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The microbiome is the collection of genetic material from all microorganisms inhabiting a given environment. Microbiome analyses can identify differences in colony structure and abundance, and predict or annotate differences in colony function. The metabolome represents all small molecules present in the same environment, and it reflects colony-host interactions. Both the microbiome and metabolome play critical roles in regulating host health, disease development, and ecosystem dynamics. Integrated microbiome and metabolome analyses can help understand how microflora influence the metabolic state of the host through colony metabolism and co-metabolism with the host, and can be used to gain insights into microbial interactions and functions in a system.
Creative Proteomics is an industry leader in multi-omics analysis. In integrated metabolome and microbiome analysis, we analyze the microbiome and metabolome separately, and then use multi-omics analysis technology to correlate the microbiome data with the metabolome data. Integrated metabolome and microbiome analysis can investigate the mechanisms of disease development, microbial-plant and animal-plant interactions. etc.
Integrated microbiome and metabolome analysis reveals a novel interplay between commensal bacteria and metabolites in colorectal cancer. (Yang Y, et al. 2019)
What do we offer?
We have state-of-the-art technology platforms and offer high-throughput sequencing technologies, such as 16S rRNA gene sequencing and macro-genomics for identifying microorganisms in microbiome studies. Meanwhile, we identify and quantify metabolites through mass spectrometry and NMR spectroscopy. In addition, we provide bioinformatics analysis services for integrating microbiome and metabolome data to help our clients with in-depth analysis and discussion.
Applications of integrated microbiome and metabolome analysis
- The complex relationships between microbial communities and their metabolic activities can be elucidated by integrating microbiome and metabolome data. It also helps to contribute to a more comprehensive understanding of disease progression and the molecular mechanisms of disease response.
- Human diseases. The microbiome has an important role in maintaining human health and preventing disease. Integrating microbial combinatorial metabolite analysis is important for identifying microbiota dysbiosis and altering metabolite profiles associated with various diseases. Also, integrated analysis helps in disease diagnosis and prognosis, discovery of potential biomarkers for better application in human healthcare applications.
- Environmental systems. Integrated microbiome and metabolome analyses can help researchers gain insights into the environmental impact of microbial communities on nutrient cycling, greenhouse gas emissions and pollutant degradation in terrestrial and aquatic ecosystems. This research application has significant implications for ecological conservation.
- Agricultural research. In agricultural production, understanding the complex interactions between soil microbiota and plant metabolites is imperative for improving crop quality and increasing crop yields. Integrated microbiome and metabolite analyses have also revealed the role of beneficial microorganisms in improving plant nutrient availability and stress tolerance.
Our service workflow
Creative Proteomics has extensive experience in metabolomics and microbiomics integration and analysis services. With advanced experimental platforms and a team of experienced experts, we aim to provide high-quality integrated analysis services to our clients. If you are interested in us, please feel free to contact us.
- Yang Y,Misra BB,Liang L, et al. Integrated microbiome and metabolome analysis reveals a novel interplay between commensal bacteria and metabolites in colorectal cancer. Theranostics. 2019;9 (14):4101-4114.
Integrated fecal microbiome-metabolome signatures reflect stress and serotonin metabolism in irritable bowel syndrome
Journal: Gut Microbes
The gastrointestinal disorder irritable bowel syndrome (IBS) is a classic example of microbiome-gut-brain axis involvement. The complexity of the underlying etiology of IBS, the involvement of psychosocial comorbidities, and its heterogeneity have proved to be a hurdle in the search for biomarkers and in the development of more effective therapeutic strategies. There are significant differences in IBS patients' gut microbiota characteristics compared to healthy controls (HC). However, there is still a lack of consensus on the exact nature of the changes in the gut microbiota composition in IBS. In addition to microbial composition, available data on microbial metabolic activity are limited and uncertain. Host-microbiome interactions may be largely driven by metabolic and microbial processes. Furthermore, knowledge of how changes in the gut microbiome and metabolome in IBS in particular reflect underlying pathophysiologic mechanisms or subgroups of IBS patients is very limited in this heterogeneous disease, and studies evaluating these pathways are needed to improve our understanding of host-microbiome interactions in IBS.
In the present study, the authors used whole-genome shotgun metagenomic sequencing (MGS) of gut microbiota composition combined with data on gut microbiota metabolic activity using proton nuclear magnetic resonance (1 H-NMR) spectroscopy to demonstrate that IBS microbiome-metabolome profiles are associated with altered serotonin metabolism and unfavorable stress responses associated with gastrointestinal symptoms, supporting the microbiota-gut-brain in the IBS pathogenesis link.
Based on H-NMR spectra, 50 unique metabolites have been identified in the fecal water of IBS patients and HC. Based on these metabolites, it was possible to differentiate between HC and IBS patients with an AUC of 79.5%. The metabolites responsible for this differentiation were increased in 10 metabolites in HC and 16 metabolites in IBS patients (Figure 1).
When combining fecal microbiota and fecal metabolites at the family level, it was possible to differentiate the two groups with an AUC of 83.6%. The model consists of microbial families and metabolites that distinguish HC and IBS patients. As shown in Figure 2c the combination of the two histologic levels provided the best differentiation between HC and IBS patients compared to using only the microbiota or fecal metabolites to differentiate the groups (Figure 2).
When considering IBS patients only, different patient clusters can be identified based on fecal microbiota and metabolites separately and in combination with both histologic data. These clusters are then investigated based on differences in the extensive clinical and biological metadata available in this cohort (Figure 3)
To determine the link between the gut microbiota and corresponding metabolites, an extensive metabolic response network was constructed involving gut microbial families and fecal metabolites significantly increased and decreased in patients with IBS. In this interaction diagram, microbial families with increased IBS (purple) and increased HC (green) are shown on the left. The pathways of fecal water metabolites can be traced on the right side of the graph by concentrating on enzymes; again, purple indicates an increase in IBS and green indicates an increase in HC (Figure 4). The pathways of glycolytic and proteolytic metabolic activity can be inferred from this figure.
In this study, the authors used integrated metabolomic and microbiomic analyses to identify fecal microbiome-metabolomic features of IBS that are associated with altered serotonin metabolism and adverse stress responses associated with gastrointestinal symptoms. Metabolic response networks integrated with microbiome information revealed pathways of host-microbiome interactions. These results support a microbiome-gut-brain link in the pathogenesis of IBS.
- Mujagic Z, Kasapi M, Jonkers DM, et al. Integrated fecal microbiome-metabolome signatures reflect stress and serotonin metabolism in irritable bowel syndrome. Gut Microbes. 2022;14(1):2063016.