Microbes interact with Enteroendocrine Cells

Microbes also interact with enteroendocrine cells (EECs) in the gut lining to send hormones throughout the body. EECs sense changes in luminal microorganisms via microbial metabolites, and communicate with host body systems via neuroendocrine molecules such as serotonin or GLP-1. A recent transcriptome-wide association study of 23 tissues revealed shared susceptibility genes between Crohn's disease, ulcerative colitis, and schizophrenia. Analysis of bulk and single-cell RNA-sequencing data showed that gene expression was strongest in neurons and enteroendocrine cells in the colon and rectum, indicating a possible link to the gut-brain-axis.⁹

Gut Microbes Impact Inflammation

More indirectly, gut microbiota influence immune cells and inflammation pathways, which can affect the brain. For more than 20 years, inflammation has been associated with depression. One demonstration of this is the fact that several antidepressants have been shown to reduce the endogenous production of pro-inflammatory cytokines, thus modifying immune reactivity in the brain. There is also evidence in the pathogenesis of depression that there is increased bacterial translocation due to the disruption of tight junctions and barrier integrity of the GI tract. Moreover, recent evidence indicates that microbiota dysbiosis is associated with the development of several chronic inflammatory disorders. More specifically, several gut microbial taxa have been shown to stimulate the anti-inflammatory cytokine, including IL-10 and downregulate inflammatory cytokines. Evidence from rodent experiments also supports a link between microbiota and depression through inflammatory markers. Furthermore, many clinical studies have shown a decrease in depressive symptoms following probiotic treatment.^10,11

Metagenomics and Metabolomics Links the Gut Microbiome to MDD

Researchers recently analyzed whole-genome shotgun metagenomic sequences and combined that with untargeted metabolomic data from over 300 individuals with Major Depressive Disorder (MDD) and paired Healthy Controls (HCs). They identified a network of bacteria, bacteriophages, and metabolites that were differentially expressed between patients with MDD and HCs. Patients with MDD were mainly characterized by increased abundance of the genus Bacteroides, and decreased abundance of the genera Blautia and Eubacterium. There was concordance between the differentially expressed genes and fecal metabolites as both data sets point to differential expression of amino acids (ℽ-aminobutyrate, phenylalanine, and tryptophan). Together, these findings may lead to the development of probiotics or postbiotics and easier diagnosis as they identified a combinatorial marker panel that robustly discriminates MDD from HC individuals.¹²

Combining Host and Microbiome Sequencing

Long-term cohort studies that collect multiple datasets can provide a wealth of information. Recently, one such cohort study, FINRISK 2002, analyzed matching human genotypes and shotgun fecal metagenomes for almost 6,000 individuals. They combined these genome-wide associations with extensive health and dietary data to predict incident disease linked to gut microbial variation. They had health records for up to 16 years after the initial microbiome samples, which allowed for observational validations of predicted effects. Using Mendelian randomization, they predicted 96 causal effects in both microbe-to-disease and disease-to-microbe directions. Of these effects, 34 indicated that microbial abundances can be used to predict a disease, and a large proportion of those diseases were psychiatric and neurological. For example, an increased abundance of Faecalicoccus may have a causal effect on anorexia nervosa, and an increased abundance of Morganella and Raoultella are predicted to have causal effects on MDD. Interestingly, when Mendelian randomization was performed in the reverse direction, using disease risk as an exposure and microbial level as an outcome, most predicted causal effects involved autoimmune and inflammatory diseases.¹³

Consider the Microbiome in Any Research Question

Any field of Human Health research should take into account the effect of the microbes that live within and on us. Whatever your field of research is, from psychology to immunology, and whether your expertise is in metabolomics, proteomics, biochemistry, or human genetics, you should consider including analysis of RNA or DNA extracted from fecal samples in your study design.

Norgen's Stool Microbiome Workflow

Norgen has a complete workflow for studying the fecal microbiome, encompassing collection, extraction of both DNA and RNA, and sequencing. Norgen has a variety of sample storage and preservation tubes, including the patented Stool Nucleic Acid Collection and Preservation tubes, either CE-IVD marked for diagnostic purposes (Cat. Dx45660) or for research purposes (Cat. 45660). We also have Fecal collection mini tubes (Cat. 27650) for mouse or other rodent microbiome studies, and a Fecal Swab Collection and Preservation System (Cat. 45670-B). Then there are Norgen's Stool DNA extraction kits using spin columns (Cat. 27600, 65600) or magnetic beads (Cat. 55700, Cat. 63100) for more high throughput approaches. These magnetic bead protocols can be automated on the Hamilton Vantage, or similar machines, or magnetic rod-based systems. Or if you would like to investigate transcriptomics, there is Norgen's Stool Total RNA Purification Kit (Cat. 49500), or the Stool Nucleic Acid Isolation Kit (Cat. 45600), to extract both DNA and RNA. You can also prepare your own 16S or ITS Metagenomic libraries for sequencing. Lastly, Norgen offers Metagenomic Sequencing Services.