Integrative multi-omics decoding of the host response to Klebsiella pneumoniae infection reveals an itaconate-centred metabolic-immune axis and a spatially organised inflammatory programme

Abstract

Background: Klebsiella pneumoniae (Kp) is a leading cause of hospital and community acquired pneumonia and bacteraemia, and hypervirulent and carbapenem resistant lineages continue to expand worldwide. Although individual omics layers of Kp infection have been profiled, the host-level molecular logic that connects transcriptional, cellular, metabolic and spatial programmes has not been systematically integrated. Methods: We curated 16 public datasets spanning four modalities-bulk and dual host pathogen RNA-seq (six datasets; 118 libraries), single-cell RNA-seq (four datasets; {approx}164,000 cells), untargeted/targeted metabolomics (four datasets; 1,842 molecular features) and Visium spatial transcriptomics (two datasets; {approx}11,400 spots) covering murine lung infection models, hypervirulent and classical Kp strains, carbapenem-resistant isolates and human clinical specimens. Datasets were harmonised through a standardised pipeline (Salmon/DESeq2; Scanpy/Harmony; MetaboAnalyst; RCTD/spacexr), and integrated by WGCNA, GSVA, CellChat, Monocle3, SCENIC, joint-pathway analysis, RCTD deconvolution, and machine-learning feature selection (LASSO, random forest, SVM-RFE, XGBoost) with 1,000x bootstrap internal validation and independent external validation. Results: Kp infection evoked a coherent 920 gene neutrophil inflammatory response ({approx}520 up-/{approx}400 down-regulated genes) dominated by IL-17/TNF/NF-{kappa}B signalling, neutrophil degranulation, HIF-1-linked glycolysis and itaconate biosynthesis. A turquoise co-expression module (r = 0.86 with infection status) yielded a ten-gene hub signature (IRG1, S100A9, IL1B, CXCL2, SLC7A11, HMOX1, PTGS2, NFKBIA, LST1, FCGR3B). Single-cell profiling resolved twelve major lung lineages and eleven myeloid substates, tracing a Monocle3 trajectory from Cxcr2hi inflammatory neutrophils through an Irg1/Slc7a11hi oxidative phase into Cxcr4hi/Trem2hi suppressive states; CellChat identified S100A8/A9-TLR4 and CXCL2-CXCR2 as the most amplified axes (8.5x and 4.2x). Metabolomics revealed 30-fold pulmonary itaconate accumulation together with succinate and lactate elevation, glucose/glutamine depletion and glutathione collapse, and joint-pathway analysis positioned the TCA-cycle itaconate and ferroptosis modules as the strongest convergent perturbations. Spatial transcriptomics mapped these programmes onto five anatomical niches, with IRG1 expression peaking in the infection core (58% neutrophil content) and declining radially. A ten-gene host-response classification model reached AUC=0.958 in discovery, 0.937 in internal validation and 0.884-0.912 in two independent external cohorts (Brier score 0.071). Conclusions: By vertically integrating public multi-omics data, we define an itaconate-centred metabolic-immune axis that couples inflammatory myeloid expansion to spatially segregated metabolic niches, and we deliver a validated host-side molecular signature that discriminates Kp infection from non-infected states.