Introduction
The human microbiome, or human microbiota is the aggregate of microorganisms, a microbiome that resides on the surface and in deep layers of skin, in the saliva and oral mucosa, in the conjunctiva, and in the gastrointestinal tracts. They include bacteria, fungi, and archaea. Some of these organisms perform tasks that are useful for the human host. However, the majority have been too poorly researched for us to understand the role they play. Most of the microbes associated with humans appear to be not harmful at all, but rather assist in maintaining processes necessary for a healthy body.
The total microbial cells found in association with humans may exceed the total number of cells making up the human body by a factor of ten-to-one. The total number of genes associated with the human microbiome could exceed the total number of human genes by a factor of 100-to-one. In 2008, the Human Microbiome Project (HMP) was lunched with the goal of identifying and characterizing the microorganisms which are found in association with both healthy and diseased humans (the Human microbiome). Important components of the Human Microbiome Project will be culture-independent methods of microbial community characterization using metagenomics approaches, which focus on sequencing metagenomes from five body sites: skin, vaginal, gut, and nasal/lung. The HMP also performs deep sequencing of bacterial 16S rRNA gene sequences to understand the phylogenetic diversity and microbial community composition from human subjects. In addition, the HMP extensively sequences whole genomes for isolated strains/species, which serve as reference genomic sequences with 3,000 such sequences of individual bacterial isolates currently planned. Those references are very useful for metagenome sequence analysis.
Although such tremendous amounts of sequences available are available, this is only the first step to understand the diversity, composition, structure, function and dynamics of the human microbiome. More important is to develop subsequent technologies to use such sequence information to address biological questions related to human health. Development of high throughput microarray-based metagenomic technologies for detecting microbial strains/populations and their mediated functional processes in human microbiota should be one of the next logical steps of the HMP. Therefore, we have developed human microbiome chips (HuMiChip) for identifying microbial strains/species, characterizing metabolic functions, and linking the human microbiome structure with human health and disease.
HuMiChip as a Solution
Generally, HuMiChip technology is similar to GeoChip technology, and it aims to: (i) identify microbial strains/species with sequenced genomes; (ii) be specific, sensitive, and quantitative detection of microbial functional genes; and (iii) link the human microbiome with human health and disease.
HuMiChip was able to specifically profile functional gene families, validated by next generation sequencing technologies (Tu et al., 2013, submitted). HuMiChip is expected to specifically identify microbial strains/species (in test). Please see GeoChip Technology for details.
HuMiChip was able to detect gene families at as low as 0.001% relative abundance (Tu et al., 2013, submitted).
Similar to the GeoChip technology, HuMiChip can be used to quantitatively analyze human microbiomes.
Another important issue is whether GeoChip can provide quantitative information. We have demonstrated that linear relationships were observed between target DNA or RNA concentrations and hybridization signal intensity using pure culture, mixed culture, and environmental samples without amplification (Rhee et al., 2004; Wu et al., 2001; Wu et al., 2006). With the WCGA approach, robust quantitative detection was observed by significant linear relationships between signal intensity and initial DNA concentrations or cell numbers (Wu et al. 2006) (Figure 3 ). These studies demonstrate that GeoChip can be used to quantitatively analyze environmental samples.
Another important issue is whether GeoChip can provide quantitative information. We have demonstrated that linear relationships were observed between target DNA or RNA concentrations and hybridization signal intensity using pure culture, mixed culture, and environmental samples without amplification (Rhee et al., 2004; Wu et al., 2001; Wu et al., 2006). With the WCGA approach, robust quantitative detection was observed by significant linear relationships between signal intensity and initial DNA concentrations or cell numbers (Wu et al. 2006) (Figure 3 ). These studies demonstrate that GeoChip can be used to quantitatively analyze environmental samples.
History & Legacy
A functional gene-based microarray for profiling human microbiomes (HuMiChip) was developed with 36,802 probes targeting 50,007 protein coding sequences for 139 key functional gene families involved the metabolism of amino acids, carbohydrates, glycans, lipids, nucleotides, cofactors and vitamins, energy, and terpenoids and polyketides, glycan biosynthesis and translation. The results indicate that the developed HuMiChip is a useful and effective tool for functional profiling of human microbiomes. HuMiChip 1.0 was a subset of GeoChip 4.0, and developed on a NimbleGen 12x135K array platform that each chip contains 12 arrays (Tu et al., 2013, submitted).
HuMiChip 2.0 is the current version in use, and contains three types of probes: (i) 30,396 strain-/species-specific probes for 2,063 sequenced genomes with up to 15 probes for each genome; (ii) 83,518 functional gene probes for sequenced genomes targeting 423,898 protein coding sequences for 139 key functional gene families involved the metabolism of amino acids, carbohydrates, glycans, lipids, nucleotides, cofactors and vitamins, energy, and terpenoids and polyketides, glycan biosynthesis and translation; and (iii) 36,449 functional gene probes for representative metagenomes 56,253 protein coding sequences for 139 key functional gene families, and other important functional processes in the human micorbiome. HuMiChip 2.0 is a separate array and developed on the Agilent platform with a 180 K x 4 (4 arrays on each slide with 180 K probes for each array) format.
Recent Studies
Pharmaceutical wastewater systems
2013
Antarctic Dry Valley Functional Ecology
2013
Landfill leachate-contaminated aquifer
2013