Transcriptome-guided parsimonious flux analysis improves predictions with metabolic networks in complex environments
Fig 5
RIPTiDe reveals differential host-associated, metabolism utilizing in vivo metatranscriptomic data.
Transcriptomic reads attributable to E. coli were extracted from a metatranscriptomic dataset sequenced from the cecum of mice in which E. coli is the most highly abundant community member [8]. (A) In vivo transcript abundance of reads recruited to the E. coli K-12 MG-1655 genome (left y-axis) and the weights assigned by RIPTiDe to the associated metabolic reactions during each step (right y-axis). Metrics listed at the top of the plotting area reflect the resultant context-specific model compared to the complete iJO1366 model. (B) PCoA ordination of Bray-Curtis dissimilarities between flux distributions among reactions of each contextualized iJO1366 model either from in vivo or LB rich media (aerobic, in vitro) conditions. Significance was calculated by PERMANOVA. (C) Metabolite substrates of exchange reactions exclusive to the contextualized models shown. Inverse, normalized flux was calculated by dividing each flux sample by the associated flux through biomass in the same distribution, then multiplied by the overall median flux through biomass across all conditions analyzed. Median and interquartile ranges are displayed.