isolates, these results highlight the environmental context in shaping bacterial evolution under phage pressure and permit larger-scale studies. While our in vitro system recapitulates key CRD-like mucosal features, it lacks the cellular and immune complexity of the airway 66 . Future studies incorporating organoids, airway-on-chip systems, or animal models, alongside diverse phage cocktails, will be critical to fully capture mucin-bacterial-phage-epithelium interactions. Strategies that enhance phage delivery in mucinous environments or directly modulate mucin composition may represent promising therapeutic avenues 57 , including mucoactive-phage combinations 38 . In summary, our findings reveal the dual role of mucin-rich environments: sensitizing epithelial cells to bacterial virulence while enhancing phage-mediated protection. By reshaping epithelial and microbial responses, mucin modulates both infection severity and therapeutic potential. Understanding these interactions lays the foundation for phage-based interventions tailored to mucosal surfaces in chronic airway disease. 4. Methods 4.1. Cell culture and reagents A549 (ATCC®, CCL-185™) and HT-29 (ATCC®, HTB-38™) cells were maintained at 37 °C with 5% CO 2 in DMEM (ThermoFisher, 25100039) supplemented with 10% fetal bovine serum (FBS; ThermoFisher, A5256701), 1% Glutamax (ThermoFisher, 35050038), and 1 U/mL penicillin/streptomycin (ThermoFisher, 15140122). Both cell lines were tested monthly for mycoplasma contamination by real-time PCR (primers Myc_526_F: ACATTGGGACTGAGATACGGC; Myc_1031_R: TCGTTTACGGCGTGGACTAC) using the p_m16S plasmid (addgene, 160549) as a positive control. For experiments, 1 x 10 5 A549 or 2 x 10 5 HT-29 cells (passages 10-25) were seeded in 96-well plates. The mucin-enriched conditions were generated by supplementing culture medium with porcine gastric mucin (PGM; Sigma-Aldrich, M1778), a mucin source replicating structural features of human MUC5AC and previously validated in phage-bacteria-mucin studies 30,32,39,40,51,53,56 . A 2% (wt/vol) stock solution was prepared in PBS, autoclaved, filtered through 5 µm filters (Sigma-Aldrich, SLSV025LS), and diluted into medium prior use. PBS-only controls maintained equivalent volumes. Human TNF (100 ng/mL; ThermoFisher, PHC3011) served as a positive control for qPCR, and 20% DMSO (Avantor, 67-68-5) as a positive control for cell viability assays. 4.2. Bacterial strains and growth conditions P. aeruginosa strain PA14 (DSM 19882), a highly virulent isolate, and strain 573, a less virulent clinical isolate from bone marrow interstitial fluid 32 , 67 , 68 , were cultured in Luria-Bertani Lennox medium (LB). For experiments, single colonies were grown overnight in 5 mL LB at 37 °C with agitation (200 rpm). Cultures were diluted 1:1 and incubated for 1 h under the same conditions, harvested by centrifugation (4,000 × g , 5 min, RT ∼22 °C), washed in PBS, and resuspended in LB or DMEM (10% FBS, 1% Glutamax, antibiotic-free). Suspensions were standardized to OD 600 0.3 (∼2 x 10 8 CFU/mL) before dilution. Bacterial quantification was performed by CFU plating or OD 600 readings (Multiskan FC, ThermoScientific). Growth was monitored at 600 nm (Tecan Intinite 220 PRO M Nano) every 30 min at 37 °C with shaking. 4.3. Cell viability To assess bacterial cytotoxicity, culture supernatants and cells were collected into microtubes. Residual adherent cells were detached with 0.05% trypsin (ThermoFisher, 15400054; 5 min, 37 °C) and pooled. Samples were centrifuged (270 x g , 5 min, 4 °C), resuspended in DMEM (10% FBS), mixed 1:1 with Trypan Blue (ThermoFisher, 15250061), and transferred to cell counting chambers (Bio-Rad, 1450011). Viability was determined using TC20 automated cell counter (Bio-Rad). 4.4. Real-Time PCR Total RNA was extracted using RNeasy kit (Qiagen, 74106). Reverse transcription performed with the High-Capacity cDNA Kit (ThermoFisher, 4368813) using 200 ng RNA. qPCR was conducted with Gotaq qPCR Master Mix (Promega, A6002) on a CFX96 C1000 cycler (Bio-Rad). Reactions contained 2 µL 1:10 diluted cDNA, 0.2 µM primers, and 10 µL total volume. Human 18S served as the reference gene, and oprL was used for P. aeruginosa . Data were analyzed in CFX Maestro v2.3 (Bio-Rad) using the 2 -ΔΔCT method. 4.5. Bacterial internalization Epithelial cells were incubated with 400 µg/mL gentamicin (ThermoFisher, 15710064) for 1 h at 37 °C to eliminate extracellular bacteria (see Fig. S3). Following PBS washes, intracellular bacteria were released by treatment with 0.05% trypsin plus 0.2% Triton X-100 (Sigma-Aldrich, X100). CFU quantification was performed by serial dilutions and plating. Control groups without epithelial cells served as negative controls. 4.6. Pyocyanin production Pyocyanin production was quantified using chloroform-HCl extraction. Overnight cultures were diluted to 2 x 10 8 CFU/well in LB and incubated at 37 °C for 6 and 48 h in a 12-well plate (DTS-4 shaker, ELMI). Cultures were centrifuged (5000 x g , 10 min), and supernatants were mixed 5:3 with chloroform by repeated vortexing. The organic layer was mixed 2:1 with 0.2 M HCl, vortexed, and the aqueous phase absorbance was measured at 520 nm (Tecan). 4.7. Biofilm formation Overnight cultures were diluted to OD 600 = 0.1 and seeded in 96-well plates. Plates were incubated at 37 °C for 24 h under static conditions, washed with water, and stained with 0.1% crystal violet (20 min, RT). Excess stains were removed by washing, plates were dried, and biofilms were solubilized with 96% ethanol. Absorbance was read at 595 nm (Multiskan FC). 4.8. Bacteriophage The lytic phage DMS3vir 69 was propagated on P. aeruginosa strain PA14. Lysates were filtered (0.22 µm; Sarstedt, 83.1826.001), sterilized with 10% chloroform (Sigma-Aldrich, C2432), concentrated using 100 KDa Amicon filters (Sigma-Aldrich, UFC100), and purified with Endotrap HD 1/1 Kit (Lionex, LET0009). Endotoxin levels decreased from 7158 EU/10 9 PFU to 2 EU/10 9 PFU (Pierce Chromogenic Endotoxin Quant Kit, Thermo Fisher, A39552). Phage titers were determined by double-layer agar assay and stored at 4 °C. 4.9. Isolation of phage-resistant bacteria Resistant clones were isolated from A549 cultures incubated with DMS3vir for 24 h. Triplicate colonies were obtained from two conditions: (i) BIM (A549 + DMS3vir) and (ii) BIM(M) (A549 + DMS3vir + 0.2% PGM). Control clones included (i) PA14(WT), (ii) PA14(C) (A549-exposed), and (iii) PA14(M) (A549 + PGM). Colonies were re-streaked ≥ 3 times for purification and stored at –80 °C in 15% glycerol. 4.10. Swarming motility Cultures were diluted to OD 600 = 0.1, and 2 µL was spotted onto LB soft agar. Plates were incubated at 37 °C for 24 h under static conditions. Swarming patterns were imaged alongside a ruler, and colony diameters measured using ImageJ2 v2. 4.11. Twitching motility Bacterial colonies were stabbed to the bottom of LB agar plates with inoculation needle and incubated at 37 °C for 48 h. Agar was removed, plates were stained with 0.1% crystal violet, and twitching diameters were imaged and quantified with ImageJ2 v2. 4.12. RNA sequencing and analysis Total RNA was extracted from A549 cells (n=3 per group; control and PGM-treated) with RNeasy Mini Kit. RNA integrity was confirmed (Agilent 2100 Bioanalyzer RIN>8). Strand-specific mRNA libraries were commercially sequenced on the DNBseq platform (BGI Tech, PE150, ∼20–30M reads/sample) in BGI, China. Processing followed the Chipster RNA-seq workflow (accessed October 2025; https://chipster.csc.fi/manual/rna-seq-summary.html ) with defaut parameters. Differentially expressed genes considered significant (FDR < 0.05) in both DESeq2 (v.48.2) and edgeR (v4.6.3) tools were retained as the intersect (“Venn” intersection). Gene annotations used biomaRt (v2.62.1) and merged with org.Hs.eg.db (v3.30.0). PCA was performed on the top 1,000 variable genes. Visualization included ggplot2 (tidyverse v3.0.0) and ComplexHeatmap (v2.22.0). GO enrichment (clusterProfiler v4.6.2, org.Hs.eg.db) was curated and displayed as bar plots. Additional description available in Supplementary Information. 4.13. Whole-genome sequencing and analysis Genomic DNA was extracted with DNeasy Blood & Tissue Kit (Qiagen, 69504) and quantified on Qubit fluorometer (Invitrogen). Libraries (≤800 bp inserts) were sequenced on DNBseq (BGI Tech, PE150). BIM2 sample sequencing failed due to technical issues. Reads were filtered with fastp (v0.24.0) and summarized with MultiQC (v1.31). Alignments used BWA-MEM (v0.7.19) and were processed with SAMtools (v1.21) and GATK MarkDuplicates (v4.6.2). Variants were called with SAMtools mpileup and VarScan (v2.4.2), annotated in R (VariantAnnotation v1.52.0, PA14 GFF and UniProt), and filtered to exclude synonymous and background variants. Heatmaps were generated with ComplexHeatmap. Genes were grouped by KEGG pathways/function and visualized as stacked bar plots. Assemblies were generated with SPAdes (v4.0.0), and CRISPR arrays were detected with minced (v0.2.0), parsed in R, and visualized as tile plots. Additional description available in Supplementary Information. 4.14. Statistical analysis Statistical analyses were performed in GraphPad Prism v10.3.0. Two-tailed Student’s t -tests, one-way ANOVA with Turkey’s post hoc test, and two-way ANOVA with Sidak’s correction were applied as appropriate. Differential expression analyses used Wald tests (DESeq2) and quasi-likelihood F-tests (edgeR), with Benjamini-Hochberg correction. Exact P -values are reported. RNA-seq sample sizes were based on detecting fold-changes >1.5 with 80% power at α = 0.05. No statistical tests were applied to CRISPR spacer acquisition, results are shown descriptively. Variant calling results were not corrected for multiple testing due to low variant counts. 5. Data availability The datasets generated during the current study are available in Supplementary Information files and at Zenodo (DOI: 10.5281/zenodo.17278999). The RNA sequencing data has been deposited in the NCBI Gene Expression Omnibus (GEO) under accession number GSE307737. Raw RNA from epithelial cells and bacterial whole-genome sequence reads are available in the NCBI Sequence Read Archive (SRA) under BioProject PRJNA1308451. 6. Code availability All analysis scripts and visualization code are deposited in Zenodo (DOI: 10.5281/zenodo.17278999). 9. Author information Contributions All authors contributed to the preparation of the manuscript. L.R.S., G.M.F.A, and D.O.P. contributed with project conception and design. L.R.S. and D.O.P. designed methodology. D.O.P., K.N., V.S, and L.W.G contributed with data acquisition and analysis. D.O.P. performed statistical analysis and bioinformatics. L.R.S. acquired and administered funding. All authors gave final approval for publication. 10. Ethics declarations Competing interest statement We declare that L.R.S and G.M.F.A. are owners of a patent titled “Improved methods and culture media for production, quantification and isolation of bacteriophages” ( https://patentscope.wipo.int/search/en/WO2019150003 ). All the other authors have no competing interests that might be perceived to influence the results and/or discussion reported in this paper. 8. Acknowledgments We would like to thank MSc Jenne Auramo and Mr Petri Papponen for help in the laboratory, Dr. Nina Chanisvili (George Eliava Institute of Bacteriophages, Microbiology & Virology, Tbilisi, Georgia) for donating P. aeruginosa strain 573, and Prof. Varpu Marjomäki for providing equipment and for donating reagents and the enterovirus Coxsackievirus A9 (CVA9) used as a IFNB expression positive control. This study was funded by the Research Council of Finland grant (#346772) (L.-R.S.) and Centre for New Antibacterial Strategies (CANS) of the Arctic University of Norway (project ID #2520855) (G.M.F.A). Funder Information Declared Research Council of Finland, https://ror.org/05k73zm37 , #346772 References 1. ↵ Hauber , H.-P. , Foley , S. C. & Hamid , Q. Mucin overproduction in chronic inflammatory lung disease . Can Respir J 13 , 327 – 35 ( 2006 ). OpenUrl PubMed 2. ↵ Shah , B. K. , Singh , B. , Wang , Y. , Xie , S. & Wang , C. Mucus Hypersecretion in Chronic Obstructive Pulmonary Disease and Its Treatment . Mediators Inflamm 2023 , 8840594 ( 2023 ). OpenUrl PubMed 3. ↵ Symmes , B. A. , Stefanski , A. L. , Magin , C. M. & Evans , C. M. Role of mucins in lung homeostasis: regulated expression and biosynthesis in health and disease . Biochem Soc Trans 46 , 707 – 719 ( 2018 ). OpenUrl Abstract / FREE Full Text 4. ↵ Fenker , D. E. et al. 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Share Mucin-enriched environment shapes bacteriophage protection against Pseudomonas aeruginosa in airway epithelial cells Daniel de Oliveira Patricio , Katri Niitti , Lucilene Wildner Granella , Valtteri Suokko , Gabriel Magno de Freitas Almeida , Lotta-Riina Sundberg bioRxiv 2025.10.17.683030; doi: https://doi.org/10.1101/2025.10.17.683030 Share This Article: Copy Citation Tools Mucin-enriched environment shapes bacteriophage protection against Pseudomonas aeruginosa in airway epithelial cells Daniel de Oliveira Patricio , Katri Niitti , Lucilene Wildner Granella , Valtteri Suokko , Gabriel Magno de Freitas Almeida , Lotta-Riina Sundberg bioRxiv 2025.10.17.683030; doi: https://doi.org/10.1101/2025.10.17.683030 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Microbiology Subject Areas All Articles Animal Behavior and Cognition (7635) Biochemistry (17691) Bioengineering (13892) Bioinformatics (41936) Biophysics (21452) Cancer Biology (18588) Cell Biology (25504) Clinical Trials (138) Developmental Biology (13378) Ecology (19899) Epidemiology (2067) Evolutionary Biology (24320) Genetics (15609) Genomics (22506) Immunology (17736) Microbiology (40394) Molecular Biology (17181) Neuroscience (88605) Paleontology (666) Pathology (2832) Pharmacology and Toxicology (4824) Physiology (7641) Plant Biology (15153) Scientific Communication and Education (2045) Synthetic Biology (4294) Systems Biology (9825) Zoology (2271)