Was the Scanner Calibration Slide used for its intended purpose?

In the article, Scanner calibration revisited, BMC Bioinformatics 2010, 11:361, Dr. Pozhitkov used the Scanner Calibration Slide, a key product of Full Moon BioSystems to generate data in his study of microarray scanner PMT response and proposed a mathematic model for PMT response [1]. In the end, the author concluded that "Full Moon BioSystems calibration slides are inadequate for performing calibration," and recommended "against using these slides." We found these conclusions are seriously flawed and misleading, and his recommendation against using the Scanner Calibration Slide was not properly supported

Scanner calibration revisited

<p>Abstract</p> <p>Background</p> <p>Calibration of a microarray scanner is critical for accurate interpretation of microarray results. Shi et al. (<it>BMC Bioinformatics</it>, 2005, <b>6</b>, Art. No. S11 Suppl. 2.) reported usage of a Full Moon BioSystems slide for calibration. Inspired by the Shi et al. work, we have calibrated microarray scanners in our previous research. We were puzzled however, that most of the signal intensities from a biological sample fell below the sensitivity threshold level determined by the calibration slide. This conundrum led us to re-investigate the quality of calibration provided by the Full Moon BioSystems slide as well as the accuracy of the analysis performed by Shi et al.</p> <p>Methods</p> <p>Signal intensities were recorded on three different microarray scanners at various photomultiplier gain levels using the same calibration slide from Full Moon BioSystems. Data analysis was conducted on raw signal intensities without normalization or transformation of any kind. Weighted least-squares method was used to fit the data.</p> <p>Results</p> <p>We found that initial analysis performed by Shi et al. did not take into account autofluorescence of the Full Moon BioSystems slide, which led to a grossly distorted microarray scanner response. Our analysis revealed that a power-law function, which is explicitly accounting for the slide autofluorescence, perfectly described a relationship between signal intensities and fluorophore quantities.</p> <p>Conclusions</p> <p>Microarray scanners respond in a much less distorted fashion than was reported by Shi et al. Full Moon BioSystems calibration slides are inadequate for performing calibration. We recommend against using these slides.</p

A Revised Design for Microarray Experiments to Account for Experimental Noise and Uncertainty of Probe Response

Background Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance. Results Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other based on 60 mer probes from an Agilent design. To assess experimental variance in probe binding, all probes were replicated ten times. To assess probe performance, the probes were calibrated using a dilution series of target molecules and the signal response was fitted to an adsorption model. We found that significant variance of the signal could be controlled by averaging across probes and removing probes that are nonresponsive or poorly responsive in the calibration experiment. Taking this into account, one can obtain a more reliable signal with the added option of obtaining absolute rather than relative measurements. Conclusion The assessment of technical variance within the experiments, combined with the calibration of probes allows to remove poorly responding probes and yields more reliable signals for the remaining ones. Once an array is properly calibrated, absolute quantification of signals becomes straight forward, alleviating the need for normalization and reference hybridizations

An algorithm for the determination and quantification of components of nucleic acid mixtures based on single sequencing reactions

BACKGROUND: Determination and quantification of nucleic acid components in a mixture is usually accomplished by microarray approaches, where the mixtures are hybridized against specific probes. As an alternative, we propose here that a single sequencing reaction from a mixture of nucleic acids holds enough information to potentially distinguish the different components, provided it is known which components can occur in the mixture. RESULTS: We describe an algorithm that is based on a set of linear equations which can be solved when the sequencing profiles of the individual components are known and when the number of sequenced nucleotides is larger than the number of components in the mixture. We have implemented the procedure for one type of sequencing approach, pyrosequencing, which produces a stepwise output of peaks that is particularly suitable for the procedure. As an example we use signature sequences from ribosomal RNA to distinguish and quantify several different species in a mixture. Using simulations, we show that the procedure may also be applicable for dideoxy sequencing on capillary sequencers, requiring only some instrument specific adaptations of protocols and software. CONCLUSION: The parallel sequencing approach described here may become a simple and cheap alternative to microarray experiments which aim at routine re-determination and quantification of known nucleic acid components from environmental samples or tissue samples

Revision of the nonequilibrium thermal dissociation and stringent washing approaches for identification of mixed nucleic acid targets by microarrays

Microarray experiments typically involve washing steps that remove hybridized nonspecific targets with the purpose of improving the signal-to-noise ratio. The quality of washing ultimately affects downstream analysis of the microarray and interpretation. The paucity of fundamental studies directed towards understanding the dissociation of mixed targets from microarrays makes the development of meaningful washing/dissociation protocols difficult. To fill the void, we examined activation energies and preexponential coefficients of 47 perfect match (PM) and double-mismatch (MM) duplex pairs to discover that there was no statistical difference between the kinetics of the PM and MM duplexes. Based on these findings, we evaluated the nonequilibrium thermal dissociation (NTD) approach, which has been used to identify specific microbial targets in mixed target samples. We found that the major premises for various washing protocols and the NTD approach might be seriously compromised because: (i) nonspecific duplexes do not always dissociate before specific ones, and (ii) the relationship between dissociation rates of the PM and MM duplexes depends on temperature and duplex sequence. Specifically for the NTD, we show that previously suggested use of reference curves, indices of curves and temperature ramps lead to erroneous conclusions

Molecular taxonomy. Bioinformatics and practical evaluation

Summary Molecular taxonomy is a field that studies the diversity of organisms based on molecular markers. This work is devoted to develop a methodology of molecular taxonomy of small organisms. The ribosomal RNA (rRNA) is used as a molecular marker since its nucleotide sequence includes stretches of various levels of conservation, which can be used as species, genus and taxa specific regions. The organisms live in complex communities. To discover the composition of these communities, a hybridization assay employing oligonucleotide microarrays is developed to indicate the presence of a certain rRNA, in a sample under investigation. An additional method based on the pyrosequencing process is proposed here. In this case the mixture of rRNA genes is directly sequenced and the proportion of individual sequences is then calculated from the obtained pyrogram. The work comprises two parts: theoretical bioinformatics and practical evaluation. The first part tackles the problem of DNA-RNA duplex stability prediction. As a result, an ad hoc stability function is proposed. An algorithm and a program are developed for the design of oligonucleotides employed in the microarray approach. The kinetics of DNA-RNA duplex dissociation is considered as well. In addition, the formalism of the pyrosequencing approach is elaborated theoretically. The experimental part deals with the issues of oligonucleotide microarray establishment, including fabrication, immobilization, hybridization and scanning. A real-time kinetic setup for observing the RNA-DNA duplex dissociation was developed. The theoretical findings and quality of the oligonucleotide design are practically evaluated. The theory is found to be in a good accordance with experiment. The pyrosequencing approach is tested as well and is demonstrated to have enough power to discover the composition of a complex mixture of rRNA genes

A new procedure for microarray experiments to account for experimental noise and the uncertainty of probe response

Although microarrays are routine analysis tools in biomedical research, theystill yield noisy output that often requires experimental confirmation. Manystudies have aimed at optimizing probe design and statistical analysis totackle this problem. However, less emphasis has been placed on controlling thenoise inherent to the experimental approach. To address this problem, weinvestigate here a procedure that controls for such experimental variance andcombine it with an assessment of probe performance. Two custom arrays were usedto evaluate the procedure: one based on 25mer probes from an Affymetrix designand the other based on 60mer probes from an Agilent design. To assessexperimental variance, all probes were replicated ten times. To assess probeperformance, the probes were calibrated using a dilution series of targetmolecules and the signal response was fitted to an absorption model. We foundthat significant variance of the signal could be controlled by averaging acrossprobes and removing probes that are nonresponsive. Thus, a more reliable signalcould be obtained using our procedure than conventional approaches. We suggestthat once an array is properly calibrated, absolute quantification of signalsbecomes straight forward, alleviating the need for normalization and referencehybridizations.<br

Beyond Affymetrix Arrays: Expanding the Set of Known Hybridization Isotherms and Observing Pre-Wash Signal Intensities

Microarray hybridization studies have attributed the nonlinearity of hybridization isotherms to probe saturation and post-hybridization washing. Both processes are thought to distort \u27true\u27 target abundance because immobilized probes are saturated with excess target and stringent washing removes loosely bound targets. Yet the paucity of studies aimed at understanding hybridization and dissociation makes it difficult to align physicochemical theory to microarray results. To fill the void, we first examined hybridization isotherms generated on different microarray platforms using a ribosomal RNA target and then investigated hybridization signals at equilibrium and after stringent wash. Hybridization signal at equilibrium was achieved by treating the microarray with isopropanol, which prevents nucleic acids from dissolving into solution. Our results suggest that (i) the shape of hybridization isotherms varied by microarray platform with some being hyperbolic or linear, and others following a power-law; (ii) at equilibrium, fluorescent signal of different probes hybridized to the same target were not similar even with excess of target and (iii) the amount of target removed by stringent washing depended upon the hybridization time, the probe sequence and the presence/absence of nonspecific targets. Possible physicochemical interpretations of the results and future studies are discussed

Datasets used to discover the microbial signatures of oral dysbiosis, periodontitis and edentulism in humans

AbstractThis article provides supporting data for the research article ‘Microbial Signatures of Oral Dysbiosis, Periodontitis and Edentulism Revealed by Gene Meter Methodology’ (M.C. Hunter, A.E. Pozhitkov, P.A. Noble, 2016) [1]. In that article, we determined the microbial abundance signatures for patient with periodontics, edentulism, or health using Gene Meter Technology. Here we provide the data used to make the DNA microarray and the resulting microbial abundance data that was determined using the calibrated probes and the 16S rRNA genes harvested from patients. The first data matrix contains two columns: one is the GenInfo Identifier (GI) numbers of the 16S rRNA gene sequences and the other is the corresponding oral bacterial taxonomy. The probes were then screened for redundancy and if they were found to be unique, they were synthesized onto the surface of the DNA microarrays. The second data matrix consists of the abundances of the 576 16S rRNA genes that was determined using the median value of all individual calibrated probes targeting each gene. The data matrix consists of 16 columns and 576 rows, with the columns representing the 16 patients and the rows representing 576 different oral microorganisms. The third data matrix consists of the abundances of 567 16S rRNA genes determined using the calibrated abundance of all aggregated probes targeting the same 16S rRNA gene. The data matrix of the aggregated probes consists of 16 samples and 567 rows