Functional dynamics between resident transcriptionally active microbes (TAMs) and host genes underlie Dengue severity.

ABSTRACT: Host-microbe interactions are increasingly recognized as an important module to understand disease progression and potential treatment strategies. Increasing evidence points to the microbiome's ability to modulate host gene expression, and thereby influencing host physiology. By integrating dual RNA sequencing with machine learning, we uncover how transcriptionally active microbes (TAMs) may influence host genes involved in immune and metabolic functions in the hospital admitted dengue patients. Towards this, we analyzed 112 whole transcriptomes from the blood samples of patients with differential dengue disease severity. Using a machine learning-based integrated host-microbial transcriptomic analysis framework, combining Lasso regression and sparse canonical correlation analysis (SCCA), w

SUBMITTER: Kumari P 

PROVIDER: S-EPMC12716792 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature