Applications of functional gene microarrays for profiling microbial communities

Functional gene arrays (FGAs) have been considered as a specific, sensitive, quantitative, and high throughput metagenomic tool to detect, monitor and characterize microbial communities. Especially GeoChips, the most comprehensive FGAs have been applied to analyze the functional diversity, composition, structure, and metabolic potential or activity of a variety of microbial communities from different habitats, such as aquatic ecosystems, soils, contaminated sites, extreme environments, and bioreactors. FGAs are able to address fundamental questions related to global change, bioremediation, land use, human health, and ecological theories, and link the microbial community structure to environmental properties and ecosystem functioning. This review focuses on applications of FGA technology for profiling microbial communities, including target preparation, hybridization and data processing, and data analysis. We also discuss challenges and future directions of FGA applications.     

Sediment denitrifier community composition and nirS gene expression investigated with functional gene microarrays

A functional gene microarray was used to investigate denitrifier community composition and nitrite reductase (nirS) gene expression in sediments along the estuarine gradient in Chesapeake Bay, USA. The nirS oligonucleotide probe set was designed to represent a sequence database containing 539 Chesapeake Bay clones, as well as sequences from many other environments. Greatest nirS diversity was detected at the freshwater station at the head of the bay and least diversity at the higher salinity station near the mouth of the Bay. The most common OTUs from the sequence database were detected on the array with high signal strength in most samples. One of the most abundant OTUs, CB2-S-138, was identified as dominant at the mid-bay site by both microarray and quantitative PCR assays, but it comprised a much smaller fraction of the assemblage in the north and south bay samples. cDNA (transcribed from total RNA extracts) targets were hybridized to the same array to compare the profiles of community composition at the DNA (relative abundance) and mRNA (gene expression) levels. Only the three dominant denitrifying groups (in terms of relative strength of DNA hybridization signal) were detected at the mRNA level. These results suggest that the most actively denitrifying groups are responsible for most nirS expression as well.     

Design of long oligonucleotide probes for functional gene detection in a microbial community

MOTIVATION: Analysis of the functions of microorganisms and their dynamics in the environment is essential for understanding microbial ecology. For analysis of highly similar sequences of a functional gene family using microarrays, the previous long oligonucleotide probe design strategies have not been useful in generating probes. RESULTS: We developed a Hierarchical Probe Design (HPD) program that designs both sequence-specific probes and hierarchical cluster-specific probes from sequences of a conserved functional gene based on the clustering tree of the genes, specifically for analyses of functional gene diversity in environmental samples. HPD was tested on datasets for the nirS and pmoA genes. Our results showed that HPD generated more sequence-specific probes than several popular oligonucleotide design programs. With a combination of sequence-specific and cluster-specific probes, HPD generated a probe set covering all the sequences of each test set. AVAILABILITY: http://brcapp.kribb.re.kr/HPD/     

VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

Background  

All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance.     

Genome analysis with gene expression microarrays

Advances in biochemistry, chemistry and engineering have enabled the development of a new gene expression assay. This ‘chip-based’ approach utilizes microscopic arrays of cDNAs printed on glass as high-density hybridization targets. Fluorescent probe mixtures derived from total cellular messenger RNA (mRNA) hybridize to cognate elements on the array, allowing accurate measurement of the expression of the corresponding genes. Array densities of >1,000 cDNAs per cm² enable quantitative expression monitoring of a large number of genes in a single hybridization. A two-color fluorescence detection scheme allows rapid and simultaneous differential expression analysis of independent biological samples. Mass-produced microarrays provide a new tool for genome expression analysis that may revolutionize genetic dissection, drug discovery and human disease diagnostics.     

VennMaster: Area-proportional Euler diagrams for functional GO analysis of microarrays

Background  

Microarray experiments generate vast amounts of data. The functional context of differentially expressed genes can be assessed by querying the Gene Ontology (GO) database via GoMiner. Directed acyclic graph representations, which are used to depict GO categories enriched with differentially expressed genes, are difficult to interpret and, depending on the particular analysis, may not be well suited for formulating new hypotheses. Additional graphical methods are therefore needed to augment the GO graphical representation.     

Microarrays for bacterial detection and microbial community analysis

Several types of microarrays have recently been developed and evaluated for bacterial detection and microbial community analysis. These studies demonstrated that specific, sensitive and quantitative detection could be obtained with both functional gene arrays and community genome arrays. Although single-base mismatch can be differentiated with phylogenetic oligonucleotide arrays, reliable specific detection at the single-base level is still problematic. Microarray-based hybridization approaches are also useful for defining genome diversity and bacterial relatedness. However, more rigorous and systematic assessment and development are needed to realize the full potential of microarrays for microbial detection and community analysis.     

土壤微生物生态过程与微生物功能基因多样性

土壤微生物在陆地生态系统中具有重要的生态功能,包括参与地球化学物质循环、污染物降解、环境剧烈变化的缓冲等.土壤微生物的生态功能与土壤功能联系密切,微生物群落结构与组成变化会直接影响土壤功能的发挥.土壤微生物通过具有生物活性的酶参与一系列的代谢活动,编码酶的功能基因成为微生物功能标记物.近10年中,以功能基因多样性为核心的分子生态学研究迅速发展,为从功能基因角度了解土壤微生物的生态功能提供了一个新的切入点.本文综述了与土壤微生物生态功能相关的功能基因多样性研究进展,并对该领域的发展前景提出展望.     

Molecular and functional analysis using live cell microarrays

Understanding cellular behavior in both healthy and diseased states requires the ability to molecularly delineate the characteristics of individual cells from complex mixtures. The recent development of cellular microarrays allows such an undertaking. By immobilizing different cell capture and analysis reagents on a solid support, mixtures of cells can be rapidly interrogated for their composition and phenotype. Thus, one can identify and quantitate distinct cell types based on the expression of particular cell surface molecules, as well as analyze their response to defined signals through the secretion of specific factors or other measurable cellular activities. This review focuses on the use of cellular microarrays to detect antigen-specific T cells and their responsiveness, analyze cancer cell types and behavior and to investigate the control of stem cell differentiation.     

Transfected cell microarrays: an efficient tool for high-throughput functional analysis

Transfected cell microarrays are considered to be a breakthrough methodology for high-throughput and high-content functional genomics. Here, recent advances in the cell microarray field are reviewed, along with its potential to increase the speed of determining gene function. These advances, combined with an increasing number and diversity of gene perturbing systems, such as RNAi and ectopic gene expression, provide tools for expanding our understanding of biology at the systems level.     

Improvement of oligonucleotide probe design criteria for functional gene microarrays in environmental applications

To optimize oligonucleotide probe design criteria, PCR products with different similarities to probes were hybridized to a functional gene microarray designed to detect homologous genes from different organisms. In contrast to more restrictive probe designs based on a single criterion, simultaneous consideration of the percent similarity (< or =90%), the length of identical sequence stretches (< or =20 bases), and the binding free energy (> or =-35 kcal mol(-1)) was found to be predictive of probe specificity.     

Monitoring gene expression in mixed microbial communities by using DNA microarrays

A DNA microarray to monitor the expression of bacterial metabolic genes within mixed microbial communities was designed and tested. Total RNA was extracted from pure and mixed cultures containing the 2,4-dichlorophenoxyacetic acid (2,4-D)-degrading bacterium Ralstonia eutropha JMP134, and the inducing agent 2,4-D. Induction of the 2,4-D catabolic genes present in this organism was readily detected 4, 7, and 24 h after the addition of 2,4-D. This strain was diluted into a constructed mixed microbial community derived from a laboratory scale sequencing batch reactor. Induction of two of five 2,4-D catabolic genes (tfdA and tfdC) from populations of JMP134 as low as 10(5) cells/ml was clearly detected against a background of 10(8) cells/ml. Induction of two others (tfdB and tfdE) was detected from populations of 10(6) cells/ml in the same background; however, the last gene, tfdF, showed no significant induction due to high variability. In another experiment, the induction of resin acid degradative genes was statistically detectable in sludge-fed pulp mill effluent exposed to dehydroabietic acid in batch experiments. We conclude that microarrays will be useful tools for the detection of bacterial gene expression in wastewaters and other complex systems.     

Transfected cell microarrays: an efficient tool for high-throughput functional analysis

Transfected cell microarrays are considered to be a breakthrough methodology for high-throughput and high-content functional genomics. Here, recent advances in the cell microarray field are reviewed, along with its potential to increase the speed of determining gene function. These advances, combined with an increasing number and diversity of gene perturbing systems, such as RNAi and ectopic gene expression, provide tools for expanding our understanding of biology at the systems level.     

Illumina-based analysis of microbial community diversity

Microbes commonly exist in milieus of varying complexity and diversity. Although cultivation-based techniques have been unable to accurately capture the true diversity within microbial communities, these deficiencies have been overcome by applying molecular approaches that target the universally conserved 16S ribosomal RNA gene. The recent application of 454 pyrosequencing to simultaneously sequence thousands of 16S rDNA sequences (pyrotags) has revolutionized the characterization of complex microbial communities. To date, studies based on 454 pyrotags have dominated the field, but sequencing platforms that generate many more sequence reads at much lower costs have been developed. Here, we use the Illumina sequencing platform to design a strategy for 16S amplicon analysis (iTags), and assess its generality, practicality and potential complications. We fabricated and sequenced paired-end libraries of amplified hyper-variable 16S rDNA fragments from sets of samples that varied in their contents, ranging from a single bacterium to highly complex communities. We adopted an approach that allowed us to evaluate several potential sources of errors, including sequencing artifacts, amplification biases, non-corresponding paired-end reads and mistakes in taxonomic classification. By considering each source of error, we delineate ways to make biologically relevant and robust conclusions from the millions of sequencing reads that can be readily generated by this technology.     

Molecular community analysis of microbial diversity

New technologies that avoid the need for either gene amplification (e.g. microarrays) or nucleic acid extraction (e.g. in situ PCR) have recently been implemented in microbial ecology. Together with new approaches for culturing microorganisms and an increased understanding of the biases of molecular methods, these techniques form the most exciting advances in this field during the past year.     

Biosynthetic approach for functional protein microarrays

Protein microarrays have emerged as an indispensable research tool for providing information about protein functions and interactions through high-throughput screening. Traditional methods for immobilizing biomolecules onto solid surfaces have been based on covalent and noncovalent binding, entrapment in semipermeable membranes, microencapsulation, sol gel, and hydrogel methods. Each of these techniques has its own strengths but fails to combine the most important tenets of a functional protein microarray such as covalent attachment, native protein conformation, homogeneity of the protein monolayer, control over active site orientation, and retention of protein activity. Here we present a selective and site-directed covalent immobilization technique for proteins via a benzoxazine ring formation through a Diels-Alder reaction in water and a genetically encoded 3-amino-L-tyrosine (3-NH(2)Tyr) amino acid. Fully functional protein microarrays, with monolayer arrangements and complete control over their orientations, were generated using this strategy.