Elsevier

Journal of Biotechnology

Volume 149, Issue 3, 1 September 2010, Pages 183-190
Journal of Biotechnology

Whole-body systems approaches for gut microbiota-targeted, preventive healthcare

https://doi.org/10.1016/j.jbiotec.2010.02.008Get rights and content

Abstract

Humans are superorganisms with two genomes that dictate phenotype, the genetically inherited human genome (25,000 genes) and the environmentally acquired human microbiome (over 1 million genes). The two genomes must work in harmonious integration as a hologenome to maintain health. Nutrition plays a crucial role in directly modulating our microbiomes and health phenotypes. Poorly balanced diets can turn the gut microbiome from a partner for health to a “pathogen” in chronic diseases, e.g. accumulating evidence supports the new hypothesis that obesity and related metabolic diseases develop because of low-grade, systemic and chronic inflammation induced by diet-disrupted gut microbiota. Due to the tight integration of gut microbiota into human global metabolism, molecular profiling of urine metabolites can provide a new window for reflecting physiological functions of gut microbiomes. Changes of gut microbiota and urine metabolites can thus be employed as new systems approaches for quantitative assessment and monitoring of health at the whole-body level with the advantage of measuring human health based on the results of interactions between the two genomes and the environment rather than just host genomic information. Large-scale population-based studies in conjunction with these whole-body level systems methods will generate pre-disease biomarkers with predictive power, thus making preventive health management of populations with rapidly changing disease spectrums possible through re-engineering of the imbalanced gut microbiomes with specially designed foods/diets.

Section snippets

Preventive healthcare and new health assessment technologies

It seems that most countries on this planet are facing a devastating epidemic of chronic diseases, particularly diet and lifestyle-related disorders such as obesity, diabetes, and cardiovascular diseases (Consultation, 2000). These diseases are characterized by deranged metabolism, which is progressive over a long period of time and which appears to be non-reversible (i.e., patients are affected with a chronic condition.) The endpoint is often death that results from system failure due to

Emergent functions and systems health monitoring

Human bodies are complex biological systems, within which individual cells/tissues/organs integrate and coordinate with each other to achieve the global functions. The most important feature of a complex system is its emergent properties (i.e., “the whole is bigger than the sum of the parts”), and the formation of one emergent property is the result of the integrated functions of many if not all parts of the system. Understanding the structure and function of each part of the body will not

Superorganism concept and gut origin of chronic diseases

Human beings are “Superorganisms” or “Ecosystem man” (Lederberg, 2000). Proportionally, the human body consists of only 10% human cells and the remaining 90% are cells of microbial origin. Thus, there are two genomes within the human body, the human genome, genetically inherited from parents and the human microbiome, acquired from the environment after birth. The human genome and human microbiome work together via enterohepatic circulation and other anatomic and physiological connections to

Metabolic profiling of the urine metabonome for health assessment

The kidney is a key organ for the maintenance of physiological homeostasis by eliminating unwanted metabolites from the body through urine. Hence, urine contains various metabolite species arising from endogenous metabolism, gut microbiota activities and the co-metabolism of both host and microbiome (Nicholson and Wilson, 2003). The biochemical composition of the urine reflects the physiological processes occurring in the superorganism (Nicholson and Wilson, 1989).

The concept of metabonomics

Metagenomic profiling of gut microbiota for health assessment

Evidence is accumulating rapidly that the balance within the gut microbiota is an important determinant for the host health (Guarner and Malagelada, 2003). An imbalance within the gut microbiota is involved in the etiology of diseases not only of the bowel but also other organs. Since the microbial composition in feces is a collection of all symbiotic microorganisms from the gut, fecal samples are used in most studies on the relationship between the gut microbiota composition and disease.

Multivariate statistics for data mining in health assessment

Large amounts of multivariate data are produced in metabonomic and microbiomic studies, thus, multivariate statistical analytical methods must be used to model the data of different sample groups and to identify biomarkers or drug targets from the complex information on the host metabolism and gut microbiota (Nicholson et al., 1999).

Multivariate statistical approaches include unsupervised and supervised methods. Principal Components Analysis (PCA) is an unsupervised method, in which no priori

The future of gut microbiota-targeted analysis in health assessment

As whole-body systems approaches, gut microbiota-targeted analysis (GMTA) can be applied in large-scale epidemiological research to discover pre-disease biomarkers. Urine and feces are two windows to reflect the health status of the human body; the comprehensive and precise profiling of the metabolites and microbes in these samples with metabonomic and metagenomic techniques can be used to characterize and monitor the health status of the whole human body at the molecular level. Analysis and

Conflict of interest

None.

Acknowledgements

The authors would like to acknowledge the support by the National Natural Science Foundation of China Program Grants 30730005 and 20875061; 973 Program Grants 2007CB513002 and 2004CB518600; 863 Program Grant 2008AA02Z315; International Cooperation Program Grants 2007DFC30450 and 075407001, and Chinese Academy of Sciences (Knowledge Innovation Program KSCX1-YW-02).

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