AXL-GAS6/PROS1 Interaction: A Critical Switch Between Aberrant- and Healthy Repair Following Alveolar Lung Injury

AXL-GAS6/PROS1 Interaction: A Critical Switch Between Aberrant- and Healthy Repair Following Alveolar Lung Injury | 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 AXL-GAS6/PROS1 Interaction: A Critical Switch Between Aberrant- and Healthy Repair Following Alveolar Lung Injury View ORCID Profile Devona Soetopo , Christoph H. Mayr , Katrin Fundel-Clemens , Fidel Ramirez , Coralie Viollet , Alec Dick , Werner Rust , Diana Santacruz , Yvette Hoevels , Christopher J. Applebee , Sam Legg , Anastasia Funk , Gisela Schnapp , Julian Padget , Benjamin Strobel , Matthew J. Thomas , Stephen G. Ward , Banafshé Larijani , Kerstin Geillinger-Kästle doi: https://doi.org/10.1101/2025.04.07.647567 Devona Soetopo 1 Immunology and Respiratory Diseases Research , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany 5 Centre for Therapeutic Innovation and Department of Life Sciences, University of Bath , Bath, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Devona Soetopo Christoph H. Mayr 1 Immunology and Respiratory Diseases Research , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Katrin Fundel-Clemens 2 Computational Biology and Digital Sciences , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Fidel Ramirez 2 Computational Biology and Digital Sciences , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Coralie Viollet 2 Computational Biology and Digital Sciences , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alec Dick 2 Computational Biology and Digital Sciences , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Werner Rust 2 Computational Biology and Digital Sciences , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Diana Santacruz 2 Computational Biology and Digital Sciences , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yvette Hoevels 3 Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG , Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Christopher J. Applebee 5 Centre for Therapeutic Innovation and Department of Life Sciences, University of Bath , Bath, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sam Legg 6 Department of Computer Science, University of Bath , Bath, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anastasia Funk 1 Immunology and Respiratory Diseases Research , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gisela Schnapp 3 Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG , Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Julian Padget 6 Department of Computer Science, University of Bath , Bath, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Benjamin Strobel 4 Drug Discovery Sciences , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Matthew J. Thomas 1 Immunology and Respiratory Diseases Research , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany 5 Centre for Therapeutic Innovation and Department of Life Sciences, University of Bath , Bath, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Stephen G. Ward 5 Centre for Therapeutic Innovation and Department of Life Sciences, University of Bath , Bath, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Banafshé Larijani 5 Centre for Therapeutic Innovation and Department of Life Sciences, University of Bath , Bath, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kerstin Geillinger-Kästle 1 Immunology and Respiratory Diseases Research , Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: kerstin.geillinger-kaestle{at}boehringer-ingelheim.com Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT Previous studies have shown that altered AXL signaling is implicated in various diseases, with GAS6 recognized as its only relevant ligand to date. In this study, we show for the first-time a direct interaction between AXL and PROS1 using biochemical methods. Furthermore, we validate the biological significance of PROS1-AXL interaction through advanced quantitative and functional spatial imaging in both murine lung tissue, as well as human lung samples of idiopathic pulmonary fibrosis (IPF) patients. Our findings reveal the role of AXL-mediated biology in alveolar repair and the fibrotic response driven by GAS6 as well as PROS1. Notably, this effect involves PROS1 interacting with AXL to counteract GAS6 mediated effects. Together with the distinct temporal expression of profibrotic genes and the interplay between AXL and TGF-ß pathway, this emphasizes the potential of targeting AXL mediated biology for therapeutic intervention in IPF to allow alveolar restoration. INTRODUCTION Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease characterized by excessive scarring of lung tissue, occurring for the most part in patients with advanced age. Currently, there is no cure for IPF, resulting in a life expectancy of only 2 – 5 years post diagnosis 1 . While the precise etiology of IPF remains unclear, it is hypothesized that the disease arises from alveolar epithelial injury followed by aberrant repair processes, leading to irreversible fibrosis 2 – 4 . Understanding the mechanisms of normal lung repair in response to alveolar specific injury can provide crucial insights into the pathogenesis of IPF by enabling comparisons between the signaling pathways activated in normal tissue repair and those in fibrotic tissue. Lineage tracing studies have shown that different stem cell populations are engaged in lung repair and their activation is likely influenced by different signaling pathways, depending on the location of the injury and its severity 5 – 7 . However, the specific cellular and molecular mechanisms governing these responses remain poorly understood, limiting our ability to target these processes therapeutically. Recently, transgene delivery via adeno-associated virus (AAV) vector has gained more interest due to its time and cost efficiency compared to conventional transgenic mouse models. In this regard, we previously developed a novel and flexible mouse model of acute epithelial lung injury based on AAV variant 6.2-mediated expression of the human diphtheria toxin receptor (DTR). Following intratracheal administration of diphtheria toxin (DT), a cell- specific death of bronchial and alveolar epithelial cells can be observed. In contrast to other lung injury models, this mouse model provides the possibility of targeted injury using specific tropisms of AAV vectors or cell-type-specific promotors to drive the human DTR expression. Also, generation of cell-specific mouse lines is not required 8 . In this current study, we exploit the unique tropism of AAV serotypes to achieve cell type specific ablation in the lung, allowing investigation into the cellular and molecular responses to cell type specific injury. Hence, we utilized AAV serotype 9 (AAV9), which has a tropism for alveolar cells 9 in combination with DTR/DT system to induce targeted ablation of alveolar cells. Here we demonstrate that the upregulation of a receptor tyrosine kinase (RTK) AXL occurs exclusively in response to alveolar specific injury, suggesting its crucial role in lung repair and fibrosis. RTK AXL belongs to the family of TYRO3, AXL, MERTK (TAM) receptors, which is differentially activated by its two ligands, GAS6 and PROS1, with GAS6 showing the highest affinity for AXL, while PROS1 predominantly binds to TYRO3 and MERTK 10 , 11 . Although the interaction between PROS1 and AXL has been debated 12 – 17 , our findings validate this interaction and its potential contribution to lung repair process. Gaining a deeper understanding of the roles of AXL and its ligands in alveolar repair and IPF pathogenesis could unlock new avenues for therapeutic intervention. RESULTS Longitudinal analysis of lung repair processes after selective epithelial injury informs distinct phases of repair To investigate lung repair mechanisms in response to alveolar specific- versus whole lung injury, mice were intratracheally (i.t.) transduced with either AAV9-DTR or AAV6.2-DTR. As a control, AAV6.2/9-stuffer, which contained non-coding “stuffer” DNA was utilized. To minimize the DT-off target effect described in a previous study 8 , as low as 50 ng DT (i.t.) was administered 14 days post AAV application to induce epithelial cell depletion. Mice were sacrificed at various time points (day 1, 2 ,4, 8, and 14) post DT to follow the repair over time. Body weight and the plasma surfactant protein D (SP-D) levels were monitored and quantified dynamically during the injury and repair process ( Figure 1A ). The preference of AAV9 for alveolar cells and AAV6.2 for whole lung epithelial cells was validated ( Figure S1 ). Download figure Open in new tab Figure 1 Longitudinal analysis of lung repair process after selective epithelial injury. (A) Experimental setup to study the normal lung repair mechanism after epithelial injury. AAV6.2/9- Stuffer/ AAV6.2-DTR/ AAV9-DTR were administered (i.t) into the mice. Lung tissue and plasma were collected at indicated time points post DT application for further readouts. Scheme was created in BioRender. Geillinger-kästle, K. (2025) https://BioRender.com/l78u806 (B) Weight of the mice over the course of repair. (C) Plasma SP-D level over the course of repair. Data were normalized to the corresponding stuffer control. (D) Representative flow cytometry gating to quantify epithelial cells proliferation. Cells were pregated for singlets, CD45 - and CD31 - . Proliferation of all epithelial cells: CD45 - CD31 - EpCAM + Ki67 + ; AT-2 cells: CD45 - CD31 - EpCAM + MHC-II + Ki67 + ; AT-1 cells: CD45 - CD31 - EpCAM + PDPN + Ki67 + . (E-G) Quantification of Ki67 + epithelial cells, AT-2 cells, and AT-1 cells. Data were normalized to the corresponding stuffer control. (H) PCA plot analysis of MACS-enriched epithelial cells (CD45 - EpCAM + ) mRNA sequencing datasets. Data are shown as mean ± SEM of n= 3-7. P ≤ 0.05 (*); P ≤ 0.01 (**); P ≤ 0.001 (***); P ≤ 0.0001 (****) compared with stuffer control. No weight loss was observed in the stuffer group, instead, these mice gained weight. In contrast, significant weight loss occurred in the AAV6.2-DTR group at day 4 post-DT and in the AAV9-DTR group at day 8 post DT, with recovery to baseline weight by day 14 in both AAV-treated groups ( Figure 1B ). SP-D levels, a biomarker for lung injury, showed a corresponding increase, peaking at day 4 in the AAV6.2-DTR group (25-fold increase) and at day 8 in the AAV9-DTR group (50-fold increase) ( Figure 1C ). Cellular proliferation assessed by flow cytometry ( Figure 1D ), showed that Ki67 + epithelial cells increased strongly at day 4 post injury in both AAV-treated groups ( Figure 1E ), correlating with weight loss and elevated SP-D level ( Figure 1B-C ). Proliferation of alveolar type 2 (AT-2) cells began at day 2, peaking at day 4 post injury, with a higher induction observed in the AAV9-DTR group compared to AAV6.2-DTR ( Figure 1F ). In the AAV9-DTR group, Ki67 + alveolar type 1 (AT-1) cells increased at day 8 post injury, whereas minimal Ki67 + AT-1 cells were noted in the AAV6.2-DTR group ( Figure 1G ). By day 14 post DT, the Ki67 + cell count had reverted to baseline in all groups ( Figure 1E-G ). To further explore the molecular processes underlying lung epithelial repair, mRNA sequencing (mRNA-seq) was performed on magnetic activated cell sorting (MACS) enriched epithelial cells from all groups. Principal component analysis (PCA) of mRNA-seq data revealed that the AAV6.2-DTR group from day 8 clustered together with both AAV6.2-DTR and AAV9-DTR groups from day 14, as well as all with stuffer groups from all time points. The rest of the AAV-DTR groups clustered separately along PC1 ( Figure 1H ). These results suggest that the AAV6.2-DTR injured lung has a faster repair rate in comparison to AAV9-DTR, with similar transcriptomic profiles suggesting repair in both groups by day 14 post injury as indicated by weight of the mice, SP-D level, Ki67 + cell count, and gene expression profiles. Alveolar- and whole lung injury activate distinct signaling pathways Studies have shown that the activation of signaling pathways varies based on the specific location of the lung injury 5 – 7 . Therefore, the epithelial sequencing datasets were analyzed using Ingenuity Pathway Analysis (IPA) to identify canonical pathways that are crucial during the repair process and upstream regulators that contribute to these signaling pathways involved in alveolar- versus whole lung injury dynamically. In this study, alveolar injury induced by AAV9-DTR was compared to whole lung injury induced by AAV6.2-DTR. Differential gene expression analysis and functional annotation with IPA showed that different signaling pathways ( Figure 2A ) and upstream regulators ( Figure 2B ) were activated during the course of repair for these two types of injuries, dynamically. While some pathways (e.g idiopathic pulmonary signaling pathway, GP6 signaling pathway) were identified in both groups, whole lung injury appeared to elicit a more immune- driven response. In contrast, alveolar-specific injury activated pathways like HIF-1α signaling, which has long been associated with the pathogenesis of IPF 18 , 19 . Detailed analysis of top 50 significantly activated pathways in both AAVs for each timepoints are depicted in Figure S2. Download figure Open in new tab Figure 2 Transcriptomic analysis of MACS enriched epithelial cells after selective epithelial injury. (A) Canonical IPA pathways that are increasingly activated in the course of AAV6.2-DTR and AAV9-DTR mediated lung epithelial injury. (B) Upstream regulators that are increasingly involved in AAV6.2-DTR and AAV9-DTR mediated lung epithelial injury. (C-F) Fold change of mRNA expression levels of EMT-related genes, Tgfb1 , Col1a1 , Acta2 , Fn1 over the course of repair. Data were normalized to the corresponding stuffer control. Data are shown as mean ± SEM of n= 3-7. P ≤ 0.05 (*); P ≤ 0.01 (**); P ≤ 0.001 (***); P ≤ 0.0001 (****) compared with stuffer control. Further analysis focused on specific gene expression, particularly marker genes associated with epithelial-mesenchymal transition (EMT) such as Tgfb1 , Col1a1, Acta2 , and Fn1 . The analysis revealed upregulation of these genes, especially in the AAV9-DTR groups, compared to the stuffer controls on day 4 and day 8 timepoints. On day 14 post DT, these genes appeared to return to their basal expression level ( Figure 2C-F ). Upregulation of IPF signaling pathways involving Axl upon alveolar injury The IPA analysis unveiled numerous affected signaling pathways, including the idiopathic pulmonary signaling pathway. Further investigation of the gene sets influencing this pathway revealed predominantly genes associated with EMT. Hierarchical clustering of the genes along the time course revealed clusters of early and late profibrotic genes, indicating a sequential upregulation that coordinated the initiation of the repair process. Early response to lung injury (days 1 and 2 post DT) was characterized by acute inflammation and the upregulation of pro-inflammatory genes. By day 4 post DT, there was a transition from inflammation to early fibrotic signaling, evidenced by the increased expression of common fibrotic/ EMT markers (e.g. collagen family, Acta2 , Fn1 , Vim ), which are the TGF-ß downstream genes 20 . Additionally, the tyrosine kinase receptor Axl and its downstream signaling pathway, Pi3k were upregulated 21 . On day 8 post DT, the expression of Axl and Pi3k isoforms was further enhanced, particularly in the AAV9-DTR group. By days 8 and 14, the downregulation of EMT associated markers compared to day 4 post DT suggests that repair was being achieved ( Figure 3A ). Download figure Open in new tab Figure 3 Upregulation of IPF signaling pathways involving Axl in response to alveolar injury. (A) IPF signaling pathway was one of the increasingly upregulated pathways over time as revealed by IPA analysis. The gene set contributing to this pathway included distinct groups of early and late profibrotic associated genes (marked by black rectangles) that were serially and time dependently upregulated. Timepoint order forced, genes hierarchical clustered. (B- D) Fold change of mRNA expression levels of TAM RTK family, Axl , Mertk and Tyro3 over the course of repair. (E-F) Fold change of expression level of TAM RTK ligands, Gas6 and Pros1 over the course of repair. Data are shown as mean ± SEM of n= 3-7. P ≤ 0.05 (*); P ≤ 0.01 (**); P ≤ 0.001 (***); P ≤ 0.0001 (****) compared with stuffer control. It is important to highlight that days 4 and 8 were critical phases for lung repair in this mouse model. Epithelial proliferation peaked on day 4, while differentiation was most prominent on day 8, as shown by previous data ( Figure 1E ) . During this crucial period, Axl , a tyrosine kinase receptor known for its role in cancer development, and its downstream Pi3k signaling pathway was specifically upregulated following alveolar-specific injury 11 , 21 ( Figure 3A-B ). Notably, other TAM receptors, Mertk only showed upregulation on day 8 in AAV9-DTR group ( Figure 3C ), while Tyro3 did not show upregulation ( Figure 3D ). Given the established role of AXL in cancer, and the shared pathological features between cancer and fibrosis 22 , 23 , these findings prompted further investigation into the role of AXL in lung epithelial repair. Although AXL signaling pathway in IPF is not yet well investigated, emerging evidence has shown the involvement of AXL signaling in pulmonary fibrosis 24 – 26 . Upon further investigation of Axl ligands 10 , 11 , the expression levels of Gas6 and Pros1 , were analyzed. Gas6 , traditionally recognized as the highest affinity ligand for Axl , displayed downregulation ( Figure 3E ), while Pros1 exhibited upregulation in AAV9-DTR group compared to the stuffer control on day 4 and 8 post DT ( Figure 3F ). On day 14 post DT, both ligands seem to return to their baseline expression levels. Quantitative functional imaging to investigate AXL-GAS6/PROS1 interactive states as opposed to their expression levels Under normal repair conditions, we observed that following alveolar-specific injury, Axl and Pros1 were upregulated, while Gas6 was downregulated, compared to the stuffer control on days 4 and 8 post injury ( Figure 3B , E, F ). Since current and former smokers represent a higher proportion of IPF cases, we mimicked stress repair by exposing the mice to chronic cigarette smoke for 28 days prior to the AAV-DTR treatment ( Figure 4A ). However, the expression of these genes was not significantly affected in stress repair upon smoking ( Figure S3 ). Download figure Open in new tab Figure 4 AXL interacts with both GAS6 and PROS1 ligands: determined by two-site time-resolved-FRET (aFRET) and surface plasmon resonance. (A) Schematic of the e xperimental setup to study AXL-GAS6/PROS1 interaction using aFRET in mouse lung tissue sections. Lungs were isolated on day 4 post DT. aFRET is a coincidence assay, labels both receptor (AXL) and ligands (GAS6 or PROS1) (see Methods for details). FRET occurs in the range of 1-10 nm. Scheme was created in BioRender. Geillinger-kästle, K. (2025) https://BioRender.com/h45x771 (B) Representative image of AXL-GAS6 interaction. (C) Representative image of AXL-PROS1 interaction. (B-C) Upper figures showed the mean of the donor lifetime (Ƭ) in the absence of acceptor. Lower figures showed the interaction state between AXL-GAS6/ PROS1 for each coincidental region (marked by yellow and black circles). Different coincidental regions possessed different interaction state. (D) Box and whiskers plots showed the heterogeneity of AXL-GAS6/PROS1 interaction states represented as FRET efficiency (Ef%). Ef% below 4% represents the Förster Radius (R 0 at 5.83nm) and not proteins, interactive state as marked by red dashed line. Data are shown as box and whiskers plot of n=5-6. Each dot represents median of Ef% for each mouse. P ≤ 0.05 (*). (E) Correlation plot between Ef% AXL-GAS6 and AXL expression. (F) Correlation plot between Ef% AXL-PROS1 and AXL expression. (G-H) Surface plasmon resonance response curve showing the binding of rhGAS6 and rhPROS1 in different concentration to rhAXL. (I-J) Concentration dependent binding of rhGAS6 and rhPROS1 to rhAXL. Different colored lines in (G-H) correspond to different colored dots in (I-J), which indicate different concentrations of rhGAS6 and rhPROS1. (K-L) GAS6 and PROS1 concentration in human BALF of non- diseased control, ILD/IPF-, and COPD patients. Data are shown as mean ± SEM of n= 4-8. P ≤ 0.01 (**); P ≤ 0.001 (***). To investigate the molecular interaction between AXL and its ligands in-situ , Time Resolved Förster Resonance Energy Transfer (TR-FRET) microscopy was employed to ascertain the molecular interaction between AXL and GAS6 or PROS1. The experiment involved two-site labeling of lung tissue sections with primary antibodies against both AXL and its ligands GAS6 or PROS1. The established amplified two-site TR-FRET assay was used for this study 27 ( Figure 4A ). When interaction between AXL and its ligands GAS6 or PROS1 occurred in coincident regions, a decrease in lifetime of the donor chromophore in the presence of acceptor was determined. These FRET efficiencies (%Ef) were calculated as shown in the Methods (TR-FRET section). %Ef correlates with the interaction state of the of the ligand and receptor. Figure 4B-C shows the heterogeneity in the interactive state of both AXL-GAS6 and AXL-PROS1 in various coinciding regions within an individual mouse. The representative image from a mouse showed two different coinciding regions, indicating lower AXL-GAS6 interactions (%Ef of 1.55% and 6.96%), compared to AXL-PROS1 interactions (%Ef of 14.34% and 19.09%). For each individual mouse, 10 coincident regions were obtained, and the median of the %Ef of all acquired coincident areas are represented as box and whisker plots. A higher interactive state between AXL and PROS1 was observed in the AAV9-DTR smoke- treated group compared to its non-smoke counterpart and the AAV6.2-DTR smoke group. Of note, a FRET efficiency of 4% or lower is considered as non-interactive (indicated by red dashed line), as this corresponds to the Förster radius (R 0 ) of 5.84 nm between Atto488 and Alexa594 28 ( Figure 4D ). Finally, to assess whether the expression level of the AXL receptor correlated with its interactive state with the ligands, the AXL protein expression levels obtained from the donor fluorescence intensity in the presence of the acceptor were plotted against %Ef. The analysis revealed no correlation between the %Ef of AXL-GAS6, as well as AXL-PROS1 with AXL expression ( Figure 4E-F ). This indicates that the level of AXL receptor expression did not correspond to its interactive state with its ligands. These findings suggest that while the expression levels of AXL and its ligands remained unchanged, cigarette smoke led to specifically an enhanced interaction between AXL and PROS1 upon alveolar injury. AXL-GAS6/ PROS1 binding determined by surface plasmon resonance To examine further the interaction between the receptor and its ligands we utilized surface plasmon resonance (SPR). We assessed the binding of recombinant human GAS6 (rhGAS6) and PROS1 (rhPROS1) to recombinant human AXL (rhAXL). SPR results showed that both rhGAS6 and rhPROS1 exhibited concentration dependent binding to rhAXL ( Figure 4G-H ). However, higher concentrations of rhPROS1 were required to achieve a comparable binding response with rhAXL compared to rhGAS6 ( Figure 4I-J ). Specifically, rhGAS6 bound to rhAXL with a much higher affinity with dissociation constant (Kd) of 0.11 nM, compared to rhPROS1 with Kd of 52.15 nM. Of note, SDS-PAGE was performed to evaluate the purity of the rhPROS1 and rhGAS6. Both proteins were found to be highly pure, with rhPROS1 and rhGAS6 exhibiting expected molecular weight of ∼80 kDa and ∼70 kDa, respectively ( Figure S4 ). Following this finding, we measured the GAS6 and PROS1 concentrations in human BALF of ILD/ IPF and COPD patients using ELISA. Compared to non-diseased controls and COPD patients, the levels of GAS6 and PROS1 were significantly elevated in ILD/ IPF patients, with PROS1 being present in much higher quantities than GAS6, approximately 20 - 30-fold higher. ( Figure 4K-L ). Functional spatial mapping using %Ef shows a significant interaction of AXL-GAS6 and AXL-PROS1 in healthy and IPF human lung sections To examine whether the in-situ ligand-receptor results from the mouse models showed a similar outcome with human samples, we exploited functional spatial mapping (FuncOmap). FuncOmap maps automatically the %Ef on to each coincident pixel where there is interaction between AXL-GAS6 and AXL-PROS1. For the FuncOmap experiments we used healthy human lung tissue and tissue from IPF patients. Figure 5A shows tissue sections from a healthy lung (7664) and from IPF patients (1015 and 1033) with various advanced degrees of IPF. The figures show representative images mapping the interactive states of GAS6 and PROS1 with AXL (pseudo-colour heat map of %Ef on the expression level of GAS6 and PROS1 (fluorescence images in grey scale). The individual violin plots quantify the heterogeneity of interactive states for both ligands and the receptor. The dotted line at 4% Ef represents the Förster Radius (R 0 ). Values below 4% are not representative of ligand-receptor interactions. Figure 5B is a global violin plot of all coincident regions (per pixel) of AXL-GAS6 and AXL-PROS1. The individual violin plots for all coincident regions of the tissue sections are shown in Figure S5 . Download figure Open in new tab Figure 5 Functional spatial mapping using FRET-Efficiency (%Ef) shows a significant interaction of AXL-GAS6 and AXL-PROS1 in healthy and IPF human lung sections. (A) 7664 is a tissue section from a healthy lung whereas 1015 and 1033 are sections from IPF patients with various advanced degrees of IPF. The panels show representative images mapping the interactive states of GAS6 and PROS1 with AXL (pseudo-colour heat map of (Ef%) on the expression level of GAS6 and PROS1 (fluorescence images in grey scale). The individual violin plots quantify the heterogeneity of interactive states for both ligands and the receptor. The dotted line at 4% Ef represents the Förster Radius (R 0 ). Values below 4% are not representative of ligand-receptor interactions. (B) Global violin plots of all coincident regions (per pixel) of AXL-GAS6 and AXL-PROS1. Each global violin plot represents 2x10 6 data points. To determine the p values for AXL-GAS6 and AXL-PROS1, using non-parametric Mann- Whitney U test, we utilised 1000 randomly generated data points of the 2x10 6 . Healthy lung has similar distribution of AXL-GAS6 and AXL-PROS1 interactions, whereas the two patient samples show, in one case (1015) no interaction of AXL-GAS6 or AXL-PROS1 and another case (1033) a significantly higher distribution of AXL-PROS1 versus AXL-GAS6. The p values between AXL-GAS6 and AXL-PROS1 are 1.9x10 -3 (7664), 2.4x10 -1 (1015) and 8.2x10 - 33 respectively. The dotted line at 4% Ef represents the Förster Radius (R 0 ). Each global violin plot represents 2x10 6 data points. To determine the p values for AXL-GAS6 and AXL-PROS1, using non-parametric Mann-Whitney U test, we utilized 1000 randomly generated data points of the 2x10 6 . Healthy lung has similar distribution of AXL-GAS6 and AXL-PROS1 interactions, whereas the two patient samples show, in one case (1015) no interaction of AXL-GAS6 or AXL-PROS1 and another case (1033) a significantly higher distribution of AXL-PROS1 versus AXL-GAS6. The p values between AXL-GAS6 and AXL- PROS1 are 1.9x10 -3 (7664), 2.4x10 -1 (1015) and 8.2x10 - 33 respectively. AXL was upregulated especially in the basal cells and aberrant basaloid of IPF patients To determine whether AXL and its ligands were localized on IPF patient epithelial cells, we conducted an analysis of single cell RNA sequencing data from a recently published integrated human IPF atlas 29 . The result of this analysis confirmed that AXL , GAS6 , and PROS1 were enriched in IPF patients. This higher expression was particularly observed in basal cells, aberrant basaloid cells, and AT-1 cells ( Figure 6A-C ). Notably, aberrant basaloid cells were described as the cells found predominantly in IPF 29 – 31 . Download figure Open in new tab Figure 6 AXL is predominantly expressed in basal and aberrant basaloid cells, promoting proliferation via AXL-GAS6 signaling. (A) UMAP plots visualize AXL and its ligands, GAS6 and PROS1 normalized expression in the epithelial cell compartment of an integrated scRNA-seq IPF atlas. (B) Quantification of AXL and its ligands expression in epithelial cells of IPF patients and the non-diseased controls. (C) Expression of AXL and its ligands within the epithelial cells compartment in the lung of PF patients and the non-diseased controls. (D-E) AXL and its ligands expression in SAEC under submerged culture condition. (F) Representative western blot image validating knockout of AXL via CRISPR/Cas9 in 2 different donors. AXL (140 KDa, red bands), loading control ß-Actin (42 KDa, green bands), and M is protein marker. (G) Quantification of AXL expressions of each donor before and after CRISPR/Cas9 mediated knockdown. Experiments were done in duplicate. (H) Proliferation of AXL WT and AXL KD SAEC as assessed by BrdU in all donors 48 hours post seeding. (I) Correlation between AXL expression in (G) and SAEC proliferation in (H). (J) Proliferation of AXL WT and (K) AXL KD SAEC as assessed by BrdU 48 hours post treatment with rhGAS6/ rhPROS1/ combination of both proteins. WT: Wildtype; KD: Knockdown. Data are shown as mean ± SEM of n= 4 – 7. P > 0.05 (ns/ non-significant); P ≤ 0.05 (*); P ≤ 0.001 (***). Since AXL was mostly expressed in basal cells of IPF patients, we sought to determine whether AXL is also expressed in primary human small airway epithelial basal cells (SAEC). mRNA-seq of SAEC unveiled significant expression of AXL under submerged culture condition, while the expression levels of other TAM receptors, MERTK and TYRO3 were low. Additionally, the ligand GAS6 appeared to be highly expressed, whereas PROS1 demonstrated minimal expression. Treatment with TGF-ß slightly enhanced AXL and GAS6 expression, while PROS1 decreased ( Figure 6D-E ). Influence of AXL signaling on the SAEC basal cell proliferation capacity As AXL was identified to be expressed in basal cells including SAEC, we used SAEC as a model system to investigate the role of AXL signaling in lung epithelial repair, particularly in proliferation and differentiation. The impact of AXL signaling on proliferation was assessed by knocking out (KO) AXL in SAECs using CRISPR/Cas9 system. Quantification of AXL expression illustrated varying basal levels of AXL expression among seven different SAEC donors, with Donor SAEC_2 having the highest AXL expression and Donor SAEC_1 having the lowest. Additionally, post-KO quantification of AXL expression showed that the KO efficiency differed across donors, thereby achieving a bulk knockdown (KD). To account for this variation at the start of the experiment, we assessed AXL expression ( Figure 6F-G ). Comparing AXL KD SAECs to wild-type (WT) cells, we found that AXL KD SAECs displayed a significantly decreased proliferation capacity ( Figure 6H ). Moreover, the differential AXL expression among SAEC donors positively correlated with their proliferation capacities ( Figure 6I ). Treatment of SAECs with 400 ng/ml rhGAS6 enhanced their proliferation capacity. However, combination treatment with 400 ng/ml rhGAS6 and 1200 ng/ml rhPROS1 appeared to abolish this effect ( Figure 6J ). Conversely, treatment with rhGAS6, rhPROS1, or a combination of both in AXL KD SAECs had no impact on proliferation ( Figure 6K ). Of note, these concentrations reflect the levels of both proteins in the BALF of IPF patients, with PROS1 concentration being significantly higher than GAS6 ( Figure 4K-L ). In addition, the selected concentrations were also based on the dose response curve for proliferation ( Figure S6 ). Influence of TGF-ß on AXL signaling in fully differentiated SAEC After investigating the role of AXL signaling in the proliferation of SAEC, we expanded our study to examine its impact on epithelial barrier integrity in fully differentiated SAEC. SAEC were cultured in an air-liquid interface (ALI) system until differentiation was achieved. On day 27 post ALI, SAEC were treated with rhGAS6, rhPROS1, or a combination of both. However, these treatments with agonist alone, did not significantly affect epithelial barrier integrity. ( Figure S7 ). Given that TGF-ß is the most extensively studied pathway implicated in IPF progression 22 and is reported to interact with AXL signaling 24 , we then explored whether TGF-ß stimulation could enhance AXL signaling by inducing the release of endogenous GAS6 and PROS1. To test this, SAEC were fully differentiated by day 23 post ALI, at which point the cells were primed with rhTGF-ß to mimic profibrotic environment and subsequently treated with rhGAS6, rhPROS1, or a combination of both ( Figure 7A ). Download figure Open in new tab Figure 7 AXL-TGF-ß crosstalk drives the secretion of AXL ligands, influencing AXL expression and epithelial permeability. (A) SAEC basal cells were allowed to differentiate for 23 days. On day 23 post ALI, 5 ng/ml rhTGF-ß was added to the culture. On day 26 post ALI, rhTGF-ß was added together with rhGAS6, rhPROS1, or a combination of both. Analysis was performed on day 29 post ALI. Scheme was created in BioRender. Geillinger-kästle, K. (2025) https://BioRender.com/k46g355 . (B) GAS6 and (C) PROS1 concentration in the SAEC cell culture supernatant post rhTGF-ß treatment compared to the BSA control. (D) Epithelial barrier integrity as measured by FITC-dextran permeability assays. (E) Fold change of AXL mRNA expression as measured by qPCR. (F) Correlation between slope measured by FITC- dextran permeability assay (D) and ΔCT of AXL (r= -0.9519 R 2 = 0.9062) measured by qPCR (E). Data are shown as mean ± SEM of n= 4 – 5. P > 0.05 (ns/ non-significant); P ≤ 0.05 (*); P ≤ 0.01 (**). On day 29 post ALI, ELISA analysis of the supernatant revealed that rhTGF-ß treatment increased the secretion of GAS6 and PROS1 compared to BSA control ( Figure 7B-C ). The proportions of GAS6 and PROS1 reflected the relative concentrations observed in BALF from ILD/IPF patients, where PROS1 levels were significantly higher than GAS6 ( Figure 4K-L ). To assess epithelial barrier integrity, we performed transepithelial electrical resistance (TEER) measurement and FITC-dextran permeability assay. Treatment with rhTGF-ß alone resulted in reduced TEER values ( Figure S8 ) and increased FITC-dextran permeability, though not significantly, indicating epithelial barrier breakdown. However, the addition of agonist on top of rhTGF-ß treatment did not further exacerbate these effects ( Figure 7D ) We also investigated the expression of AXL using qPCR. Axl expression tends to increase after treatment with rhTGF-ß alone. However, there were no significant changes in Axl expression when the agonist was added in addition to rhTGF-ß compared to treatment with rhTGF-ß alone ( Figure 7E ). Interestingly, while there were no apparent differences in FITC-dextran permeability upon additional treatment with agonist and rhTGF-ß alone, the degree of the permeability represented as slope showed a negative correlation with ΔCT value of AXL . This suggests that higher AXL expression correlates with increased epithelial barrier permeability ( Figure 7F ). Furthermore, a correlation was not observed between the expression of other TAM receptors, MERTK and TYRO3 and epithelial permeability ( Figure S9 ). DISCUSSION Insights into IPF have predominantly been derived from transbronchial or end-stage biopsies, which mainly reflect the advanced stages of the disease. This makes understanding the early development of IPF challenging with patient samples alone. Identifying which cell subpopulations are activated or reprogrammed early, along with understanding the molecular mechanisms and signaling pathways involved, could facilitate earlier detection, potentially prevent IPF, and support the development of regenerative therapies 32 . A deeper exploration into the repair processes and a better understanding of the specific cellular actors remains significantly challenging, partly due to the difficulty in identifying specific progenitor and stem cells in alveolar repair. Although AT-2 cells are generally considered as stem cells for AT-1, recent evidence suggests that basal cells might have the ability to differentiate to AT-2 cells in disease context 33 – 36 . Since IPF is proposed to be caused by aberrant alveolar repair 2 – 4 , this study utilized AAV9- DTR/DT mouse model to specifically injure alveolar cells and study the subsequent repair process, as opposed to whole lung epithelium injury mediated by AAV6.2-DTR/DT. Moreover, our AAV-DTR/DT mouse model offers a more time- and cost-effective method for targeting specific cell types compared to the generation of transgenic mouse model for each target of interest. IPA analysis of epithelial cell datasets revealed the temporal regulation of gene sets involved in IPF signaling pathways, suggesting a coordinated gene expression pattern essential for initiating homeostatic repair ( Figure 3 ). Disruption of these patterns may lead to aberrant repair and fibrosis. Interestingly, AXL signaling was among the pathways that exhibited this specific pattern. While AXL itself was highly upregulated, its ligands GAS6 and PROS1, displayed opposing expression patterns, with GAS6 being downregulated and PROS1 being increased. The identification of AXL RTK as a key player in the repair process, along with its interaction with pro-fibrotic pathways such as TGF-ß, has significant implications for understanding and treating IPF. Previous studies have also reported the upregulation of AXL signaling in IPF fibroblast, supporting its role in fibroblast activation 37 – 40 . While our study mainly focused on the epithelial compartment, scRNA seq data from IPF patients revealed altered expression of AXL, GAS6 and PROS1 in epithelial cells and particularly in aberrant basaloid cells ( Figure 6A-C ). Additionally, we confirmed the interaction between TGF-ß and AXL signaling, as TGF- ß stimulation of primary epithelial cells led to secretion of GAS6 and PROS1 ( Figure 7B and C ). Until recently, GAS6 was considered the primary ligand of AXL. However, we demonstrated PROS1 interaction to AXL both biochemically and in our mouse models with injured lung tissue sections. Using the two-site TR-FRET assay we quantified by %Ef the molecular interaction between PROS1 and AXL. We determined that the highest interactive AXL-PROS1 state was in lung tissue during stress repair ( Figure 4A-D ), with these mice also exhibiting increased barrier breakdown and histological changes ( Figure S10 ). Importantly, our functional spatial imaging (FuncOmap ) ( Figures 5 and S5 ) showed that PROS1-AXL interacted in healthy lung samples but with IPF patients there was a significant difference between PROS1-AXL and GAS6-AXL interactions. Although studies have already linked GAS6-AXL signaling to TGF-ß signaling and fibrotic processes, no research to date has demonstrated the involvement of PROS1 in these complex interactions in any context, especially in human samples. The lack of PROS1 binding to AXL 12 , 41 , 42 may be due to its requirement for significantly higher concentrations to interact effectively. Furthermore, elevated levels of PROS1 and GAS6 were also measured in the BALF of IPF patients, with PROS1 being 20-30- fold higher than GAS6 ( Figure 4K-L ). This highlights the critical role of AXL in the complex interplay with these two ligands, suggesting its relevance in disease initiation and potential progression. Based on our experimental data from primary human epithelial cells demonstrate that AXL expression is closely linked to epithelial proliferation and permeability ( Figure 6 and 7 ). These effects appear to be mediated by GAS6, consistent with existing literature 43 . However, while PROS1 alone did not alter epithelial biology, it was able to blunt GAS6 mediated effects, halting the proliferative phase after injury and shifting towards differentiation phase. Observations in human lung multipotent cells, which exhibited an AT-2 phenotype upon AXL knockdown 38 , further support our hypothesis that a high AXL-PROS1 interaction is crucial for modulating classical GAS6 signaling. This balance appears necessary to initiate the repair process, limiting AXL-GAS6 driven proliferation and facilitating differentiation. The differential expression of AXL and its ligands as well as its molecular interactions with both its ligands, along with the upregulation of EMT-associated genes, suggests that targeting AXL signaling could modulate fibrotic responses and improve repair outcomes. The complexity of ligand interaction with AXL underscores the need for a balance between GAS6 and PROS1 to facilitate normal lung repair, highlighting the necessity for precise therapeutic targeting in IPF. Since AXL is predominantly expressed in basal cells, excessive AXL-GAS6 interaction may lead to an uncontrolled basal cell proliferation, which in turn could result in insufficient differentiation into AT-2 cells. The delicate balance of proliferation, differentiation, and apoptosis of AT-2 cells is essential in successful lung repair 2, 32 , 44 . In IPF, this balance is probably severely disturbed, due to inefficient and insufficient differentiation of basal cells into AT-2 cells, leading to the loss of AT-1 cells, impaired repair, and progression into fibrosis. This imbalance may explain the abnormal expansion of basal cells into the distal parts of the lung (bronchiolization) in IPF 30 , 45 . Our refined model ( Figure 8 ) proposes a “Yin-Yang” relationship between PROS1 and GAS6, which appears to be disrupted in IPF patients. In these patients, although PROS1 is upregulated as a repair effort, the concurrent upregulation of GAS6 hinders the normal repair process. Download figure Open in new tab Figure 8 Refined mechanism of AXL-GAS6/PROS1 interaction during lung repair. After injury, the normal repair process involves an initial inflammatory response, followed by AXL- GAS6 interaction, which promotes cell proliferation. Once sufficient proliferation is achieved, AXL-PROS1 binding occurs, halting proliferation and triggering cell differentiation. This balance between proliferation and differentiation ensures proper repair, leading to healthy alveoli. However, dysbalanced AXL signaling due to repeated injury and persistently high TGF- ß levels, can result in aberrant repair and irreversible fibrosis (IPF). This may occur due to high-affinity interaction between AXL and GAS6 prevents PROS1 from effectively binding to AXL. As a result, excessive proliferation occurs with insufficient differentiation, leading to aberrant repair and fibrosis. Scheme was created in BioRender. Geillinger-kästle, K. (2025) https://BioRender.com/q77c168.xss In summary, we have demonstrated for the first time the interaction between AXL and PROS1, both biochemically and within mouse and human lung tissue during lung repair. BALF analysis from IPF patients and the spatial molecular interactions revealed significantly higher PROS1 concentrations compared to GAS6, emphasizing its biological relevance. These findings have important implications not only for IPF treatment, but also in cancer field, where GAS6-AXL signaling in immune cells is already being targeted. Our data show that AXL signaling in disease is not solely mediated by GAS6, rather the balance between PROS1/GAS6 and AXL plays a pivotal moment in directing healthy versus aberrant repair. METHODS Animals Male C57BL/6JRj mice (8-12 weeks old) were purchased from Janvier Labs (France) or Charles River (Germany). The mice were enclosed in groups of 2-7 in individually ventilated cages (IVC GR900) (Techniplast) at 22-25 °C, maintained on 12 h light cycle, and given a regular ad libitum food and water. Ethical approval was obtained from the regional board for animal care and welfare (Regierungspräsidium Tübingen, Germany, TVV- 20-006-G, TVV 18-030-O). AAV to overexpress GFP or human DTR Recombinant AAVs were produced by transient triple-transfection (pRep/Cap, pHelper, ITR- flanked expression construct) in adherently cultured HEK-293H cells in 16-layered CELLdiscs and purified by PEG-precipitation, Iodixanol gradient ultracentrifugation and ultrafiltration, as described in detail before 46 . Following sterile filtration, AAV preparations were titrated by digital PCR, using an ITR-specific primer/probe set. Self-complementary CMV-eGFP-poly(A) or CMV-hDTR-p(A) 8 expression cassettes were packaged into either AAV6.2 or AAV9. Human bronchoalveolar lavage fluid (BALF) Human non-diseased and COPD BALF samples were purchased from Tissue Solutions, Ltd., UK and ILD/IPF BALF samples were received from Wangen hospital, Germany. Patients consent was obtained for the use of samples in research application. ELISA ELISA’s were performed according to manufacturer’s protocol. SP-D was measured in plasma using the mouse SP-D Quantikine ELISA kit (R&D Systems, #MSFPD0). GAS6 was measured in human BALF or SAEC supernatant using the human GAS6 DuoSet ELISA kit (R&D Systems, #DY885B) and the human PROS1 ELISA Kit (Aviva Systems Biology, #OKBB010207). Tissue dissociation The mice were euthanized using pentobarbital (Narcoren, Boehringer-Ingelheim) overdose and the lungs were perfused with 10 ml RPMI (ThermoFisher, #11835030) through the right ventricle of the heart. The lungs and tracheas were harvested and placed into ice-cold RPMI. The tissues were minced with scissors into 1 mm size in 24 well plate and digested with 6.8 U/ml elastase (Merck KGAa, #324682-1000U), 0.3 Wünsch/ml liberase DL (Roche, #05466202001), and 0.1 mg/ml DNAse I (Roche, #10104159001) in 2.4 ml RPMI supplemented with 1% FBS (ThermoFisher #16140071) and 0.1 mM EDTA (ThermoFisher, #15575020). The tissues with the digestion mix were incubated for 90 minutes on a thermoblock at 37°C with 300 rpm agitation. The tissues with the enzyme solution were then pipetted with 2.5 ml pipette into a 100 µm strainer and pushed with the rubber end of a syringe plunger to obtain a single cell suspension. The strainer was washed with 10 ml RPMI supplemented with 1% FBS, 0.1 mM EDTA, and 0.1 mg/ ml DNAse I. The cells were pelleted by centrifugation at 300g for 5 minutes. If there were still red blood cells (RBC) visible, RBC lysis was performed for 2 minutes at RT using red blood cell lysing buffer Hybri-Max™ (Sigma, #R7757-100ML). After the washing step, the cell suspension was resuspended in PBS (ThermoFisher #14190094) supplemented with 1% FBS. This protocol was adapted and modified from Donati, Y. et al. (2020) 47 . Flow Cytometry Lung and trachea cell suspension was used to measure proliferation by flow cytometry. The single cell suspension was stained with fluorochrome conjugated antibody for 45 minutes at 4°C for extracellular staining with CD45 PerCp (BD Biosciences, #561047), CD31 PE-Cy7 (BD Biosciences, #561410), CD326 (EpCAM) BB515 (BD Biosciences, #565425), Pdpn PE (BD Biosciences, #566390), I-A/I-E (MHC-II) BV786 (BD Biosciences, #742894), and CD24 AF700 (BD Biosciences, #564237). The cells were fixed with BD Cytofix/Cytoperm TM and then subjected to intracellular staining overnight at 4°C with Ki67 AF647 (BD Biosciences, #561126). The antibody mix was supplemented with CD16/CD32 (Fc-block) (BD Biosciences, #553141). Fluorescence minus one (FMO) controls were included in all measurements. Acquisition was performed on BD LSR Fortessa X-20 (BD Biosciences). FlowJo was used for data analysis. Magnetic activated cell sorting (MACS) Lung and trachea cell suspension was subjected to MACS according to the manufacturer’s protocol (Miltenyi Biotec). Briefly, the cells were labelled with CD45 microbeads (Miltenyi Biotec, #130-052-301) to separate CD45 + and CD45 - cells. The CD45 - fractions were subsequently labelled with EpCAM (CD326) (Miltenyi Biotec, #130-105-958) microbeads to enrich epithelial cells. RNA Isolation for mRNA sequencing (mRNA-seq) EpCAM + cells or SAEC were lysed in 350 µl RLT (Qiagen, #79216) supplemented with 1% 2- mercaptoethanol (Sigma Aldrich, #M6250). Lysate was pipetted into Qiaschredder (Qiagen, #79656) and centrifuged for 2 minutes at full speed. Phenol-Chloroform extraction was performed on EpCAM+ cell lysate, and the RNA was isolated using RNeasy micro kit according to the manufacturer’s protocol (Qiagen, #74004)). While SAEC cell lysates were transferred into a MagMAX™ deep well plate and MagMAX™ mirVana™ Total RNA Isolation Kit (ThermoFisher, #A27828) was used alongside with the MagMAX™ Express-96 Deep Well Magnetic Particle Processor according to the manufacturer’s protocol (ThermoFisher). Total RNA was quantitatively and qualitatively assessed using the fluorescence Broad Range Quant-iT RNA Assay Kit (ThermoFisher) and the Standard Sensitivity RNA Analysis DNF-471 Kit on a 96-channel Fragment Analyzer (Agilent), respectively. Total RNA samples had a RIN >7.5 and an input of 25ng (EpCAM+ cells) or 250ng (SAECs) was employed for bulk mRNA- seq library preparation with the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (#E7760), NEBNext Poly(A) mRNA Magnetic Isolation Module (#E7490) and NEBNext Multiplex Oligos for Illumina (#E7600) as per manufacturer’s instructions (New England Biolabs). Ampure XP beads (Beckman Coulter) for double-stranded cDNA purification were used instead of the recommended SPRIselect Beads. Libraries were amplified with 15 (EpCAM+ cells) or 13 (SAECs) PCR cycles and quantified with the High Sensitivity dsDNA Quanti-iT Assay Kit (ThermoFisher) on a Synergy HTX (BioTek). Libraries were assessed for size distribution and adapter dimer presence (<0.5%) by the High Sensitivity Small Fragment DNF-477 Kit on a 96-channel Fragment Analyzer (Agilent). Libraries were normalized on the MicroLab STAR (Hamilton), pooled and sequenced on a NovaSeq 6000 (Illumina) with dual index, paired-end reads (Read Parameter: Rd1:101, Rd2:10, Rd3:10, Rd4:101) with an average sequencing depth of >25 million Pass-Filter reads per sample. mRNA-seq analysis Briefly, demultiplexing was performed using bcl2fastq v2.20.0.422 from Illumina ( https://emea.support.illumina.com/downloads/bcl2fastq-conversion-software-v2-20.html ). Sequencing reads from the RNA-seq experiment were processed with a pipeline building upon the implementation of the ENCODE “Long RNA-seq” pipeline 48 , filtered reads were mapped against the Mus musculus (mouse) genome mm10/GRCm38 or the Homo sapiens (human) genome hg38/GRCh38 (primary assembly, excluding alternate contigs), respectively using the STAR (v2.5.2b) aligner 49 allowing for soft clipping of adapter sequences. For quantification, transcript annotation files from Ensembl version 86 were used, which corresponds to GENCODE M11 for mouse and GENCODE 25 for human. Gene expression levels were quantified with the above annotations using RSEM (v1.3.0) 50 and featureCounts (v1.5.1) 51 . Quality controls were implemented using FastQC (v0.11.5) [Andrews, S. (2010): http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ], picardmetrics (v0.2.4) [Slowikowski K. (2016): https://github.com/slowkow/picardmetrics ] and dupRadar (v1.0.0) 52 at the respective steps. Finally, differential expression analysis was performed on the mapped counts derived from featureCount 52 using limma/voom 53 . An absolute log2 fold change cut-off of 1 and a false discovery rate (FDR) of <0.01 were applied. Ingenuity Pathway Analysis (IPA) Pathway analysis was performed with Qiagen Ingenuity Pathway Analysis IPA 54 [ https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis ]. Significantly regulated genes from the pre-processing for each day and virus combination were used for both the canonical pathway analysis, excluding metabolic pathways, and the upstream analysis, focusing on the molecule type of transcriptional regulators with a predicted activation state. The results, for the analysis of the individual viruses over time on the pathway and upstream level, were filtered for both increasing and decreasing z-score values per pathway over time and sorted by the last or first time point, respectively. For the comparison between AAV6.2 and AAV9 at each timepoint, the top pathways and upstream regulators were selected based on sorting the combined z-scores, but including values for the selected categories, if they existed outside the top selection for one of the viruses. RNA isolation for Quantitative Real-Time PCR (qPCR) Cells were lysed directly in the cell culture well plate using 350 µl RLT buffer supplemented with 1% 2-mercaptoethanol. Lysates were then transferred into a MagMax™ (ThermoFisher) deep well plate and MagMAX™-96 total RNA isolation kit (ThermoFisher, #AM1830) was used alongside with the MagMAX™ Express-96 Deep Well Magnetic Particle Processor according to the manufacturer’s protocol. Isolated RNA was converted into cDNA using the High- Capacity cDNA Reverse Transcription Kit (ThermoFisher, #4368813) according to the manufacturer’s protocol. For qPCR experiments, Taqman-based real-time PCR assays using the TaqMan Gene Expression Master Mix (ThermoFisher, #4444557) and Taqman probes (ThermoFisher), Axl (Hs0106444_m1), Mertk (Hs01031979_m1), and Tyro3 (Hs03986773_m1) were used. Reactions performed on Viia7 system (ThermoFisher). Histology and Immunohistochemistry Left lobes of the lung were pressure filled with 0.75% low melting agarose (Sigma Aldrich, #A9539-100G) in PBS. Once the agarose has solidified inside the lungs, lungs were placed into the histosettes, fixed with ROTI® Histofix 4% PFA (Carl Roth, #P087.1) for 24 hours. Samples were processed with Sakura Tissue-Tek® VIP® 6 automated tissue processor before embedding them in paraffin. Paraffin embedded lungs were cut into 4 µm sections for immunohistochemical stainings. Masson’s trichrome and GFP (1:175) (Abcam, #Ab290) staining were performed using Leica ST5020 automated stainer following the standard manufacturer’s protocol. Positive-, negative-, and IgG controls were included to differentiate between true staining and unspecific binding. Slides were imaged with Axio imager (Carl Zeiss). Two-site amplified Time Resolved-Forster Resonance Energy Transfer (aFRET) Paraffin embedded mouse lungs were cut into 4 µm sections. The slides were subjected to dewaxing and rehydration, followed by heat antigen retrieval in target retrieval solution. They were then treated with a peroxidase suppressor, followed by blocking the slide with 3% BSA in PBS for an hour. Next, the slides were incubated overnight at 4°C with the primary antibodies (Donor: AXL (1:100) (R&D, #AF854), Acceptor: GAS6 (1:100) (ThermoFisher, #BS- 7549R)) or PROS1 (1:100) (ThermoFisher, #14-5791-85) in 1% BSA in PBS. For secondary antibody labelling, slides designated as donor-only were incubated with self-conjugated F(ab’) 2 -Atto488 (Jackson ImmunoResearch, #705-006-147, Sigma Aldrich, #41698-1MG-F), while those labelled as donor-acceptor were exposed to F(ab’) 2 -Atto488 and F(ab’) 2 -HRP (Jackson ImmunoResearch #711-036-152) for 2 hours at RT. Tyramide signal amplification was conducted on donor-acceptor slides, where F(ab’) 2 -HRP was bound to the acceptor primary antibody. Tyramide, conjugated to the Alexa594 chromophore (ThermoFisher, #B40925), was introduce to the HRP molecule, thereby fluorescently labelling the acceptor site. Finally, the slides were mounted using prolong diamond anti-fade mounting medium. This protocol was adapted from Veeriah, et al . (2014) 27 . This two-site assay (aFRET) is patented: Patent US 10578,620 B2: Methods for detecting molecules in a sample: patent rights are held by Hawk Biosystems. aFRET determined by frequency-domain Fluorescence Lifetime Imaging The quantitative molecular imaging platform employs a custom-built, semi-automated frequency-domain fluorescence lifetime imaging (FLIM) system. The system is a modified Lambert FLIM. The donor and donor acceptor samples are excited at 473nm by a solid-state modulatable diode laser. The system is a homodyne system that is modulated at a frequency of 40 MHz. The reduction in donor lifetime due to resonance energy transfer, caused by the acceptor, correlated with measurement of distances in the range of 1-10 nm allows the quantification of receptor-ligand interactions. Coincidence regions, where both donor and acceptor signals were identified and a total of 10 regions of interest (ROIs) selected within those regions. The fluorescence lifetimes and their corresponding standard deviations are automatically calculated and exported to an Excel spreadsheet for further analysis. Photophysical parameters for quantification of protein interactive states We automatically calculate lifetime image of donor in the presence of acceptor ( τ DA ) and a lifetime image of the donor (τ D ), followed by calculation of reduction of ( τ DA ) compared to (τ D ), which is reflected in a parameter called FRET-efficiency (%Ef): ’R0’ the Förster radius in this case, between Atto-488 and Alexa 594, is 5.83nm and it is the distance at which the transfer efficiency is 50%. R0 of 5.83nm corresponds to 4% Ef, therefore an Ef lower than 4% is considered non-interactive. Functional Spatial mapping of AXL and Its Ligands GAS6 and PROS1 The computational approach for the functional mapping of the coincident regions from the two- site assay follows that described in Safrygina, et al. 2024 28 . Briefly, the initial data capture from the FLIM images provides a donor and a donor-acceptor image. For each pixel the lifetime is recorded in the control donor and the donor/acceptor image and hence the FRET efficiency calculated automatically. The FLIM output is processed using the FuncOmap software 28 , outputting a spatially resolved FRET efficiency map, where each pixel value corresponds to the calculated FRET efficiency. A heatmap is applied to the FRET efficiency at a scale of 0-50% across the region of interest. The %Ef is mapped automatically on the acceptor fluorescent image (grey scale). FuncOmap software is available under licence from the University of Bath. For enquiries, please contact Julian Padget and/or Banafshe Larijani. Analysis of the Functional Spatial mapping The per pixel FRET efficiency values from the maps are plotted automatically as violin plots. For each mapped coincidence region there is a unique violin plot showing the distribution of the interactive states of AXL-GAS6 and AXL-PROS1. Each global violin plot represents 2x10 6 data points. To determine p values for AXL-GAS6 and AXL-PROS1, we used the non- parametric Mann-Whitney U test with 1000 randomly selected data points from the 2x10 6 . Surface plasmon resonance to study AXL-GAS6/PROS1 binding kinetics Binding kinetics of recombinant human GAS6 (rhGAS6) (R&D, #885-GSB) and recombinant human PROS1 (rhPROS1) (R&D, #9489-PS) to recombinant human AXL was assessed using surface plasmon resonance using a Biacore T200 system. Biotinylated AXL (Boehringer- Ingelheim, #33-227) was immobilized on a streptavidin chip. Increasing concentrations of rhGAS6 (0,000069 µM - 0,05 µM; 1:3) or rhPROS1 (0,00069 µM - 5 µM; 1:3) were then injected onto the immobilized target in 25mM MES, 150 mM NaCl, 10 mM CaCl2, 0.05% Tween, pH 6.0. Mean association rate (K on ) and dissociation rate (K off ) was calculated from 3 individual experiments using Biacore T200 analysis software. The dissociation constant (Kd) was calculated from K on /K off . Generation of CRISPR-Cas9 AXL knockout SAEC A ribonuclear protein complex (RNP) was prepared by combining 1250 ng of TrueCut™ Cas9 protein V2 (ThermoFisher, #A36498) with 7.5 pmol TrueGuide™ Mod human AXL sgRNA (ThermoFisher, CRISPR932418_SGM). The mixture was then incubated for 15 – 30 minutes at RT. 24- or 6-well plates were coated with rat tail collagen. Afterwards, SAEC submerged complete medium without antibiotics was pipetted into the well plates. Plates were kept in the incubator until cells were electroporated. For electroporation, the AMAXA basic nucleofector kit for primary mammalian epithelial cells (Lonza, #VPI-1005) was used according to manufacturer’s protocol. Briefly, 2 µg of pmaxGFP™ vector (included in the kit) was pipetted directly into the electroporation cuvette. Following this, 700,000 cells were resuspended in 100 µl of AMAXA nucleofector solution and mixed thoroughly with the RNP complex. The mixture was then pipetted into the cuvette and proceeded to electroporation (Program T-020 for transfection of primary small airway epithelial cells). Finally, 500 µl of pre-warmed SAEC submerged complete medium was pipetted into the cuvette and transfer immediately into the pre-prepared well plates. 24 – 48 hours post electroporation, cells are ready to use for further assays Western blot For validation of AXL knockout SAEC, a western blot was conducted. Protein lysate was obtained by lysing the cells in RIPA buffer (Sigma Aldrich, #R0278-500ML) supplemented with phosphatase- (Roche, #04906837001) and protease inhibitors (Roche, #05892970001). Protein concentration was quantified using Pierce™ BCA protein assay kit (ThermoFisher, #23225). Before loading the protein lysate onto the Bolt™ 4-12% gradient Bis-Tris polyacrylamide gel (ThermoFisher, #NW04125BOX), all samples were brought to the same concentration and combined with 4x NuPAGE LDS sample buffer (ThermoFisher, #NP0007) and 10x NuPAGE reducing agent (ThermoFisher, #NP0004). The mixture was then heated for 10 minutes at 70°C and cooled on ice. After loading the protein onto the gel, proteins were transferred onto a nitrocellulose membrane via dry transfer using iBlot (ThermoFisher). The membrane was subsequently blocked in 5% BSA in TBS (Carl Roth, #1060.1) and incubated with primary antibodies total AXL 1:200 (R&D, #AF154) and ß-actin 1:1000 (Cell Signaling, #8457) as a loading control in 3% BSA in TBST (Carl Roth, #1061.1) overnight. Next, the membrane was washed in TBST, fluorescence secondary antibodies (donkey anti goat IR dye® 680 LT 1:5000 (LI-COR, #926-68021) and donkey anti rabbit IR dye® 800 CW 1:5000 (LI-COR, #926-32213) were applied for 1 hour at RT. After washing out the unbound secondary antibodies, the membrane was ready for imaging on an Odyssey Imager (LI-COR). Intensity could then be quantified using the LI-COR acquisition software. SAEC submerged culture T175 flasks were coated with 15 ml of 30µg/ml rat tail collagen (Corning, #354236) in PBS and left in the incubator for 45 minutes. 7 different healthy human SAEC donors (Lonza) were thawed in the 7 different precoated T175 flasks containing SAEC submerged complete medium (490 ml Pneumacult TM Ex Plus basal medium (STEMCELL, #05041) supplemented with 10 ml 50x Pneumacult TM Ex Plus supplement (STEMCELL, #05042), 0.5 ml hydrocortisone (STEMCELL, #07925), and 5 ml penicillin-streptomycin (ThermoFisher, #15140122). Upon reaching 80% confluence, the cells were detached using ACF enzymatic dissociation kit (STEMCELL, #05426). The cells were then transferred to falcon tubes and centrifuged at 300g for 5 minutes. Following centrifugation, 50,000 cells were seeded onto 24- well plates with SAEC submerged complete medium. The cells were then subjected to starvation in DMEM (ThermoFisher, #11966025) without any additives for further assays. SAEC air liquid interface (ALI) culture SAEC were thawed and detached from the flask using the same method as described previously. After centrifugation, 30,000 cells were seeded onto the rat tail collagen coated transwell insert using complete SAEC submerged medium. The medium was added to both the apical and basolateral chambers of the wells until they reached confluence. Once confluence was achieved (usually 5 days post seeding), the cells underwent airlifting by removing the apical media entirely and replacing the basal media with SAEC ALI complete medium (450 ml Pneumacult TM ALI-S medium (STEMCELL, #05051) supplemented with 50 ml 10x ALI-S supplement (STEMCELL, #05052), 2.5 ml hydrocortisone, 5 ml maintenance system supplement (STEMCELL, #050502), 1 ml heparin (STEMCELL, #07980), and 5 ml penicilin-streptomycin) to promote cell differentiation. Subsequent assays were conducted in SAEC ALI complete medium. Cells are usually fully differentiated 21-30 days post ALI. Bromodeoxyuridine (BrdU) proliferation assay A total of 50,000 SAEC were initially cultured in a 24-well plate with SAEC submerged complete medium. The following day, cells were starved overnight with DMEM without any supplements. Subsequently rhGAS6 (400 ng/ml), rhPROS1 (1200 ng/ml), or combination of both rhGAS6 and rhPROS1 were added directly into the medium for 48 hours. Bromodeoxyuridine (BrdU) assay was performed according to the manufacturer’s protocol (Roche, #11647229001). Briefly, cells were labelled with BrdU for 4 hours. Following this, the supernatant was removed, FixDenat solution was added, and cells were exposed to anti-BrdU for 90 minutes. Finally, cells were washed, and substrate was applied for 15 minutes. Substrate solution was then transferred to 96-well plate for measurement. Optical density was measured using a SpectraMax microplate reader (Molecular Devices) at 370 nm with a reference wavelength of 492 nm. FITC-dextran permeability assay FITC-dextran permeability assay was also employed to assess the epithelial barrier integrity of SAEC ALI culture. Firstly, basolateral medium of the SAEC ALI culture was replaced with 500 µl of pre-warmed phenol red free RPMI medium. Next, 5 mg/ml of FITC-dextran 10s (Sigma Aldrich, FD10S-1G) was added into the transwell insert. 10 µl of samples were collected from the basolateral compartment at 0, 30, 60, and 90 minutes post FITC-dextran addition. Samples were transferred to a 384-well plate for FITC fluorescence intensity measurement. The amount of FITC that went through from the apical to the basolateral chamber was quantified using EnVision multilabel plate reader (ex. 490 nm, em. 520 nm). Statistical analysis The data are represented as means ± standard error mean (SEM). Statistical analysis was performed using GraphPad Prism 9 and 10 software. Mean values were compared using t- test for experiment with two groups and one-way- or two-way ANOVA for experiments with three or more groups, followed by Tukey’s or Dunnet’s multiple comparisons test. Median values of FRET efficiencies were compared in box and whiskers plots and the global violin plots from FuncOmap were compared using non-parametric Mann-Whitney U test. Correlation analysis was performed using Pearson or Spearman. p-values are represented as asterisk with, p > 0.05 (ns/ non-significant); p ≤ 0.05 (*); p ≤ 0.01 (**); p ≤ 0.001 (***); p ≤ 0.0001 (****). AUTHOR CONTRIBUTIONS DS designed and performed most of the experiments and analyzed data. DS wrote manuscript. CV and AD supervised sequencing experiments. DSc and WR performed sequencing experiments. CHM, KFC, and FR analyzed sequencing data. AF performed experiments. GS and YH supervised and performed SPR experiment. DS and CJA supervised and performed TR-FRET experiment. JP, SL, and BL performed FuncOmap analysis and interpretation of functional spatial mapping. BS provided AAV and conceptual advice. MJT provided conceptual advice. SGW, BL, and KGK conceptualized, supervised the study, and designed experiments. All authors edited and commented on the manuscript. Competing interests All authors except CJA, SL, JP, SGW, and BL are employed by Boehringer Ingelheim Pharma GmbH & Co KG. This study was funded by Boehringer Ingelheim Pharma GmbH & Co KG. CJA, SL, JP, SGW, and BL are currently employed by University of Bath. CV is currently employed by AstraZeneca. Data availability RNA-seq data generated within this study is deposited in the Gene Expression Omnibus (GEO) and will be made accessible upon acceptance of the manuscript. All other data is available upon request. Materials and Correspondence Correspondence and request for materials should be addressed to Kerstin Geillinger-Kästle ( kerstin.geillinger-kaestle{at}boehringer-ingelheim.com ) ACKNOWLEDGEMENTS We thank Sylvia Blum, Anita Schönleber, Annika Meier, Michael Schilling, Eva Thaler, and Helene Lichius for assistance with the in-vivo experiments, Birgit Stierstorfer, Tanja Schönberger, Fabian Heinemann, and Nadine Rehm for their support in histology, Wioletta Skronska-Wasek and Wangen Hospital, Germany for the human IPF BALF samples. Marc Kästle for providing SAEC mRNA seq data. Holger Schlüter and Medizinische Hochschule Hannover (Hannover medical school) for providing the human lung sections. This work is funded by Boehringer Ingelheim Pharma GmbH & Co. KG, Germany. Schemes were created in BioRender. References 1. ↵ Meltzer , E. B. & Noble , P. W. Idiopathic pulmonary fibrosis . Orphanet J. Rare Dis. 3 , 8 ( 2008 ). OpenUrl CrossRef PubMed 2. ↵ Sgalla , G. et al. 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