Recent research indicates that a human body contains 39 trillion microbes! These organisms are part of our normal biology and are essential for our survival and well-being.
The collective genetic material of these organisms makes up the human microbiome. Many scientists use the term microbiome interchangeably with microbiota (the actual normal microorganism in a particular environment, such as the human body). For the purposes of this article, the microbiome will indicate the total genome of the human microbiota.
Many illnesses are linked to disturbances in the body’s microbiota. Dysbiosis, an imbalance in the normal flora in or on the body, is characterized by a reduction in the normal and beneficial flora and an overgrowth of pathogenic microorganisms. Dysbiosis contributes to many health conditions, including obesity, inflammatory bowel disease (IBD), and even cancer.
New diagnostic tools can detect changes in the microbiome. The NIH Human Microbiome Project was established in 2007 to characterize the human microbiome in healthy and diseased states. This project used many NGS technologies, including 16S sequencing, metagenomic shotgun sequencing, and other omics methods.
The resources generated by this project can be used to determine the role of various microbiome differences in human disease. For example, research using Human Microbiome Project data has identified a set of bacterial taxa that serve as a promising biomarker for colorectal cancer.
In this article, we discuss different microbiome environments and their potential for improving diagnostic efforts.
The ideal diagnostic method is non-invasive, cost effective, and accurate. Biomarkers of disease in the human microbiome are promising tools for improved diagnostics.
The identification of biomarkers in the mouth could easily and quickly obtain actionable information to support disease diagnosis. Recent advancements include the use of high-throughput sequencing methods to identify pathogenic organisms in saliva, plaque and on the tongue. Site specific microbiome identification can support disease associations.
In 2012, US Federal Drug Administration approved an ELISA-based HIV test that uses saliva samples. This test is available over-the-counter, and is less invasive than a traditional HIV blood test. A positive ELISA test must be followed up with a traditional blood test; in that case, diagnoses are 99.9% accurate.
Intestinal microbiota play important roles in regulating bodily functions and protecting the body from pathogens. The gastrointestinal (GI) tract’s microbiome could provide non-invasive, accurate methods to diagnose and choose treatment plans for systemic diseases associated with an altered microbiome.
Cardiovascular disease, IBD, and diabetes have been linked to alterations in the GI tract microbiota.
The link between microbiota and cardiovascular disease is based on findings that microorganisms metabolize dietary phosphatidylcholine into trimethylamine-N-oxide (TMAO). TMAO is a metabolite associated with the development of atherosclerosis. When healthy individuals were provided phosphatidylcholine, TMAO levels increased. This increase was inhibited with antibiotic treatment.
Studies using 16S sequence analysis of patients with IBD showed that they had lower diversity and increased abundances of specific bacteria including, for example, Enterobacteriaceae, Pasteurellaceae, Clostridiales, and Bacteroidales. They also found that antibiotic treatment exacerbated the microbial dysbiosis common with IBD.
Diabetes is also linked to dysbiosis. In a study involving the transplantation of nonobese-male fecal microbiota in males with metabolic syndrome, improvement in insulin sensitivity was observed. Fecal microbiota transplants have been used in a similar way to treat diarrheal infections, and, at an experimental level, in treating malnutrition.
Research has identified nearly 600 species of bacteria in the human vagina. However, individuals typically fall into one of five vaginal types classified by the dominant bacterium. Some vaginal types are at an increased risk of STIs and other infections.
Vaginal Community state Type 4, for example, is made up of an extremely diverse but less protective group of microbes. All other vaginal types are dominated by a species of Lactobacillus, making them less susceptible to conditions like bacterial vaginosis and STIs. In 2013, researchers published a study linking non-Lactobacillus dominant vaginal types with an increased risk of Trichomonas vaginalis, a more common STI than either gonorrhea or chlamydia. More susceptible microbiomes were dominated by Mycoplasma, Parvimonas, Sneathia, and other anaerobes.
Sampling this microbiome is relatively easy and provides important insights into an individual’s health status. Some at-home vaginal profiling tests are able to identify a user’s vaginal type and explain their risk level for contracting diseases.
Normally, the physiological environment of the GI tract prevents microorganisms from entering other parts of the body. However, translocation through an intact barrier and its link to sepsis has been observed. Microbial translocation has also been associated with increased infections in critically ill patients.
For example, microbial translocation to the circulatory system from the GI tract is responsible for systemic immune activation that causes progressive HIV infection. The mechanism of the microbial translocation-related disease process is yet to be fully understood. Next-generation sequencing has emerged as a vital tool for uncovering information to decipher the microbiome-disease links and mechanisms.
The availability of high-throughput massively parallel sequencing methods such as NGS has generated massive amounts of information regarding the human microbiome and its link to health and disease. It has proven valuable in studying microbiome-health relationships. Diagnostics and drug resistance detection are already benefitting from this technology.
Candida albicans, a member of the healthy human microbiome, is pathogenic in those who are immunocompromised. Drug resistance to common treatments for C. albicans infection has been observed. Using NGS, Ford et al. identified new C. albicans mutations such as single-nucleotide polymorphisms (SNPs) and loss-of-heterozygosity events that are believed to contribute to this drug resistance.
Mutla et al. used NGS to detect GI mucosal microbiome dysbiosis in HIV patients. They also found that these alterations correlated with immune activation in HIV. The alterations noted were a decrease in microbiome diversity and loss of commensals. Further, there was an increase in pathogenic microorganisms.
To determine the role of microbiota changes in infants with necrotizing enterocolitis, Leach et al. analyzed 16S rDNA using NGS. They found that although the fecal microbiota did not change significantly in comparison to controls, more potentially pathogenic bacteria were found in those infants. However, a potential biomarker for disease progression was identified (S100A12) and found to increase after diagnosis.
The massive data generated by NGS, the low cost of application, and the speed to obtain data have changed how diseases are diagnosed and treated. We better understand the mechanisms of disease and their applications in personalized medicine. This is particularly important for disease mechanisms that aren’t fully understood. Diagnostic and treatment efforts that target the microbiome have great potential to answer disease questions.
Psomagen thanks Dr. Stacy Matthews Branch for her contributions to the research and writing of the original version of this article. Dr. Branch is a biomedical consultant, medical writer, and veterinary medical doctor. She owns Djehuty Biomed Consulting and has published research articles and book chapters in the areas of molecular, developmental, reproductive, forensic, and clinical toxicology. Dr. Matthews Branch received her DVM from Tuskegee University and her Ph.D. from North Carolina State University.
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