What is Metabolomics and 16S rDNA Sequencing

Metabolomics studies can elucidate the origin of abnormal metabolites and metabolite-associated disease-regulation pathways within complex diseases. Numerous life processes taking place within the cell are actually metabolite-dependent, including the release of cellular signals, energy transfer, and intercellular communication. By analyzing the metabolome under various physiological conditions, we can garner a comprehensive understanding of the biochemical state of the organism or cell. As the data obtained from Metabolomics analyses align closely with the phenotype or physiological state of an organism, theoretically, the information provided by these analyses can better illuminate the relationship between genes and phenotypes, thus allowing for effective monitoring and inference of gene function.

16S rDNA sequencing involves PCR amplification targeted at a particular highly variable region of the gene encoding small subunit rRNA in bacteria. Spanning approximately 1542 base pairs in its full length, this gene comprises nine variable regions (V1 to V9) and ten conserved regions. The conserved sections reflect phylogenetic relationships across biological species, while the variable sections highlight inter-species differences. Indeed, the level of variation is intimately linked to bacterial phylogenetics, thus rendering these regions suitable markers for bacterial phylogeny and taxonomic identification. Typically, next-generation sequencing focuses on approximately 200 bp length of the V3-V4 or V4-V5 segments.

Through 16S rDNA sequencing technology, we can investigate the composition of microbial communities in environmental samples. This analysis facilitates an understanding of microbial diversity, richness and community structure, and provides insights into the relations between microbes and their environment or host.

Microorganisms are inextricably linked to human health and implicated in numerous aspects such as growth (e.g., malnutrition), development (e.g., maturation of the immune system), metabolic diseases (e.g., obesity), and various cancers (colon, rectal, breast, liver cancers etc.), which often associate with gut microbial irregularities.

Microorganisms also play pivotal roles in agriculture and environmental changes, making the study of their interactions with plants, the influence of plant endophytes on plant growth, and the prevalence of microbes in various ecosystems (air pollution, bodies of water like oceans, glaciers, sewage, etc.) current hot topics for research.

Why to Integrated Analyze Metabolomics and 16S rDNA Sequencing

Through the combined analysis of Metabolomics and 16S rDNA sequencing, investigations can be conducted into the interrelationships between microorganisms and metabolites. This includes studying the relationship of microbial communities with their respective living environments, the impact of metabolites on microbial homeostasis, the mechanistic roles of microbial community alterations in complex diseases, and the interactions between physiologic actions of microbial communities and their metabolic products and functions. Likewise, the range of metabolic regulatory pathways with microbial community participation can also be examined.

Recently, a particularly illustrative example of the combined analysis of Metabolomics and 16S rDNA sequencing is the research into the relationship between gut microbial communities and host metabolic phenotypes. In addition, it studies how microbial communities influence metabolic functions. Furthermore, research has demonstrated that microbial entities and metabolites exhibit a high degree of correlation within various disease models. It signaled that the relationships between metabolites, microbes, and diseases can be examined through the integrative analytical methodologies of Metabolomics and 16S rDNA sequencing.

How to Integrated Analysis of Metabolomics and 16S rDNA Sequencing

The correlative analysis of microbiome and metabolome can be executed either within the same sample from an individual (focusing on the microorganisms and their metabolites), or between different sample types from the same organism (concentrating on the impact of microbial metabolites on the host). The specific experimental setting can be tailored to meet the research requirements. Conventional common practices in Metabolomics and 16S rDNA sequencing seek correlations between the category or abundance of species and the abundance of metabolic products.

In this context, preliminary steps of correlation analysis involve identifying significant alterations in metabolites and microbial communities within two academic fields. Metabolomics typically harnesses intergroup variations within secondary metabolites after they have been screened, while 16S rDNA sequencing more commonly employs significantly different taxa at the genus level.

Following this, Spearman's correlational analysis is performed on the differentiated secondary metabolites obtained from the metabolomics screening and the significantly differentiated genera level microbial communities from the 16S sequencing. This unveils the relationships among differently abundant microbial groups, different metabolites, and between different metabolites and microbial factions.

Based on the calculated results, appropriate screening conditions are selected to obtain the final relationships among the different metabolites and diagrams of their relevant networks, thereby shedding light on the interactions between microorganisms and their metabolites. Such comprehensive understanding provides invaluable guidance for subsequent explorations and verification studies.

Research Approach for Integrative Analysis of Metabolomics and 16S rDNA Sequencing

Case of Integrated Analysis of Metabolomics and 16S rDNA Sequencing

Host-microbiota interaction-mediated resistance to infammatory bowel disease in pigs

Journal: Microbiome (IF=16.837)
Published: July 2022
Sample Type: Pig colon, colonic contents
Research Method: 16S rDNA sequencing, Metabolomics

The resistance phenotype is intricately linked to immune regulatory function and immunological tolerance, imposing major implications for livestock farming and human health. Microbiota play an important role in host immune modulation. However, the effect of host-microbiota interactions on resistance phenotypes remains unclear. In this study, we established models for a control group of Min and Yorkshire pigs as well as a group with acute colitis and employed 16S rDNA sequencing and metabolomics to probe the potential anti-disease regulatory mechanisms at the microbiota and host levels in these two pig breeds.

Research Findings: The results showed that under identical nutritional and handling conditions, Min pigs have superior disease resistance compared to Yorkshire pigs. 16S rDNA sequencing results indicated an increase in potentially harmful microbes, such as Desulfovibrio, Bacteroides, and Streptococcus, in diseased individuals of both breeds. In contrast, potentially beneficial microbes, such as lactobacillus, clostridium, and eubacterium, as well as several genera from the Ruminococcaceae and Christensenellaceae families, were enriched in diseased Min pigs and showed positive correlations with intestinal barrier-associated microbial metabolites. Specifically, the concentrations of indole derivatives and short-chain fatty acids (SCFAs) increased in diseased Min pigs, underpinning their protective roles within the intestinal barrier. Furthermore, the diseased Yorkshire pigs exhibited lower concentrations of bile acid metabolites and SCFAs, relating to the expansion of potentially harmful microbes such as Bilophila and Parabacteroides. During the immune response, the augmentation of resident CD4+ T cells contributed to enhanced regulatory control of the host immune response in diseased Min pigs. This was further supported by the beneficial microbiota, which helped maintain Th2 immune dominance and immunologic tolerance, controlling excess inflammation. Conversely, in diseased Yorkshire pigs, harmful microbial proliferation and intestinal barrier damage led to exacerbated immune-biological processes such as Toll-like receptor signaling, NF-κB signaling, and Th1 and Th17 type immune responses. Taken together, these findings underscore that host-microbiota interactions in the two pig breeds fostered three types of resistance phenotypes: maintaining partial PRR non-activation, preserving Th2 immune dominance and immunologic tolerance, and restoring intestinal barrier function to prevent colonic disease.

Gut Microbiota Dysbiosis Induced by decreasing Endogenous Melatonin Mediates the Pathogenesis of Alzheimer's Disease and Obesity

Journal: Frontiers in Immunology (IF= 8.786)
Published: May 2022
Sample Types: Mouse feces, serum, tissues
Methods: 16S rDNA sequencing, Metabolomics, transcriptomics

Research Content: Lifestyle choices, external environment, and aging can all affect the production of melatonin. While the physiological functions of melatonin are closely related to specific organs, the systemic effects of reduced endogenous melatonin have not yet been reported. This study used a murine model with a knockout of the arylalkylamine N-acetyltransferase (Aanat) gene, which is a rate-limiting enzyme in melatonin synthesis, to evaluate the systemic changes and potential pathogenic risks brought about by endogenous melatonin reduction (EMR).

The results demonstrated that EMR mice exhibit a broad range of metabolic diseases, significant transcriptome-level changes in 11 organs, alterations in serum metabolomics, and dysbiosis of the microbiota. Gut permeability was found to increase in EMR mice, accompanied by intestinal and systemic inflammation. Correlation analyses indicated that systemic inflammation might be associated with an increased relative abundance of Ruminiclostridium_5. Eight-month-old EMR mice displayed Alzheimer's Disease-like phenotypes, including activated Iba-1, Aβ protein deposition, and impaired spatial memory. Furthermore, EMR mice demonstrated a diminished ability to cope with stress. Under high-fat diet conditions, compared to the wild-type group, EMR mice showed more significant weight gain and liver steatosis.

Fecal microbial transplants (FMT) ameliorated gut permeability, systemic inflammation, and Alzheimer's Disease-associated phenotypes, concurrently mitigating the obesity of EMR mice. These findings suggest that EMR triggers systemic changes mediated by gut microbiota dysbiosis, which could potentially serve as a pathogenic factor for Alzheimer's Disease and obesity.

Fecal microbiota and metabolomics revealed the effect of long-term consumption of gallic acid on canine lipid metabolism and gut health

Journal: Food Chemistry: X (IF = 6.443)
Published: June 2022
Sample Type: Fecal and Serum Samples from Beagles
Research Methods: 16S rDNA sequencing, Metabolomics

Gallic acid (GA) is a natural polyphenolic compound known for its array of health benefits. To evaluate its potential risks and contribution to gut health under chronic ingestion, this study supplemented Beagles' daily diet with varying levels of GA (0%, 0.02%, 0.04%, and 0.08%) for 45 days. Evaluations were carried out on fecal microbiota and metabolome.

Results indicated that GA supplementation modified serum lipid metabolism by significantly reducing serum triglycerides, fat digestibility, and the Bacteroidetes/Firmicutes ratio. Moreover, a notable reduction in the relative abundance of Parabacteroides was observed in the 0.08% GA group, simultaneously witnessing an increase in short-chain fatty acid (SCFAs)-producing bacteria with an increase in fecal acetate and total SCFAs.

Further metabolomic data analyzation revealed that 0.08% GA markedly impacted carbohydrate metabolism by downregulating fecal succinic acid, potentially ameliorating inflammation and oxidative stress. Taken together, this research provides evidence of the beneficial effects of prolonged GA ingestion on lipid metabolism and gut health, with an optimal supplementation level of 0.08%.

References

1. Zhao X, Jiang L, Fang X, et,al. Host-microbiota interaction-mediated resistance to inflammatory bowel disease in pigs. Microbiome. 2022 Jul 30;10(1):115.
2. Zhang B, Chen T, Cao M, et,al. Gut Microbiota Dysbiosis Induced by Decreasing Endogenous Melatonin Mediates the Pathogenesis of Alzheimer's Disease and Obesity. Front Immunol. 2022 May 10;13:900132.
3. Yang K, Jian S, Guo D, et,al. Fecal microbiota and metabolomics revealed the effect of long-term consumption of gallic acid on canine lipid metabolism and gut health. Food Chem X. 2022 Jun 27;15:100377.