Refining microbial community metabolic models derived from metagenomics using reference-based taxonomic profiling.

IF 5 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2024-09-17 Epub Date: 2024-08-13 DOI:10.1128/msystems.00746-24
Marwan E Majzoub, Laurence D W Luu, Craig Haifer, Sudarshan Paramsothy, Thomas J Borody, Rupert W Leong, Torsten Thomas, Nadeem O Kaakoush
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引用次数: 0

Abstract

Characterization of microbial community metabolic output is crucial to understanding their functions. Construction of genome-scale metabolic models from metagenome-assembled genomes (MAG) has enabled prediction of metabolite production by microbial communities, yet little is known about their accuracy. Here, we examined the performance of two approaches for metabolite prediction from metagenomes, one that is MAG-guided and another that is taxonomic reference-guided. We applied both on shotgun metagenomics data from human and environmental samples, and validated findings in the human samples using untargeted metabolomics. We found that in human samples, where taxonomic profiling is optimized and reference genomes are readily available, when number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach. The two approaches showed significant overlap but each identified metabolites not predicted in the other. Pathway enrichment analyses identified significant differences in inferences derived from data based on the approach, highlighting the need for caution in interpretation. In environmental samples, when the number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach for total metabolites in both sample types and non-redundant metabolites in seawater samples. Nonetheless, as was observed for the human samples, the approaches overlapped substantially but also predicted metabolites not observed in the other. Our findings report on utility of a complementary input to genome-scale metabolic model construction that is less computationally intensive forgoing MAG assembly and refinement, and that can be applied on shallow shotgun sequencing where MAGs cannot be generated.IMPORTANCELittle is known about the accuracy of genome-scale metabolic models (GEMs) of microbial communities despite their influence on inferring community metabolic outputs and culture conditions. The performance of GEMs for metabolite prediction from metagenomes was assessed by applying two approaches on shotgun metagenomics data from human and environmental samples, and validating findings in the human samples using untargeted metabolomics. The performance of the approach was found to be dependent on sample type, but collectively, the reference-guided approach predicted more metabolites than the MAG-guided approach. Despite the differences, the predictions from the approaches overlapped substantially but each identified metabolites not predicted in the other. We found significant differences in biological inferences based on the approach, with some examples of uniquely enriched pathways in one group being invalidated when using the alternative approach, highlighting the need for caution in interpretation of GEMs.

利用基于参照的分类剖析,完善从元基因组学中得出的微生物群落代谢模型。
鉴定微生物群落的代谢产物对了解其功能至关重要。通过元基因组组装基因组(MAG)构建基因组尺度的代谢模型可以预测微生物群落的代谢产物产量,但人们对其准确性知之甚少。在这里,我们研究了两种元基因组代谢物预测方法的性能,一种是以 MAG 为指导的方法,另一种是以分类参考为指导的方法。我们将这两种方法应用于人类和环境样本的散弹枪元基因组学数据,并使用非靶向代谢组学验证了人类样本的研究结果。我们发现,在人类样本中,分类剖析得到了优化,参考基因组也很容易获得,当输入分类群的数量归一化时,参考指导方法比 MAG 指导方法预测了更多的代谢物。这两种方法有明显的重叠,但各自都发现了对方未预测到的代谢物。通路富集分析表明,基于不同方法的数据得出的推断结果存在显著差异,因此需要谨慎解释。在环境样本中,当输入分类群的数量归一化时,对于两种样本类型中的总代谢物和海水样本中的非冗余代谢物,参考指导方法比 MAG 指导方法预测出更多的代谢物。尽管如此,正如在人类样本中观察到的那样,这两种方法在很大程度上是重叠的,但也预测出了在另一种方法中没有观察到的代谢物。我们的研究结果报告了基因组尺度代谢模型构建的补充输入的实用性,这种输入的计算密集度较低,无需进行 MAG 组装和细化,而且可以应用于无法生成 MAG 的浅层霰弹枪测序。重要意义尽管微生物群落的基因组尺度代谢模型(GEMs)对推断群落代谢输出和培养条件具有重要影响,但人们对其准确性知之甚少。通过对来自人类和环境样本的霰弹枪元基因组数据应用两种方法,评估了元基因组代谢物预测 GEM 的性能,并使用非靶向代谢组学验证了人类样本中的发现。结果发现,方法的性能取决于样本类型,但总体而言,参考指导方法比 MAG 指导方法预测了更多的代谢物。尽管存在差异,但这两种方法的预测结果在很大程度上是重叠的,但每种方法都发现了另一种方法未预测到的代谢物。我们发现,基于不同方法的生物学推断存在显著差异,其中一些例子表明,一组中独特富集的通路在使用另一种方法时无效,这突出表明在解释 GEM 时需要谨慎。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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