ResearchBioengineeringPeer-reviewed journal article
Probing Biomass Precursor Synthesis as a Key Factor in Microbial Adaptation to Unadapted Carbon Sources
Jingyi CaiiD, Jiayu LiuiD, Fan Wei, Wenjun WuiD, Wenqi Xu, Zhitao MaoiD, Qianqian YuaniD, Hongwu MaiD
Abstract
Industrial microorganisms often face challenges in utilizing renewable substrates such as methanol, formate, and xylose. We present findings that the proportion of biomass precursors that must be synthesized from unadapted carbon sources is a critical determinant of the evolutionary driving force and minimal substrate requirements, using a new computational framework, AdaptUC. We predict metabolic engineering strategies for Adaptive Laboratory Evolution (ALE). These strategies enable microorganisms to co-utilize an adapted co-substrate and an unadapted carbon source or, in some cases, rely exclusively on the unadapted source. AdaptUC was validated through experimental records and literature, confirming its effectiveness in identifying gene knockout strategies. Case studies in Escherichia coli and Corynebacterium glutamicum highlight superior strategies with higher driving forces and reduced substrate requirements. This method has the potential to transform industrial biosynthesis by enabling more efficient use of renewable carbon sources. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/619944v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@36fe02org.highwire.dtl.DTLVardef@5e73fdorg.highwire.dtl.DTLVardef@110ffdaorg.highwire.dtl.DTLVardef@10d45dc_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: E. coli
- organism: C. elegans
- assay: metabolomics
- research focus: metabolism & bioenergetics
- research focus: gene regulatory network inference
- research focus: perturbation response prediction
- approach: deep learning
- approach: statistical model
- Citations
- 1
- FWCI
- 0.28
- Field percentile
- 47th percentile
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