Biology subjects

de Jonge, M.

Publications and source records attributed to de Jonge, M..

3 recordsLinked to original sources

bioRxiv2026

Multi-omics integration identifies a reproducible inflammatory host-response axis in pediatric sepsis

Sepsis is a major cause of morbidity and mortality in children, yet biological heterogeneity in host responses has limited progress toward targeted therapies and patient stratification. Multiomics integration can combine complementary molecular layers to identify coordinated disease programs not captured by individual assays. Here, we integrated genomic, bulk transcriptomic, proteomic and metabolomic data from blood samples of 22 children with culture-confirmed bacterial sepsis enrolled in the Swiss Pediatric Sepsis Study. Multi-Omics Factor Analysis identified a dominant host-response axis reflecting systemic inflammation. This axis was driven primarily by transcriptomic variation and supported by coordinated proteomic and metabolomic signals, including circulating inflammatory mediators and altered amino-acid metabolism. It was associated with C-reactive protein and a severity score proxy. Projection into an independent pediatric sepsis cohort (n = 22) reproduced the inflammatory and severity-related interpretation of this axis. Single-omic projections showed that the integrated signal could be approximated from individual layers, particularly transcriptomics. In three external pediatric whole-blood transcriptomic datasets, the RNA-derived projection separated septic shock from healthy controls and increased across clinical inflammatory syndromes. These findings define a reproducible inflammatory host-response axis in pediatric sepsis and support multi-omics-guided selection of molecular readouts suitable for clinical translation.

immunology↗

bioRxiv2021

Kawasaki Disease patient stratification and pathway analysis based on host transcriptomic and proteomic profiles

The aetiology of Kawasaki Disease (KD), an acute inflammatory disorder of childhood, remains unknown despite various triggers of KD having been proposed. Host omic profiles offer insights into the host response to infection and inflammation, with the interrogation of multiple omic levels in parallel providing a more comprehensive picture. We used differential abundance analysis, pathway analysis, clustering and classification techniques to explore whether the host response in KD is more similar to the response to bacterial or viral infection at the transcriptomic and proteomic levels through comparison of omic profiles from children with KD to those with bacterial and viral infections. Pathways activated in patients with KD included those involved in anti-viral and anti-bacterial responses. Unsupervised clustering showed that the majority of KD patients clustered with bacterial patients on both omic levels, whilst application of diagnostic signatures specific for bacterial and viral infections revealed that many transcriptomic KD samples had low probabilities of having bacterial or viral infections, suggesting that KD may be triggered by a different process not typical of either common bacterial or viral infections. Clustering based on the transcriptomic and proteomic responses during KD revealed three clusters of KD patients on both omic levels, suggesting heterogeneity within the inflammatory response during KD. The observed heterogeneity may reflect differences in the host response to a common trigger, or variation dependent on different triggers of the condition.

bioinformatics↗

bioRxiv2019

Growth rate alterations of human colorectal cancer cells by 157 gut bacteria

Several bacteria in the human gut microbiome have been associated with colorectal cancer (CRC) by high-throughput screens. In some cases, molecular mechanisms have been elucidated that drive tumorigenesis, including bacterial membrane proteins or secreted molecules that interact with the human cancer cells. For most gut bacteria, however, it remains unknown if they enhance or inhibit cancer cell growth. Here, we screened bacteria-free supernatants (secretomes) and inactivated cells of over 150 cultured bacterial strains for their effect on CRC cell growth. We observed family-level and strain-level effects that often differed between bacterial cells and secretomes, suggesting that different molecular mechanisms are at play. Secretomes of Bacteroidaceae, Enterobacteriaceae, and Erysipelotrichaceae bacteria enhanced CRC cell growth, while most Fusobacteriaceae cells and secretomes inhibited growth, contrasting prior findings. In some bacteria, the presence of specific functional genes was associated with CRC cell growth rates, including the virulence genes TcdA in Clostridiales and FadA in Fusobacteriaceae, which both inhibited growth. Bacteroidaceae cells that enhanced growth were enriched for genes of the cobalamin synthesis pathway, while Fusobacteriaceae cells that inhibit growth were enriched for genes of the ethanolamine utilization pathway. Together, our results reveal how different gut bacteria have wide-ranging effects on cancer cells, contribute a better understanding of the effects of the gut microbiome on the human host, and provide a valuable resource for identifying candidate target genes for potential microbiome-based diagnostics and treatment strategies.

microbiology↗