Physico-chemical foundations underpinning microarray and next-generation sequencing experiments

Unraveling the Enigma of Organismal Death: Insights, Implications, and Unexplored Frontiers

Significant knowledge gaps exist regarding the responses of cells, tissues, and organs to organismal death. Examining the survival mechanisms influenced by metabolism and environment, this research has the potential to transform regenerative medicine, redefine legal death, and provide insights into life's physiological limits, paralleling inquiries in embryogenesis.

Engineering a Rigid Nucleic Acid Structure to Improve the Limit of Detection for Genetic Assays

Detecting nucleic acids at ultralow concentrations is critical for research and clinical applications. Particle-based assays are commonly used to detect nucleic acids. However, DNA hybridization on particle surfaces is inefficient due to the instability of tethered sequences, which negatively influences the assay's detection sensitivity. Here, we report a method to stabilize sequences on particle surfaces using a double-stranded linker at the 5' end of the tethered sequence. We termed this method Rigid Double Stranded Genomic Linkers for Improved DNA Analysis (RIGID-DNA). Our method led to a 3- and 100-fold improvement of the assays' clinical and analytical sensitivity, respectively. Our approach can enhance the hybridization efficiency of particle-based assays without altering existing assay workflows. This approach can be adapted to other platforms and surfaces to enhance the detection sensitivity.

How Surfaces Affect Hybridization Kinetics

Hybridization between nucleic acid strands immobilized on a solid support with partners in solution is widely practiced in bioanalytical technologies and materials science. An important fundamental aspect of understanding these reactions is the role played by immobilization in the dynamics of duplex formation and disassembly. This report reviews and analyzes literature kinetic data to identify commonly observed trends and to correlate them with probable molecular mechanisms. The analysis reveals that while under certain conditions impacts from immobilization are minimal so that surface and solution hybridization kinetics are comparable, it is more typical to observe pronounced offsets between the two scenarios. In the forward (hybridization) direction, rates at the surface commonly decrease by one to two decades relative to solution, while in the reverse direction rates of strand separation at the surface can exceed those in solution by tens of decades. By recasting the deviations in terms of activation barriers, a consensus of how immobilization impacts nucleation, zipping, and strand separation can be conceived within the classical mechanism in which duplex formation is rate limited by preassembly of a nucleus a few base pairs in length, while dehybridization requires the cumulative breakup of base pairs along the length of a duplex. Evidence is considered for how excess interactions encountered on solid supports impact these processes.

Enhancing the Performance of DNA Surface-Hybridization Biosensors through Target Depletion

DNA surface-hybridization biosensors utilize the selective hybridization of target sequences in solution to surface-immobilized probes. In this process, the target is usually assumed to be in excess, so that its concentration does not significantly vary while hybridizing to the surface-bound probes. If the target is initially at low concentrations and/or if the number of probes is very large, and they have high affinity for the target, the DNA in solution may become depleted. In this paper we analyze the equilibrium and kinetics of hybridization of DNA biosensors in the case of strong target depletion, by extending the Langmuir adsorption model. We focus, in particular, on the detection of a small amount of a single-nucleotide "mutant" sequence (concentration c₂) in a solution, which differs by one or more nucleotides from an abundant "wild-type" sequence (concentration c₁ ≫ c₂). We show that depletion can give rise to a strongly enhanced sensitivity of the biosensors. Using representative values of rate constants and hybridization free energies, we find that in the depletion regime one could detect relative concentrations c₂/c₁ that are up to 3 orders of magnitude smaller than in the conventional approach. The kinetics is surprisingly rich and exhibits a nonmonotonic adsorption with no counterpart in the no-depletion case. Finally, we show that, alongside enhanced detection sensitivity, this approach offers the possibility of sample enrichment, by substantially increasing the relative amount of the mutant over the wild-type sequence.

ImtRDB: a database and software for mitochondrial imperfect interspersed repeats annotation

BACKGROUND

Mitochondria is a powerhouse of all eukaryotic cells that have its own circular DNA (mtDNA) encoding various RNAs and proteins. Somatic perturbations of mtDNA are accumulating with age thus it is of great importance to uncover the main sources of mtDNA instability. Recent analyses demonstrated that somatic mtDNA deletions depend on imperfect repeats of various nature between distant mtDNA segments. However, till now there are no comprehensive databases annotating all types of imperfect repeats in numerous species with sequenced complete mitochondrial genome as well as there are no algorithms capable to call all types of imperfect repeats in circular mtDNA.

RESULTS

We implemented naïve algorithm of pattern recognition by analogy to standard dot-plot construction procedures allowing us to find both perfect and imperfect repeats of four main types: direct, inverted, mirror and complementary. Our algorithm is adapted to specific characteristics of mtDNA such as circularity and an excess of short repeats - it calls imperfect repeats starting from the length of 10 b.p. We constructed interactive web available database ImtRDB depositing perfect and imperfect repeats positions in mtDNAs of more than 3500 Vertebrate species. Additional tools, such as visualization of repeats within a genome, comparison of repeat densities among different genomes and a possibility to download all results make this database useful for many biologists. Our first analyses of the database demonstrated that mtDNA imperfect repeats (i) are usually short; (ii) associated with unfolded DNA structures; (iii) four types of repeats positively correlate with each other forming two equivalent pairs: direct and mirror versus inverted and complementary, with identical nucleotide content and similar distribution between species; (iv) abundance of repeats is negatively associated with GC content; (v) dinucleotides GC versus CG are overrepresented on light chain of mtDNA covered by repeats.

CONCLUSIONS

ImtRDB is available at http://bioinfodbs.kantiana.ru/ImtRDB/ . It is accompanied by the software calling all types of interspersed repeats with different level of degeneracy in circular DNA. This database and software can become a very useful tool in various areas of mitochondrial and chloroplast DNA research.

Comparison of statistical methods and the use of quality control samples for batch effect correction in human transcriptome data

Batch effects are technical sources of variation introduced by the necessity of conducting gene expression analyses on different dates due to the large number of biological samples in population-based studies. The aim of this study is to evaluate the performances of linear mixed models (LMM) and Combat in batch effect removal. We also assessed the utility of adding quality control samples in the study design as technical replicates. In order to do so, we simulated gene expression data by adding “treatment” and batch effects to a real gene expression dataset. The performances of LMM and Combat, with and without quality control samples, are assessed in terms of sensitivity and specificity while correcting for the batch effect using a wide range of effect sizes, statistical noise, sample sizes and level of balanced/unbalanced designs. The simulations showed small differences among LMM and Combat. LMM identifies stronger relationships between big effect sizes and gene expression than Combat, while Combat identifies in general more true and false positives than LMM. However, these small differences can still be relevant depending on the research goal. When any of these methods are applied, quality control samples did not reduce the batch effect, showing no added value for including them in the study design.

Two-dimensional Ising model for microarray hybridization: cooperative interactions between bound target molecules

The Langmuir adsorption model is widely used for description and quantification of microarray oligo-target hybridization. According to the model, the binding centers for adsorption of target molecules from solution are represented by oligo-probes. However, the Langmuir model does not consider the interactions between the targets adsorbed at the neighboring binding centers, which are possible due to high-density of array-bound probes. We have shown that the two-dimensional Ising model, which takes into account the nearest neighboring target molecules interactions, better describes the experimental data of oligo-target hybridization in comparison with the Langmuir model. Thus, we found an evidence for existence of positive cooperative interactions between adsorbed target molecules: so, binding of the first target molecules facilitates the binding of subsequent ones to the neighboring probes. Communicated by Ramaswamy H. Sarma.

VSITA, an Improved Approach of Target Amplification in the Identification of Viral Pathogens

OBJECTIVE

Unbiased next generation sequencing (NGS) is susceptible to interference from host or environmental sequences. Consequently, background depletion and virome enrichment techniques are usually needed for clinical samples where viral load is much lower than background sequences.

METHODS

A viral Sequence Independent Targeted Amplification (VSITA) approach using a set of non-ribosomal and virus-enriched octamers (V8) was developed and compared with traditionally used random hexamers (N6). Forty-five archived clinical samples of different types were used in parallel to compare the V8 and N6 enrichment performance of viral sequences and removal performance of ribosomal sequences in the step of reverse transcription followed by quantitative PCR (qPCR). Ten sera samples from patients with fever of unknown origin and 10 feces samples from patients with diarrhea of unknown origin were used in comparison of V8 and N6 enrichment performance following NGS analysis.

RESULTS

A minimum 30 hexamers matching to viral reference sequences (sense and antisense) were selected from a dataset of random 4,096 (46) hexamers (N6). Two random nucleotides were added to the 5' end of the selected hexamers, and 480 (30 × 42) octamers (V8) were obtained. In general, VSITA approach showed higher enrichment of virus-targeted cDNA and enhanced ability to remove unwanted ribosomal sequences in the majorities of 45 predefined clinical samples. Moreover, VSITA combined with NGS enabled to detect not only more viruses but also achieve more viral reads hit and higher viral genome coverage in 20 clinical samples with diarrhea or fever of unknown origin.

CONCLUSION

The VSITA approach designed in this study is demonstrated to possess higher sensitivity and broader genome coverage than traditionally used random hexamers in the NGS-based identification of viral pathogens directly from clinical samples.

Linear Chain Formation of Split-Aptamer Dimers on Surfaces Triggered by Adenosine

The detection of small molecules impacts various fields; however, their small size and low concentration are usually the cause of limitations in their detection. Thus, the need for biosensors with appropriate probes and signal amplification strategies is required. Aptamers are appropriate probes selected specifically against small targets such as adenosine. The possibility to split aptamers in parts led to original amplification strategies based on sandwich assays. By combining the self-assembling of oligonucleotide dimers with split-aptamer dangling ends and a surface plasmon resonance imaging technique, we developed an original amplification approach based on linear chain formation in the presence of the adenosine target. In this article, on the basis of sequence engineering, we analyzed its performance and the effect of the probe grafting density on the length of the chains formed at the surface of the biosensor.

Gene Meter: Accurate abundance calculations of gene expression

We previously reported that thousands of transcripts in the mouse and zebrafish significantly increased in abundance in a time series spanning from life to several days after death. Transcript abundances were determined by: calibrating each microarray probe using a dilution series of pooled RNAs, fitting the probe-responses to adsorption models, and back-calculating abundances using the probe signal intensity of a sample and the best fitting model. The accuracy of the abundance measurements was not assessed in our previous study because individual transcript concentrations in the calibration pool were not known. Accurate transcript abundances are highly desired for modeling the dynamics of biological systems and investigating how systems respond to perturbations. In this study, we show that accurate transcript abundances can be determined by calibrating the probes using a calibration pool of transcripts with known concentrations. Instructions for determining accurate transcript abundances using the Gene Meter approach are provided.

Gene expression in the twilight of death: The increase of thousands of transcripts has implications to transplantation, cancer, and forensic research

After a vertebrate dies, many of its organ systems, tissues, and cells remain functional while its body no longer works as a whole. We define this state as the "twilight of death" - the transition from a living body to a decomposed corpse. We claim that the study of the twilight of death is important to ethical, legal and medical science. We examined gene expression at the twilight of death in the zebrafish and mouse reaching the conclusion that apparently thousands of transcripts significantly increase in abundance from life to several hours/days postmortem relative to live controls. Transcript dynamics of different genes provided "proof-of-principle" that models accurately predict an individual's elapsed-time-of-death (i.e. postmortem interval). While many transcripts were associated with survival and stress compensation, others were associated with epigenetic factors, developmental control, and cancer. Future studies are needed to determine whether the high incidence of cancer in transplant recipients is due to the postmortem processes in donor organs.

Array Analysis Manager-An automated DNA microarray analysis tool simplifying microarray data filtering, bias recognition, normalization, and expression analysis

Desoxyribonucleic acid (DNA) microarray experiments generate big datasets. To successfully harness the potential information within, multiple filtering, normalization, and analysis methods need to be applied. An in-depth knowledge of underlying physical, chemical, and statistical processes is crucial to the success of this analysis. However, due to the interdisciplinarity of DNA microarray applications and experimenter backgrounds, the published analyses differ greatly, for example, in methodology. This severely limits the comprehensibility and comparability among studies and research fields. In this work, we present a novel end-user software, developed to automatically filter, normalize, and analyze two-channel microarray experiment data. It enables the user to analyze single chip, dye-swap, and loop experiments with an extended dynamic intensity range using a multiscan approach. Furthermore, to our knowledge, this is the first analysis software solution, that can account for photobleaching, automatically detected by an artificial neural network. The user gets feedback on the effectiveness of each applied normalization regarding bias minimization. Standardized methods for expression analysis are included as well as the possibility to export the results in the Gene Expression Omnibus (GEO) format. This software was designed to simplify the microarray analysis process and help the experimenter to make educated decisions about the analysis process to contribute to reproducibility and comparability.

Thermodynamic framework to assess low abundance DNA mutation detection by hybridization

The knowledge of genomic DNA variations in patient samples has a high and increasing value for human diagnostics in its broadest sense. Although many methods and sensors to detect or quantify these variations are available or under development, the number of underlying physico-chemical detection principles is limited. One of these principles is the hybridization of sample target DNA versus nucleic acid probes. We introduce a novel thermodynamics approach and develop a framework to exploit the specific detection capabilities of nucleic acid hybridization, using generic principles applicable to any platform. As a case study, we detect point mutations in the KRAS oncogene on a microarray platform. For the given platform and hybridization conditions, we demonstrate the multiplex detection capability of hybridization and assess the detection limit using thermodynamic considerations; DNA containing point mutations in a background of wild type sequences can be identified down to at least 1% relative concentration. In order to show the clinical relevance, the detection capabilities are confirmed on challenging formalin-fixed paraffin-embedded clinical tumor samples. This enzyme-free detection framework contains the accuracy and efficiency to screen for hundreds of mutations in a single run with many potential applications in molecular diagnostics and the field of personalised medicine.

Hamming Distance as a Concept in DNA Molecular Recognition

DNA microarrays constitute an in vitro example system of a highly crowded molecular recognition environment. Although they are widely applied in many biological applications, some of the basic mechanisms of the hybridization processes of DNA remain poorly understood. On a microarray, cross-hybridization arises from similarities of sequences that may introduce errors during the transmission of information. Experimentally, we determine an appropriate distance, called minimum Hamming distance, in which the sequences of a set differ. By applying an algorithm based on a graph-theoretical method, we find large orthogonal sets of sequences that are sufficiently different not to exhibit any cross-hybridization. To create such a set, we first derive an analytical solution for the number of sequences that include at least four guanines in a row for a given sequence length and eliminate them from the list of candidate sequences. We experimentally confirm the orthogonality of the largest possible set with a size of 23 for the length of 7. We anticipate our work to be a starting point toward the study of signal propagation in highly competitive environments, besides its obvious application in DNA high throughput experiments.

Accurate predictions of postmortem interval using linear regression analyses of gene meter expression data

In criminal and civil investigations, postmortem interval is used as evidence to help sort out circumstances at the time of human death. Many biological, chemical, and physical indicators can be used to determine the postmortem interval - but most are not accurate. Here, we sought to validate an experimental design to accurately predict the time of death by analyzing the expression of hundreds of upregulated genes in two model organisms, the zebrafish and mouse. In a previous study, the death of healthy adults was conducted under strictly controlled conditions to minimize the effects of confounding factors such as lifestyle and temperature. A total of 74,179 microarray probes were calibrated using the Gene Meter approach and the transcriptional profiles of 1063 genes that significantly increased in abundance were assembled into a time series spanning from life to 48 or 96h postmortem. In this study, the experimental design involved splitting the transcription profiles into training and testing datasets, randomly selecting groups of profiles, determining the modeling parameters of the genes to postmortem time using over- and/or perfectly-defined linear regression analyses, and calculating the fit (R²) and slope of predicted versus actual postmortem times. This design was repeated several thousand to million times to find the top predictive groups of gene transcription profiles. A group of eleven zebrafish genes yielded R² of 1 and a slope of 0.99, while a group of seven mouse liver genes yielded a R² of 0.98 and a slope of 0.97, and seven mouse brain genes yielded a R² of 0.95 and a slope of 0.87. In all cases, groups of gene transcripts yielded better postmortem time predictions than individual gene transcripts. The significance of this study is two-fold: selected groups of gene transcripts provide accurate prediction of postmortem time, and the successfully validated experimental design can now be used to accurately predict postmortem time in cadavers.

Effect of Probe-Probe Distance on the Stability of DNA Hybrids on Surfaces

We have used temperature gradient surface plasmon resonance (SPR) measurements to quantitatively evaluate how the stability of different types of hybrids formed with DNA probes on surfaces is affected by probe spacing. SPR sensors with different average surface densities of probes were prepared by coadsorbing probes with lateral spacers strands comprised of phosphorothioated adenine nucleotides (A15*). Increasing the fraction of A15* spacers in the immobilization solution results in larger distances between probes on the sensor, determined here using a combination of SPR and X-ray photoelectron spectroscopy (XPS) measurements. The hybridization activities of probes were simultaneously measured over a temperature range that spanned the denaturation temperature (T_m) of hybrids by applying a spatial temperature gradient across the sensor surface. The resulting temperature profiles of hybridization activity show how the stability of hybrids increases as either the distance between probes or the ionic strength of the hybridization buffer increase. Additionally, hybridization activity profiles sharpen as the spacing between probes increases, indicating more homogeneous hybridization behavior of probes. The results provide quantitative experimental data for testing theoretical models of stability, supporting models that account for both repulsive interactions between DNA strands and local variability in probe surface density.

Tracing the dynamics of gene transcripts after organismal death

In life, genetic and epigenetic networks precisely coordinate the expression of genes-but in death, it is not known if gene expression diminishes gradually or abruptly stops or if specific genes and pathways are involved. We studied this by identifying mRNA transcripts that apparently increase in relative abundance after death, assessing their functions, and comparing their abundance profiles through postmortem time in two species, mouse and zebrafish. We found mRNA transcript profiles of 1063 genes became significantly more abundant after death of healthy adult animals in a time series spanning up to 96 h postmortem. Ordination plots revealed non-random patterns in the profiles by time. While most of these transcript levels increased within 0.5 h postmortem, some increased only at 24 and 48 h postmortem. Functional characterization of the most abundant transcripts revealed the following categories: stress, immunity, inflammation, apoptosis, transport, development, epigenetic regulation and cancer. The data suggest a step-wise shutdown occurs in organismal death that is manifested by the apparent increase of certain transcripts with various abundance maxima and durations.

Effects of Chain-Chain Associations on Hybridization in DNA Brushes

Hybridization of solution nucleic acids to DNA brushes is widely encountered in diagnostic and materials science applications. Typically, brush chain lengths of ten or more nucleotides are used to provide the needed sequence specificity and binding affinity. At these lengths, coincidental occurrence of complementary regions is expected to lead to associations between the nominally single-stranded brush chains due to intra- or interchain base pairing. This report investigates how these associations impact the brushes' hybridization activity toward complementary "target" sequences. Brushes were prepared from 20-mer chains with four-nucleotide-long "adhesive regions" through which neighboring chains could interact. The affinity and position of the adhesive region along the chain backbone were varied. DNA brushes were exposed to complementary solution targets, and the corresponding melting transitions were measured to estimate free energies of the brush-target hybridization. These results revealed that higher affinity adhesive regions more extensively suppressed brush hybridization relative to hybridization in solution. Associations near the middle of the chains were found to be more penalizing than those at the immobilized or the free end of the chains. Provided that the brush chains were close enough to associate, changes in brush density did not exert a significant effect on hybridization thermodynamics within the investigated coverage window. Comparison of the DNA brush results with those from commercial Affymetrix single-nucleotide-polymorphism (SNP) microarrays revealed agreement in the impact of chain associations on hybridization.

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

This 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.

Microbial signatures of oral dysbiosis, periodontitis and edentulism revealed by Gene Meter methodology

Conceptual models suggest that certain microorganisms (e.g., the "red" complex) are indicative of a specific disease state (e.g., periodontitis); however, recent studies have questioned the validity of these models. Here, the abundances of 500+ microbial species were determined in 16 patients with clinical signs of one of the following oral conditions: periodontitis, established caries, edentulism, and oral health. Our goal was to determine if the abundances of certain microorganisms reflect dysbiosis or a specific clinical condition that could be used as a 'signature' for dental research. Microbial abundances were determined by the analysis of 138,718 calibrated probes using Gene Meter methodology. Each 16S rRNA gene was targeted by an average of 194 unique probes (n=25nt). The calibration involved diluting pooled gene target samples, hybridizing each dilution to a DNA microarray, and fitting the probe intensities to adsorption models. The fit of the model to the experimental data was used to assess individual and aggregate probe behavior; good fits (R²>0.90) were retained for back-calculating microbial abundances from patient samples. The abundance of a gene was determined from the median of all calibrated individual probes or from the calibrated abundance of all aggregated probes. With the exception of genes with low abundances (<2 arbitrary units), the abundances determined by the different calibrations were highly correlated (r~1.0). Seventeen genera were classified as 'signatures of dysbiosis' because they had significantly higher abundances in patients with periodontitis and edentulism when contrasted with health. Similarly, 13 genera were classified as 'signatures of periodontitis', and 14 genera were classified as 'signatures of edentulism'. The signatures could be used, individually or in combination, to assess the clinical status of a patient (e.g., evaluating treatments such as antibiotic therapies). Comparisons of the same patient samples revealed high false negatives (45%) for next-generation-sequencing results and low false positives (7%) for Gene Meter results.

Surface vs. solution hybridization: effects of salt, temperature, and probe type

Hybridization thermodynamics on solid supports are compared with those in solution for two types of hybridization probe, DNA and uncharged morpholino oligonucleotides of identical sequences. Trends in hybridization affinity are discussed with respect to ionic strength, temperature, and surface behavior.

Molecular Crowding Effects on Microgel-Tethered Oligonucleotide Probes

Microgel tethering is a nontraditional method with which to bind oligonucleotide hybridization probes to a solid surface. Microgel-tethering physically positions the probes away from the underlying hard substrate and maintains them in a highly waterlike environment. This paper addresses the question of whether molecular crowding affects the performance of microgel-tethered molecular beacon probes. The density of probe-tethering sites is controlled experimentally using thin-film blends of biotin-terminated [PEG-B] and hydroxyl-terminated [PEG-OH] poly(ethylene glycol) from which microgels are synthesized and patterned by electron beam lithography. Fluorescence measurements indicate that the number of streptavidins, linear DNA probes, hairpin probes, and molecular beacon probes bound to the microgels increases linearly with increasing PEG-B/PEG-OH ratio. For a given tethering-site concentration, more linear probes can bind than structured probes. Crowding effects emerge during the hybridization of microgel-tethered molecular beacons but not during the hybridization of linear probes, as the tethering density increases. Crowding during hybridization is associated with conformational constraints imposed by the close proximity of closed and hybridized structured probes. The signal-to-background ratio (SBR) of hybridized beacons is highest and roughly constant for low tethering densities and decreases at the highest tethering densities. Despite differences between microgel tethering and traditional oligonucleotide surface-immobilization approaches, these results show that crowding defines an optimum tethering density for molecular beacon probes that is less than the maximum possible, which is consistent with previous studies involving various linear and structured oligonucleotide probes.

Information Limited Oligonucleotide Amplification Assay for Affinity-Based, Parallel Detection Studies

Molecular communication systems encounter similar constraints as telecommunications. In either case, channel crosstalk at the receiver end will result in information loss that statistical analysis cannot compensate. This is because in any communication channel there is a physical limit to the amount of information that can be transmitted. We present a novel and simple modified end amplification (MEA) technique to generate reduced and defined amounts of specific information in form of short fragments from an oligonucleotide source that also contains unrelated and redundant information. Our method can be a valuable tool to investigate information overflow and channel capacity in biomolecular recognition systems.

Mismatch detection in DNA monolayers by atomic force microscopy and electrochemical impedance spectroscopy

Background: DNA hybridization is at the basis of most current technologies for genotyping and sequencing, due to the unique properties of DNA base-pairing that guarantee a high grade of selectivity. Nonetheless the presence of single base mismatches or not perfectly matched sequences can affect the response of the devices and the major challenge is, nowadays, to distinguish a mismatch of a single base and, at the same time, unequivocally differentiate devices read-out of fully and partially matching sequences.

Results: We present here two platforms based on different sensing strategies, to detect mismatched and/or perfectly matched complementary DNA strands hybridization into ssDNA oligonucleotide monolayers. The first platform exploits atomic force microscopy-based nanolithography to create ssDNA nano-arrays on gold surfaces. AFM topography measurements then monitor the variation of height of the nanostructures upon biorecognition and then follow annealing at different temperatures. This strategy allowed us to clearly detect the presence of mismatches. The second strategy exploits the change in capacitance at the interface between an ssDNA-functionalized gold electrode and the solution due to the hybridization process in a miniaturized electrochemical cell. Through electrochemical impedance spectroscopy measurements on extended ssDNA self-assembled monolayers we followed in real-time the variation of capacitance, being able to distinguish, through the difference in hybridization kinetics, not only the presence of single, double or triple mismatches in the complementary sequence, but also the position of the mismatched base pair with respect to the electrode surface.

Conclusion: We demonstrate here two platforms based on different sensing strategies as sensitive and selective tools to discriminate mismatches. Our assays are ready for parallelization and can be used in the detection and quantification of single nucleotide mismatches in microRNAs or in genomic DNA.

Towards microbiome transplant as a therapy for periodontitis: an exploratory study of periodontitis microbial signature contrasted by oral health, caries and edentulism

BACKGROUND

Conventional periodontal therapy aims at controlling supra- and subgingival biofilms. Although periodontal therapy was shown to improve periodontal health, it does not completely arrest the disease. Almost all subjects compliant with periodontal maintenance continue to experience progressive clinical attachment loss and a fraction of them loses teeth. An oral microbial transplant may be a new alternative for treating periodontitis (inspired by fecal transplant). First, it must be established that microbiomes of oral health and periodontitis are distinct. In that case, the health-associated microbiome could be introduced into the oral cavity of periodontitis patients. This relates to the goals of our study: (i) to assess if microbial communities of the entire oral cavity of subjects with periodontitis were different from or oral health contrasted by microbiotas of caries and edentulism patients; (ii) to test in vitro if safe concentration of sodium hypochlorite could be used for initial eradication of the original oral microbiota followed by a safe neutralization of the hypochlorite prior transplantation.

METHODS

Sixteen systemically healthy white adults with clinical signs of one of the following oral conditions were enrolled: periodontitis, established caries, edentulism, and oral health. Oral biofilm samples were collected from sub- and supra-gingival sites, and oral mucosae. DNA was extracted and 16S rRNA genes were amplified. Amplicons from the same patient were pooled, sequenced and quantified. Volunteer's oral plaque was treated with saline, 16 mM NaOCl and NaOCl neutralized by ascorbate buffer followed by plating on blood agar.

RESULTS

Ordination plots of rRNA gene abundances revealed distinct groupings for the oral microbiomes of subjects with periodontitis, edentulism, or oral health. The oral microbiome in subjects with periodontitis showed the greatest diversity harboring 29 bacterial species at significantly higher abundance compared to subjects with the other assessed conditions. Healthy subjects had significantly higher abundance in 10 microbial species compared to the other conditions. NaOCl showed strong antimicrobial properties; nontoxic ascorbate was capable of neutralizing the hypochlorite.

CONCLUSIONS

Distinct oral microbial signatures were found in subjects with periodontitis, edentulism, or oral health. This finding opens up a potential for a new therapy, whereby a health-related entire oral microbial community would be transplanted to the diseased patient.

The Impact of Photobleaching on Microarray Analysis

DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner’s laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube’s voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results.

Crowding-induced cooperativity in DNA surface hybridization

High density DNA brush is not only used to model cellular crowding, but also has a wide application in DNA-functionalized materials. Experiments have shown complicated cooperative hybridization/melting phenomena in these systems, raising the question that how molecular crowding influences DNA hybridization. In this work, a theoretical modeling including all possible inter and intramolecular interactions, as well as molecular details for different species, is proposed. We find that molecular crowding can lead to two distinct cooperative behaviours: negatively cooperative hybridization marked by a broader transition width, and positively cooperative hybridization with a sharper transition, well reconciling the experimental findings. Moreover, a phase transition as a result of positive cooperativity is also found. Our study provides new insights in crowding and compartmentation in cell, and has the potential value in controlling surface morphologies of DNA functionalized nano-particles.

On the use of aptamer microarrays as a platform for the exploration of human prothrombin/thrombin conversion

Microarrays are particular biosensors with multiple grafted probes that are generally used for parallel and simultaneous detection of various targets. In this study, we used microarrays with aptamer probes in order to follow up the different biomolecular interactions of a single enzyme, the thrombin protein, involved in the complex coagulation cascade. More precisely, thanks to label-free surface plasmon resonance imaging, we were able to monitor in real time an important step in the firing of the coagulation cascade in situ-the enzymatic transformation of prothrombin into thrombin, catalyzed by factor Xa. We were also able to appraise the influence of other biochemical factors and their corresponding inhibiting or enhancing behaviors on thrombin activation. Our study opens the door for the development of a complete microarray-based platform not only for the whole coagulation cascade analysis but also for novel drug screening assays in pharmacology.

Variation of RNA Quality and Quantity Are Major Sources of Batch Effects in Microarray Expression Data

The great utility of microarrays for genome-scale expression analysis is challenged by the widespread presence of batch effects, which bias expression measurements in particular within large data sets. These unwanted technical artifacts can obscure biological variation and thus significantly reduce the reliability of the analysis results. It is largely unknown which are the predominant technical sources leading to batch effects. We here quantitatively assess the prevalence and impact of several known technical effects on microarray expression results. Particularly, we focus on important factors such as RNA degradation, RNA quantity, and sequence biases including multiple guanine effects. We find that the common variation of RNA quality and RNA quantity can not only yield low-quality expression results, but that both factors also correlate with batch effects and biological characteristics of the samples.

Quantitative PCR as a predictor of aligned ancient DNA read counts following targeted enrichment

Targeted DNA enrichment through hybridization capture (EHC) is rapidly replacing PCR as the method of choice for enrichment prior to genomic resequencing. This is especially true in the case of ancient DNA (aDNA) from long-dead organisms, where targets tend to be highly fragmented and outnumbered by contaminant DNA. However, the behavior of EHC using aDNA has been quite variable, making success difficult to predict and preventing efficient sample equilibration during multiplexed sequencing runs. Here, we evaluate whether quantitative PCR (qPCR) measurements of aDNA samples correlate with on-target read counts before and after EHC. Our data indicate that not only do simple target qPCRs correlate strongly with high-throughput sequencing (HTS) data but that certain sample characteristics, such as overall target abundance as well as experimental parameters (e.g., bait concentration and secondary structure propensity), consistently influenced enrichment of our diverse set of aDNA samples. Taken together, our results should help guide experimental design, screening strategies, and multiplexed sample equilibration, increasing yield and reducing the expected and actual cost of aDNA EHC high-throughput sequencing projects in the future.

Single-stranded DNA catalyzes hybridization of PCR-products to microarray capture probes

Since its development, microarray technology has evolved to a standard method in the biotechnological and medical field with a broad range of applications. Nevertheless, the underlying mechanism of the hybridization process of PCR-products to microarray capture probes is still not completely understood, and several observed phenomena cannot be explained with current models. We investigated the influence of several parameters on the hybridization reaction and identified ssDNA to play a major role in the process. An increase of the ssDNA content in a hybridization reaction strongly enhanced resulting signal intensities. A strong influence could also be observed when unlabeled ssDNA was added to the hybridization reaction. A reduction of the ssDNA content resulted in a massive decrease of the hybridization efficiency. According to these data, we developed a novel model for the hybridization mechanism. This model is based on the assumption that single stranded DNA is necessary as catalyst to induce the hybridization of dsDNA. The developed hybridization model is capable of giving explanations for several yet unresolved questions regarding the functionality of microarrays. Our findings not only deepen the understanding of the hybridization process, but also have immediate practical use in data interpretation and the development of new microarrays.

Emerging technologies for hybridization based single nucleotide polymorphism detection

Detection of single nucleotide polymorphisms (SNPs) is a crucial challenge in the development of a novel generation of diagnostic tools. Accurate detection of SNPs can prove elusive, as the impact of a single variable nucleotide on the properties of a target sequence is limited, even if this sequence consists of only a few nucleotides. New, accurate and facile strategies for the detection of point mutations are therefore absolutely necessary for the increased adoption of point-of-care molecular diagnostics. Currently, PCR and sequencing are mostly applied for diagnosing SNPs. However these methods have serious drawbacks as routine diagnostic tools because of their labour intensity and cost. Several new, more suitable methods can be applied to enable sensitive detection of mutations based on specially designed hybridization probes, mutation recognizing enzymes and thermal denaturation. Here, an overview is presented of the most recent advances in the field of fast and sensitive SNP detection assays with strong potential for integration in point-of-care tests.

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.

Estimating differential expression from multiple indicators

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR.

Strategies for optimizing DNA hybridization on surfaces

Specific and predictable hybridization of the polynucleotide sequences to their complementary counterparts plays a fundamental role in the rational design of new nucleic acid nanodevices. Generally, nucleic acid hybridization can be performed using two major strategies, namely hybridization of DNA or RNA targets to surface-tethered oligonucleotide probes (solid-phase hybridization) and hybridization of the target nucleic acids to randomly distributed probes in solution (solution-phase hybridization). Investigations into thermodynamic and kinetic parameters of these two strategies showed that hybridization on surfaces is less favorable than that of the same sequence in solution. Indeed, the efficiency of DNA hybridization on surfaces suffers from three constraints: (1) electrostatic repulsion between DNA strands on the surface, (2) steric hindrance between tethered DNA probes, and (3) nonspecific adsorption of the attached oligonucleotides to the solid surface. During recent years, several strategies have been developed to overcome the problems associated with DNA hybridization on surfaces. Optimizing the probe surface density, application of a linker between the solid surface and the DNA-recognizing sequence, optimizing the pH of DNA hybridization solutions, application of thiol reagents, and incorporation of a polyadenine block into the terminal end of the recognizing sequence are among the most important strategies for enhancing DNA hybridization on surfaces.

Targeted resequencing of HIV variants by microarray thermodynamics

Within a single infected individual, a virus population can have a high genomic variability. In the case of HIV, several mutations can be present even in a small genomic window of 20–30 nucleotides. For diagnostics purposes, it is often needed to resequence genomic subsets where crucial mutations are known to occur. In this article, we address this issue using DNA microarrays and inputs from hybridization thermodynamics. Hybridization signals from multiple probes are analysed, including strong signals from perfectly matching (PM) probes and a large amount of weaker cross-hybridization signals from mismatching (MM) probes. The latter are crucial in the data analysis. Seven coded clinical samples (HIV-1) are analyzed, and the microarray results are in full concordance with Sanger sequencing data. Moreover, the thermodynamic analysis of microarray signals resolves inherent ambiguities in Sanger data of mixed samples and provides additional clinically relevant information. These results show the reliability and added value of DNA microarrays for point-of-care diagnostic purposes.