Brain-derived neurotrophic factor and the derived dodecapeptide function as Toll-like receptor 4 antagonists in acute lung injury

Domain: neuroscience
Published: 2026-02-14
Editorial outcome: minor_revision

Abstract
The neurotrophic factor (NTF) family has recently expanded its role beyond neurological conditions, but its involvement in acute inflammatory lung diseases remains largely unclear. Using well-established acute lung injury (ALI) and sepsis models, we demonstrate that brain-derived neurotrophic factor (BDNF), a key NTF, is impaired in pulmonary epithelial cells and negatively correlates with the inflammatory response. Raising the BDNF level alleviates inflammatory lung injury, but these effects are absent in macrophage-deleted mice. Both in vivo and in vitro results show BDNF inhibits macrophage inflammation, and further proteomics analysis identifies macrophage TLR4 as a receptor that BDNF antagonizes via direct binding. The BDNF fragment (aa 104-115) is critical for BDNF-TLR4 interaction, and the corresponding synthetic BDNF-derived dodecapeptide (BDP-12) retains TLR4-antagonistic and anti-inflammatory effects both in vitro and in vivo, without pro-proliferative side effects. In conclusion, our findings reveal that epithelial-derived BDNF prevents macrophage inflammation by directly targeting TLR4 and highlights BDP-12 as a potential therapeutic agent for acute inflammatory diseases.

Introduction
Neurotrophic factors (NTFs) are a class of proteins or peptides first identified in the nervous system, where they play crucial roles in regulating neuronal fate through binding to classic receptors such as TrkA, TrkB, TrkC, and p75NTR, respectively1. In recent years, it has been discovered that the NTFs family not only exerts essential functions in the neurological system but also plays significant roles in a variety of non-neurological pathophysiological processes. For instance, glial cell-derived neurotrophic factor (GDNF), derived from the bone tissues, promotes the proliferation and osteogenic differentiation of jaw bone marrow mesenchymal stem cells2. Ciliary neurotrophic factor (CNTF) activates AMPK pathways in skeletal muscle, helping to reverse obesity-induced insulin resistance3. Nerve growth factor (NGF) level has been found to be associated with the development and reproduction of primordial follicles4. Muscle-secreted neurturin (NRTN) enhances capillary density and oxidative capacity in myofibers, while favoring fatty acid metabolism over glycolysis through transcriptional reprogramming5. Additionally, neurotrophin-3 (NT-3), derived from cardiovascular progenitor cells, can protect cardiomyocytes from death during re-perfused myocardial infarction6. These findings highlight the functional diversity of the NTF family across different tissues. Therefore, a systematic exploration of the relationship and mechanisms between NTFs and certain diseases may provide new targets and strategies for their treatment.

Acute inflammation is a critical defense mechanism triggered by external factors such as infections, trauma, toxins, or other forms of injury7. Its primary role is to eliminate harmful substances and promote tissue repair. However, when the inflammatory response becomes excessive or prolonged, it can lead to the progression of acute inflammatory diseases. In the context of infections, pathogen-associated molecular patterns (PAMPs) stimulate tissue-resident macrophages via pattern recognition receptors (PRRs), such as Toll-like receptors (TLRs)8,9. This process initiates the release of pro-inflammatory cytokines, which, when present in excessive amounts, induce apoptosis in parenchymal cells10. Concurrently, tissue-resident macrophages secrete adhesion molecules and chemokines, facilitating the infiltration of leukocytes, particularly neutrophils and monocytes, thereby exacerbating the inflammatory response. Furthermore, damage-associated molecular patterns (DAMPs) released by injured parenchymal cells act as additional pro-inflammatory stimuli, sustaining the inflammatory cascade, leading to rapid deterioration and potentially fatal outcomes11,12. Despite the sporadic reports, the connection and molecular mechanisms between NTFs and acute inflammatory diseases outside the brain are still largely unexplored. A comprehensive investigation into this area is of significant importance and may provide valuable insights and candidates for guiding the discovery of new therapeutic drugs for clinical anti-inflammatory treatment.

In this study, we utilized the well-established acute lung injury (ALI) and sepsis models to investigate the potential role of NTFs in regulating the progression of acute inflammatory diseases. Our findings revealed that brain-derived neurotrophic factor (BDNF), specifically expressed in the pulmonary epithelium, was significantly and negatively correlated with the progression of ALI and the severity of inflammation. Using high-throughput omics technologies, we further discovered that BDNF secreted by alveolar epithelial cells, or administered exogenously, can directly antagonize TLR4 in macrophages, thereby exerting anti-inflammatory effects and alleviating ALI and sepsis. Molecular studies confirmed that the BDNF aa 104-115 is the key segment responsible for binding to TLR4. Based on this fragment antagonizing TLR4, we synthesized the BDNF-derived dodecapeptide (BDP-12), which was ultimately identified as a therapeutic candidate for acute inflammation, without potential pro-proliferative side effects.

Results
Pulmonary epithelial-specific BDNF is negatively correlated with the progression of ALI
We performed RNA-seq using lung tissues of control and LPS-challenged mice to analyze the mRNA expression profile of 9 typical NTFs (Fig. 1A). In addition, we also checked two public RNA-seq datasets from P. aeruginosa-infected ALI model (GSE233206) and LPS-treated lungs (GSE214249) (Fig. 1A). Among the 9 typical NTFs, only BDNF mRNA (Bdnf) was found to be monotonically downregulated across all three datasets (Fig. 1B). Additional RNA-seq datasets from both murine models and human samples of pneumonitis also showed significantly decreased Bdnf expression compared to the control groups (Supplementary Fig. S1A–C). A rough time-dependent pattern of Bdnf transcripts was underscored in P. aeruginosa- (GSE204709) and hvKp- (GSE199546) infected lungs as well (Fig. 1C, D). Interestingly, the close relationship between BDNF and ALI was emphasized with the highest abundant and most significant decline of Bdnf expression in the lungs compared to other organs in an endotoxemia model (Supplementary Fig. S1D).

BDNF protein, as a secreted cytokine cleaved from its precursor proBDNF and exhibiting 100% homology across various species (Supplementary Fig. S2A, B), was measured in both human and mouse samples. Notably, a significant decrease in BDNF levels was observed exclusively in BALF from both ALI mice and ARDS patients, without corresponding changes in blood, suggesting that the ALI progression is associated with the change of local production of BDNF in lung, rather than the systemic or central BDNF secretion (Fig. 1E, F). To further investigate the cellular source of BDNF in lungs, 13 distinct lung cell types were identified in cecal ligation and puncture (CLP)-induced and sham-operated mice using 26 specific cell markers (Fig. 1G, H). Mapping Bdnf transcripts revealed an overall decrease, with predominant expression and reduction observed in lung epithelial cells following CLP modeling (Fig. 1I, J). These findings were corroborated by additional scRNA-seq datasets (Supplementary Fig. S1E, F). Parallelly, significant reductions in BDNF protein level were detected in LPS-treated mouse lungs and primary epithelial cells, but not in LPS-treated primary fibroblasts or macrophages (Fig. 1K, L). Together, these results highlight a critical association between reduced BDNF expression in lung epithelial cells and the pathogenesis of ALI.

Epithelial BDNF expression is regulated by GATA2 during ALI
We then tried to elucidate the regulatory mechanisms behind the decreased expression of BDNF in lung epithelial cells during ALI. We employed five databases for transcription factor prediction, identifying a total of 11 high-potential common transcription factors (Supplementary Fig. S3A). We then assessed the expression changes of these transcription factors using transcriptomic data, revealing that seven of them exhibited a consistent downregulation trend (Supplementary Fig. S3B, C). Further single-cell transcriptomic analysis indicated that only GATA2 and E2F1 displayed decreased expression levels in damaged lung epithelial cells (Supplementary Fig. S3D). Protein-level analysis corroborated these findings, confirming the reduction of GATA2 and E2F1 in lung tissues of ALI mice (Supplementary Fig. S3E, F). We then overexpressed GATA2 and E2F1 in MLE-12 cells and found that overexpression of GATA2 resulted in a significant increase in Bdnf transcription (Supplementary Fig. S3G). We then further applied ChIP-qPCR to verify the ability of GATA2 to directly bind and regulate the Bdnf gene promoter. Based on our lung RNA-seq dataset, we identified two BDNF transcripts with high basal expression that were markedly downregulated after LPS stimulation (Supplementary Fig. S3H). Four primer pairs were designed to cover the promoter regions corresponding to these transcripts. ChIP-qPCR using primer set 2 demonstrated that GATA2 directly binds to the Bdnf promoter, and this binding was substantially reduced in LPS-treated epithelial cells (Supplementary Fig. S3I). Together, these findings indicate that GATA2 is a key transcriptional regulator of Bdnf in lung epithelial cells, and that its downregulation during ALI contributes to the reduced BDNF expression observed in injured lungs.

Epithelial-specific BDNF overexpression and exogenous BDNF administration alleviate LPS-induced ALI in mice
Then, the lung epithelial-specific BDNF-overexpressed mice (Ad-BDNF) were successfully constructed via injecting AAV6 encoding mature BDNF and the lung epithelial-specific promoter, and then modeled to ALI by LPS installation (Fig. 2A; and Supplementary Fig. S4A, B). From the results of wet-to-dry ratio, protein concentration in BALF, and histological staining, we found distinct indications of pulmonary edema, protein leakage, and increased thickness of the alveolar wall in ALI mice. However, these pathological features were ameliorated in LPS-challenged Ad-BDNF mice (Fig. 2B–E). Furthermore, the heightened total cell counts in BALF pointed to immunocyte infiltration in LPS-exposed lungs, while BDNF overexpression effectively blocked this infiltration and reduced the number of neutrophils, as evidenced by diminished MPO activity and cell nuclear staining (Fig. 2F–H). This effect was consistent with the decreased expression of the adhesion molecules Icam1 and Vcam1, which are critical for immune cell infiltration and localization (Fig. 2I, J). Flow cytometric analysis of BALF samples also demonstrated the attenuation of both neutrophil and macrophage infiltration in LPS-challenged Ad-BDNF mice (Fig. 2K). In addition, BDNF overexpression significantly increased survival rates in mice with E. coli-induced septic mice (Fig. 2L).

Recombinant BDNF protein (rBDNF) was also administered intravenously to evaluate the therapeutic effect of exogenous BDNF against ALI in mice (Fig. 2M). The mice treated with rBDNF showed increased BNDF protein levels in serum and lung tissues (Supplementary Fig. S4C, D). As expected, exogenous rBDNF administration alleviated wet-to-dry ratio, protein concentration in BALF, and histopathological injury in LPS-treated mice (Fig. 2N–Q). Immunocyte infiltration was also inhibited by rBDNF in ALI mice, as indicated by total cell counts in BALF, MPO activity, neutrophil staining, qPCR analysis of lung Icam1 and Vcam1, and flow cytometry assay (Fig. 2R–W). Also, rBDNF administration significantly reduced septic death in E. coli-injected mice (Fig. 2X). In summary, these data show that either epithelial-specific BDNF overexpression or exogenous rBDNF treatment alleviates LPS-induced ALI in mice.

BDNF alleviates ALI through inhibiting inflammation in macrophages
Given that macrophage inflammation is a key driver of ALI, we further investigated whether BDNF is directly associated with the inflammatory response in ALI. Our results revealed a negative correlation between Bdnf transcript levels and Il6, a gene encoding the pro-inflammatory cytokine IL-6 in RNA-seq datasets of ALI mice (Fig. 3A). Similarly, secreted BDNF protein content was negatively correlated with both IL-6 and TNF-α concentrations in both mice and human BALF (Fig. 3B, C). These data suggest that BDNF negatively regulates the inflammatory response during ALI progression.

An inflammatory gene PCR array further demonstrated the anti-inflammatory effects of rBDNF in LPS-challenged macrophages, showing that rBDNF suppresses LPS-induced expression of over 40 key inflammatory genes, including chemokines, interleukins, and interferons (Fig. 3D). ALI mice treated with rBDNF also showed decreased inflammatory cytokines transcription, accompanied by reduced secretion of TNF-α, IL-6, and IFN-α in both serum and BALF (Fig. 3E–G). Subsequently, to determine the role of macrophages in the anti-ALI effects of rBDNF in mice, we used clodronate liposomes (Clo-lip) to delete macrophages in mice (Fig. 3H). Macrophage deletion led to increased tolerance to LPS challenge, but when rBDNF was administered after macrophage deletion, the therapeutic effects of rBDNF were lost, as indicated by no further reduction in histopathological injury, wet-to-dry ratio, BALF protein concentration, immune cell infiltration, and sepsis-induced mouse mortality (Fig. 3I-N). These data indicate that macrophages are the primary effector cells targeted by BDNF. Epithelial cell-secreted BDNF establishes a new cell-cell communication pathway to mitigate macrophage-driven inflammation during ALI.

Identification of BDNF as an antagonistic ligand of TLR4 in macrophages
It is unclear which receptor in macrophages recognizes the extracellular BDNF and mediates its anti-inflammatory effect. Initially, we hypothesized that tyrosine receptor kinase B (TrkB), the canonical and previously reported receptor of BDNF, was responsible for these effects in macrophages. However, when Ntrk2 (encoding TrkB) was silenced, the anti-inflammatory effects of BDNF in macrophages remained, indicating that TrkB was not the primary mediator (Supplementary Fig. S5A, B).

Then, dual-proteomics and bioinformatics approaches were employed to uncover the actual but unknown receptor governing the BDNF’s anti-inflammatory ability (Fig. 4A). These analyses highlighted TLR4 and CCR1 as high-potential BDNF-interacting candidates (Fig. 4B). Subsequent co-immunoprecipitation assays demonstrated that BDNF interacted with TLR4, but not CCR1 (Fig. 4C–D). Surface plasmon resonance analysis further confirmed a direct and high-affinity binding between recombinant BDNF and TLR4 proteins (Fig. 4E). Consistently, Fig. 4D also showed that BDNF did not interact with the TLR4 accessory protein MD2, supporting TLR4 as the primary binding partner. Treatment of macrophages with rBDNF increased BDNF-TLR4 complex content, inversely correlated with MD2-TLR4 complex, suggesting that BDNF competitively binds to TLR4 to prevent MD2-TLR4 interaction in LPS-challenged macrophages (Fig. 4F–H; and Supplementary Fig. S5C). After activation, TLR4 recruits two adaptor proteins (MyD88 and TRIF) to activate downstream kinases (TAK1, MAPKs, TBK1, and IRF3) and transcriptional factors such as NF-κB, AP-1, and IRF, respectively, inducing inflammatory gene transcription and cytokine expression13. We then examined the downstream signaling and response in the TLR4 inflammatory cascade in primary macrophages. As shown in the following results, we found that rBDNF treatment dose-dependently inhibited LPS-induced phosphorylation of TAK1, MAPKs, TBK1, and IRF3 (Fig. 4I; and Supplementary Fig. S5D), as well as activation of transcriptional factors (including NF-κB, AP-1, and IRF) (Fig. 4J), corresponding inflammatory gene transcription (including Tnf, Il6, Il1b, Ccl2, Ifna1, Ifnb1, and Ifng) (Fig. 4K), and cytokine production (including TNF-α, IL-6, and IFN-α) (Fig. 4L) in primary macrophages. We also examined the TLR4 inflammatory cascade in rBDNF-treated mice. As shown in Supplementary Fig. S6A, rBDNF administration increased BDNF-TLR4 interaction in mouse lung tissues. LPS challenges induced MD2-TLR4 interaction, phosphorylation of TAK1, MAPKs, TBK1, and IRF3, and NF-κB activation, while rBDNF treatment reversed these changes in mouse lung tissues (Supplementary Fig. S6B–G).

We then examined if TLR4 mediates the anti-inflammatory effects of BDNF in vivo. We constructed macrophage-specific Tlr4-deficient mice which were generated through bone marrow transplantation, and then exposed these mice to LPS or E. coli challenges (Fig. 4M). As shown in Fig. 4N–S, rBDNF treatment failed to further protect mouse lung tissues and septic death in macrophage-specific Tlr4-/- mice challenged with LPS or E. coli.

BDNF has been reported to suppress the inflammatory response of microglia through TrkB14. However, paradoxical evidence demonstrates the absence of TrkB in microglia, leaving the true receptor unclear15. Based on the high abundance of TLR4 in microglia, we hypothesize that BDNF inhibits neuroinflammation by targeting TLR4. To test this, we knocked down Tlr4 in microglia and found that BDNF’s anti-inflammatory effects were markedly reduced upon LPS stimulation (Supplementary Fig. S7A, B). Taken together, our data identified TLR4 as a new receptor for BDNF and revealed that BDNF inhibits LPS-induced inflammation in macrophages by antagonizing TLR4.

The aa 104-115 peptide segment in BDNF binds to the extracellular LRR domain of TLR4
We try to unravel the BDNF-TLR4 binding mechanism. TLR4 protein consists of the extracellular LRR domain, intracellular TIR domain, and the transmembrane sequence (Fig. 5A). Our immunoprecipitation assay showed that TLR4 lacking LRR domain failed to form complex with BDNF, indicating that BDNF binds to the extracellular LRR domain of TLR4 (Fig. 5B). Immunoprecipitation assay further validated that rBDNF protein could interact with the recombinant protein of LRR domain (rLRR) (Fig. 5C). Subsequently, rBDNF was enzymatically digested to generate BDNF-derived short peptides (BDPs) to identify the TLR4-binding segment in BDNF (Fig. 5D; and Supplementary Table S1). Among these BDPs, a dodecapeptide segment of BDNF aa 104-115 (BDP-12, IDTSCVCTLTIK) was identified as the key fragment responsible for rBDNF-rLRR interaction by using immunoprecipitation-MALDI-TOF analysis (Fig. 5D–F). To reinforce this discovery, we synthesized two random BDPs (BDP-18 and BDP-15), which are far away from the binding segment BDP-12, as the negative comparison (Fig. 5E). We mixed BDP-12, BDP-18, and BDP-15 with rLRR, respectively, and then performed the immunoprecipitation-MALDI-TOF analysis. As expected, only BDP-12 showed the interaction with rLRR protein (Fig. 5G). Circular dichroism analysis also showed BDP-12 could change the spectrum of rLRR protein in 210-240 nm, indicating BDP-12 affects the secondary structure of rLRR, while BDP-18 and BDP-15 failed (Fig. 5H). Further normal CETSA or ITDRF-CETSA studies highlighted the binding ability of BDP-12 with TLR4 in macrophages (Fig. 5I, J). As negative comparisons, BDP-18 and BDP-15 failed to interact with TLR4, and BDP-12 did not bind to MD2 (Fig. 5I, J; and Supplementary Fig. S8). Finally, we constructed a plasmid encoding BDNF lacking aa 104-115 (BDNFΔ) and the immunoprecipitation results showed that BDNFΔ lost its binding ability with the extracellular domain of TLR4 (Fig. 5K). Taken together, the extracellular LRR of TLR4 and BDNF aa 104-115 cooperate to mediate the binding between BDNF and TLR4.

Identification of key residues involved in BDNF-TLR4 interaction
Molecular docking was employed to further investigate the residues critical for the interaction between BDNF aa 104–115 and TLR4 LRR domain (Fig. 6A). Residue-binding free energy analysis pointed out the significance of T107 and L113 in BDNF, along with L444, F463, and F487 in TLR4 (Supplementary Table S2, S3). Immunoprecipitation assay revealed that BDNF mutation at either T107A or L113A resulted in reduced affinity to TLR4, and the affinity almost disappeared when both mutations were present at T107A/L113A (Fig. 6B). TLR4 mutations including TLR4F463A and TLR4F487A also exhibited impaired or diminished interaction with BDNF (Fig. 6C). Besides, BDNF variants were overexpressed in 293T cells and secreted into the culture medium, which was then applied to stimulate macrophages (Fig. 6D). The concentrations of the various BDNF variants were consistent across the media (Fig. 6E). Analysis of mRNA levels of the inflammatory markers revealed that BDNFT107A and BDNFL113A displayed a partial reversal, while BDNFT107A/L113A completely abolished the anti-inflammatory effect in LPS-challenged macrophages (Fig. 6F). Taken together, these data underscore the critical roles of T107 and L113 in BDNF and F463 and F487 in TLR4, which jointly contribute to the BDNF-TLR4 interaction.

BDP-12 shows strong anti-inflammatory effects without pro-proliferative activity
We tried to examine whether the BDNF-derived BDP-12 could be developed as a peptide drug for treating inflammatory lung injury. BDNF, known for its pro-proliferative effects via activating TrkB, is overexpressed in several cancers and is considered as a potential proto-oncogene16–18. Since BDP-12 differs from the aa 93-96 within the β-turn of BDNF loop 4, which is the segment known to mediate TrkB activation and promote cell proliferation19, we guess that BDP-12 may avoid the pro-proliferative side effect, a key advantage for its development as an anti-inflammatory drug candidate. We administered rBDNF or BDP-12 to mice for three consecutive days and then assessed PCNA-positive cells in lung tissues. rBDNF treatment induced a marked increase in proliferating (PCNA+) cells, particularly within the epithelial compartment (ECAD+-PCNA+), while macrophages (F4/80+-PCNA+) showed no apparent proliferative response. In contrast, BDP-12 did not trigger any detectable increase in cell proliferation in the lungs (Fig. 7A; and Supplementary Fig. S9A, B). Similarly, in vitro experiments using alveolar epithelial cells revealed that, unlike rBDNF, BDP-12 did not induce TrkB phosphorylation and cell proliferation (Fig. 7B, C; Supplementary Fig. S9C). These data show the safety profile of BDP-12 over BDNF, without potential oncogenic side-effects.

Subsequently, we tested the anti-inflammatory activity of BDP-12 both in vitro and in vivo. BDP-12 treatment dose-dependently disrupted the formation of the MD2-TLR4 complex (Fig. 7D; and Supplementary Fig. S9D) and significantly inhibited the transcription of inflammatory genes (Fig. 7E–G). In contrast, the two negative controls, BDP-15 and BDP-18, failed to suppress inflammatory gene transcription in LPS-challenged macrophages (Supplementary Fig. S9E). Notably, comparison of the dose-response curves revealed that the maximal anti-inflammatory efficacy of rBDNF reached ~60%, whereas BDP-12 achieved over 85%, underscoring the superior therapeutic potential of BDP-12 (Supplementary Fig. S9F). As expected, LPS induced only a weak inflammatory response in Tlr4-deficient macrophages, which may be mediated by alternative inflammatory pathways independent of TLR4. However, BDP-12 treatment showed no effect on this residual inflammatory response (Fig. 7E–G), confirming that BDP-12 exerts its anti-inflammatory effects specifically by targeting TLR4.

Given that neutrophils also express high levels of TLR4, we isolated primary neutrophils to assess whether BDP-12 exerts similar effects in this population. Interestingly, BDP-12 failed to suppress LPS-induced inflammatory responses in neutrophils (Supplementary Fig. S9G), which may be attributable to the ability of neutrophils to phagocytose LPS and activate intracellular alternative pro-inflammatory pathways20. These findings collectively demonstrate that BDP-12 potently and specifically targets macrophage TLR4 to exert its anti-inflammatory effects.

BDP-12 alleviates ALI through inhibiting MD2-TLR4-mediated inflammation
The protective effect of BDP-12 was further explored in LPS-induced ALI mice (Fig. 7H). Before assessing the in vivo efficacy of BDP-12, we evaluated its pharmacokinetic characteristics and found that BDP-12 showed high and sustained pulmonary concentration in mice during the experimental time (Supplementary Fig. S9H). Histological analysis revealed that BDP-12 dose-dependently ameliorated hyaline membrane formation and reduced alveolar wall thickness (Fig. 7I, J). Trends in LPS-induced pulmonary edema and protein leakage aligned with H&E results (Fig. 7K, L). Measurements of BALF total cell count revealed a significant reduction in immunocyte infiltration in ALI mice with BDP-12 injection (Fig. 7M). Moreover, BDP-12 treatment resulted in improved survival rates in LPS-induced septic mice (Fig. 7N). Mechanistically, BDP-12 dose-dependently blocked MD2-TLR4 interaction (Fig. 7O; Supplementary Fig. S9I) and suppressed the production of inflammatory cytokines in LPS-challenged mouse lung tissues, serum, and BALF (Fig. 7P–R).

In addition, we noted that both AAV-BDNF (preventive-like administration) and exogenous rBDNF protein (therapeutic-like administration) exerted protective effects in the ALI model. This prompted us to investigate whether BDP-12 would exhibit similar benefits when administered at different time points. Therefore, BDP-12 was delivered either 6h before LPS challenge (preventive) or 0.5h after challenge (therapeutic) (Supplementary Fig. S10A). Remarkably, both preventive and therapeutic BDP-12 administration significantly ameliorated lung histopathological injury, restored membrane barrier integrity, reduced inflammatory cell infiltration, and suppressed inflammatory responses (Supplementary Fig. S10B–H). Notably, the preventive regimen showed a modestly greater protective effect, likely attributable to the slow clearance and prolonged retention of BDP-12 in lung tissue.

We further examined the pharmacological effects of BDP-12 in the cecal ligation and puncture (CLP)-induced polymicrobial septic mouse model, which is recognized as the gold standard for mimicking the clinical features of sepsis in patients (Fig. 8A). As expected, BDP-12 injection exhibited systemic protective effects in a dose-dependent manner, as evidenced by the reductions in pathological damage not only in the lungs but also in the kidneys and hearts (Fig. 8B–F). Focusing on the lungs, BDP-12 significantly alleviated lung edema, restored permeability, and reduced immune cell infiltration in CLP-challenged mouse lung tissues (Fig. 8G–N). Mechanistically, BDP-12 also prevented the MD2-TLR4 interaction in lung tissue (Fig. 8O, P) and suppressed the inflammatory gene expression in lung tissue, BALF, and serum (Fig. 8Q–S). Collectively, these data indicate the substantial translational potential of BDP-12 as a therapeutic agent for ALI, sepsis, and systemic inflammation, without oncogenic side effects.

Methods
Antibodies and general reagents
The main antibodies and reagents used in this study were provided in Supplementary Table S4.

Cell isolation and culture
Mouse primary fibroblasts were isolated according to a previously established protocol and cultured in DMEM supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin50. Briefly, fresh lung tissue is obtained from euthanized mice and rinsed thoroughly to remove excess blood. Under sterile conditions, the lung tissue is minced into small pieces and evenly distributed across a 10 cm culture dish. Complete culture medium is added, and the dish is incubated at 37°C with 5% CO₂ for 24 h. The medium is then carefully removed and replaced with fresh complete culture medium, with subsequent medium changes performed every 3 d. The outgrowth of fibroblasts is monitored under a microscope. Once the cells approach confluence, all remaining tissue fragments are removed, and the fibroblasts are further cultured as required for experimental purposes.

Mouse primary macrophages were prepared as described previously and maintained in RPMI-1640 medium with 10% FBS and 1% penicillin-streptomycin13. Briefly, mice were intraperitoneally injected with 2 mL of 6% thioglycolate solution (prepared with 0.3g beef extract, 1g tryptone, and 0.5g sodium chloride in 100mL double-distilled water, filtered through a 0.22 μm filter) and maintained under pathogen-free conditions for 3 days. Peritoneal macrophages were isolated by washing the peritoneal cavity with 8 mL RPMI-1640 medium. Collected cells were centrifuged and resuspended in complete RPMI-1640 medium. Primary cultures were seeded at 700,000 cells per 35 mm well, with non-adherent cells removed by medium washing 4 h after seeding. Adherent macrophages were used for experiments 24 h post-plating.

Mouse primary neutrophils were isolated from mouse bone marrow using the Mouse Neutrophil Negative Selection Kit (MCE; NJ, USA) according to the manufacturer’s instructions. Briefly, femurs and tibias were flushed with ice-cold PBS containing 2% FBS to obtain single-cell suspensions, which were subsequently filtered through a 40-µm strainer. Red blood cells were lysed using ACK lysis buffer. The cell suspension was then incubated with a cocktail of biotin-conjugated antibodies targeting non-neutrophil populations, followed by magnetic beads. Labeled cells were depleted using a magnetic separation column, and the untouched neutrophils were collected in the flow-through fraction.

Mouse primary alveolar epithelial cells were obtained from Procell (CP-M330; Wuhan, China) and cultured in their specified medium (Procell: CM-M003). The mouse pulmonary epithelial cell line MLE-12 was purchased from Cellverse (iCell-m036; Shanghai, China) and cultured in a specified medium (Cellverse: iCell-m036-001b). HEK-293T cell line and BV-2 microglial cell line (Procell: CL-0493) were cultured in DMEM supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin.

Mice
All animal care and experimental procedures were approved by the Animal Policy and Welfare Committee of the Wenzhou Medical University (Wenzhou, Zhejiang, China; approval number: wydw2020-0012). Six-week-old male C57BL/6JGpt (Wild-type) mice and Male Tlr4−/− mice (strain number: T051714) were purchased from Gempharmatech (Jiangsu, China). All animals were housed in a pathogen-free room at 22°C ± 2°C, 50%–60% humidity, 12 h:12 h light/dark cycle and fed with a standard rodent diet and water that was available ad libitum. The animals were acclimatized to the laboratory for 2 weeks before initiating the studies. All animal experiments were performed and analyzed by blinded researchers. The mice were divided randomly into groups and housed in the microisolator cages with 6 mice per cage. Each mouse was assigned a temporary random number within the weight range and then given a permanent numerical designation in the cages. For each group, one cage was randomly selected from the pool of all cages. Our study examined male mice because male animals exhibited less variability in phenotype.

Human serum and BALF samples
Blood samples were collected from ARDS patients (n=12) and non-ARDS patients (n=5), along with bronchoalveolar lavage fluid (BALF) samples from ARDS patients (n=10) and non-ARDS patients (n=13) at the Affiliated Cangnan Hospital of Wenzhou Medical University (Approval no. 2024-004). Following collection, the samples were centrifuged at 3000×g, and the resulting supernatants and serum were carefully separated and stored for subsequent analysis.

Adeno-associated virus infection
Adeno-associated virus serotype 6 (AAV6) encoding mature BDNF with an N-terminal fusion albumin signal peptide sequence under the control of the epithelial-specific surfactant protein C (SPC) promoter (AAV6-SPC-BDNF) and negative control (AAV6-SPC-NC) were obtained from Genechem (Shanghai, China). Mice were anesthetized with 2% sodium pentobarbital (80 mg/kg, i.p.), with heart rate, body temperature, and toe pinch reflex monitored to ensure adequate depth of anesthesia. AAV6 was then administered via intratracheal injection at a dose of 5×1010 vg per mouse. The mice were subsequently maintained for 2 weeks to achieve optimal infection efficiency.

Macrophages deletion
Eight-week-old mice were intranasally challenged with 50 μL clodronate liposomes combined with an intravenous injection of 150 μL clodronate liposomes. PBS-containing liposomes were used as a control. The mice were subsequently maintained for 2 days to achieve optimal clearance efficiency.

Bone marrow transplantation
Eight-week-old male recipient mice were housed in filter-top cages and provided with sterile water containing 1000 U/L polymyxin B and 1.1 mg/L neomycin for one week prior to receiving total body irradiation (6 Gy). 12 h post-irradiation, femurs, and tibias were collected from donor mice, and bone marrow cells were flushed out using a 24-gauge syringe. Following red blood cell lysis, the cell suspension was filtered through a 100-μm nylon mesh to create a single-cell suspension. Each irradiated recipient mouse then received an intravenous injection of 2×106 bone marrow cells. The mice were allowed a two-week recovery period before proceeding with subsequent experiments.

LPS-induced ALI model and endotoxemia model
Mice were adequately anesthetized with 2% sodium pentobarbital (80 mg/kg, i.p.). Following anesthesia, mice were challenged via intratracheal injection with LPS (5 mg/kg, dissolved in 0.9% saline) or 0.9% saline alone. Recombinant BDNF (300 ng), BDNF-derived dodecapeptide (BDP-12; 4, 10 mg/kg), or a solvent control were injected intravenously or intraperitoneally at different timepoint according to the experimental design. After 6 h, the mice were sacrificed, and BALF was collected by perfusing the lungs with 2×200 μL of PBS solution through a tracheae cannula. Blood and lung tissue samples were also collected for subsequent analyses.

The collected BALF samples were centrifuged at 3000×g for 5 min. The supernatant was analyzed for total protein levels and cytokine concentrations using ELISA. Cell pellets were resuspended in 100 μL of 0.9% saline, and total cell counts were determined using a hemocytometer. Neutrophil counts were obtained by counting 200 cells on a smear prepared with Wright–Giemsa staining. Lung wet-to-dry weight ratios were assessed as an index of pulmonary edema. Right middle lobes were collected, and wet weights were recorded. Tissues were then dried in a thermostatically controlled oven at 65°C for 24 h, after which dry weights were measured.

Additionally, to induce an endotoxemia model, mice were intravenously injected with 5 mg/kg LPS and sacrificed 12 h later. Various visceral organs were then collected for further analysis.

Survival analysis in E. coli-induced sepsis model
E. coli strain DH5α was grown in Luria Broth (LB) media and the density was determined at 600 nm (OD600) using NanoDrop 2000. The corresponding colony-forming units (CFUs) were determined on LB agar plates. Viable E. coli DH5α (1×109 CFU per mice) in 0.5 mL PBS was injected into the peritoneal cavity (i.p.). Survival of the mice was monitored every 6 h for 3 days.

Cecal ligation and puncture-induced polymicrobial sepsis model
Cecal ligation and puncture (CLP) was performed to induce polymicrobial sepsis in mice. Mice were first anesthetized with 2% sodium pentobarbital (80 mg/kg, i.p.), after which the abdomen was shaved and sterilized with ethanol. A midline incision was made to expose the cecum, which was ligated ~40% from the tip using sterile sutures. A single puncture was created in the ligated segment with a 21-gauge needle to allow a small amount of fecal material to extrude. The cecum was then gently returned to the abdominal cavity, and the incision was closed in layers using absorbable sutures. Postoperative care included fluid supplementation and maintaining a warm environment to promote recovery. 1 h later, BDP-12 (4, 10 mg/kg) or a solvent control was injected intraperitoneally according to the experimental design. 12 h post-CLP, the mice were sacrificed, and blood, BALF, and major visceral tissues were collected for subsequent analyses.

Histological analysis
Tissues were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned to a thickness of 5 μm. For routine histology, the sections were stained with hematoxylin and eosin. The lung injury scores, tubular injury scores, and cardiac injury scores were blindly determined by pathologists using the criteria in previous reports13,51,52.

Immunohistochemistry (IHC) and immunofluorescence (IF) staining were performed on deparaffinized and rehydrated lung sections. For both procedures, antigen retrieval was carried out by heating sections in sodium citrate buffer (pH 6.0). After cooling, sections were blocked with 1% bovine serum albumin (BSA; Sigma-Aldrich) in PBS, and permeabilized with 0.3% Triton X-100 when required (IF). For IHC, sections were incubated with primary antibodies (1:100) overnight at 4°C, followed by horseradish peroxidase (HRP)–conjugated secondary antibodies for 1 h at 37°C. Immunoreactivity was visualized using diaminobenzidine (DAB) and counterstained with hematoxylin. For IF, sections were incubated with mixed primary antibodies raised in different species (1:100 each) overnight at 4°C, followed by species-specific fluorophore-conjugated secondary antibodies for 1 h at room temperature in the dark; nuclei were counterstained with DAPI. Images were captured using brightfield (IHC) or fluorescence (IF) microscopy. Quantification of staining intensity and colocalization was performed using ImageJ software (NIH, Bethesda, MD, USA).

Tissue distribution of BDP-12
Mice were intraperitoneally injected with BDP-12 at 10 mg kg−1 and sacrificed under anesthesia at 4, 8, and 12 h. Organs including heart, liver, spleen, lung and kidney were collected, weighed and homogenized with 0.9% saline solution (1:2 w/v). The homogenate was centrifuged at 12000×g, 4°C for 10 min; an aliquot of the supernatant was mixed with trifluoroacetic acid containing loratadine (100 ng mL−1) as internal standard, vortexed for 3 min, and re-centrifuged at 12000×g for 10 min. The final supernatant was transferred to an autosampler vial and BDP12 concentration was quantified by UPLC-MS/MS.

Myeloperoxidase activity assay
Neutrophil tissue infiltration was evaluated in terms of myeloperoxidase (MPO) activity in lung tissue samples using an MPO Activity Assay Kit (Thermo Fisher). Lung tissues were homogenized in 1 ml of 50 mM potassium PBS (pH 6.0) containing 0.5% hexadecyltrimethylammonium hydroxide and centrifuged at 15000×g, 4°C for 20 min. Ten microliters of the supernatant were transferred into PBS (pH 6.0) containing 0.17 mg/ml 3,3’-dimethoxybenzidine and 0.0005% H2O2. MPO activity in the supernatant was determined by measuring the absorbance at 460 nm. Total protein levels were measured using a Pierce BCA Protein Assay Kit (Thermo Fisher). Data are presented as U/g tissue.

Western blot
Proteins were isolated using RIPA lysis and extraction buffer, and protein concentrations were measured using the Pierce BCA Protein Assay Kit. Protein lysates were separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes. The membranes were blocked with skim milk for 1 h at room temperature, and then incubated with primary antibodies, at 4°C overnight. Secondary antibodies were applied for 1 h at room temperature. Immunoreactivity was visualized using an enhanced chemiluminescence reagent (Bio-Rad; Hercules, CA, USA). Protein-protein interactions were evaluated using co-immunoprecipitation. Protein lysates were incubated with specific precipitating antibodies at 4°C overnight, precipitated with protein A/G agarose beads, and used for the detection of interacting proteins by means of immunoblotting. ImageJ analysis software was used for densitometric quantification of the blots. Densitometric quantification data were normalized to the total protein levels or loading controls.

Transcriptome sequencing
Total RNA from the tissues was isolated and purified using TRIzol reagent following the manufacturer’s procedure. The RNA amount and purity of each lung sample were quantified using NanoDrop ND-1000 (NanoDrop; DE, USA). The RNA integrity was determined using Bioanalyzer 2100 (Agilent; CA, USA), and confirmed by electrophoresis with denaturing agarose gel. Poly(A) RNA is purified from 1 μg total RNA using Dynabeads Oligo(dT)25 (Thermo Fisher). Then the poly(A) RNA was fragmented into small pieces using a Magnesium RNA Fragmentation Module (NEB; MA, USA). The cleaved RNA fragments were then reverse transcribed into cDNA by SuperScript™ II Reverse Transcriptase (Thermo Fisher). Finally, the sequence analysis was performed on an Illumina Novaseq™ 6000 following the manufacturer’s instructions. After generating the final transcriptome, the expression levels of all transcripts were estimated. The differentially expressed mRNAs were selected with adj. p value < 0.05.

ELISA assay
Cytokines and BDNF levels were quantified in mouse serum, BALF, various tissues, cell culture media, and human samples. Mouse TNF-α, IL-6, IFN-α, and BDNF levels were measured using ELISA kits according to the manufacturer’s instructions, as were human TNF-α, IL-6, and BDNF levels. Additionally, we constructed custom ELISA to detect the BDNF-TLR4 and MD2-TLR4 complexes. Briefly, 96-well plates were coated with TLR4 antibody and blocked with BSA. Protein lysates from cells subjected to different treatments were then added, followed by incubation with either MD2 or BDNF antibody. After washing, HRP-conjugated secondary antibody against MD2 or BDNF antibody was added, and the reaction was developed using TMB solution. Absorbance was measured at 450 nm using a SpectraMax® M5 Multi-Mode Microplate Reader (Molecular Devices; San Jose, CA, USA) for all ELISA assays.

Flow cytometry
Cell pellets obtained from BALF were resuspended in 100 μL of FACS buffer (PBS with 2% FBS and 1 mM EDTA). The cells were stained with FITC-anti-CD45, PE-anti-F4/80, and PerCP-anti-Ly6G for 30 min on ice. Following staining, the cells were washed three times with FACS buffer and analyzed using a BD Accuri™ C6 Cytometer (BD Biosciences; Franklin Lakes, NJ, USA). Total viable single cells were initially gated for CD45-positive immune cells and subsequently analyzed for F4/80 and Ly6G expression. Neutrophils were identified as Ly6G+, while macrophages were identified as F4/80+.

Real-time qPCR
Total RNA was extracted from tissues using Trizol Reagent. RNA was reverse-transcribed using PrimeScript TM RT reagent (Takara: RR047A). Real-time PCR was conducted using TB Green® Premix Ex TaqTM II (Takara: RR820A) on CFX96 Touch Real-Time PCR Detection System (Bio-Rad). Relative expression was normalized to Actb. Target gene sequences are listed in Supplementary Table S6. For some studies, we utilized a pre-coated inflammatory factor qPCR Array (CT Bioscience; Changzhou, Jiangsu, China). Data from pre-loaded arrays was normalized to Hprt1.

Chromatin immunoprecipitation (ChIP)-PCR
ChIP assays were performed in MLE-12 cells to assess whether GATA2 binds to the Bdnf promoter. Cells were crosslinked with 1% formaldehyde, quenched with glycine, and lysed according to standard procedures. Chromatin was fragmented using micrococcal nuclease (MNase) digestion to yield nucleosomal DNA fragments (150-500 bp). The digested chromatin was incubated overnight at 4°C with anti-GATA2 antibody or normal IgG control, and immune complexes were captured with Protein A/G magnetic beads. Following a series of stringent washes, crosslinks were reversed and DNA was purified using a column-based method. Four primer pairs (Supplementary Table S6) were designed to span four contiguous segments of the Bdnf promoter, enrichment at each segment was assessed by qPCR.

Cell transfections
To silence Ntrk2 (encoding TrkB) in macrophages, we purchased the corresponding Ntrk2 targeted siRNA (MCE: HY-RS09632) and transfected it into the cells using Lipofectamine RNAiMAX (Thermo Fisher: 13778150) according to the manufacturer’s instructions. To knockout Tlr4 (encoding TrkB) in microglial, we constructed the corresponding targeted All-in-one CRISPR/Cas9 plasmid through GeneScript and transfected it into the cells using Lipofectamine 2000 (Thermo Fisher: 11668019) according to the manufacturer’s instructions. For the overexpression of BDNF, TLR4, CCR1, and MD2 in HEK-293T cells, we utilized pcDNA3.1 plasmids containing the coding sequences of wild-type or mutated genes, synthesized by GeneScript, and transfected the cells using Lipofectamine 2000. In the luciferase reporter assay, we transfected the p65 reporter plasmid (Beyotime: D2206), AP-1 reporter plasmid (Beyotime: D2108), and ISRE reporter plasmid (Beyotime: D2179) into the cells using Lipofectamine 2000, following the manufacturer’s guidelines for all transfections.

Proteome microarray assays
HuProt™ v4.0 Human Proteome Microarrays (CDI Laboratories; Baltimore, MD, USA), containing over 21,000 unique human proteins, were used to identify BDNF-interacting proteins. The microarrays were blocked with a blocking buffer, and either biotinylated BDNF or biotinylated BSA was added. Following washing, Cy5-streptavidin was incubated. Scanning was performed using the GenePix 4200A (Axon Instruments; Sunnyvale, CA, USA), and the raw data were analyzed with GenePix Pro v6.0 software. The signal-to-noise ratio (SNR) was defined as the ratio of the median foreground signal to the median background signal for each protein. The SNR for each protein was averaged from two duplicate spots on each microarray. Proteins with an SNR in the BDNF-treated group greater than both the BSA-treated group and 1.5 were considered potential interacting proteins.

Immunoprecipitation-coupled mass spectrometry (IP-MS)
Primary macrophages were stimulated with recombinant BDNF for 1 h and subsequently lysed in NP-40 lysis buffer containing protease and phosphatase inhibitors. After clarification by centrifugation, the supernatants were incubated overnight at 4°C with anti-BDNF antibody (2 μg per mg protein) pre-bound to magnetic Protein A/G beads (Thermo Fisher). Following extensive washing to eliminate nonspecific interactors, bound proteins were eluted by heating in denaturing buffer. Samples were subjected to in-solution tryptic digestion after reduction (10 mM DTT) and alkylation (55 mM iodoacetamide), and the resulting peptides were desalted on C18 cartridges. Peptide mixtures were analyzed by DIA-based LC–MS/MS on a high-resolution mass spectrometer. Data processing was performed against the Mus musculus UniProt database, using a 1% false discovery rate at both peptide and protein levels.

Surface plasmon resonance assay
The binding affinity of BDNF to rTLR4 was determined using a Biacore T200 instrument (Cytiva; Marlborough, MA, USA) with a CM5 sensor chip (Cytiva). Briefly, rTLR4 was loaded onto the sensors using an Amine Coupling Kit (Cytiva). rBDNF samples (at concentrations of 0, 3.13, 6.25, 12.5, 25, 50, or 100 nM) were prepared in a running buffer (PBS, 0.5% P20). The sensor and sample plates were placed on the instrument and the rBDNF samples flowed over the black and target sensors. Seven concentrations were injected successively, at a flow rate of 30 μL·min-1, for a 200-s association phase, which was followed by a 200-s dissociation phase at 25°C. The final graphs were obtained by subtracting the blank sensorgrams and blank samples from the duplex. The data were analyzed using Biacore T200 software EV (Cytiva). The dissociation constant (KD) was calculated by global fitting of kinetic data from various concentrations of rBDNF using a 1:1 Langmuir binding model.

Tryptic digestion and immunoprecipitation
Immobilized TPCK trypsin (30 μL) was used to digest 30 μg of human BDNF at 37°C for 1 hour. The cleavage sites and resulting peptides were analyzed using PeptideCutter (https://web.expasy.org/peptide_cutter/), and fragments containing 10-20 residues were synthesized as standard polypeptides53. The BDNF fragments or standard polypeptides were aliquoted and incubated with 30 μg of human TLR4 or a solvent control overnight on ice. Following this, protein A/G agarose beads and a TLR4 antibody were added to immunoprecipitated TLR4 and its interacting molecules. After centrifugation, the beads were collected, denatured in 0.1 M Glycine-HCl (pH 2.7), and heated at 95°C for 5 min. Finally, the beads were removed by centrifuge again and the supernatant was used for subsequent Mass spectrometry identification.

Mass spectrometry
The samples derived from tryptic digestion and immunoprecipitation were loaded onto ground steel (Bruker: 8280784; Billerica, MA, USA) using the dried droplet method. Briefly, α-Cyano-4-hydroxycinnamic acid (HCCA) was dissolved in TA30 (30:70 v/v Acetonitrile: 0.1% TFA in water) to create a saturated solution. Equal volumes of the samples and HCCA solution were mixed and spotted onto the ground steel to air dry. Finally, the ground steel was analyzed using the Autoflex Max MALDI-TOF mass spectrometer (Bruker).

Circular dichroism spectroscopy
Polypeptide standards synthesized based on the amino acid sequence fragments of BDNF were mixed with 16 μM recombinant TLR4 at concentrations of 0, 8, 16, and 32 μM, respectively. Subsequently, changes in ellipticity were immediately measured using a ChiraScan circular dichroism spectrometer (Applied Photophysics; Leatherhead, Surrey, UK) over the wavelength range of 200–280 nm.

Cellular thermal shift assay
Cellular thermal shift assay (CETSA) experiments were conducted following a standard CETSA protocol54. Briefly, cultured primary macrophages were treated with standard polypeptides for 24 h. The cells were then harvested and resuspended in phosphate-buffered saline. Treated samples were aliquoted and heated at different temperatures for 3 min in a PCR plate (Thermo Fisher). Following heating, a protease inhibitor cocktail was added, and the cells were lysed using three freeze-thaw cycles with liquid nitrogen and a heat block. The cell lysates were centrifuged at 20,000×g for 20 min. Supernatants were analyzed by Western blot.

Additionally, isothermal dose-response fingerprints (ITDRF)-CETSA were performed on the same cells. Briefly, cultured primary macrophages were treated with gradient concentrations of standard polypeptides for 24 h. The cells were harvested and resuspended as before, then heated at 61°C for 3 min. The cells were subsequently lysed and analyzed using the same procedures.

Molecular docking
The crystal structures of TLR4 (PDB code: 3FXI) and BDNF (PDB code: 1B8M) were obtained from the Protein Data Bank. Molecular docking between TLR4 and BDNF was performed using Hawkdock (http://cadd.zju.edu.cn/hawkdock/)55. Among the top 10 results, only the conformation with interactions involving BDNF amino acids 104–116 was selected for MM/GBSA analysis. The top 10 key residues responsible for protein-protein interactions were identified based on per-residue decomposition energy calculations.

Proliferation and viability assay
The effects of rBDNF and BDP-12 on cell proliferation and viability were assessed using a CCK-8 kit according to the manufacturer’s instructions. Additionally, mice were administered rBDNF (300 ng) and BDP-12 (4, 10 mg/kg) once daily for 3 consecutive days, after which they were sacrificed, and lung tissues were collected for immunohistochemical staining of PCNA, as well as dual-immunofluorescence co-staining for ECAD+PCNA and F4/80+PCNA to determine in vivo proliferative activity.

RNA-seq data processing
RNA sequencing was performed using the Illumina NovaSeq™ 6000 platform to generate paired-end reads. Raw sequencing data in FASTQ format were first processed using FastQC to assess the quality of the reads. Adapter sequences and low-quality bases were removed using Trimmomatic to ensure high-quality data. Clean reads were then aligned to the reference genome using HISAT2. The resulting aligned reads in BAM format were sorted and indexed using SAMtools. Gene-level quantification was performed using featureCounts from the Subread package to obtain raw read counts. Differential gene expression analysis was conducted using DESeq2 in R. Genes with an adj. p value < 0.05 and |log2(fold change)| > 1 were considered significantly differentially expressed.

Publicly available single-cell and bulk transcriptomic data
Public single-cell RNA sequencing data for CLP and sham lung samples were obtained from the GEO database (accession number: GSE207651)56. Subsequent analyses and visualizations were conducted using the Majorbio cloud platform (https://www.majorbio.com/)57. More single-cell expression results of liver Bdnf were obtained from public databases including The Human Protein Atlas (https://www.proteinatlas.org/) and Single Cell Expression Atlas (https://www.ebi.ac.uk/gxa/sc/home)58,59. Additionally, several bulk RNA sequencing datasets from both human and mouse lungs, with or without acute pneumonia, were sourced from the GEO database, including GSE233206, GSE214249, GSE104214, GSE199546, GSE38092, GSE64027, GSE150910, and GSE21369. Differentially expressed gene lists were extracted directly from the supplementary files of each dataset or analyzed using the GEO2R web tool when applicable. For datasets providing only raw counts or FPKM values, expression matrices were analyzed using the ExpressAnalyst web tool (https://www.expressanalyst.ca/)60.

Statistics & reproducibility
All data are reported as Mean ± SEM. Statistical analysis was performed with GraphPad Prism 8.0 software (San Diego, CA, USA). Sample sizes were not predetermined using statistical methods but were consistent with those commonly used in the field. All assays were performed in at least three independent experiments. Each dot point represents an individual animal or independent experiment. The Shapiro–Wilk test was applied to assess normality. For comparisons between two groups, unpaired Student’s t-tests were used, or the Mann–Whitney U-test if applicable. For multiple group comparisons, two-sided one-way ANOVA followed by Tukey’s post hoc test was conducted. Statistical tests were selected based on data distribution, with statistical significance defined as p < 0.05. All data collection and analysis were conducted in a blinded manner, and no animals were excluded.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript investigates the anti-inflammatory effects of BDNF and its binding target TLR4. The novel short peptide, BDP-12, is developed and evaluated for its therapeutic effects in models of lung inflammation, bacterial infection and CLP. The findings suggest that both full-length BDNF and BDP-12 can ameliorate inflammation, reducings numbers of macrophage and neutrophils. Lastly, GATA2 is proposed as a regulator of BDNF expression in lung epithelial cells. In conclusion, this manuscript shows that BDP-12 may hold a promising potential of treatment of inflammation conditions. Despite of extensive bioinformatic analyses of discovery datasets and multiples in vitro and in vivo models, the lack of direct side-by-side comparisons of full-length BDNF and BDP-12 potency and efficacy in all critical assays, the unresolved questions regarding cell-specific targets and mechanisms beyond macrophages, and the shift in focus from TLR4 in macrophages to GATA2 in epithelial cells, all compromise the clarity and the impact of the conclusions. By addreassing all the concerns below, this manuscript will significantly improve in the scientific rigor and clarity, making it is more impactful.\n1. The manuscript presents a significant discrepancy in the doses of rBDNF (used in µM range) and BDP-12 (used in nM range) in both in vitro and in vivo assays. rBDNF appears to be used at much lower concentrations to achieve an effect, suggesting higher potency. A thorough side-by-side dose-response comparison of rBDNF and BDP-12 in both in vitro and in vivo models may be necessary. Without such a direct comparison, the claims regarding BDP-12 therapeutic potency relative to rBDNF may be unsubstantiated.\n2. The authors highlight the advantage of BDP-12 over rBDNF being its inability to promote cell proliferation in the lungs. While this is a crucial claim for its therapeutic safety, the evidence presented is primarily PCNA staining. PCNA indicates proliferation but it does not identify the specific proliferating cell types. To directly assess whether BDP-12 has a direct lack of proliferative effect on specific cells in the lung tissues, co-staining of PCNA with cell-specific markers would be helpful. This will provide a more direct evidence to support the claim that BDP-12 does not promote non-specific cell proliferation in critical lung cell types, including macrophages. Moreover, the results will differentiate it from the known regenerative effects of BDNF on epithelial cells (BDNF-TrkB promoting lung epithelial regeneration, Nature Med. 26, 1422–1432 (2020)). However, this may lead to the question of whether BDP-12 should be considered a therapeutic if it lacks the regenerative aspects of full-length BDNF, especially in the context of ALI/ARDS where regeneration is crucial. This needs to be discussed.\n3. The manuscript effectively demonstrates the protective effect of BDP-12 across several disease models and shows decreased numbers of macrophages and neutrophils in lung tissues. While the authors investigate the role of macrophages using clodronate depletion (Fig 3H-3N), leading to the conclusion that BDNF's effect is macrophage-dependent, the role of neutrophils that also play significant roles in lung and systemic inflammation remains largely unexplored. Given that neutrophil numbers also significantly decrease (Fig 2H, 2K, 2T, 2W), it is imperative to investigate whether BDP-12 (or BDNF) has a direct effect on neutrophils, their recruitment, survival, or inflammatory function. Additional neutrophil experiments will be essential to determine the extent to which neutrophil modulation contributes to the observed anti-inflammatory effects. The current data in this manuscript imply macrophages are the major pathogenic factor. But with the existing neutrophil data, there is a significant gap without further investigation.\n4. Figure 2 and S3 demonstrate that despite a substantial difference in BDNF levels in the lung between mice receiving AAV-BDNF (60 ng/ml) and rBDNF (200 ng/ml), the outcomes in various parameters (protein concentration, total cells, neutrophils, macrophages, and survival rate) are quite similar. This finding is intriguing and requires explicit discussion. The authors should consider to elaborate on the potential implications of this observation: a) does it suggest a plateauing effect of BDNF at certain concentrations, where higher levels do not confer additional benefit? b) does it hint at differences in bioavailability, sustained release kinetics, or cell-specific targeting between AAV-mediated expression and recombinant protein administration? A dedicated discussion paragraph addressing this point would significantly enhance the manuscript to a broader audience.\n5. In Figure 2A, AAV-BDNF was administered before LPS injection, suggesting a preventive effect. In contrast, Figure 2M shows rBDNF administered after LPS injection, indicating a dual protective/therapeutic effect. From these models, the authors may imply both preventive and protective effects for the potential rBDNF/BDP-12. It would be beneficial to explicitly state this potency by demonstrating side-by-side data of both preventive and protective efficacy of both rBDNF and BDP-12 within the same experimental model or section, for clearer comparison.\n6. The manuscript concludes with a claim that GATA2 is a regulator of BDNF expression in lung epithelial cells. This claim represents a significant shift from the primary focus on macrophage-mediated inflammation. While mechanistic insights are valuable, the connection between macrophage-associated TLR4-BDNF binding and its inflammation reduction (the main finding) and GATA2-regulated BDNF in epithelial cells feels somewhat disconnected given the depth of investigation into macrophage roles vs. epithelial cell roles. In addition, what kind of protein/signaling pathways that suppressed GATA2 in lung inflammation? Because BDNF, but not BDP-12, activates phosphorylation of TrkB in lung epithelial cells (Fig 7B), is GATA2 directly under TrkB regulation, or is this an independent pathway influencing BDNF expression? More context and perhaps some preliminary data on upstream regulators of GATA2 from ALI or CLP murine models, and its direct link to TrkB signaling in epithelial cells, may be pivotal to justify the final regulatory mechanism.\n7. Fig 7A-C show that BDP-12 lacks proliferative effect. If BDP-12 does not promote this regeneration, its therapeutic value might be limited for recovery aspects of ALI, even if it is anti-inflammatory. This needs to be discussed thoroughly to clarify the therapeutic niche of BDP-12.\n8. The description of the protein-protein interaction network is insufficient. The key methodological details are missing, making it impossible for readers to understand how the network was constructed or how conclusions were drawn. The authors should provide a detailed methodology for the network generation, including sources, criteria for selecting nodes and edges, specific algorithms for network analysis. Furthermore, the selection of TLR4 as a key candidate BDNF-binding partner (hub protein) lacks a clear, quantifiable justification. TLR4 has 6 edges (Fig 4C), but other transmembrane proteins identified in the protein microarray assay (which directly assessed BDNF binding) such as PDCD1 and CXCR3, also appear to have a similar number of edges. If these proteins can indeed bind BDNF (as suggested by the protein microarray, which should be the primary evidence for binding), and they also have significant connectivity. The rationale for prioritizing TLR4 over these equally candidates must be explicitly described.\n9. TLR4 is up-regulated after LPS stimulation. This fact is highly relevant and should be integrated into the discussion of BDNF-TLR4 interactions, leading to questions about the dynamics of the proposed BDNF-TLR4 binding. Since LPS binds to TLR4 via MD2, does the increased TLR4 expression, or the presence of BDNF, create a rate-limiting step for BDNF-TLR4 binding that could affect competitive binding with MD2 and LPS?\n10. Given that TLR4 activation itself triggers robust inflammatory signaling, is there any evidence or hypothesis for a negative feedback loop whereby BDNF binding to TLR4 (or its downstream effects) might modulate the signaling cascades initiated by LPS in macrophages? A discussion about this area may be required to support the proposed role of BDNF in modulating TLR4 signaling.", "reviewer_2": "The authors demonstrated that brain-derived neurotrophic factor (BDNF), released from pulmonary epithelial cells, acts as a toll-like receptor 4 (TLR4) agonist, which attenuates sepsis. They also developed a BDNF-derived peptide that mitigated sepsis. The study's design and storyline are straightforward and logical. The authors implemented many interventional approaches, such as lung epithelial-specific overexpression of BDNF, enhancing the rigor and significance of the study. The study offers valuable insights into the field of immunology. The following are my specific comments.\nFig. 1K, W. Could the authors create graphs with multiple samples like other parameters? Y-axis label: \"Normalized Count (% of Max)\" or an equivalent would be less confusing.\nFig. 2F. Serum BDNF was not associated with ARDS, as shown in Fig 1E, F. Why was rBDNF injected iv instead of it? Does iv result in increased BDNF in the BALF? Even if so, it could seem contradictory if the authors want to keep the serum data. (I do understand it was presented to show the rationale for focusing on the lungs/epithelial cells.)\nFig. 3H-N. The study design is not very convincing. It can be interpreted as simply showing that macrophages exacerbate ALI. Since they are absent in the Clo-lip groups, less lung injury is observed irrespective of rBDNF. The lack of further alleviation by rBDNF does not necessarily mean that macrophages are responsible for the effect of rBDNF, as there is no guarantee that such situation exists.\nFig. 4D. Why was BDNF pulled down instead of TLR4? If TLR4 was pulled down, it could have had TLR4 as a loading control in the IB membrane in addition to the Input. If you pull down BDNF in samples without BDNF, nothing will be detected, and you cannot have a proper control. According to the \"Tryptic digestion and immunoprecipitation\" section of the Methods, it appears that the authors IP'ed with TLR4 Ab, which makes more sense. BDNF in both samples, TLR4 -/+, and pulling down BDNF would also work. Moreover, I might have overlooked it but could not find the information that the proteins were tagged as in the figures.\nFig. 4M-S. The similar issue as Fig. 3H-N. It can be interpreted as simply showing that TLR4 exacerbates ALI irrespective of rBDNF. The lack of further alleviation by rBDNF does not necessarily mean that TLR4 are responsible for the effect of rBDNF.\nFig. 5B, C. The same issue for IP as Fig 4D.\nHow is baseline BDNF maintained? How does GATA2 decrease in sepsis?", "reviewer_3": "The manuscript by Weiwei Zhu et al. presents novel findings about the role of the major neurotrophin BDNF on Acute Lung Injury (ALI), its mechanism of action on macrophages and the subsequent regulation of inflammation, and most importantly, the authors reveal the direct interaction of BDNF with the TLR4 receptor. This interaction has also significant translational outcome, expecially upon the detailed characterization of the interacting residues and the development of a BDNF-derivative which could offer a clinical use. It is very interesting the cross talk humoral-cellular immunity, both in the fields of immunology but also on neurotrophins' action outside the nervous system.\nThe study is very well designed, all experiments are adequately performed and the results are presented in a clear manner, emphasizing on the most important findings and providing new pharmacological agents for pre-clinical evaluation in ALI and perhaps in more inflammatory diseases.\nHowever, the important findings of the present study require some clarification and complementary experiments, in order to fully support the conclusions and claims. Specifically:\nGeneral Comments\n1. The authors have shown that the high affinity receptor for BDNF, namely TrkB, is not involved in the anti-inflammatory effects of this neurotrophin. However, there are many studies showing that the low-affinity receptor of all mature and immature neurotrophins (proneurotrophins), the p75 pan-neurotrophin receeptor, is expressed in macrophages and moreover, TLRs could interact with p75 signaling. Thus, the expression of p75 receptor, as well as the expression of proBDNF, should be explored. Is the reduction of BDNF during ALI accompanied by an increase in proBDNF expression? This could induce p75 signaling, separetely or in parallel with the BDNF-TLR4 signaling. Additonally, the BDP-12 peptide should be investigated for activating the p75NTR.\n2. The detailed characterization of the amino residues of BDNF that directly interact with TLR4 and the development of a novel dodecapeptide which selectively activate this receptor and protects against inflammation, are of high importance for further pre-clinical evaluation. The authors should perform a pharmacokinetic-pharmacodynamic (PK/PD) study in order to define the effective concentration in the tissues of interest (lung for macrophages, brain for microglia). Additionally, the detection of BDP-12 in tissues should be presented upon its administration. Toxicity studies could also enhance the pre-clinical characterization of this molecule.\n3. The authors should check the effect of BDP-12 in macrophage specific TLR4KO mice to exclude that it may have anti-inflammatory effects by targeting other immune cell types.\nSpecific comments\n1. Figure1K\nIn the western blot showing reduction of BDNF levels, the authors should show up-regulation of an inflammatory marker in the same samples.\n2. Figure 4 O-R\nInclude the control without LPS in the graphs to show the effect of TLR4 alone. Here we don’t see any reverse by BDNF but there is anyway reduced (or any) pathology in the TLR4KO mice.\n3. Figure 5\nThe authors should perform pharmacokinetic analysis of BDP-12 to support their suggestion of its therapeutic potential.\n4. Suppl. Figure S9\n- Missing Chip-qPCR for GATA2 in BDNF promoter +/- LPS in the primary lung epithelial cell line.\nMinor Comments\n- Line 408. Correct to cell isolation and culture.\n- The authors should discuss the fact that TLR4 downregulates the expression of BDNF in inflammation (Tan et al., 2025, Gao et al.,2021) and discuss any possible negative feedback loop as BDNF inhibits TLR4 activity.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We sincerely appreciate the editor and the four reviewers and their insightful comments on our study. As suggested by the reviewers, we have performed additional studies to address the questions raised. In addition, the manuscript is extensively revised to incorporate the new data as well as to correct typographical and grammatical errors.\nBelow is our point-to-point response to the comments. Editor and Reviewers’ comments are in grey shaded text.\nREVIEWER 1\nOverview: This manuscript investigates the anti-inflammatory effects of BDNF and its binding target TLR4. The novel short peptide, BDP-12, is developed and evaluated for its therapeutic effects in models of lung inflammation, bacterial infection and CLP. The findings suggest that both full-length BDNF and BDP-12 can ameliorate inflammation, reducings numbers of macrophage and neutrophils. Lastly, GATA2 is proposed as a regulator of BDNF expression in lung epithelial cells. In conclusion, this manuscript shows that BDP-12 may hold a promising potential of treatment of inflammation conditions. Despite of extensive bioinformatic analyses of discovery datasets and multiples in vitro and in vivo models, the lack of direct side-by-side comparisons of full-length BDNF and BDP-12 potency and efficacy in all critical assays, the unresolved questions regarding cell-specific targets and mechanisms beyond macrophages, and the shift in focus from TLR4 in macrophages to GATA2 in epithelial cells, all compromise the clarity and the impact of the conclusions. By addreassing all the concerns below, this manuscript will significantly improve in the scientific rigor and clarity, making it is more impactful..\nReviewer #1-1: The manuscript presents a significant discrepancy in the doses of rBDNF (used in µM range) and BDP-12 (used in nM range) in both in vitro and in vivo assays. rBDNF appears to be used at much lower concentrations to achieve an effect, suggesting higher potency. A thorough side-by-side dose-response comparison of rBDNF and BDP-12 in both in vitro and in vivo models may be necessary. Without such a direct comparison, the claims regarding BDP-12 therapeutic potency relative to rBDNF may be unsubstantiated.\nResponse: Thank you for this important comment. The substantial difference in effective doses between rBDNF and BDP-12 is indeed expected, given the inherent biophysical and pharmacological differences between a full-length protein and a short peptide fragment. Short peptides generally display reduced structural rigidity, stability, and half-life compared with their parent proteins, and therefore often require higher concentrations to achieve comparable biological effects. This phenomenon has also been documented in other systems—for example, recombinant adiponectin requires a dose of 28 ng/g to improve insulin resistance in mice (PMID: 32880686), 1 whereas its peptide derivative ALY688 requires approximately 5 µg/g (PMID: 38847320). To further clarify the relative potency of rBDNF and BDP-12, we additionally performed concentration–response analyses of their anti-inflammatory effects. We found that rBDNF produced a maximal inhibition of inflammatory responses of ~60%, whereas BDP-12 achieved >85% inhibition at its optimal concentration (Reviewer Figure 1). These results indicate that, despite requiring different absolute dosing ranges, BDP-12 exhibits superior functional efficacy when considering overall anti-inflammatory activity, specificity, and safety.\nReviewer Figure 1 (new Supplementary Figure S9F)\nMPMs were pretreatment of rBDNF (0, 3.125, 6.25, 12.5, 25, 50, 100, 200, 400 ng/mL) or BDP- 12 (0, 0.0625, 0.125, 0.25, 0.5, 1, 2, 4, 8 µM) for 0.5 h, then the cells were stimulated with LPS (500 ng/mL) for 24 hours. IL-6 levels in the medium were measured by ELISA, and relative content were calculated.\nReviewer #1-2: The authors highlight the advantage of BDP-12 over rBDNF being its inability to promote cell proliferation in the lungs. While this is a crucial claim for its therapeutic safety, the evidence presented is primarily PCNA staining. PCNA indicates proliferation but it does not identify the specific proliferating cell types. To directly assess whether BDP-12 has a direct lack of proliferative effect on specific cells in the lung tissues, co-staining of PCNA with cell-specific markers would be helpful. This will provide a more direct evidence to support the claim that BDP-12 does not promote non-specific cell proliferation in critical lung cell types, including macrophages. Moreover, the results will differentiate it from the known regenerative effects of BDNF on epithelial cells (BDNF-TrkB promoting lung epithelial regeneration, Nature Med. 26, 1422–1432 (2020)). However, this may lead to the question of whether BDP-12 should be considered a therapeutic if it lacks the regenerative aspects of full-length BDNF, especially in the context of ALI/ARDS where regeneration is crucial. This needs to be discussed.\nResponse: Thank you for this valuable suggestion. Following your recommendation, we have added PCNA co-staining with cell-specific markers in the revised manuscript. As expected, the results show that only rBDNF induces noticeable proliferative activity in lung tissues, and this effect occurs predominantly in epithelial cells, rather than macrophages (Reviewer Figure 2A-B). This is likely due to the limited expression of the classical BDNF receptor TrkB in macrophages. In contrast, BDP-12 does not exhibit detectable proliferative effects. We also acknowledge the reviewer’s point that BDNF-TrkB-mediated epithelial regeneration plays an important role in ALI/ARDS recovery. However, excessive or ectopic proliferation may result in maladaptive repair, fibrotic remodeling, or potential oncogenic risks. Thus, we consider that BDP-12’s therapeutic advantage lies in its potent anti-inflammatory efficacy without eliciting undesirable proliferative effects. While BDP-12 can be administered alone when strong anti-inflammatory activity is required, it could be used in combination with other regenerative therapies to support epithelial repair when appropriate. We have incorporated this point into the revised Discussion section. 2\nReviewer Figure 2 (new Supplementary Figure S9A-B)\nMice treated with rBDNF or BDP-12 for 3 days underwent double immunofluorescence staining for ECAD–PCNA (A) or F4/80–PCNA (B) in lung tissues.\nReviewer #1-3: The manuscript effectively demonstrates the protective effect of BDP-12 across several disease models and shows decreased numbers of macrophages and neutrophils in lung tissues. While the authors investigate the role of macrophages using clodronate depletion (Fig 3H- 3N), leading to the conclusion that BDNF's effect is macrophage-dependent, the role of neutrophils that also play significant roles in lung and systemic inflammation remains largely unexplored. Given that neutrophil numbers also significantly decrease (Fig 2H, 2K, 2T, 2W), it is imperative to investigate whether BDP-12 (or BDNF) has a direct effect on neutrophils, their recruitment, survival, or inflammatory function. Additional neutrophil experiments will be essential to determine the extent to which neutrophil modulation contributes to the observed anti-inflammatory effects. The current data in this manuscript imply macrophages are the major pathogenic factor. But with the existing neutrophil data, there is a significant gap without further investigation.\nResponse: Thank you for this important comment. We isolated neutrophils from mouse bone marrow and examined the anti-inflammatory activity of BDP-12 in these cells. Our results showed that BDP-12 did not exert anti-inflammatory effects in neutrophils (Reviewer Figure 3). We speculate that this may be due, in part, to the fact that neutrophils rely heavily on their phagocytic function to mediate inflammatory responses rather than solely on membrane receptor–mediated signaling. Thus, even when membrane receptors are antagonized, LPS can still be internalized and directly promote inflammation. This is consistent with previous reports showing that engulfed LPS can activate the NLRP3 inflammasome in neutrophils (PMID: 30720889; PMID: 28462526). Taken together, these findings suggest that BDP-12 acts with higher specificity in macrophages and that its anti-inflammatory effects are primarily macrophage dependent. We have incorporated this point into the revised Discussion section. 3\nReviewer Figure 3 (new Supplementary Figure S9G)\nPrimary neuthophils were pretreatment of BDP-12 (2, 4 µM) for 0.5 h, then the cells were stimulated with LPS (500 ng/mL) for 6 hours. Relative mRNA levels of pro-inflammatory factors Tnf, Il6, and Il1b were determined.\nReviewer #1-4: Figure 2 and S3 demonstrate that despite a substantial difference in BDNF levels in the lung between mice receiving AAV-BDNF (60 ng/ml) and rBDNF (200 ng/ml), the outcomes in various parameters (protein concentration, total cells, neutrophils, macrophages, and survival rate) are quite similar. This finding is intriguing and requires explicit discussion. The authors should consider to elaborate on the potential implications of this observation: a) does it suggest a plateauing effect of BDNF at certain concentrations, where higher levels do not confer additional benefit? b) does it hint at differences in bioavailability, sustained release kinetics, or cell-specific targeting between AAV-mediated expression and recombinant protein administration? A dedicated discussion paragraph addressing this point would significantly enhance the manuscript to a broader audience.\nResponse: Thank you for this valuable comment. We sincerely apologize for the oversight—during ELISA quantification, the dilution factor was inadvertently omitted, which led to the apparent discrepancy in BDNF levels between the AAV-BDNF and rBDNF groups. This error has now been corrected, and the revised values no longer show a substantial difference.\nReviewer #1-5: In Figure 2A, AAV-BDNF was administered before LPS injection, suggesting a preventive effect. In contrast, Figure 2M shows rBDNF administered after LPS injection, indicating a dual protective/therapeutic effect. From these models, the authors may imply both preventive and protective effects for the potential rBDNF/BDP-12. It would be beneficial to explicitly state this potency by demonstrating side-by-side data of both preventive and protective efficacy of both rBDNF and BDP-12 within the same experimental model or section, for clearer comparison.\nResponse: Thank you for this helpful suggestion. We conducted an additional set of ALI experiments in which mice received BDP-12 (4 mg/kg) either 6 hours before LPS challenge or 0.5 hours after LPS administration, to directly evaluate its preventive and therapeutic efficacy (Reviewer Figure 4A). Across multiple readouts—including H&E staining, lung wet/dry ratio, BALF protein concentration, total cell counts, and pulmonary inflammatory cytokine expression— both preventive and therapeutic administration of BDP-12 markedly alleviated ALI pathology (Reviewer Figure 4B-H). Notably, the preventive regimen produced slightly greater improvements in some parameters compared with the therapeutic regimen. e speculate that this difference may be attributable to the relatively slow clearance of BDP-12 from lung tissue (see detials in our response to Reviewer #3-2). These new data have been incorporated into the revised manuscript. 4\nReviewer Figure 4 (new Supplementary Figure S10)\n(A) Schematic illustration of mice undergoing ALI modeling and preventive or therapeutic BDP- 12 injection. (B) Representative H&E-stained images of lung tissues. (C) Quantification of lung injury scores for panel I. (D) Lung wet/dry weight ratio. (E) Total protein levels in BALF samples. (F) Total cell counts in BALF samples. (G-H) mRNA levels of pro-inflammatory factors Tnf (G) and Il6 (H) in lung tissues.\nReviewer #1-6: The manuscript concludes with a claim that GATA2 is a regulator of BDNF expression in lung epithelial cells. This claim represents a significant shift from the primary focus on macrophage-mediated inflammation. While mechanistic insights are valuable, the connection between macrophage-associated TLR4-BDNF binding and its inflammation reduction (the main finding) and GATA2-regulated BDNF in epithelial cells feels somewhat disconnected given the depth of investigation into macrophage roles vs. epithelial cell roles. In addition, what kind of protein/signaling pathways that suppressed GATA2 in lung inflammation? Because BDNF, but not BDP-12, activates phosphorylation of TrkB in lung epithelial cells (Fig 7B), is GATA2 directly under TrkB regulation, or is this an independent pathway influencing BDNF expression? More context and perhaps some preliminary data on upstream regulators of GATA2 from ALI or CLP murine models, and its direct link to TrkB signaling in epithelial cells, may be pivotal to justify the final regulatory mechanism.\nResponse: Thank you for this thoughtful and constructive comment. As you noted, our initial evidence for GATA2-mediated regulation of BDNF expression in lung epithelial cells was not sufficiently complete. To address this, we performed additional ChIP-qPCR assays. Based on our lung tissue RNA-seq data, we first identified two BDNF transcripts with high basal expression in the lung that were markedly downregulated following LPS stimulation (Reviewer Figure 5A). We then designed four primer pairs covering the promoter regions corresponding to these transcripts. ChIP-qPCR using primer 2 demonstrated that GATA2 directly binds to the BDNF promoter, and this binding was significantly reduced in LPS-treated epithelial cells (Reviewer Figure 5B). These results support that decreased GATA2 activity contributes to reduced BDNF transcription in the ALI setting. To further explore why GATA2 is suppressed during lung inflammation, we examined 5 previously published methylation profiling data from rat ALI models. These data revealed significantly increased methylation at the GATA2 locus in injured lung tissue (PMID: 23546543). Such epigenetic modifications offer a plausible mechanism underlying the observed reduction of GATA2 protein levels in LPS- and CLP-induced lung injury. We have incorporated these findings and mechanistic insights into the revised manuscript and have relocated the GATA2–BDNF results to follow Figure 1 for a better logical flow.\nReviewer Figure 5 (new Supplementary Figure S3H-I)\n(A) TPM values of different Bdnf transcripts in RNA-seq data from control and LPS-treated lungs. (B) MLE-12 cells were treated with or without LPS for 24 h, followed by chromatin immunoprecipitation–quantitative PCR analysis to assess GATA2 binding to the Bdnf promoter.\nReviewer #1-7: Fig 7A-C show that BDP-12 lacks proliferative effect. If BDP-12 does not promote this regeneration, its therapeutic value might be limited for recovery aspects of ALI, even if it is anti-inflammatory. This needs to be discussed thoroughly to clarify the therapeutic niche of BDP- 12.\nResponse: Thanks for your comment. We acknowledge the reviewer’s point that proliferative effect partly contribute to the ALI/ARDS recovery. However, excessive or ectopic proliferation may result in maladaptive repair, fibrotic remodeling, or potential oncogenic risks. Thus, we consider that BDP-12’s therapeutic advantage lies in its potent anti-inflammatory efficacy without eliciting undesirable proliferative effects. While BDP-12 can be administered alone when strong anti-inflammatory activity is required, it could be used in combination with other regenerative therapies to support epithelial repair when appropriate. We have incorporated this point into the revised Discussion section.\nReviewer #1-8: The description of the protein-protein interaction network is insufficient. The key methodological details are missing, making it impossible for readers to understand how the network was constructed or how conclusions were drawn. The authors should provide a detailed methodology for the network generation, including sources, criteria for selecting nodes and edges, specific algorithms for network analysis. Furthermore, the selection of TLR4 as a key candidate BDNF-binding partner (hub protein) lacks a clear, quantifiable justification. TLR4 has 6 edges (Fig 4C), but other transmembrane proteins identified in the protein microarray assay (which directly assessed BDNF binding) such as PDCD1 and CXCR3, also appear to have a similar number of edges. If these proteins can indeed bind BDNF (as suggested by the protein microarray, which should be the primary evidence for binding), and they also have significant connectivity. The rationale for prioritizing TLR4 over these equally candidates must be explicitly described. 6\nResponse: Thank you for this valuable comment. To strengthen the reliability of our protein– protein interaction analysis and minimize false-positive signals from the protein microarray, we additionally employed IP-MS–based proteomic profiling to further identify BDNF-interacting proteins (Reviewer Figure 6A). This approach substantially reduced nonspecific candidates and narrowed the potential membrane-associated receptors to only two proteins—TLR4 and CCR1 (Reviewer Figure 6B). Subsequent co-immunoprecipitation experiments demonstrated that BDNF does not interact with CCR1, thereby allowing us to confidently designate TLR4 as the bona fide receptor that directly recognizes BDNF (Reviewer Figure 6C-D).\nReviewer Figure 6 (new Figure 4A-D)\n(A) Schematic illustration of the workflow integrating protein microarray screening, IP-MS analysis, and subcellular localization filtering to determine the potential receptor for BDNF. (B) Venn diagram showing TLR4 and CCR1 as the two membrane proteins with potential BDNF- binding capacity. (C) Co-immunoprecipitation analysis in 293T cells transfected with or without CCR1 and BDNF plasmids, demonstrating no detectable interaction between CCR1 and BDNF. (D) Co-immunoprecipitation analysis in 293T cells transfected with TLR4, MD2, and BDNF plasmids, showing a clear interaction between BDNF and TLR4, but not MD2.\nReviewer #1-9: TLR4 is up-regulated after LPS stimulation. This fact is highly relevant and should be integrated into the discussion of BDNF-TLR4 interactions, leading to questions about the dynamics of the proposed BDNF-TLR4 binding. Since LPS binds to TLR4 via MD2, does the increased TLR4 expression, or the presence of BDNF, create a rate-limiting step for BDNF-TLR4 binding that could affect competitive binding with MD2 and LPS?\nResponse: Thank you for this insightful comment. Our data support the notion that BDNF-bound TLR4 represents an inactive, non-signaling form of the receptor. During ALI, BDNF levels decrease while TLR4 expression is markedly upregulated. These two changes synergistically increase the pool of unbound, activatable TLR4 (“free TLR4”), thereby facilitating LPS recognition and amplifying downstream inflammatory signaling. This dynamic suggests that endogenous BDNF functions as a limiting factor that constrains TLR4 availability under physiological conditions. We have incorporated this mechanistic interpretation into the revised Discussion section.\nReviewer #1-10: Given that TLR4 activation itself triggers robust inflammatory signaling, is there any evidence or hypothesis for a negative feedback loop whereby BDNF binding to TLR4 (or its 7 downstream effects) might modulate the signaling cascades initiated by LPS in macrophages? A discussion about this area may be required to support the proposed role of BDNF in modulating TLR4 signaling.\nResponse: Thank you for this important point. Our scRNA-seq data show that macrophages express negligible levels of BDNF, indicating that an intrinsic BDNF-mediated feedback loop is unlikely to occur within individual macrophages. However, previous studies have reported that NF-κB negatively regulates Bdnf transcription (PMID: 24119288). In an inflammatory environment, epithelial cells are exposed to multiple cytokines that robustly activate the NF-κB pathway, which may further suppress epithelial BDNF production. This reduction in extracellular BDNF would diminish its antagonistic effect on TLR4, thereby increasing the availability of free, activatable TLR4 and amplifying inflammatory signaling. We propose that this constitutes a multicellular positive feedback loop in which NF-κB–mediated suppression of epithelial BDNF reinforces TLR4-driven inflammation. We have integrated this mechanistic perspective into the revised Discussion section.\nREVIEWER 2\nOverview: The authors demonstrated that brain-derived neurotrophic factor (BDNF), released from pulmonary epithelial cells, acts as a toll-like receptor 4 (TLR4) agonist, which attenuates sepsis. They also developed a BDNF-derived peptide that mitigated sepsis. The study's design and storyline are straightforward and logical. The authors implemented many interventional approaches, such as lung epithelial-specific overexpression of BDNF, enhancing the rigor and significance of the study. The study offers valuable insights into the field of immunology. The following are my specific comments.\nReviewer #2-1: Fig. 1K, W. Could the authors create graphs with multiple samples like other parameters? Y-axis label: \"Normalized Count (% of Max)\" or an equivalent would be less confusing.\nResponse: Thanks for the suggestion. We have revised the graphs accordingly.\nReviewer #2-2: Fig. 2F. Serum BDNF was not associated with ARDS, as shown in Fig 1E, F. Why was rBDNF injected iv instead of it? Does iv result in increased BDNF in the BALF? Even if so, it could seem contradictory if the authors want to keep the serum data. (I do understand it was presented to show the rationale for focusing on the lungs/epithelial cells.\nResponse: Thank you for this question. Our ELISA data, together with previous reports (PMID: 26656852; PMID:32989251), show that serum BDNF concentrations—primarily derived from platelets and skeletal muscle—are in the ng range, whereas lung and BALF BDNF levels— originating mainly from epithelial cells—are in the pg range. Because of this large difference in baseline abundance, ALI-induced reductions in epithelial BDNF are readily detectable in the BALF but are difficult to detect in the circulation, where the high and stable serum BDNF pool masks such changes. When rBDNF is administered intravenously, circulating BDNF levels are directly increased, and a portion of this elevated serum BDNF subsequently redistributes from blood into lung tissue, thereby raising BALF BDNF concentrations and mitigating the progression of ALI. 8\nReviewer #2-3: Fig. 3H-N. The study design is not very convincing. It can be interpreted as simply showing that macrophages exacerbate ALI. Since they are absent in the Clo-lip groups, less lung injury is observed irrespective of rBDNF. The lack of further alleviation by rBDNF does not necessarily mean that macrophages are responsible for the effect of rBDNF, as there is no guarantee that such situation exists.\nResponse: Thank you for this insightful comment. In these experiments, we applied a classical loss- of-function + non-additivity epistasis strategy to test whether the protective effect of BDNF in ALI requires macrophages. This analytical framework is well established and widely used to determine pathway dependence (e.g., PMID: 37160898; 40125948; 36180407). Under this logic, if BDNF alleviates ALI primarily through macrophages, then macrophage depletion should phenocopy the effect of BDNF, and exogenous rBDNF should no longer provide additional benefit—consistent with our observations. We agree, however, that without including non-ALI controls, interpreting these interactions may be less intuitive. To address this, we have now added the corresponding baseline (non-ALI) groups in the revised version (Reviewer Figure 7). These additional data make the epistasis design more explicit and allow a clearer, more direct understanding of why the absence of further improvement by rBDNF in the Clo-lip group supports macrophage dependence rather than representing a ceiling or saturation effect. We have updated the figures in the revised manuscript.\nReviewer Figure 7 (new Figure 3H-N)\n(A) Schematic illustration of mice undergoing macrophage deletion, ALI modeling, and rBDNF injection. (B) Representative H&E-stained images of lung tissues. (C) Quantification of lung injury scores for panel B. (D) Lung wet/dry weight ratio. (E) Total protein levels in BALF samples. (F) Total cell counts in BALF samples. (G) Survival curve of mice with or without macrophage deletion and rBDNF injection in an E.coli-induced sepsis model.\nReviewer #2-4: Fig. 4D. Why was BDNF pulled down instead of TLR4? If TLR4 was pulled down, it could have had TLR4 as a loading control in the IB membrane in addition to the Input. If you pull down BDNF in samples without BDNF, nothing will be detected, and you cannot have a proper control. According to the \"Tryptic digestion and immunoprecipitation\" section of the Methods, it appears that the authors IP'ed with TLR4 Ab, which makes more sense. BDNF in both samples, TLR4 -/+, and pulling down BDNF would also work. Moreover, I might have overlooked it but could not find the information that the proteins were tagged as in the figures. 9\nResponse: Thank you for this insightful comment. Our Co-IP experiments were designed specifically to identify and validate the receptor directly interacting with BDNF. For this purpose, we performed pull-down using an anti-BDNF antibody. After carefully re-examining both our experimental procedures and the corresponding data, we confirm that conducting Co-IP in BDNF- positive and BDNF-negative samples using anti-BDNF for immunoprecipitation is an appropriate and widely used approach. Similar strategies can be found in multiple published studies (PMID: 30111359; PMID: 34408636; PMID: 38032196). In addition, methodological descriptions from established resources (e.g., Creative-Proteomics Co-IP workflow, https://www.creative- proteomics.com/services/co-immunoprecipitation-co-ip.htm) also illustrate procedures consistent with ours.\nReviewer #2-5: Fig. 4M-S. The similar issue as Fig. 3H-N. It can be interpreted as simply showing that TLR4 exacerbates ALI irrespective of rBDNF. The lack of further alleviation by rBDNF does not necessarily mean that TLR4 are responsible for the effect of rBDNF.\nResponse: Thank you for the question. A similar comment was also raised by Reviewer #2-3; please refer to our response to Reviewer #2-3. Besides, we have now added the corresponding baseline (non-ALI) groups (Reviewer Figure 8) and updated the figures in the revised manuscript.\nReviewer Figure 8 (new Figure 4M-S)\n(A) Schematic illustration of mice undergoing bone marrow transplantation, ALI modeling, and rBDNF injection. (B) Representative H&E-stained images of lung tissues. (C) Quantification of lung injury scores for panel B. (D) Total protein levels in BALF samples. (E) Lung wet/dry weight ratio. (F) Total cell counts in BALF samples. (G) Survival curve of mice with or without macrophage deletion and rBDNF injection in an E.coli-induced sepsis model.\nReviewer #2-6: Fig. 5B, C. The same issue for IP as Fig 4D.\nResponse: Thank you for the question. A similar comment was also raised by Reviewer #2-4; please refer to our response to Reviewer #2-4.\nReviewer #2-7: How is baseline BDNF maintained? How does GATA2 decrease in sepsis?\nResponse: Thank you for the important questions. In our study, we observed that BDNF levels in BALF markedly decrease during acute lung injury, whereas circulating BDNF levels remain 10 relatively stable. This is likely because systemic skeletal muscle and platelet is the predominant source of circulating BDNF, with much higher basal expression than lung tissue. Thus, despite reduced pulmonary secretion, the overall blood BDNF pool is buffered and maintained at baseline during ALI. Regarding GATA2, previously published DNA methylation profiling in rat models of acute lung injury has shown a significant increase in methylation at the GATA2 locus in injured lung tissue (PMID: 23546543). Such epigenetic modifications are a plausible mechanism underlying the pronounced reduction of GATA2 protein levels observed during sepsis-induced lung injury. These points have been incorporated into the revised Discussion section.\nREVIEWER 3\nOverview: The manuscript by Weiwei Zhu et al. presents novel findings about the role of the major neurotrophin BDNF on Acute Lung Injury (ALI), its mechanism of action on macrophages and the subsequent regulation of inflammation, and most importantly, the authors reveal the direct interaction of BDNF with the TLR4 receptor. This interaction has also significant translational outcome, expecially upon the detailed characterization of the interacting residues and the development of a BDNF-derivative which could offer a clinical use. It is very interesting the cross talk humoral-cellular immunity, both in the fields of immunology but also on neurotrophins' action outside the nervous system.\nThe study is very well designed, all experiments are adequately performed and the results are presented in a clear manner, emphasizing on the most important findings and providing new pharmacological agents for pre-clinical evaluation in ALI and perhaps in more inflammatory diseases.\nHowever, the important findings of the present study require some clarification and complementary experiments, in order to fully support the conclusions and claims.\nReviewer #3-1: The authors have shown that the high affinity receptor for BDNF, namely TrkB, is not involved in the anti-inflammatory effects of this neurotrophin. However, there are many studies showing that the low-affinity receptor of all mature and immature neurotrophins (proneurotrophins), the p75 pan-neurotrophin receeptor, is expressed in macrophages and moreover, TLRs could interact with p75 signaling. Thus, the expression of p75 receptor, as well as the expression of proBDNF, should be explored. Is the reduction of BDNF during ALI accompanied by an increase in proBDNF expression? This could induce p75 signaling, separetely or in parallel with the BDNF-TLR4 signaling. Additonally, the BDP-12 peptide should be investigated for activating the p75NTR.\nResponse: Thank you for this insightful comment. We additionally examined the expression patterns of proBDNF and p75NTR in the LPS-induced ALI model. Our data show that proBDNF levels were markedly decreased, whereas its receptor p75NTR was significantly upregulated (Reviewer Figure 9A). This opposing trend suggests that any potential proBDNF–p75NTR signaling may be functionally counterbalanced, and therefore not strongly associated with ALI progression. Moreover, p75NTR activation typically results in the generation of the intracellular domain fragment (p75ICD) through regulated intramembrane proteolysis. We therefore assessed whether BDP-12 could activate p75NTR. As expected, rBDNF—known to act as a low-affinity ligand for p75— induced a detectable increase in p75 cleavage. In contrast, BDP-12 did not trigger p75NTR activation or cleavage, indicating that BDP-12 exhibits higher target specificity without engaging p75- dependent signaling (Reviewer Figure 9B). 11\nReviewer Figure 9 (only for review)\n(A) The protein level of proBDNF and P75NTR in lung tissues from mice treated with or without LPS, and GAPDH was used as loading control. (B) MLE-12 cells were treated with 10 nM rBDNF or 2 μM BDP-12 for 0.5 h. Then the P75NTR, P75ICD, and GAPDH were assessed by immunoblotting.\nReviewer #3-2: The detailed characterization of the amino residues of BDNF that directly interact with TLR4 and the development of a novel dodecapeptide which selectively activate this receptor and protects against inflammation, are of high importance for further pre-clinical evaluation. The authors should perform a pharmacokinetic-pharmacodynamic (PK/PD) study in order to define the effective concentration in the tissues of interest (lung for macrophages, brain for microglia). Additionally, the detection of BDP-12 in tissues should be presented upon its administration. Toxicity studies could also enhance the pre-clinical characterization of this molecule\nResponse: Thank you for this valuable suggestion. To better support the therapeutic potential of BDP-12, we assessed its pharmacokinetic distribution across five major organs (heart, liver, spleen, lung, and kidney) at 4, 8, and 16 hours after administration. Our results show that BDP-12 accumulates substantially in the lung, with levels only slightly lower than those in the spleen and kidney (Reviewer Figure 10). Notably, BDP-12 exhibited a much slower decline in the lung compared with other organs, resulting in the highest concentration among all tissues at 16 hours. This pharmacokinetic profile suggests that BDP-12 may exert a sustained effect within lung tissue. The corresponding data have been incorporated into Supplementary Figure S8 and described in both the Results and Discussion sections.\nReviewer Figure 10 (new Supplementary Figure S9H)\nTissue distribution of BDP-12 (10 mg/kg) in heart, liver, spleen, lung, and kidney at 4, 8, and 16 hours after intravenous injection in mice.\nReviewer #3-3: The authors should check the effect of BDP-12 in macrophage specific TLR4KO mice to exclude that it may have anti-inflammatory effects by targeting other immune cell types.\nResponse: Thank you for this important comment. We acknowledge that, compared with macrophage-specific TLR4 knockout, bone marrow transplantation (BMT) models can also affect other myeloid cells, particularly neutrophils. To address this, we performed additional experiments in isolated neutrophils and confirmed that BDP-12 does not exert anti-inflammatory effects in these cells (see details in response to Reviewer #1-3). Although time constraints prevented us from generating and testing TLR4 conditional knockout mice, we believe that the combination of our 12 BMT data and the additional neutrophil experiments provides strong evidence supporting the macrophage-specific targeting of BDP-12.\nReviewer #3-4: Figure1K\nIn the western blot showing reduction of BDNF levels, the authors should show up-regulation of an inflammatory marker in the same samples.\nResponse: Thank you for this suggestion. We have now added data showing the relative levels of BALF IL-6 in the CON- and LPS-treated mice (Reviewer Figure 11), demonstrating the upregulation of this inflammatory marker alongside the reduction of BDNF.\nReviewer Figure 11 (new Figure 1K)\nThe protein level of BDNF in lung tissues from mice treated with or without LPS, with GAPDH as a loading control. Corresponding relative BALF IL-6 levels for each group are shown on the right.\nReviewer #3-5: Figure 4 O-R\nInclude the control without LPS in the graphs to show the effect of TLR4 alone. Here we don’t see any reverse by BDNF but there is anyway reduced (or any) pathology in the TLR4KO mice.\nResponse: Thank you for your comment. We have now included the corresponding baseline (non- ALI) groups, which makes our loss-of-function + non-additivity epistasis strategy easier to interpret. A similar point was also raised by Reviewer #2-5; please refer to our response to Reviewer #2-5 for a more detailed explanation and the revised figures.\nReviewer #3-6: Figure 5\nThe authors should perform pharmacokinetic analysis of BDP-12 to support their suggestion of its therapeutic potential.\nResponse: Thank you for this valuable suggestion. We have performed tissue distribution analysis of BDP-12 to evaluate its pharmacokinetic profile. A a similar point was raised in Reviewer #3-2, we kindly refer the reviewer to our detailed response to Reviewer #3-2, where the full data summary and corresponding revisions are provided.\nReviewer #3-7: Suppl. Figure S9\n- Missing Chip-qPCR for GATA2 in BDNF promoter +/- LPS in the primary lung epithelial cell line.\nResponse: Thank you for pointing this out. We have performed Chip-qPCR accordingly. A similar comment was also raised by Reviewer #1-6, and please refer to our response to Reviewer #1-6.\nReviewer #3-8: Line 408. Correct to cell isolation and culture.\nResponse: Thank you for the comment. We have revised the text accordingly.\nReviewer #3-9: The authors should discuss the fact that TLR4 downregulates the expression of BDNF in inflammation (Tan et al., 2025, Gao et al.,2021) and discuss any possible negative feedback loop as BDNF inhibits TLR4 activity.\nResponse: Thank you for this important point. Consistent with your comment, previous studies have reported that NF-κB—the common downstream effector of multiple inflammatory receptors, including TLR4—negatively regulates Bdnf transcription (PMID: 24119288). In an inflammatory environment, epithelial cells are exposed to multiple cytokines that robustly activate NF-κB, which may further suppress epithelial BDNF production. The resulting reduction in extracellular BDNF diminishes its antagonistic effect on TLR4, thereby increasing the pool of free, activatable TLR4 and amplifying inflammatory signaling. We propose that this mechanism constitutes a multicellular positive feedback loop, in which NF-κB–mediated suppression of epithelial BDNF reinforces TLR4-driven inflammation. This mechanistic perspective has been incorporated into the revised Discussion section. 13\nREVIEWER 4\nOverview: I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: We appreciate the transparency regarding the co-review process. We thank both the primary reviewer and the co-reviewer for their thoughtful comments and constructive suggestions, which have helped us improve the quality and clarity of our manuscript. 14"}, {"round": 2, "reviewer_comments": {"reviewer_1": "In the revised manuscript, the authors clearly addressed all of my initial concerns.", "reviewer_2": "The authors addressed my comments.", "reviewer_3": "I thank the authors for addressing all outstanding concerns, performing the required experiments and making the recommended changes. Hence, I highly recommend that this manuscript be moved forward for publication in Nature Communictions journal.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We are very pleased to learn that the reviewers are satisfied with our revisions and support the publication of our work. We sincerely appreciate the thorough and constructive feedback from all reviewers throughout the review process, which has significantly strengthened our manuscript. We are also grateful for the editorial support and efficient handling of our submission by Nature Communications."}]

Decision letter