Human gut microbiota: repertoire and variations

Abstract

The composition of human gut microbiota and their relationship with the host and, consequently, with human health and disease, presents several challenges to microbiologists. Originally dominated by culture-dependent methods for exploring this ecosystem, the advent of molecular tools has revolutionized our ability to investigate these relationships. However, many biases that have led to contradictory results have been identified. Microbial culturomics, a recent concept based on a use of several culture conditions with identification by MALDI-TOF followed by the genome sequencing of the new species cultured had allowed a complementarity with metagenomics. Culturomics allowed to isolate 31 new bacterial species, the largest human virus, the largest bacteria, and the largest Archaea from human. Moreover, some members of this ecosystem, such as Eukaryotes, giant viruses, Archaea, and Planctomycetes, have been neglected by the majority of studies. In addition, numerous factors, such as age, geographic provenance, dietary habits, antibiotics, or probiotics, can influence the composition of the microbiota. Finally, in addition to the countless biases associated with the study techniques, a considerable limitation to the interpretation of studies of human gut microbiota is associated with funding sources and transparency disclosures. In the future, studies independent of food industry funding and using complementary methods from a broad range of both culture-based and molecular tools will increase our knowledge of the repertoire of this complex ecosystem and host-microbiota mutualism.

Keywords: antibiotics; archaea; culturomics; gut microbiota; metagenomics; transparency disclosures.

Figure 1

Using the key words “human gut microbiota” or “human fecal flora” and using the ISI Web of Knowledge database, (A) shows citations in each year regarding this subject, and (B) shows the number of published items each year, both between 1993 and 2011.

Figure 2

A comparison of Gram staining, electron microscopy, and pyrosequencing to determine the proportion of Gram-positive/Gram-negative bacteria in the same stool sample (personal data).

Figure 3

The statistical detection thresholds of metagenomic methods. The statistical detection thresholds of metagenomic methods are correlated with the number of bacteria in the ecosystem studied by the number of sequences generated.

Figure 4

A non-exhaustive representation of different bacterial phyla found in culture (outer star in blue) or phyla with no representative in culture (inner star in gray). Gram-positive bacteria are colored in green, and Gram-negative bacteria are colored in white. Bacteria with an atypical cell wall (triple-layered structure of Mycobacterium) or without a cell wall (Tenericutes) have abnormal Gram staining and are shown in pink. The purple triangle represents the absence of lipopolysaccharide in the outer membrane of Gram-negative bacteria. The red square symbolizes phyla that do not have a peptidoglycan structure.

Figure 5

A non exhaustive overview of human gut microorganisms among bacterial, Archaea, viral, and Eukaryota domains.

Figure 6

The influence of external factors determining the composition of the human gut microbiota.