Antimicrobial resistance (AMR) poses a major global health threat that demands the discovery of new antimicrobial agents. Antimicrobial peptides (AMPs) offer a promising therapeutic alternative due to their broad-spectrum activity and reduced likelihood of resistance development. In the current study, we developed COMPASS, a comprehensive database aggregating 75,381 unique AMP sequences from nine public repositories, and created AmpGPT2, a transformer-based generative model specifically fine-tuned for AMP sequence generation. Unlike directed approaches, which optimize antimicrobial sequences or certain properties, our foundational model learns general AMP sequence patterns through an undirected training strategy. AmpGPT2 generated peptide sequences, of which 95.41% were predicted to be AMPs by AMP Scanner, representing a substantial improvement over existing models. The generated peptides exhibit physicochemical properties consistent with natural AMPs, including appropriate length distributions and molecular characteristics. Experimental validation demonstrated that one of five tested peptides, which shares structural features with dermaseptin-family AMPs, exhibited significant concentration-dependent antimicrobial activity against Klebsiella pneumoniae and Pseudomonas aeruginosa, supporting the model’s potential for functional AMP discovery. Highlighting the persistent challenge of translating computational predictions into biological function, this work establishes a foundational framework for AMP discovery that can serve as a basis for subsequent directed optimization strategies, potentially accelerating the development of novel antimicrobial therapeutics.

BACKGROUND AND OBJECTIVE:Incident airflow limitation is frequently diagnosed at advanced stages. Identifying individuals at risk through primary care spirometry may enable earlier intervention, yet validated, pragmatic frameworks remain lacking. METHODS:We applied a framework of three mutually exclusive spirometric at-risk phenotypes, termed Three-Phenotype Spirometry-Based Identification (hereafter TriSpi), to 6123 participants from two population-based cohorts: KORA (n = 1973, 3-year Follow-up, derivation) and SHIP (n = 4150, 5-year Follow-up, validation). TriSpi+ individuals were defined as meeting criteria for one of the three phenotypes: Early airflow limitation (EAL, FEV1/FVC > 0.7 and < 10th percentile or < 0.7 and > 5th percentile), small airway dysfunction (SAD) defined using FEF50- or FEF75-based thresholds; and preserved-ratio impaired-spirometry (PRISm). Associations with incident airflow limitation were tested using Firth's regression. RESULTS:EAL, PRISm, and SAD (defined using either FEF50 or FEF75-based thresholds) were significantly associated with incident airflow limitation across cohorts and follow-ups. TriSpi+ individuals accounted for 26%-36% of the population, identifying 74%-93% of future cases, while TriSpi+ was associated with a 10-25-fold increase in risk. Negative predictive values exceeded 95% across definitions, and the number needed to screen among TriSpi+ individuals ranged from 7 to 13. EAL showed the strongest individual association (OR up to 53.2), while SAD was more common in younger adults. CONCLUSION:Combining definitions for EAL, PRISm, and SAD enables robust prediction of incident airflow limitation. TriSpi may serve as a scalable, pragmatic approach for early risk stratification in primary care, in absence of post-BD spirometry.

Influenza A virus (IAV)-induced exacerbations are a major contributor to morbidity in chronic obstructive pulmonary disease (COPD), yet the epithelial mechanisms that govern these events remain unknown. We profiled the response to IAV infection of differentiated airway epithelial cells from healthy donors and individuals with COPD at single-cell resolution. The analysis revealed infection-driven shifts across multiple epithelial compartments and distinct alterations in cell-cell communication in COPD, associated with an increased CXCL11 expression. Functional assays demonstrated that CXCL11 augments mucus-associated gene and protein expression, particularly MUC5AC, increases mucus secretion and viscosity and is associated with reduction of virus-related immune pathways. This highlights CXCL11 as a contributor to both mucus hypersecretion and impaired antiviral epithelial responses in COPD exacerbations.

Macrophages are essential for both, to clear pathogens and preserve tissue homeostasis, yet the molecular regulators of this equilibrium remain incompletely defined. Here, we identify SAILR (survival associated immune-regulatory RNA), a primate-specific long noncoding RNA (lncRNA), as a critical modulator of macrophage viability under infection conditions. SAILR is induced during monocyte-to-macrophage differentiation, but rapidly downregulated upon bacterial challenge in a nuclear factor kappa B (NF-κB) dependent manner. In both naïve and immune-activated macrophages, SAILR dampens the expression of adhesion, phagocytosis, and invasion factors, which include SIGLEC1 and MMP7. During infection with Salmonella Typhimurium, depletion of SAILR sensitizes macrophages to apoptosis, resulting in loss of intracellular replication niches and reduced bacterial recovery. Conversely, enforced SAILR expression promotes macrophage survival and increases intracellular pathogen burden. Mechanistically, SAILR interacts with the antiapoptotic adaptor protein 14-3-3β to support macrophage survival. Notably, downregulation of SAILR is mirrored in circulating immune cells from patients with severe COVID-19 and sepsis. Together, our findings position SAILR as a central regulator in linking macrophage survival to host-pathogen interaction and disease pathophysiology.

Die chronisch-obstruktive Lungenerkrankung trägt weltweit erheblich zu Morbidität und Mortalität bei. Charakterisierend sind chronische Atemwegsbeschwerden, persistierende Atemwegsobstruktion und Exazerbationen. Die Diagnose erfolgt spirometrisch nach Bronchodilatation. Für eine erfolgreiche Langzeittherapie ist die strukturierte Erhebung auslösender Noxen, der Symptomlast, der Exazerbationsanamnese sowie relevanter Komorbiditäten essenziell. Therapieziele sind die Prävention von Lungenfunktionsverlust und Exazerbationen sowie die Reduktion der Symptomlast. Dieser Beitrag stellt Konzepte zur Diagnostik und Therapie bei Diagnosestellung, im Langzeitverlauf, bei Exazerbationen und im Rahmen der palliativen Versorgung vor. Ein besonderes Augenmerk liegt auf der individualisierten Inhalationstherapie unter Beachtung von Symptomen, Exazerbationen und der Eosinophilenzahl im Blut sowie auf evidenzbasierten nichtpharmakologischen Interventionen wie Tabakentwöhnung, Rehabilitation, Langzeitsauerstofftherapie, nichtinvasiver Beatmung und Lungenvolumenreduktion.

Abstract Aging is a major risk factor for chronic lung diseases, associated with chronic low-grade inflammation (inflammaging) and impaired epithelial regeneration. How epithelial-intrinsic aging intersects with inflammaging across the lifespan remains poorly understood. Here, we systematically analyzed lung epithelial cells from neonatal, young adult, and aged mice to define age-dependent changes in regenerative capacity. RNA sequencing revealed lifespan-associated shifts characterized by early repression of developmental and WNT/β-catenin programs and progressive activation of DNA damage, inflammation, and senescence signatures. Functionally, neonatal epithelial cells exhibited markedly enhanced organoid-forming capacity compared with young and aged cells. Aged organoids maintained a pro-inflammatory secretory profile indicative of cell-intrinsic inflammaging, and transfer of the aged secretome or TNF-α to young cultures significantly impaired regeneration. Comparison of freshly isolated cells and long-term organoid cultures revealed sustained repression of regenerative pathways with age, consistent with stable epigenetic imprinting. Pharmacological inhibition of DNA methylation and WNT signalling partially restored regenerative capacity in adult organoids. Together, these findings identify epigenetic reprogramming and epithelial-intrinsic inflammaging as key determinants of age-dependent regenerative decline.

Background:Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality. While tools predicting short-term prognosis exist, there is urgent need for the early identification of patients requiring close follow-up monitoring for post-acute mortality. We therefore conducted cluster analysis of baseline clinical data to investigate predictors of post-acute mortality in CAP. Methods:We analysed 7840 participants from the German CAPNETZ cohort, using self-organising map (SOM)-clustering and survival analyses. Random survival forest (RSF) models were used to identify key predictors of mortality, which were then analysed using time-dependent area under the curve and Cox proportional hazard regression models. Results:SOM-clustering based on 10 predictors identified 879 (12%, in four clusters) patients with high risk for post-acute (30-180 days) mortality. Across the cohort, age and urea were the most important predictors of post-acute mortality, while in the high-risk cohort, body mass index emerged as the strongest predictor, as identified by RSF modelling. In one high-risk cluster, there was an association with elevated platelet counts (HR: 1.13, 95% CI 1.03-1.21, p=0.01; increments of 40 platelets·nL-1, c14, 35% of high-risk patients), in another (c15, 50% of high-risk patients) with elevated urea (HR: 1.06, 95% CI 1.01-1.11, p=0.02) and C-reactive protein (CRP) (HR: 1.27, 95% CI 1.01-1.58, p=0.04). Conclusion:Using 10 clinical predictors for post-acute mortality in CAP, predictive SOM-clustering revealed several high-risk subgroups, with heterogeneous biomarkers, suggestive of differences in the underlying pathophysiology (thrombocytes, urea, CRP). Adapting medical therapy to these high-risk subgroups may reduce post-acute mortality following CAP.

Neonatal sepsis remains a major cause of morbidity and mortality in preterm infants and is characterized by dysregulated inflammation and metabolic dysfunction. Excessive glycolysis has been linked to inflammatory injury during neonatal infection, but whether metabolic reprogramming can improve host defense and survival remains unclear. We investigated whether ketone-supported mitochondrial metabolism, together with anti-inflammatory signaling actions of beta-hydroxybutyrate (BHB), promotes disease tolerance during neonatal sepsis. Using a preterm piglet model of Staphylococcus epidermidis bloodstream infection, we assessed the effects of glycolytic inhibition with 2-deoxyglucose and parenteral BHB supplementation on survival, acid-base balance, bacterial burden, systemic inflammation, plasma metabolome, and hepatic transcriptional responses. Mechanistic studies were performed in infected THP-1 macrophages, and human relevance was explored in a cohort of 538 children with plasma metabolomics and cytokine profiling. Animal data were analyzed using additive linear or linear mixed-effects models with estimated marginal means and Tukey adjustment for multiple comparisons; in vitro comparisons used paired t-tests or Wilcoxon signed-rank tests, as appropriate. Glycolytic inhibition protected infected piglets from lethal sepsis and was associated with reduced inflammatory responses and induction of mitochondrial and ketone-associated metabolic pathways. BHB supplementation prevented sepsis-related mortality, improved acid-base homeostasis, and promoted a disease-tolerant phenotype without reducing bacterial burden. Hepatic transcriptomics showed suppression of inflammatory pathways together with activation of mitochondrial and organic-acid metabolic programs. In infected THP-1 macrophages, BHB reduced pro-inflammatory cytokine expression, and this effect persisted despite blockade of ATP synthesis, supporting anti-inflammatory actions beyond metabolic modulation. In the pediatric cohort, higher circulating ketone levels were associated with higher IL-10 and lower interferon-gamma concentrations, consistent with an anti-inflammatory effect of BHB in humans. Ketone supplementation promotes disease tolerance and survival in experimental neonatal sepsis through combined metabolic and anti-inflammatory effects, with data supporting a signaling-active role for BHB in shaping inflammatory responses. These findings identify BHB as a candidate host-directed intervention for neonatal sepsis and support further translational evaluation in preterm infants.

Chronic obstructive pulmonary disease (COPD) is among the leading causes of death worldwide and is characterized by chronic respiratory symptoms, persistent airflow limitation, and exacerbations. Diagnosis is confirmed by post-bronchodilator spirometry. Effective long-term management requires a structured assessment of relevant exposures, symptom burden, exacerbation history, and comorbidities. Key goals of treatment include reducing both symptom and disease burden and preventing future exacerbations, which are often associated with increased lung function decline. This article summarizes practical concepts for diagnostic work-up and therapeutic decision-making at the time of diagnosis, during follow-up, in acute exacerbations, and in the context of palliative care. It highlights individualized inhaled therapy, guided by symptoms, exacerbations, and blood eosinophil counts, as well as evidence-based non-pharmacological interventions such as smoking cessation, pulmonary rehabilitation, long-term oxygen therapy/non-invasive ventilation, and lung volume reduction strategies.

BACKGROUND:Eosinopenia has been associated with adverse outcomes in community-acquired pneumonia (CAP). However, its relationship with hospital resource use remains unclear. RESEARCH QUESTION:What is the association between admission eosinophil counts and hospital resource use among adults with CAP? STUDY DESIGN AND METHODS:This prospective multicenter cohort study (Community-Acquired Pneumonia Network of Competence [CAPNETZ]; Identifier: 2024-07-11-CHV6) has enrolled patients ≥ 18 years of age with CAP in university hospitals in Germany since 2017. Associations between admission blood eosinophil counts and hospital resource use-ICU admission, mechanical ventilation, and length of stay-were assessed using multivariable regression models. The optimal eosinophil count threshold for stratifying patients by ICU admission and mechanical ventilation rates was identified, and outcomes were compared between patients above and below this threshold. RESULTS:Lower eosinophil counts at admission were associated with increased ICU admission (n = 1,639; P < .001), including among patients treated with systemic glucocorticoids (P = .002) and those not receiving glucocorticoids (P = .047). Lower eosinophil counts also were associated with higher rates of mechanical ventilation (P = .014) and longer hospital stays (P = .024). An eosinophil count threshold of 10 cells/μL was identified as the cutoff that best distinguished patients with higher vs lower risk of ICU admission and mechanical ventilation. Patients with eosinopenia (≤ 10 cells/μL) showed higher ICU admission rates (14.2% vs 8.5%; P < .001; adjusted OR, 1.78), increased mechanical ventilation rates (9.1% vs 5.2%; P = .003; adjusted OR, 1.82), and longer hospitalization (mean, 10.2 days vs 9.0 days; P = .013). INTERPRETATION:Our results show that admission eosinopenia (≤ 10 cells/μL) was associated with greater hospital resource use and may serve as a practical biomarker for health care resource planning. CLINICAL TRIAL REGISTRATION:German Clinical Trials Register; No.: DRKS00005274; URL: https://drks.de/.

Bacterial extracellular vesicles (bEVs) are nano-sized, mostly spherical, double-membrane structures secreted by bacteria throughout their life cycle. In addition to their role in many prokaryotic processes, they can interact with cells of the host immune system, enabling a potential for medical application. This study investigated how bEVs from various pathogenic bacteria modulate human macrophage immune responses and their subsequent ability to protect lung alveolar epithelial cells against SARS-CoV-2 infection. Primary human blood-derived macrophages were stimulated with bEVs derived from Legionella pneumophila (Lp), Klebsiella pneumoniae (Kp), Escherichia coli (Ec), Salmonella Typhimurium (Sal) and Streptococcus pneumoniae (Sp). bEVs from Kp, Ec and Sal strongly induced pro-inflammatory cytokines and interferon-stimulated genes via Toll-like receptor 4-dependent signaling. In contrast, bEVs from Lp or Sp elicited minimal or no immune response. Conditioned media from Kp-, Ec- or Sal- bEV-stimulated macrophages further influenced Calu-3 epithelial cells, leading to the induction of interferon-stimulated genes. Notably, SARS-CoV-2 propagation tended to be reduced in Calu-3 cells pre-stimulated with conditioned media from Kp-bEV- and Ec-bEV-treated macrophages, as demonstrated by decreased infectious virus titers in TCID50 assays. These findings provide new insights into macrophage-bEV interactions, demonstrating that gram-negative Kp- and Ec-derived bEVs induce a potent interferon-dependent antiviral state that can be propagated to lung epithelial cells in vitro. This study highlights a macrophage-driven mechanism of innate immune modulation that extends beyond immune cells to shape antiviral responsiveness in structural cells, providing a conceptual framework for future immunomodulatory or vaccine-oriented strategies.

Small extracellular vesicles (sEVs) play a role in the pathophysiology of viral respiratory infections and may be suitable biomarkers for COVID-19 and Influenza infections, or targets for treatment. We investigated differences in the surface proteome of plasma sEVs in patients with COVID-19 and Influenza. In a discovery cohort with 117 patients, we used a random forest (RF) classifier in order to discriminate COVID-19 and Influenza patients based on routine clinical parameters. Furthermore, plasma samples from these patients were analyzed with an EV Array containing 33 antibodies to capture sEVs, which were then visualized with a combination of CD9, CD63, and CD81 antibodies. We applied an RF classifier and a random depth-first search (RDFS) approach to extract markers with the best discriminatory potential. Data were then validated in an independent set of patient samples on a chip-based ExoView platform.In the initial cohort of 117 patients, leukocyte numbers, and heart rate discriminated best between COVID-19 and Influenza infection. In the plasma samples, 32 EV surface markers could be detected. Feature panels containing CD9, CD81, and CD141 allowed a discrimination between COVID-19 and Influenza. Consecutively, increased CD9 abundance was validated in a second, independent cohort, with the ExoView technology. The increased CD9 signal in Influenza patients was confirmed and shown to be mostly driven by CD9/CD41a double positive sEVs, hinting at a thrombocyte origin.We identified leukocyte numbers and heart rate, as well as CD9 as a sEV surface marker to differentiate COVID-19 from Influenza patients.

Nucleic acid-protein conjugates are valuable for synthetic biology, therapeutics, and nanotechnology, but current methods often lack site specificity and rely on non-natural linkages. RNAylation, a one-step enzymatic reaction catalyzed by the bacteriophage T4 enzyme ModB where first discovered in vivo during phage infection, enables site-specific conjugation of nucleic acids to proteins via a natural N-glycosidic bond. Here, we establish RNAylation as a novel and robust in vitro platform for generating nucleic acid-protein conjugates, overcoming key limitations of existing strategies. We define design principles for this approach, demonstrate enhanced nucleic acid stability in human cell lysates, and develop an efficient purification workflow. Furthermore, we achieve successful delivery of purified conjugates into human cells, highlighting the potential for functional in vivo applications. Our work expands RNAylation from a phage-specific phenomenon to a versatile, biologically relevant strategy with broad biotechnological potential. ### Competing Interest Statement K.H. is in the process of applying for a patent (PCT/EP2021/071295) covering the RNAylation that lists K.H. as inventor. The remaining authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. European Union, https://ror.org/019w4f821, 101114948 Max Planck Society, https://ror.org/01hhn8329, Max Planck Research Group Leader funding Deutsche Forschungsgemeinschaft, 505997786 LOEWE, LOEWE Diffusible Signals LOEWE, LOEWE Exploration Von Behring-Röntgen-Stiftung, https://ror.org/05m7g4v96