Biomarkers of human gut microbiota diversity and dysbiosis

Approach to the diagnosis and management of dysbiosis

All microorganisms like bacteria, viruses and fungi that reside within a host environment are considered a microbiome. The number of bacteria almost equal that of human cells, however, the genome of these bacteria may be almost 100 times larger than the human genome. Every aspect of the physiology and health can be influenced by the microbiome living in various parts of our body. Any imbalance in the microbiome composition or function is seen as dysbiosis. Different types of dysbiosis are seen and the corresponding symptoms depend on the site of microbial imbalance. The contribution of the intestinal and extra-intestinal microbiota to influence systemic activities is through interplay between different axes. Whole body dysbiosis is a complex process involving gut microbiome and non-gut related microbiome. It is still at the stage of infancy and has not yet been fully understood. Dysbiosis can be influenced by genetic factors, lifestyle habits, diet including ultra-processed foods and food additives, as well as medications. Dysbiosis has been associated with many systemic diseases and cannot be diagnosed through standard blood tests or investigations. Microbiota derived metabolites can be analyzed and can be useful in the management of dysbiosis. Whole body dysbiosis can be addressed by altering lifestyle factors, proper diet and microbial modulation. The effect of these interventions in humans depends on the beneficial microbiome alteration mostly based on animal studies with evolving evidence from human studies. There is tremendous potential for the human microbiome in the diagnosis, treatment, and prognosis of diseases, as well as, for the monitoring of health and disease in humans. Whole body system-based approach to the diagnosis of dysbiosis is better than a pure taxonomic approach. Whole body dysbiosis could be a new therapeutic target in the management of various health conditions.

Algorithmic Programming of Sequential Logic and Genetic Circuits for Recording Biochemical Concentration in a Probiotic Bacterium

Through the implementation of designable genetic circuits, engineered probiotic microorganisms could be used as noninvasive diagnostic tools for the gastrointestinal tract. For these living cells to report detected biomarkers or signals after exiting the gut, the genetic circuits must be able to record these signals by using genetically encoded memory. Complex memory register circuits could enable multiplex interrogation of biomarkers and signals. A theory-based approach to create genetic circuits containing memory, known as sequential logic circuits, was previously established for a model laboratory strain of Escherichia coli, yet how circuit component performance varies for nonmodel and clinically relevant bacterial strains is poorly understood. Here, we develop a scalable computational approach to design robust sequential logic circuits in probiotic strain Escherichia coli Nissle 1917 (EcN). In this work, we used TetR-family transcriptional repressors to build genetic logic gates that can be composed into sequential logic circuits, along with a set of engineered sensors relevant for use in the gut environment. Using standard methods, 16 genetic NOT gates and nine sensors were experimentally characterized in EcN. These data were used to design and predict the performance of circuit designs. We present a set of genetic circuits encoding both combinational logic and sequential logic and show that the circuit outputs are in close agreement with our quantitative predictions from the design algorithm. Furthermore, we demonstrate an analog-like concentration recording circuit that detects and reports three input concentration ranges of a biochemical signal using sequential logic.

Altered gut microbiome composition in nontreated plaque psoriasis patients

Recent studies have demonstrated that dysbiosis of the gut microbiota is associated with psoriasis, but these studies showed some conflicting results. Our study examined differences in microbiome composition associated in people with psoriasis and those without. Comparing individuals with their healthy partners was a second strategy. We explored the fecal microbiota among 32 nontreated plaque psoriasis patients, 15 healthy controls and 17 healthy couples by metagenomic gene sequencing. The relative levels of intestinal microbiota of the psoriasis cohort differed from those in healthy controls and these patients' partners. However, there was no microbial diversity among these three cohorts. On the level of the phylum, Firmicutes and Bacteroidetes' relative abundances were reversed. Escherichia coli was significantly enriched in the psoriasis group compared with the healthy people and the healthy spouses. Gene functional analysis indicated that Ribosome (ko03010) was upregulated, Flagellar assembly (ko02040) and Bacterial chemotaxis (ko02030) were downregulated in the psoriasis cohort compared with the healthy individuals and the healthy spouses. The microbiota in severe psoriasis patients differed from those with milder conditions. These findings strongly support the association between intestinal flora and psoriasis. It is necessary to perform more meaningful experiments to identify whether the differences of gut microbiota are the cause or consequences of psoriasis in future.

Unlocking the Potential of the Human Microbiome for Identifying Disease Diagnostic Biomarkers

The human microbiome encodes more than three million genes, outnumbering human genes by more than 100 times, while microbial cells in the human microbiota outnumber human cells by 10 times. Thus, the human microbiota and related microbiome constitute a vast source for identifying disease biomarkers and therapeutic drug targets. Herein, we review the evidence backing the exploitation of the human microbiome for identifying diagnostic biomarkers for human disease. We describe the importance of the human microbiome in health and disease and detail the use of the human microbiome and microbiota metabolites as potential diagnostic biomarkers for multiple diseases, including cancer, as well as inflammatory, neurological, and metabolic diseases. Thus, the human microbiota has enormous potential to pave the road for a new era in biomarker research for diagnostic and therapeutic purposes. The scientific community needs to collaborate to overcome current challenges in microbiome research concerning the lack of standardization of research methods and the lack of understanding of causal relationships between microbiota and human disease.

The role of gut microbiota in patients with benign and malignant brain tumors: a pilot study

Gut microbiota is associated with the growth of various tumors, including malignant gliomas, through the brain-gut axis. Moreover, the gut microbiota in patients with malignant tumors may considerably differ from those with benign tumors. However, the associations of gut microbiota with benign and malignant brain tumors remain unclear. Hence, in order to explore these underlying relationships, patients with benign meningioma (n = 32), malignant glioma (n = 27), and healthy individuals (n = 41) were selected to participate in this study. The results showed that the diversity of the microbial ecosystem in brain tumor patients were less than the healthy controls, while no significant differences were observed between the meningioma and glioma groups. The microbial composition also differed significantly between individuals with brain tumors and healthy participants. In meningioma group, pathogenic bacteria like Enterobacteriaceae were increased, whereas certain carcinogenic bacteria were overrepresented in the glioma group, including Fusobacterium and Akkermansia. Furthermore, benign and malignant brain tumor patients lacked SCFA-producing probiotics. Thus, a microbial biomarker panel including Fusobacterium, Akkermansia, Escherichia/Shigella, Lachnospira, Agathobacter, and Bifidobacterium was established. Diagnostic models confirmed that this panel could distinguish between brain tumor patients and healthy patients. Additionally, gut microbiota can affect the differentiation and proliferation of brain tumors via several metabolic pathways based on annotations from the Kyoto Encyclopedia of Genes and Genomes (KEGG). This is the first study designed to investigate whether gut microbiota differs between benign and malignant brain tumor patients, and our work concluded that intestinal flora is a valuable tool for the diagnosis and treatment of brain tumors.

Pelzer B, Khodamoradi Y, Vehreschild MJGT. The role of the human gut microbiota in colonization and infection with multidrug-resistant bacteria

About 100 years ago, the first antibiotic drug was introduced into health care. Since then, antibiotics have made an outstanding impact on human medicine. However, our society increasingly suffers from collateral damage exerted by these highly effective drugs. The rise of resistant pathogen strains, combined with a reduction of microbiota diversity upon antibiotic treatment, has become a significant obstacle in the fight against invasive infections worldwide.Alternative and complementary strategies to classical "Fleming antibiotics" comprise microbiota-based treatments such as fecal microbiota transfer and administration of probiotics, live-biotherapeutics, prebiotics, and postbiotics. Other promising interventions, whose efficacy may also be influenced by the human microbiota, are phages and vaccines. They will facilitate antimicrobial stewardship, to date the only globally applied antibiotic resistance mitigation strategy.In this review, we present the available evidence on these nontraditional interventions, highlight their interaction with the human microbiota, and discuss their clinical applicability.

Association of the Chronotype Score with Circulating Trimethylamine N-Oxide (TMAO) Concentrations

Individual differences in the chronotype, an attitude that best expresses the individual circadian preference in behavioral and biological rhythms, have been associated with cardiometabolic risk and gut dysbiosis. Up to now, there are no studies evaluating the association between chronotypes and circulating TMAO concentrations, a predictor of cardiometabolic risk and a useful marker of gut dysbiosis. In this study population (147 females and 100 males), subjects with the morning chronotype had the lowest BMI and waist circumference (p < 0.001), and a better metabolic profile compared to the other chronotypes. In addition, the morning chronotype had the highest adherence to the Mediterranean diet (p < 0.001) and the lowest circulating TMAO concentrations (p < 0.001). After adjusting for BMI and adherence to the Mediterranean diet, the correlation between circulating TMAO concentrations and chronotype score was still kept (r = -0.627, p < 0.001). Using a linear regression analysis, higher chronotype scores were mostly associated with lower circulating TMAO concentrations (β = -0.479, t = -12.08, and p < 0.001). Using a restricted cubic spline analysis, we found that a chronotype score ≥59 (p < 0.001, R2 = -0.824) demonstrated a more significant inverse linear relationship with circulating TMAO concentrations compared with knots <59 (neither chronotype) and <41 (evening chronotype). The current study reported the first evidence that higher circulating TMAO concentrations were associated with the evening chronotype that, in turn, is usually linked to an unhealthy lifestyle mostly characterized by low adherence to the MD.