Single Mutation in <i>iolT1</i> in <i>ptsG</i>-Deficient <i>Corynebacterium glutamicum</i> Enables Growth Boost in Xylose-Containing Media
Efficient co-utilization of glucose and xylose from lignocellulosic biomass remains a critical bottleneck limiting the viability of sustainable biorefineries. While <i>Corynebacterium glutamicum</i> has emerged as a promising industrial host due to its robustness, further improvements in...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Microorganisms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-2607/13/7/1606 |
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| Summary: | Efficient co-utilization of glucose and xylose from lignocellulosic biomass remains a critical bottleneck limiting the viability of sustainable biorefineries. While <i>Corynebacterium glutamicum</i> has emerged as a promising industrial host due to its robustness, further improvements in mixed-sugar co-utilization are needed. Here, we demonstrate how a single amino acid substitution can dramatically transform cellular sugar transport capacity. By combining rational strain engineering with continuous adaptive laboratory evolution, we evolved a <i>ptsG</i>-deficient <i>C. glutamicum</i> strain in glucose–xylose mixtures for 600 h under consistent selection pressure. Whole-genome sequencing revealed a remarkable finding: a single point mutation; exchanging proline for alanine in the <i>myo</i>-inositol/proton symporter IolT1 was sufficient to boost glucose uptake by 83% and xylose uptake by 20%, while increasing the overall growth rate by 35%. This mutation, located in a highly conserved domain, likely disrupts an alpha helical structure, thus enhancing transport function. Reverse engineering confirmed that this single change alone reproduces the evolved phenotype, representing the first report of an engineered IolT1 variant in PTS-independent <i>C. glutamicum</i> that features significantly enhanced substrate uptake. These results both provide an immediately applicable engineering target for biorefinery applications and demonstrate the power of evolutionary approaches to identify non-intuitive solutions to complex metabolic engineering challenges. |
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| ISSN: | 2076-2607 |