A new generation of functional gene arrays (FGAs; GeoChip 3.0) has been developed, with ∼28 000 probes covering approximately 57 000 gene variants from 292 functional gene families involved in carbon, nitrogen, phosphorus and sulfur cycles, energy metabolism, antibiotic resistance, metal resistance and organic contaminant degradation. GeoChip 3.0 also has several other distinct features, such as a common oligo reference standard (CORS) for data normalization and comparison, a software package for data management and future updating and the gyrB gene for phylogenetic analysis. Computational evaluation of probe specificity indicated that all designed probes would have a high specificity to their corresponding targets. Experimental analysis with synthesized oligonucleotides and genomic DNAs showed that only 0.0036–0.025% false-positive rates were observed, suggesting that the designed probes are highly specific under the experimental conditions examined. In addition, GeoChip 3.0 was applied to analyze soil microbial communities in a multifactor grassland ecosystem in Minnesota, USA, which showed that the structure, composition and potential activity of soil microbial communities significantly changed with the plant species diversity. As expected, GeoChip 3.0 is a high-throughput powerful tool for studying microbial community functional structure, and linking microbial communities to ecosystem processes and functioning.

Criteria for the design of gene-specific and group-specific oligonucleotide probes were established experimentally via an oligonucleotide array that contained perfect match (PM) and mismatch probes (50-mers and 70-mers) based upon four genes. The effects of probe-target identity, continuous stretch, mismatch position, and hybridization free energy on specificity were tested. Little hybridization was observed at a probe-target identity of <85% for both 50-mer and 70-mer probes. PM signal intensities (33 to 48%) were detected at a probe-target identity of 94% for 50-mer oligonucleotides and 43 to 55% for 70-mer probes at a probe-target identity of 96%. When the effects of sequence identity and continuous stretch were considered independently, a stretch probe (>15 bases) contributed an additional 9% of the PM signal intensity compared to a nonstretch probe (<15 bases) at the same identity level. Cross-hybridization increased as the length of continuous stretch increased. A 35-base stretch for 50-mer probes or a 50-base stretch for 70-mer probes had approximately 55% of the PM signal. Little cross-hybridization was observed for probes with a minimal binding free energy greater than ؊30 kcal/mol for 50-mer probes or ؊40 kcal/mol for 70-mer probes. Based on the experimental results, a set of criteria are suggested for the design of gene-specific and group-specific oligonucleotide probes, and the experimentally established criteria should provide valuable information for new software and algorithms for microarray-based studies.Microarrays are one of the most powerful technologies currently available for genomic research (6,7,9,12,17,19,23,28,32,34), and various formats and probe types have been developed. Two types of microarrays, DNA arrays and oligonucleotide arrays, are commonly used (29). Oligonucleotide arrays have increased in use because of several advantages, including better specificity, easy construction, and cost efficiency (21,29). In previous studies that used short oligonucleotide probes, multiple oligonucleotide probe pairs (perfect match and a single-mismatch control) per gene were necessary to detect differential gene expression under different physiological conditions (13, 32). Recent studies indicated that a single 50-mer to 70-mer oligonucleotide per gene could produce comparable hybridization signals obtained with DNA arrays under different experimental conditions (11,26; Z. He et al., unpublished data). However, a recent study that compared three different microarrays for the same gene set resulted in different sets of genes (15). To achieve specific hybridization, the major challenges are to establish probe design criteria and identify optimal probes for each gene or a group of genes in a sequence database (e.g., whole genomes) in a standardized manner.Initially, for 50-mer oligonucleotides, Kane et al. (11) suggested that an oligonucleotide probe showing Ͼ75% identity with nontargets might cause cross-hybridization. Kane et al. (11) also showed that a 50-mer probe, which had a 15-base, 20-base,...

The oligonucleotide specificity for microarray hybridization can be predicted by its sequence identity to non-targets, continuous stretch to non-targets, and/or binding free energy to non-targets. Most currently available programs only use one or two of these criteria, which may choose ‘false’ specific oligonucleotides or miss ‘true’ optimal probes in a considerable proportion. We have developed a software tool, called CommOligo using new algorithms and all three criteria for selection of optimal oligonucleotide probes. A series of filters, including sequence identity, free energy, continuous stretch, GC content, self-annealing, distance to the 3′-untranslated region (3′-UTR) and melting temperature (Tm), are used to check each possible oligonucleotide. A sequence identity is calculated based on gapped global alignments. A traversal algorithm is used to generate alignments for free energy calculation. The optimal Tm interval is determined based on probe candidates that have passed all other filters. Final probes are picked using a combination of user-configurable piece-wise linear functions and an iterative process. The thresholds for identity, stretch and free energy filters are automatically determined from experimental data by an accessory software tool, CommOligo_PE (CommOligo Parameter Estimator). The program was used to design probes for both whole-genome and highly homologous sequence data. CommOligo and CommOligo_PE are freely available to academic users upon request.

BackgroundPseudomonas aeruginosa is an opportunistic pathogen that is the leading cause of iatrogenic infections in critically ill patients, especially those undergoing mechanical ventilation. In this study, we investigated the effects of the universal signaling molecule autoinducer-2 (AI-2) in biofilm formation of P. aeruginosa PAO1.ResultsThe addition of 0.1 nM, 1 nM, and 10 nM exogenous AI-2 to P. aeruginosa PAO1 increased biofilm formation, bacterial viability, and the production of virulence factors. However, compared to the 10 nM AI-2 group, higher concentrations of AI-2 (100 nM and 1 μM) reduced biofilm formation, bacterial viability, and the production of virulence factors. Consistent with the changes in morphology, gene expression analysis revealed that AI-2 up-regulated the expression of quorum sensing-associated genes and genes encoding virulence factors at lower concentrations and down-regulated these genes at higher concentrations.ConclusionsOur study demonstrated that exogenous AI-2 acted in a dose-dependent manner to regulate P. aeruginosa biofilm formation and virulence factors secretion via modulating the expression of quorum sensing-associated genes and may be targeted to treat P. aeruginosa biofilm infections.

Background/Aims: Vagus nerve stimulation (VNS) suppresses arrhythmic activity and minimizes cardiomyocyte injury. However, how VNS affects angiogenesis/arteriogenesis in infarcted hearts, is poorly understood. Methods: Myocardial infarction (MI) was achieved by ligation of the left anterior descending coronary artery (LAD) in rats. 7 days after LAD, stainless-steel wires were looped around the left and right vagal nerve in the neck for vagus nerve stimulation (VNS). The vagal nerve was stimulated with regular pulses of 0.2ms duration at 20 Hz for 10 seconds every minute for 4 hours, and then ACh levels by ELISA in cardiac tissue and serum were evaluated for its release after VNS. Three and 14 days after VNS, Real-time PCR, immunostaining and western blot were respectively used to determine VEGF-A/B expressions and α-SMA- and CD31-postive vessels in VNS-hearts with pretreatment of α7-nAChR blocker mecamylamine (10 mg/kg, ip) or mACh-R blocker atropine (10 mg/kg, ip) for 1 hour. The coronary function and left ventricular performance were analyzed by Langendorff system and hemodynamic parameters in VNS-hearts with pretreatment of VEGF-A/B-knockdown or VEGFR blocker AMG706. Coronary arterial endothelial cells proliferation, migration and tube formation were evaluated for angiogenesis following the stimulation of VNS in coronary arterial smooth muscle cells (VSMCs). Results: VNS has been shown to stimulate VEGF-A and VEGF-B expressions in coronary arterial smooth muscle cells (VSMCs) and endothelial cells (ECs) with an increase of α-SMA- and CD31-postive vessel number in infarcted hearts. The VNS-induced VEGF-A/B expressions and angiogenesis were abolished by m-AChR inhibitor atropine and α7-nAChR blocker mecamylamine in vivo. Interestingly, knockdown of VEGF-A by shRNA mainly reduced VNS-mediated formation of CD31⁺ microvessels. In contrast, knockdown of VEGF-B powerfully abrogated VNS-induced formation of α-SMA⁺ vessels. Consistently, VNS-induced VEGF-A showed a greater effect on EC tube formation as compared to VNS-induced VEGF-B. Moreover, VEGF-A promoted EC proliferation and VSMC migration while VEGF-B induced VSMC proliferation and EC migration in vitro. Mechanistically, vagal neurotransmitter acetylcholine stimulated VEGF-A/B expressions through m/nACh-R/PI3K/Akt/Sp1 pathway in EC. Functionally, VNS improved the coronary function and left ventricular performance. However, blockade of VEGF receptor by antagonist AMG706 or knockdown of VEGF-A or VEGF-B by shRNA significantly diminished the beneficial effects of VNS on ventricular performance. Conclusion: VNS promoted angiogenesis/arteriogenesis to repair the infracted heart through the synergistic effects of VEGF-A and VEGF-B.

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