The human microbiome comprises all microorganisms like bacteria, viruses, and fungi that live within our bodies and can significantly influence our physiology and health. An imbalance in these microbial communities, known as dysbiosis, can lead to various symptoms depending on where the imbalance occurs and is associated with many systemic diseases.
Factors such as genetics, lifestyle habits, diet (especially ultra-processed foods and additives), and medications can influence dysbiosis. The microbiome holds tremendous potential in diagnosing, treating, and monitoring diseases, and a whole-body systems-based approach to diagnosing dysbiosis may be more effective than focusing solely on specific microorganisms.
Addressing whole-body dysbiosis may involve lifestyle changes, dietary adjustments, and microbial modulation, although the effectiveness of these interventions in humans is still being researched.
In eubiosis, indicative of a balanced microbial ecosystem, there is a preponderance of beneficial bacteria (Phyla Firmicutes and Bacteroidetes) over pathogenic bacteria (Phylum Proteobacteria). Dysbiosis can result when there is a microbial imbalance or compositional change, and pathogenic bacteria override beneficial bacteria, potentially causing disease.
Most patients with dysbiosis present with
Under conditions of dysbiosis, there can be a reduction of protective bacteria with a switch to more abundant pathogenic and cancer-promoting bacteria, which can include Streptococcus bovis, Sulfidogenic bacteria, Fusobacterium nucleatum, Bacteroides fragilis, Clostridium septicum, Escherichia coli, Helicobacter pylori, Enterococcus faecalis, Human papilloma virus, John Cunnigham virus, and Epstein Barr virus.
Whole-body dysbiosis could be a risk factor for many diseases. The first human microbiome is inherited at birth and is highly stable, whereas the acquired microbiome after birth depends on environmental factors. Some studies have linked dysbiosis to being born via C-section and being formula-fed from birth.
Gut vs. non-gut dysbiosis |
Organ system |
Associated diseases with an element of dysbiosis |
Gut |
Cardiovascular |
Hypertension |
Non-gut |
Respiratory |
Asthma |
Gut |
Gastrointestinal |
Irritable bowel disease |
Non-gut |
Genitourinary |
Chronic kidney disease |
Non-gut |
Central nervous systems |
Meningitis |
Gut |
Psychiatric conditions |
Dementia |
Gut/Non-gut |
Oncological conditions |
Gynecological cancers |
Gut |
Autoimmune diseases |
Rheumatoid arthritis |
Non-gut |
Skin |
Eczema |
Gut |
Endocrine or metabolic |
Diabetes mellitus type 1 |
Various extraintestinal organs play a role in the physiological function of the gut microbiome. Gut and non-gut dysbiosis communicate through different axes in a bidirectional manner. This highlights the concept of the gut–organ axis.
Oral dysbiosis
Lung dysbiosis, including ear, nose, and throat tract dysbiosis
Skin dysbiosis, including conjunctival and eye dysbiosis
Genitourinary dysbiosis
Urinary microbiome dysbiosis is associated with interstitial cystitis, urinary tract infection (UTI), bladder pain syndrome and different types of urinary incontinence.
Test |
Description |
Stool test |
This test can help determine the overall balance of bacteria and the presence of yeast. The use of polymerase chain reaction (PCR) can determine the ratio of Firmicutes to Bacteroidetes, along with the presence of Lactobacillus and Bifidobacterium. A comprehensive digestive stool analysis (CDSA) includes analysis of different microbiota such a lactobacilli, bifidobacteria, E. coli, Proteus, Pseudomonas, Salmonella, Shigella, Vibrio, yeast, and microbiome analysis including sequencing technologies, dysbiosis indexes, metagenomics, metatranscriptomics as well as assessment of microbial metabolites like Short Chain Fatty Acids |
Diversity of the microbiota (dysbiosis indexes) |
These indexes help to determine intestinal microbial communities. Often alpha and beta diversity assessments are commonly used and should be interpreted based on the context of clinical findings. Alpha-diversity was calculated using the Shannon index depending on the gene and species profile. |
Urine test |
Look for microbial metabolites in the urine using Nuclear magnetic resonance (NMR). |
Intestinal permeability assessment or mannitol-lactulose intestinal permeability test |
This test can explore intestinal permeability and dysbiosis and suggest leaky gut syndrome. An individual can will consume the sugars mannitol and lactulose, if there is permeability in the gut, these guts will be detected in the urine at elevated levels. |
Hydrogen or methane breath test |
A baseline breath gas measurement is first done and followed by the patient ingesting a standardized substrate solution (typically lactulose) that is indigestible by humans but easily digestible by bacteria. Next, the individual's breath is measured every 20 min to assess the amount of hydrogen and methane. These readings will determine the degree of microbial fermentation within the upper GI tract. A positive indication of dysbiosis is confirmed with rapid and steady rises of the hydrogen and methane readings. Repetition of this test can be used to gauge the treatment progress of a leaky gut. |
Large-scale bacterial marker profiling |
This identification method used various specific markers on species/bacteria taxa. One example is the use of 54 probes that target the 16S rRNA gene at different bacterial taxonomic levels (covering Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, Tenericutes, and Verrucomicrobia). This is known as the GA-Map dysbiosis test. When classifying a sample, it is compared to a reference population, a score of 1 to 5 is used, where a recording of greater than 2 is considered dysbiosis. It can also look at targeted species and give a score of −3 to 3 where negative values suggest a reduced abundance and positive values suggest increased abundance. |
Relevant taxon-based methods |
Other types of dysbiosis indexes have been developed to look at specific taxa and with the goal of being more simplistic and easily interpreted. These indexes are calculated based on ratios between abundance. |
Neighborhood classification |
This technique measures the microbial dysbiosis in an individual compared to a healthy control. This is determined by quantifying the deviation a specific sample is from a reference sample set using dissimilarity matrices. |
Random forest prediction |
Through the use of a machine learning, algorithm random forest and a generated dysbiosis index based on operational taxonomic units examining abundances normalized by GMPR (geometric mean of pairwise ratios). It uses a range from 0 to 1, where values approaching 1 suggest a high likelihood that the gut microbiota is from a symptomatic individual (often used in small intestine overgrowth (SIBO) patients). |
Combined alpha and beta diversity |
This method is most commonly used in sequencing-based microbiota studies that provide a general description of microbial communities. Alpha is use to describe the number of unique taxa (richness) and their distribution (evenness) within a community and is often considered a biomarker of health. Beta is used to assess difference in community composition between individuals, or can be applied when assessing patients versus healthy controls. There is a combined method described as a dysbiosis index that uses a range of 0–5, where values greater than 1 suggest dysbiosis. |
Oral carnitine challenge test |
This test was designed to help determine and apply personalized nutrition to an individual based on the function of their gut microbiome. This method considers the gut microbiome as a “bioreactor” and it is provided inputs in the form of fermentable materials and the outputs (microbial byproducts) are measured either in the blood or urine. This test can also be used to measure metabolites from microbial fermentation. |
Gut dysbiosis biomarkers |
There are certain biomarkers that may give an indication of gut dysbiosis. Certain gut microorganisms are able to release urolithins (anti-inflammatory metabolites) when exposed to dietary polyphenols. These metabolites may serve as biomarkers of gut microbiota composition and functionality (159). Other biomarkers that have been studied for metabolite profiling and diagnosing dysbiosis include, trimethylamine-N-oxide, short-chain fatty acids, 3-indoxyl sulfate, p-cresyl sulfate, secondary bile acids, hippurate, human β-defensin-2, chromogranin A, secreted immunoglobulins and zonulin. |
Dysbiosis indexes |
Dysbiosis can be determined and quantify by relevant taxon-based methods, bacterial marker profiling, alpha and beta diversity. At this time, these indexes may be used as a diagnostic marker of dysbiosis, but are not predictors of a disease or disease process. |
Classification |
Method |
Mechanisms of action |
Direct repopulation |
Fecal microbiota transplant |
A method of directly repopulating the gastrointestinal tract with beneficial bacteria |
Gut biotics |
Probiotics |
Live microorganisms that can provide health benefits and are designed to restore the beneficial bacteria of the gut |
Prebiotics |
Compounds found in food designed to promote the growth of beneficial microorganisms of the human gut |
|
Synbiotics |
Refers to food or dietary supplements that consist of both probiotics and prebiotics |
|
Diet/Food modifications |
Fermented foods |
Fermented foods may play a role in health benefit through the nutritive alteration of the ingredients, modulation of the immune system, and the presence of bioactive compounds. By modulating the gut microbiota composition and activity they can affect intestinal and systemic function. Ingestion may help intestinal barrier function along with the production of metabolites inhibiting the uptake of pathogens |
Fiber rich foods |
High-fiber diets have the ability to positively alter the microbial intestinal composition by promoting the growth of more beneficial bacteria, such as Prevotella and Bacteroides, while shifting away from Firmicutes. Dietary fiber can also selectively increase SCFAs producing bacterium abundance. |
|
Mediterranean diet |
This diet is generally described as having a greater focus on minimally processed fruits and vegetables with the inclusion of pulses (e.g., Chickpeas, lentils), nuts, seeds, and fish in relative abundance. The diet itself has also been associated with improvement in microbiome composition and diversity which can lead to lower risk of gut dysbiosis. |
|
Ketogenic diet |
This diet focused on a considerable limitation of carbohydrate sources to promote ketone body production. These ketones bodies may lead to an impact on energy metabolism and impact on the microbiome influencing bacteria taxa, richness and diversity. |
|
Microbial by-products |
Metabolite treatment |
The byproducts of the gut microbiome or even probiotics are highly bioactive and are sometimes called “postbiotics”. Some common metabolites are SCFAs, which are a fuel source for colonocytes and can help maintain the gut barrier and inhibit pathogenic microorganism proliferation due to acidic pH condition. Specific SCFAs, such as resveratrol, a phytoalexin, can decrease plasma TMAO (which is a risk factor for CVD). |
Alagiakrishnan K, Morgadinho J, Halverson T. Approach to the diagnosis and management of dysbiosis. Front Nutr. 2024 Apr 19;11:1330903. doi: 10.3389/fnut.2024.1330903. PMID: 38706561; PMCID: PMC11069313. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
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