Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover. This phenomenon, here formally defined as “metabolic pathway drift,” is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a methodological approach to formalize the logical reasoning necessary to infer reactions and molecular structures, abstracting molecular transformations based on previous biochemical knowledge.

在新兴模式生物中推断基因组规模的代谢网络面临着不完整的生化知识和进化过程中生化途径的部分保守的挑战。因此，需要特定的生物信息学工具来推断可以通过实验检查的生化反应和代谢结构。使用结合红藻模型卷曲角叉菜中的基因组和代谢组数据的综合方法，我们表明，即使被认为保守的代谢途径，如甾醇或类菌孢素氨基酸合成途径，也会经历大量的更新。这种现象在这里正式定义为“代谢途径漂移”，与进化生物学其他领域的发现一致，表明即使潜在的分子机制发生变化，给定的表型也可以保守。我们通过方法论方法提出概念证明，以形式化推断反应和分子结构所需的逻辑推理，并根据先前的生化知识抽象分子转化。