Background Colorectal cancer (CRC) is a complex multifactorial disease. Increasing evidence suggests that the microbiome is involved in different stages of CRC initiation and progression. Beyond specific pro-oncogenic mechanisms found in pathogens, metagenomic studies indicate the existence of a microbiome signature, where particular bacterial taxa are enriched in the metagenomes of CRC patients. Here, we investigate to what extent the abundance of bacterial taxa in CRC metagenomes can be explained by the growth advantage resulting from the presence of specific CRC metabolites in the tumor microenvironment. Methods We composed lists of metabolites and bacteria that are enriched on CRC samples by reviewing metabolomics experimental literature and integrating data from metagenomic case-control studies. We computationally evaluated the growth effect of CRC enriched metabolites on over 1500 genome-based metabolic models of human microbiome bacteria. We integrated the metabolomics data and the mechanistic models by using scores that quantify the response of bacterial biomass production to CRC-enriched metabolites and used these scores to rank bacteria as potential CRC passengers. Results We found that metabolic networks of bacteria that are significantly enriched in CRC metagenomic samples either depend on metabolites that are more abundant in CRC samples or specifically benefit from these metabolites for biomass production. This suggests that metabolic alterations in the cancer environment are a major component shaping the CRC microbiome. Conclusion Here, we show with in sillico models that supplementing the intestinal environment with CRC metabolites specifically predicts the outgrowth of CRC-associated bacteria. We thus mechanistically explain why a range of CRC passenger bacteria are associated with CRC, enhancing our understanding of this disease. Our methods are applicable to other microbial communities, since it allows the systematic investigation of how shifts in the microbiome can be explained from changes in the metabolome.

中文翻译：

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代谢模型预测结直肠癌中的细菌乘客

背景结直肠癌（CRC）是一种复杂的多因素疾病。越来越多的证据表明微生物组参与结直肠癌发生和进展的不同阶段。除了在病原体中发现的特定促癌机制之外，宏基因组研究还表明存在微生物组特征，其中特定的细菌类群在结直肠癌患者的宏基因组中丰富。在这里，我们研究了 CRC 宏基因组中细菌类群的丰度在多大程度上可以通过肿瘤微环境中特定 CRC 代谢物的存在所产生的生长优势来解释。方法 通过回顾代谢组学实验文献并整合宏基因组病例对照研究的数据，我们列出了 CRC 样本中富集的代谢物和细菌列表。我们通过计算评估了 CRC 富集代谢物对超过 1500 个基于基因组的人类微生物组代谢模型的生长影响。我们通过使用量化细菌生物量生产对富含 CRC 的代谢物的反应的分数来整合代谢组学数据和机制模型，并使用这些分数将细菌排名为潜在的 CRC 乘客。结果我们发现，CRC 宏基因组样本中显着富集的细菌代谢网络要么依赖于 CRC 样本中更丰富的代谢物，要么特别受益于这些代谢物用于生物质生产。这表明癌症环境中的代谢改变是塑造结直肠癌微生物群的主要组成部分。结论 在这里，我们通过计算机模型证明，用 CRC 代谢物补充肠道环境可以特异性预测 CRC 相关细菌的生长。因此，我们从机制上解释了为什么一系列 CRC 过客细菌与 CRC 相关，从而增强了我们对这种疾病的了解。我们的方法适用于其他微生物群落，因为它可以系统地研究如何从代谢组的变化来解释微生物组的变化。