Specificity of DNA microarray hybridization: characterization, effectors and approaches for data correction

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

Efficient enrichment of free target sequences in an integrated microfluidic device for point-of-care detection systems

Nucleic acid biomarker detection has great importance in the diagnosis of disease, the monitoring of disease progression and the classification of patients according to treatment decision making. Nucleic acid biomarkers found in the blood of patients have generated a lot of interest due to the possibility of being detected non-invasively which makes them ideal for monitoring and screening tests and particularly amenable to point-of-care (POC) or self-testing. A major challenge to POC molecular diagnostics is the need to enrich the target to optimise detection. In this work, we describe a microfabricated device for the enrichment of short dsDNA target sequences, which is especially valuable for potential detection methods, as it improves the probability of effectively detecting the target in downstream analyses. The device integrated a heating element and a temperature sensor with a microfluidic chamber to carry out the denaturation of the dsDNA combined with blocking-probes to enrich the target. This procedure was validated by fluorescence resonance energy transfer (FRET) technique, labelling DNA with a fluorophore and a quencher. As proof of concept, a 23-mer long dsDNA sequence corresponding to the L858R mutation of the EGFR gene was used. The qualitative results obtained determined that the most optimal blocking rate was obtained with the incorporation of 11/12-mer blocking-probes at a total concentration of 6 μM. This device is a powerful DNA preparation tool, which is an indispensable initial step for subsequent detection of sequences via nucleic acid hybridisation methods.

Heteromultivalency enables enhanced detection of nucleic acid mutations

Detecting genetic mutations such as single nucleotide polymorphisms (SNPs) is necessary to prescribe effective cancer therapies, perform genetic analyses and distinguish similar viral strains. Traditionally, SNP sensing uses short oligonucleotide probes that differentially bind the SNP and wild-type targets. However, DNA hybridization-based techniques require precise tuning of the probe's binding affinity to manage the inherent trade-off between specificity and sensitivity. As conventional hybridization offers limited control over binding affinity, here we generate heteromultivalent DNA-functionalized particles and demonstrate optimized hybridization specificity for targets containing one or two mutations. By investigating the role of oligo lengths, spacer lengths and binding orientation, we reveal that heteromultivalent hybridization enables fine-tuned specificity for a single SNP and dramatic enhancements in specificity for two non-proximal SNPs empowered by highly cooperative binding. Capitalizing on these abilities, we demonstrate straightforward discrimination between heterozygous cis and trans mutations and between different strains of the SARS-CoV-2 virus. Our findings indicate that heteromultivalent hybridization offers substantial improvements over conventional monovalent hybridization-based methods.

Inferring Gene Regulatory Networks from RNA-seq Data Using Kernel Classification

Gene expression profiling is one of the most recognized techniques for inferring gene regulators and their potential targets in gene regulatory networks (GRN). The purpose of this study is to build a regulatory network for the budding yeast Saccharomyces cerevisiae genome by incorporating the use of RNA-seq and microarray data represented by a wide range of experimental conditions. We introduce a pipeline for data analysis, data preparation, and training models. Several kernel classification models; including one-class, two-class, and rare event classification methods, are used to categorize genes. We test the impact of the normalization techniques on the overall performance of RNA-seq. Our findings provide new insights into the interactions between genes in the yeast regulatory network. The conclusions of our study have significant importance since they highlight the effectiveness of classification and its contribution towards enhancing the present comprehension of the yeast regulatory network. When assessed, our pipeline demonstrates strong performance across different statistical metrics, such as a 99% recall rate and a 98% AUC score.

Tool and techniques study to plant microbiome current understanding and future needs: an overview

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.

An advanced and efficient asymmetric PCR method for microarray applications

The sensitivity of a PCR based biochip assay relies on the efficiency of PCR amplicons in binding to the microarray spots. The essential factor determining the sensitivity is the amount of single stranded (ss) amplicons available for biochip hybridization. Asymmetric PCR can generate ss-amplicons depending on the ratio of primers used in the amplification process, but this process is often inefficient. We report a novel variant of PCR called the Asymmetric Exponential and Linear Amplification (AELA) which can overcome these issues and generate large amounts of single stranded amplicons. AELA-PCR introduces an amplification strategy that makes use of both exponential and linear amplification of the target nucleic acid. This is done by specifically designed primers and choice of adequate thermal profiles. In conventional PCR with a classical thermal profile, these specifically designed primers will work normally and contribute to an exponential increase of amplicons. A designed sequence extension of one of the primers and a very specific thermal profile, will result in a situation that the extended primer will be the only functional one for amplification, resulting in a linear phase of the amplification process. That is why during this step only one of the two strands of the target is amplified linearly and no longer exponentially. The result of the whole process is an amplification product enriched very strongly in one of the two single strands of the target. These adaptions in PCR are particularly favorable where the generation of ss-DNA/RNA is required. We demonstrate the higher biochip sensitivity of AELA-PCR compared to conventional amplification methods with an example of the Staphylococcus aureus detection on a DNA oligonucleotide microarray.

Full pathogen characterisation: species identification including the detection of virulence factors and antibiotic resistance genes via multiplex DNA-assays

Antibiotic resistances progressively cause treatment failures, and their spreading dynamics reached an alarming level. Some strains have already been classified as highly critical, e.g. the ones summarised by the acronym ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.). To restrain this trend and enable effective medication, as much information as possible must be obtained in the least possible time. Here, we present a DNA microarray-based assay that screens for the most important sepsis-relevant 44 pathogenic species, 360 virulence factors (mediate pathogenicity in otherwise non-pathogenic strains), and 409 antibiotic resistance genes in parallel. The assay was evaluated with 14 multidrug resistant strains, including all ESKAPE pathogens, mainly obtained from clinical isolates. We used a cost-efficient ligation-based detection platform designed to emulate the highly specific multiplex detection of padlock probes. Results could be obtained within one day, requiring approximately 4 h for amplification, application to the microarray, and detection.

Cross-reactive probes on Illumina DNA methylation arrays: a large study on ALS shows that a cautionary approach is warranted in interpreting epigenome-wide association studies

Illumina DNA methylation arrays are a widely used tool for performing genome-wide DNA methylation analyses. However, measurements obtained from these arrays may be affected by technical artefacts that result in spurious associations if left unchecked. Cross-reactivity represents one of the major challenges, meaning that probes may map to multiple regions in the genome. Although several studies have reported on this issue, few studies have empirically examined the impact of cross-reactivity in an epigenome-wide association study (EWAS). In this paper, we report on cross-reactivity issues that we discovered in a large EWAS on the presence of the C9orf72 repeat expansion in ALS patients. Specifically, we found that that the majority of the significant probes inadvertently cross-hybridized to the C9orf72 locus. Importantly, these probes were not flagged as cross-reactive in previous studies, leading to novel insights into the extent to which cross-reactivity can impact EWAS. Our findings are particularly relevant for epigenetic studies into diseases associated with repeat expansions and other types of structural variation. More generally however, considering that most spurious associations were not excluded based on pre-defined sets of cross-reactive probes, we believe that the presented data-driven flag and consider approach is relevant for any type of EWAS.

Evaluation of a eukaryote phylogenetic microarray for environmental monitoring of marine sediments

Increased exploitation of resources in sensitive marine ecosystems emphasizes the importance of knowledge regarding ecological impacts. However, current bio-monitoring practices are limited in terms of target-organisms and temporal resolution. Hence, developing new technologies is vital for enhanced ecosystem understanding. In this study, we have applied a prototype version of a phylogenetic microarray to assess the eukaryote community structures of marine sediments from an area with ongoing oil and gas drilling activity. The results were compared with data from both sequencing (metabarcoding) and morphology-based monitoring to evaluate whether microarrays were capable of detecting ecosystem disturbances. A significant correlation between microarray data and chemical pollution indicators, as well as sequencing-based results, was demonstrated, and several potential indicator organisms for pollution-associated parameters were identified, among them a large fraction of microorganisms not covered by traditional morphology-based monitoring. This suggests that microarrays have a potential in future environmental monitoring.

Functional and population genetic features of copy number variations in two dairy cattle populations

BACKGROUND

Copy Number Variations (CNVs) are gain or loss of DNA segments that are known to play a role in shaping a wide range of phenotypes. In this study, we used two dairy cattle populations, Holstein Friesian and Jersey, to discover CNVs using the Illumina BovineHD Genotyping BeadChip aligned to the ARS-UCD1.2 assembly. The discovered CNVs were investigated for their functional impact and their population genetics features.

RESULTS

We discovered 14,272 autosomal CNVs, which were aggregated into 1755 CNV regions (CNVR) from 451 animals. These CNVRs together cover 2.8% of the bovine autosomes. The assessment of the functional impact of CNVRs showed that rare CNVRs (MAF < 0.01) are more likely to overlap with genes, than common CNVRs (MAF ≥ 0.05). The Population differentiation index (Fst) based on CNVRs revealed multiple highly diverged CNVRs between the two breeds. Some of these CNVRs overlapped with candidate genes such as MGAM and ADAMTS17 genes, which are related to starch digestion and body size, respectively. Lastly, linkage disequilibrium (LD) between CNVRs and BovineHD BeadChip SNPs was generally low, close to 0, although common deletions (MAF ≥ 0.05) showed slightly higher LD (r2 = ~ 0.1 at 10 kb distance) than the rest. Nevertheless, this LD is still lower than SNP-SNP LD (r2 = ~ 0.5 at 10 kb distance).

CONCLUSIONS

Our analyses showed that CNVRs detected using BovineHD BeadChip arrays are likely to be functional. This finding indicates that CNVs can potentially disrupt the function of genes and thus might alter phenotypes. Also, the population differentiation index revealed two candidate genes, MGAM and ADAMTS17, which hint at adaptive evolution between the two populations. Lastly, low CNVR-SNP LD implies that genetic variation from CNVs might not be fully captured in routine animal genetic evaluation, which relies solely on SNP markers.

Deconvoluting Stress-Responsive Proteostasis Signaling Pathways for Pharmacologic Activation Using Targeted RNA Sequencing

Cellular proteostasis is maintained by stress-responsive signaling pathways such as the heat shock response (HSR), the oxidative stress response (OSR), and the unfolded protein response (UPR). Activation of these pathways results in the transcriptional upregulation of select subsets of stress-responsive genes that restore proteostasis and adapt cellular physiology to promote recovery following various types of acute insult. The capacity for these pathways to regulate cellular proteostasis makes them attractive therapeutic targets for correcting proteostasis defects associated with diverse diseases. High-throughput screening (HTS) using cell-based reporter assays is highly effective for identifying putative activators of stress-responsive signaling pathways. However, the development of these compounds is hampered by the lack of medium-throughput assays to define compound potency and selectivity for a given pathway. Here, we describe a targeted RNA sequencing (RNAseq) assay that allows cost-effective, medium-throughput screening of stress-responsive signaling pathway activation. We demonstrate that this assay allows deconvolution of stress-responsive signaling activated by chemical genetic or pharmacologic agents. Furthermore, we use this assay to define the selectivity of putative OSR and HSR activating compounds previously identified by HTS. Our results demonstrate the potential for integrating this adaptable targeted RNAseq assay into screening programs focused on developing pharmacologic activators of stress-responsive signaling pathways.

Optimizing the Toehold Strategy of On-Chip Nucleic Acid Hybridization Probe for the Discrimination of Single Nucleotide Polymorphism

The synthetic DNA hybridization probe has proved its importance in biology and biotechnology. In this study, taking advantage of a novel analytical technique called dual polarization interferometry (DPI), the influence of the toehold strategy of on-chip DNA hybridization probe on the discrimination of single nucleotide polymorphism (SNP) was investigated. Through adjusting the toehold length, the toehold strategies of on-chip toehold exchange probe were thoroughly optimized. For the "6/5" probe, an optimal discrimination factor of 78% against the spurious target was achieved. Moreover, the ability of the on-chip probe in SNP discrimination was significantly enhanced compared to its pure solution counterpart. This simple and rapid detection method for SNP discrimination based on the on-chip toehold exchange probe will show great potential in disease diagnosis.

Ultrasensitive quantification of tumor mRNAs in extracellular vesicles with an integrated microfluidic digital analysis chip

Extracellular vesicles (EVs) present a promising liquid biopsy for cancer diagnosis. However, it remains a daunting challenge to quantitatively measure molecular contents of EVs including tumor-associated mRNAs. Herein, we report a configurable microwell-patterned microfluidic digital analysis platform combined with a dual-probe hybridization assay for PCR-free, single-molecule detection of specific mRNAs in EVs. The microwell array in our device is configurable between the flow-through assay mode for enhanced hybridization capture and tagging of mRNAs and the digital detection mode based on femtoliter-scale enzymatic signal amplification for single-molecule counting of surface-bound targets. Furthermore, a dual-probe hybridization assay has been developed to enhance the sensitivity of the digital single-molecule detection of EV mRNAs. Combining the merits of the chip design and the dual-probe digital mRNA hybridization assay, the integrated microfluidic system has been demonstrated to afford quantitative detection of synthetic GAPDH mRNA with a LOD as low as 20 aM. Using this technology, we quantified the level of GAPDH and EWS-FLI1 mRNAs in EVs derived from two cell lines of peripheral primitive neuroectodermal tumor (PNET), CHLA-9 and CHLA-258. Our measurements detected 64.6 and 43.5 copies of GAPDH mRNA and 6.5 and 0.277 copies of EWS-FLI1 fusion transcripts per 105 EVs derived from CHLA-9 and CHLA-258 cells, respectively. To our knowledge, this is the first demonstration of quantitative measurement of EWS-FLI1 mRNA copy numbers in Ewing Sarcoma (EWS)-derived EVs. These results highlight the ultralow frequency of tumor-specific mRNA markers in EVs and the necessity of developing highly sensitive methods for analysis of EV mRNAs. The microfluidic digital mRNA analysis platform presented here would provide a useful tool to facilitate quantitative analysis of tumor-associated EV mRNAs for liquid biopsy-based cancer diagnosis and monitoring.

Extracellular vesicles and their nucleic acids for biomarker discovery

Extracellular vesicles (EVs) are a heterogenous population of vesicles originate from cells. EVs are found in different biofluids and carry different macromolecules, including proteins, lipids, and nucleic acids, providing a snap shot of the parental cells at the time of release. EVs have the ability to transfer molecular cargoes to other cells and can initiate different physiological and pathological processes. Mounting lines of evidence demonstrated that EVs' cargo and machinery is affected in disease states, positioning EVs as potential sources for the discovery of novel biomarkers. In this review, we demonstrate a conceptual overview of the EV field with particular focus on their nucleic acid cargoes. Current knowledge of EV subtypes, nucleic acid cargo and pathophysiological roles are outlined, with emphasis placed on advantages against competing analytes. We review the utility of EVs and their nucleic acid cargoes as biomarkers and critically assess the newly available advances in the field of EV biomarkers and high throughput technologies. Challenges to achieving the diagnostic potential of EVs, including sample handling, EV isolation, methodological considerations, and bioassay reproducibility are discussed. Future implementation of 'omics-based technologies and integration of systems biology approaches for the development of EV-based biomarkers and personalized medicine are also considered.

Gene Expression Detection Assay for Cancer Clinical Use

Cancer is a genetic disease where genetic variations cause abnormally functioning genes that appear to alter expression. Proteins, the final products of gene expression, determine the phenotypes and biological processes. Therefore, detecting gene expression levels can be used for cancer diagnosis, prognosis, and treatment prediction in a clinical setting. In this review, we investigated six gene expression assay systems (qRT-PCR, DNA microarray, nCounter, RNA-Seq, FISH, and tissue microarray) that are currently being used in clinical cancer studies. Some of these methods are also commonly used in a modified way; for example, detection of DNA content or protein expression. Herein, we discuss their principles, sample preparation, design, quantification and sensitivity, data analysis, time for sample preparation and processing, and cost. We also compared these methods according to their sample selection, particularly for the feasibility of using formalin-fixed paraffin-embedded (FFPE) samples, which are routinely archived for clinical cancer studies. We intend to provide a guideline for choosing an assay method with respect to its oncological applications in a clinical setting.

Sequence-specific sepsis-related DNA capture and fluorescent labeling in monoliths prepared by single-step photopolymerization in microfluidic devices

Fast determination of antibiotic resistance is crucial in selecting appropriate treatment for sepsis patients, but current methods based on culture are time consuming. We are developing a microfluidic platform with a monolithic column modified with oligonucleotides designed for sequence-specific capture of target DNA related to the Klebsiella pneumoniae carbapenemase (KPC) gene. We developed a novel single-step monolith fabrication method with an acrydite-modified capture oligonucleotide in the polymerization mixture, enabling fast monolith preparation in a microfluidic channel using UV photopolymerization. These prepared columns had a threefold higher capacity compared to monoliths prepared in a multistep process involving Schiff-base DNA attachment. Conditions for denaturing, capture and fluorescence labeling using hybridization probes were optimized with synthetic 90-mer oligonucleotides. These procedures were applied for extraction of a PCR amplicon from the KPC antibiotic resistance gene in bacterial lysate obtained from a blood sample spiked with E. coli. The results showed similar eluted peak areas for KPC amplicon extracted from either hybridization buffer or bacterial lysate. Selective extraction of the KPC DNA was verified by real time PCR on eluted fractions. These results show great promise for application in an integrated microfluidic diagnostic system that combines upstream blood sample preparation and downstream single-molecule counting detection.

Analysis of microRNA and Gene Expression Profiles in Alzheimer's Disease: A Meta-Analysis Approach

Understanding the molecular mechanisms underlying Alzheimer’s disease (AD) is necessary for the diagnosis and treatment of this neurodegenerative disorder. It is therefore important to detect the most important genes and miRNAs, which are associated with molecular events, and studying their interactions for recognition of AD mechanisms. Here we focus on the genes and miRNAs expression profile, which we have detected the miRNA target genes involved in AD. These are the most quintessential to find the most important miRNA, to target genes and their important pathways. A total of 179 differentially expressed miRNAs (DEmiRs) and 1404 differentially expressed genes (DEGs) were obtained from a comprehensive meta-analysis. Also, regions specific genes with their molecular function in AD have been demonstrated. We then focused on miRNAs which regulated most genes in AD, alongside we analyzed their pathways. The miRNA-30a-5p and miRNA-335 elicited a major function in AD after analyzing the regulatory network, we showed they were the most regulatory miRNAs in the AD. In conclusion, we demonstrated the most important genes, miRNAs, miRNA-mRNA interactions and their related pathways in AD using Bioinformatics methods. Accordingly, our defined genes and miRNAs could be used for future molecular studies in the context of AD.

Highly Specific Ligation-dependent Microarray Detection of Single Nucleotide Polymorphisms

The fast detection and characterization of pathogens are essential for an efficient treatment of infectious diseases. However, the development of improved and reliable diagnostic methods is still an ongoing process because not only pathogens but also their antibiotic resistances have to be identified. The gold standard today is, however, a cultivation-based characterization approach, which takes days until results can be evaluated. In patients with, for example, severe sepsis, the diagnostic test duration is a very critical parameter because a delay of treatment optimization increases the mortality rate significantly. In contrast, DNA-based molecular techniques can obtain results within a few hours. A further challenge in diagnostic laboratories is that patient samples have to be screened for hundreds of potential pathogens, antibiotic resistance genes, and virulence factors, which is achieved by using a number of specialized tests at the moment. Microarrays are outstandingly good for the simultaneous analysis of thousands of different genes and have become a popular tool in biological studies. Nevertheless, further optimizations of the microarray technology are required due to the obligatory DNA labeling and/or amplification steps and the effects of nonspecific DNA hybridization. Here, we describe a fast and highly specific solid-support-based DNA characterization method for pathogens and antibiotic resistance genes.

Detection of 16S rRNA and KPC Genes from Complex Matrix Utilizing a Molecular Inversion Probe Assay for Next-Generation Sequencing

Targeted sequencing promises to bring next-generation sequencing (NGS) into routine clinical use for infectious disease diagnostics. In this context, upfront processing techniques, including pathogen signature enrichment, must amplify multiple targets of interest for NGS to be relevant when applied to patient samples with limited volumes. Here, we demonstrate an optimized molecular inversion probe (MIP) assay targeting multiple variable regions within the 16S ribosomal gene for the identification of biothreat and ESKAPE pathogens in a process that significantly reduces complexity, labor, and processing time. Probes targeting the Klebsiella pneumoniae carbapenemase (KPC) antibiotic resistance (AR) gene were also included to demonstrate the ability to concurrently identify etiologic agent and ascertain valuable secondary genetic information. Our assay captured gene sequences in 100% of mock clinical samples prepared from flagged positive blood culture bottles. Using a simplified processing and adjudication method for mapped sequencing reads, genus and species level concordance was 100% and 80%, respectively. In addition, sensitivity and specificity for KPC gene detection was 100%. Our MIP assay produced sequenceable amplicons for the identification of etiologic agents and the detection of AR genes directly from blood culture bottles in a simplified single tube assay.

Gene regulation of two ferredoxin:NADP+ oxidoreductases by the redox-responsive regulator SurR in Thermococcus kodakarensis

The redox-responsive regulator SurR in the hyperthermophilic archaea Pyrococcus furiosus and Thermococcus kodakarensis binds to the SurR-binding consensus sequence (SBS) by responding to the presence of elemental sulfur. Here we constructed a surR gene disruption strain (DTS) in T. kodakarensis, and identified the genes that were under SurR control by comparing the transcriptomes of DTS and parent strains. Among these genes, transcript levels of ferredoxin:NADP⁺ oxidoreductases 1 and 2 (FNOR1 and FNOR2) genes displayed opposite responses to surR deletion, indicating that SurR repressed FNOR1 transcription while enhancing FNOR2 transcription. Each promoter region contains an SBS upstream (uSBS) and downstream (dSBS) of TATA. In addition to in vitro binding assays, we examined the roles of each SBS in vivo. In FNOR1, mutations in either one of the SBSs resulted in a complete loss of repression, indicating that the presence of both SBSs was essential for repression. In FNOR2, uSBS indeed functioned to enhance gene expression, whereas dSBS functioned in gene repression. SurR bound to uSBS2 of FNOR2 more efficiently than to dSBS2 in vitro, which may explain why SurR overall enhances FNOR2 transcription. Further analyses indicated the importance in the distance between uSBS and TATA for transcriptional activation in FNOR2.

Multiplex characterization of human pathogens including species and antibiotic-resistance gene identification

The efficient medical treatment of infections requires detailed information about the pathogens involved and potential antibiotic-resistance mechanisms. The dramatically increasing incidence of multidrug-resistant bacteria especially highlights the importance of sophisticated diagnostic tests enabling a fast patient-customized therapy. However, the current molecular detection methods are limited to either the detection of species or only a few antibiotic-resistance genes.In this work, we present a human pathogen characterization assay using a rRNA gene microarray identifying 75 species comprising bacteria and fungi. A statistical classifier was developed to facilitate the automated species identification. Additionally, the clinically most important β-lactamases were identified simultaneously in a 100-plex reaction using padlock probes and the same microarray. The specificity and sensitivity of the combined assay was determined using clinical isolates. The detection limit was 10(5) c.f.u. ml(-1), recovering 89 % of the detectable β-lactamase-encoding genes specifically. The total assay time was less than 7 hand the modular character of the antibiotic-resistance detection allows the easy integration of further genetic targets. In summary, we present a fast, highly specific and sensitive multiplex pathogen characterization assay.

Duplex DNA-Invading γ-Modified Peptide Nucleic Acids Enable Rapid Identification of Bloodstream Infections in Whole Blood

Bloodstream infections are a leading cause of morbidity and mortality. Early and targeted antimicrobial intervention is lifesaving, yet current diagnostic approaches fail to provide actionable information within a clinically viable time frame due to their reliance on blood culturing. Here, we present a novel pathogen identification (PID) platform that features the use of duplex DNA-invading γ-modified peptide nucleic acids (γPNAs) for the rapid identification of bacterial and fungal pathogens directly from blood, without culturing. The PID platform provides species-level information in under 2.5 hours while reaching single-CFU-per-milliliter sensitivity across the entire 21-pathogen panel. The clinical utility of the PID platform was demonstrated through assessment of 61 clinical specimens, which showed >95% sensitivity and >90% overall correlation to blood culture findings. This rapid γPNA-based platform promises to improve patient care by enabling the administration of a targeted first-line antimicrobial intervention.

Bloodstream infections continue to be a major cause of death for hospitalized patients, despite significant improvements in both the availability of treatment options as well their application. Since early and targeted antimicrobial intervention is one of the prime determinants of patient outcome, the rapid identification of the pathogen can be lifesaving. Unfortunately, current diagnostic approaches for identifying these infections all rely on time-consuming blood culture, which precludes immediate intervention with a targeted antimicrobial. To address this, we have developed and characterized a new and comprehensive methodology, from patient specimen to result, for the rapid identification of both bacterial and fungal pathogens without the need for culturing. We anticipate broad interest in our work, given the novelty of our technical approach combined with an immense unmet need.

"RADIOTRANSCRIPTOMICS": A synergy of imaging and transcriptomics in clinical assessment

Recent advances in quantitative imaging and "omics" technology have generated a wealth of mineable biological "big data". With the push towards a P4 "predictive, preventive, personalized, and participatory" approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose "radiotranscriptomics" as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations.

Microarray experiments and factors which affect their reliability

Oligonucleotide microarrays belong to the basic tools of molecular biology and allow for simultaneous assessment of the expression level of thousands of genes. Analysis of microarray data is however very complex, requiring sophisticated methods to control for various factors that are inherent to the procedures used. In this article we describe the individual steps of a microarray experiment, highlighting important elements and factors that may affect the processes involved and that influence the interpretation of the results. Additionally, we describe methods that can be used to estimate the influence of these factors, and to control the way in which they affect the expression estimates. A comprehensive understanding of the experimental protocol used in a microarray experiment aids the interpretation of the obtained results. By describing known factors which affect expression estimates this article provides guidelines for appropriate quality control and pre-processing of the data, additionally applicable to other transcriptome analysis methods that utilize similar sample handling protocols.

Villain of Molecular Biology: Why are we not reproducible in research?

Worldwide, there is an issue of  irreproducibility in life science research. In the USA alone $28 billion per year spent on preclinical research is not reproducible. Within this opinion article, I provide a brief historical account of the discovery of the Watson-Crick DNA model and introduce another neglected model of DNA. This negligence may be one of the fundamental reasons behind irreproducibility in molecular biology research.

Fast and highly specific DNA-based multiplex detection on a solid support

Highly specific and fast multiplex detection methods are essential to conduct reasonable DNA-based diagnostics and are especially important to characterise infectious diseases. More than 1000 genetic targets such as antibiotic resistance genes, virulence factors and phylogenetic markers have to be identified as fast as possible to facilitate the correct treatment of a patient. In the present work, we developed a novel ligation-based DNA probe concept that was combined with the microarray technology and used it for the detection of bacterial pathogens. The novel linear chain (LNC) probes identified all tested species correctly within 1 h based on their 16S rRNA gene in a 25-multiplex reaction. Genomic DNA was used directly as template in the ligation reaction identifying as little as 10(7) cells without any pre-amplification. The high specificity was further demonstrated characterising a single nucleotide polymorphism leading to no false positive fluorescence signals of the untargeted single nucleotide polymorphism (SNP) variants. In comparison to conventional microarray probes, the sensitivity of the novel LNC3 probes was higher by a factor of 10 or more. In summary, we present a fast, simple, highly specific and sensitive multiplex detection method adaptable for a wide range of applications.

NMR spectroscopy-based metabolic profiling of drug-induced changes in vitro can discriminate between pharmacological classes

Drug-induced changes in mammalian cell line models have already been extensively profiled at the systemic mRNA level and subsequently used to suggest mechanisms of action for new substances, as well as to support drug repurposing, i.e., identifying new potential indications for drugs already licensed for other pharmacotherapy settings. The seminal work in this field, which includes a large database and computational algorithms for pattern matching, is known as the "Connectivity Map" (CMap). However, the potential of similar exercises at the metabolite level is still largely unexplored. Only recently, the first high-throughput metabolomic assay pilot study was published, which involved screening the metabolic response to a set of 56 kinase inhibitors in a 96-well format. Here, we report results from a separately developed metabolic profiling assay, which leverages (1)H NMR spectroscopy to the quantification of metabolic changes in the HCT116 colorectal cancer cell line, in response to each of 26 compounds. These agents are distributed across 12 different pharmacological classes covering a broad spectrum of bioactivity. Differential metabolic profiles, inferred from multivariate spectral analysis of 18 spectral bins, allowed clustering of the most-tested drugs, according to their respective pharmacological class. A more-advanced supervised analysis, involving one multivariate scattering matrix per pharmacological class and using only 3 spectral bins (3 metabolites), showed even more distinct pharmacology-related cluster formations. In conclusion, this type of relatively fast and inexpensive profiling seems to provide a promising alternative to that afforded by mRNA expression analysis, which is relatively slow and costly. As also indicated by the present pilot study, the resulting metabolic profiles do not seem to provide as information-rich signatures as those obtained using systemic mRNA profiling, but the methodology holds strong promise for significant refinement.

Identification of putative ortholog gene blocks involved in gestant and lactating mammary gland development: a rodent cross-species microarray transcriptomics approach

The mammary gland (MG) undergoes functional and metabolic changes during the transition from pregnancy to lactation, possibly by regulation of conserved genes. The objective was to elucidate orthologous genes, chromosome clusters and putative conserved transcriptional modules during MG development. We analyzed expression of 22,000 transcripts using murine microarrays and RNA samples of MG from virgin, pregnant, and lactating rats by cross-species hybridization. We identified 521 transcripts differentially expressed; upregulated in early (78%) and midpregnancy (89%) and early lactation (64%), but downregulated in mid-lactation (61%). Putative orthologous genes were identified. We mapped the altered genes to orthologous chromosomal locations in human and mouse. Eighteen sets of conserved genes associated with key cellular functions were revealed and conserved transcription factor binding site search entailed possible coregulation among all eight block sets of genes. This study demonstrates that the use of heterologous array hybridization for screening of orthologous gene expression from rat revealed sets of conserved genes arranged in chromosomal order implicated in signaling pathways and functional ontology. Results demonstrate the utilization power of comparative genomics and prove the feasibility of using rodent microarrays to identification of putative coexpressed orthologous genes involved in the control of human mammary gland development.

Development of bacteria identification array to detect lactobacilli in Thai fermented sausage

To improve the quality and safety of food products, there is a need in the food industry for a reliable method for simultaneously monitoring multiple bacterial strains. Microarray technology is a high-throughput screening approach that can provide an alternative for bacteria detection. A total of 164 bacteria-specific probes were designed from 16S rRNA gene sequences to target 12 bacteria species, including lactic acid bacteria and selected food pathogens. After fabrication onto aminosilane-coated slides, hybridization conditions of the array were optimized for high specificity and signal intensities. The array was applied to detect 12 bacteria individually and was specific to all (Lactobacillus plantarum group, L. fermentum, L. brevis, L. delbrueckii, L. casei, L. sakei, Escherichia coli, Staphylococcus aureus, Micrococcus luteus and Listeria monocytogenes) except L. animalis. Multiplex detection using mixed bacteria populations was evaluated and accurate detection was obtained. The feasibility of using the array to detect the target bacteria in food was evaluated with Thai fermented sausages (Nham). Meat samples were collected on days 2, 3 and 7 after natural fermentation, L. plantarum-inoculated fermentation and L. brevis-inoculated fermentation before applying to the array. The naturally-fermented Nham contained L. sakei, L. delbrueckii, L. plantarum and L. fermentum. The L. plantarum-inoculated Nham showed a similar lactic acid bacteria population but the positive signal level for L. plantarum was higher than with natural fermentation. The L. brevis-inoculated Nham contained L. brevis, L. plantarum, L. delbrueckii and L. fermentum. The array was used to monitor bacteria population dynamics during the fermentation process. The naturally-fermented and L. brevis-inoculated samples showed lower positive signal levels of L. plantarum on day 2, but signals gradually increased on days 3 and 7 of the fermentation. In contrast, the L. plantarum-started fermentation showed a higher positive signal level on day 2 than the natural and L. brevis-inoculated samples, and the positive signal level remained high on days 3 and 7. The bacteria identification array was proven to be useful as an alternative method to detect and monitor target bacteria populations during food fermentation.

Optimizing the specificity of nucleic acid hybridization

The specific hybridization of complementary sequences is an essential property of nucleic acids, enabling diverse biological and biotechnological reactions and functions. However, the specificity of nucleic acid hybridization is compromised for long strands, except near the melting temperature. Here, we analytically derived the thermodynamic properties of a hybridization probe that would enable near-optimal single-base discrimination and perform robustly across diverse temperature, salt and concentration conditions. We rationally designed 'toehold exchange' probes that approximate these properties, and comprehensively tested them against five different DNA targets and 55 spurious analogues with energetically representative single-base changes (replacements, deletions and insertions). These probes produced discrimination factors between 3 and 100+ (median, 26). Without retuning, our probes function robustly from 10 °C to 37 °C, from 1 mM Mg(2+) to 47 mM Mg(2+), and with nucleic acid concentrations from 1 nM to 5 µM. Experiments with RNA also showed effective single-base change discrimination.

Detecting unknown sequences with DNA microarrays: explorative probe design strategies

Designing environmental DNA microarrays that can be used to survey the extreme diversity of microorganisms existing in nature, represents a stimulating challenge in the field of molecular ecology. Indeed, recent efforts in metagenomics have produced a substantial amount of sequence information from various ecosystems, and will continue to accumulate large amounts of sequence data given the qualitative and quantitative improvements in the next-generation sequencing methods. It is now possible to take advantage of these data to develop comprehensive microarrays by using explorative probe design strategies. Such strategies anticipate genetic variations and thus are able to detect known and unknown sequences in environmental samples. In this review, we provide a detailed overview of the probe design strategies currently available to construct both phylogenetic and functional DNA microarrays, with emphasis on those permitting the selection of such explorative probes. Furthermore, exploration of complex environments requires particular attention on probe sensitivity and specificity criteria. Finally, these innovative probe design approaches require exploiting newly available high-density microarray formats.

Simultaneous analysis of foodborne pathogenic bacteria by an oligonucleotide microarray assay

A rapid and accurate method for simultaneous identification of foodborne infectious pathogens was developed based on oligonucleotide microarray technology. The proposed identification method is based on PCR amplification of the target region of the groEL genes with degenerate primers, followed by the PCR products hybridization with oligonucleotide probes specific for species. The groEL gene amplification products of seventeen species of pathogenic bacteria were hybridized to the oligonucleotide array. Hybridization results were analyzed with digoxigenin-linked enzyme reaction. Results indicated that fifteen species of pathogenic bacteria showed high sensitivity and specificity for the oligonucleotide array, while two other species gave cross-reaction with the E. coli. Our results suggested that microarray analysis of foodborne infectious pathogens might be very useful for simultaneous identification of bacterial pathogens. The oligonucleotide array can also be applied to samples collected in clinical settings of foodborne infections. The superiority of oligonucleotide array over other tests lies on its rapidity, accuracy and efficiency in the diagnosis, treatment and control of foodborne infections.

Methodologic issues in the measurement of cytokines to elucidate the biological basis for cancer symptoms

Multiple concurrent symptoms are highly prevalent in patients with cancer. However, little is known about the relationships among these symptoms and their underlying mechanisms. A number of cytokines that are involved in the development of sickness behavior are hypothesized to be a mechanism for symptom clusters. Measurement of these cytokines would provide valuable information that could be used to elucidate mechanisms underlying the development of symptom clusters and the identification of potential targets for intervention studies. In this article, the authors explore several issues that warrant careful consideration when designing a research study involving the use of a cytokine as a biomarker in symptom cluster research. These issues include which molecules to measure, which specimens to collect, the timing of specimen collection and processing, and which technologies to use to measure the biomarker and the sensitivity and specificity of the assay system. The article begins with a brief discussion of cytokines and sickness behavior and the role of the cytokines in cancer-related symptoms.

Statistical expression deconvolution from mixed tissue samples

MOTIVATION

Global expression patterns within cells are used for purposes ranging from the identification of disease biomarkers to basic understanding of cellular processes. Unfortunately, tissue samples used in cancer studies are usually composed of multiple cell types and the non-cancerous portions can significantly affect expression profiles. This severely limits the conclusions that can be made about the specificity of gene expression in the cell-type of interest. However, statistical analysis can be used to identify differentially expressed genes that are related to the biological question being studied.

RESULTS

We propose a statistical approach to expression deconvolution from mixed tissue samples in which the proportion of each component cell type is unknown. Our method estimates the proportion of each component in a mixed tissue sample; this estimate can be used to provide estimates of gene expression from each component. We demonstrate our technique on xenograft samples from breast cancer research and publicly available experimental datasets found in the National Center for Biotechnology Information Gene Expression Omnibus repository.

AVAILABILITY

R code (http://www.r-project.org/) for estimating sample proportions is freely available to non-commercial users and available at http://www.med.miami.edu/medicine/x2691.xml.

Intergenic, gene terminal, and intragenic CpG islands in the human genome

Background

Recently, it has been discovered that the human genome contains many transcription start sites for non-coding RNA. Regulatory regions related to transcription of this non-coding RNAs are poorly studied. Some of these regulatory regions may be associated with CpG islands located far from transcription start-sites of any protein coding gene. The human genome contains many such CpG islands; however, until now their properties were not systematically studied.

Results

We studied CpG islands located in different regions of the human genome using methods of bioinformatics and comparative genomics. We have observed that CpG islands have a preference to overlap with exons, including exons located far from transcription start site, but usually extend well into introns. Synonymous substitution rate of CpG-containing codons becomes substantially reduced in regions where CpG islands overlap with protein-coding exons, even if they are located far downstream from transcription start site. CAGE tag analysis displayed frequent transcription start sites in all CpG islands, including those found far from transcription start sites of protein coding genes. Computational prediction and analysis of published ChIP-chip data revealed that CpG islands contain an increased number of sites recognized by Sp1 protein. CpG islands containing more CAGE tags usually also contain more Sp1 binding sites. This is especially relevant for CpG islands located in 3' gene regions. Various examples of transcription, confirmed by mRNAs or ESTs, but with no evidence of protein coding genes, were found in CAGE-enriched CpG islands located far from transcription start site of any known protein coding gene.

Conclusions

CpG islands located far from transcription start sites of protein coding genes have transcription initiation activity and display Sp1 binding properties. In exons, overlapping with these islands, the synonymous substitution rate of CpG containing codons is decreased. This suggests that these CpG islands are involved in transcription initiation, possibly of some non-coding RNAs.

Regulatory divergence in Drosophila melanogaster and D. simulans, a genomewide analysis of allele-specific expression

Species-specific regulation of gene expression contributes to the development and maintenance of reproductive isolation and to species differences in ecologically important traits. A better understanding of the evolutionary forces that shape regulatory variation and divergence can be developed by comparing expression differences among species and interspecific hybrids. Once expression differences are identified, the underlying genetics of regulatory variation or divergence can be explored. With the goal of associating cis and/or trans components of regulatory divergence with differences in gene expression, overall and allele-specific expression levels were assayed genomewide in female adult heads of Drosophila melanogaster, D. simulans, and their F1 hybrids. A greater proportion of cis differences than trans differences were identified for genes expressed in heads and, in accordance with previous studies, cis differences also explained a larger number of species differences in overall expression level. Regulatory divergence was found to be prevalent among genes associated with defense, olfaction, and among genes downstream of the Drosophila sex determination hierarchy. In addition, two genes, with critical roles in sex determination and micro RNA processing, Sxl and loqs, were identified as misexpressed in hybrid female heads, potentially contributing to hybrid incompatibility.

Sensitivity enhancement in DNA hybridization assay using gold nanoparticle-labeled two reporting probes

A simple and sensitive method for DNA detection using gold nanoparticle (AuNP) two-probe detection system (AuNP-TP) was developed. Preliminary experiment was carried out by optimizing slide types, blocking agents and hybridization times. Fluorescent-labeled probes were used along with AuNP-labeled probes to confirm specific binding event between target DNA and probes. The sensitivities between AuNP single-probe (AuNP-SP) and AuNP-TP systems using sandwich-typed assay were compared. The AuNP-TP on epoxide-coated (EP) slides increased sensitivity 1000-fold at the detection limit of 100fM when compared to the AuNP-SP. This result indicates that the assay sensitivity was simply enhanced by simultaneous adding two AuNP labeled probes which selectively recognize different regions of the target DNA. The concept of AuNP-TP could potentially be applied to a macroarray format to detect multiple DNA targets simultaneously; thereby making the assay becomes more affordable and more sensitive.

Transcript profiling during fiber development identifies pathways in secondary metabolism and cell wall structure that may contribute to cotton fiber quality

A global gene expression profiling study at different stages of fiber development was undertaken on two cotton species cultivated for fiber, Gossypium hirsutum (L.) and G. barbadense (L.). A large proportion of the genome was expressed during both fiber elongation and subsequent secondary cell wall thickening. There was a major shift in abundance of transcripts for gene regulation, cell organization and metabolism between fiber elongation and fiber thickening that was fundamentally similar in both species. Each stage had its own distinctive features represented by specific metabolic and regulatory genes, a number of which have been noted previously. Many of the genes expressed in the fibers were of a similar type and developmental expression to those seen in other fiber-producing plants, indicating a conservation of mechanisms of cell elongation and wall thickening across diverse plant genera. Secondary metabolism and pectin synthesis and modification genes were amongst the most statistically significant differentially expressed categories between the two species during fiber elongation. The gene profiles of the fiber thickening stage, however, were almost identical between the two species, suggesting that their different final fiber quality properties may be established at earlier stages of fiber development. Expression levels of representative phenylpropanoid and pectin modification genes showed high correlations with specific fiber properties in an inter-specific cotton recombinant inbred line (RIL) population, supporting a role in determining fiber quality.

An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systems

MOTIVATION

Distribution analysis is one of the most basic forms of statistical analysis. Thanks to improved analytical methods, accurate and extensive quantitative measurements can now be made of the mRNA, protein and metabolite from biological systems. Here, we report a large-scale analysis of the population abundance distributions of the transcriptomes, proteomes and metabolomes from varied biological systems.

RESULTS

We compared the observed empirical distributions with a number of distributions: power law, lognormal, loglogistic, loggamma, right Pareto-lognormal (PLN) and double PLN (dPLN). The best-fit for mRNA, protein and metabolite population abundance distributions was found to be the dPLN. This distribution behaves like a lognormal distribution around the centre, and like a power law distribution in the tails. To better understand the cause of this observed distribution, we explored a simple stochastic model based on geometric Brownian motion. The distribution indicates that multiplicative effects are causally dominant in biological systems. We speculate that these effects arise from chemical reactions: the central-limit theorem then explains the central lognormal, and a number of possible mechanisms could explain the long tails: positive feedback, network topology, etc. Many of the components in the central lognormal parts of the empirical distributions are unidentified and/or have unknown function. This indicates that much more biology awaits discovery.

Microarrays and high-throughput transcriptomic analysis in species with incomplete availability of genomic sequences

Microarrays produce a measurement of gene expression based on the relative measures of dye intensities that correspond to the amount of target RNA. This technology is fast developing and its application is expanding from Homo sapiens to a wide number of species, where enough information on sequences and annotations exist. Anyway, the number of species for which a dedicated platform exists is not high. The use of heterologous array hybridization, screening for gene expression in one species using an array developed for another one, is still quite frequent, even though cross-species microarray hybridization has raised many arguments. Some methods which are high throughput and do not rely on knowledge of the DNA/RNA sequence exist, namely serial analysis of gene expression (SAGE), Massively Parallel Signature Sequencing (MPSS) and deep sequencing of full transcriptome. Although very powerful, particularly the latter, they are still quite costly and cumbersome methods. In some species where genome sequences are largely unknown, several anonymous sequences are deposited in gene banks as a result of Expressed Sequence Tags (ESTs) sequencing projects. The ESTs databases represent a valuable knowledge that can be exploited with some bioinformatic effort to build species-specific microarrays. We present here a method of high-density in situ synthesized microarrays starting from available EST sequences in, Ovis aries. Our data indicate that the method is very efficient and can be easily extended to other species of which genetic sequences are present in public databases, but neglected so far with advanced devices like microarrays. As a perspective, the approach can be applied also to species of which no sequences are available to date, thanks to high-throughput deep sequencing methods.

c-Myc and Rel/NF-kappaB are the two master transcriptional systems activated in the latency III program of Epstein-Barr virus-immortalized B cells

The Epstein-Barr virus (EBV) latency III program imposed by EBNA2 and LMP1 is directly responsible for immortalization of B cells in vitro and is thought to mediate most immunodeficiency-related posttransplant lymphoproliferative diseases in vivo. To answer the question whether and how this proliferation program is related to c-Myc, we have established the transcriptome of both c-Myc and EBV latency III proliferation programs using a Lymphochip specialized microarray. In addition to EBV-positive latency I Burkitt lymphoma lines and lymphoblastoid cell lines (LCLs), we used an LCL expressing an estrogen-regulatable EBNA2 fusion protein (EREB2-5) and derivative B-cell lines expressing a constitutively active or tetracycline-regulatable c-myc gene. A total of 897 genes were found to be fourfold or more up- or downregulated in either one or both proliferation programs compared to the expression profile of resting EREB2-5 cells. A total of 661 (74%) of these were regulated similarly in both programs. Numerous repressed genes were known targets of STAT1, and most induced genes were known to be upregulated by c-Myc and to be involved in cell proliferation. In keeping with the gene expression patterns, inactivation of c-Myc by a chemical inhibitor or by conditional expression of dominant-negative c-Myc and Max mutants led to proliferation arrest of LCLs. Most genes differently regulated in both proliferation programs corresponded to genes induced by NF-kappaB in LCLs, and many of them coded for immunoregulatory and/or antiapoptotic molecules. Thus, c-Myc and NF-kappaB are the two main transcription factors responsible for the phenotype, growth pattern, and biological properties of cells driven into proliferation by EBV.