DNA chips: state-of-the art

ACDMBI: A deep learning model based on community division and multi-source biological information fusion predicts essential proteins

Accurately identifying essential proteins is vital for drug research and disease diagnosis. Traditional centrality methods and machine learning approaches often face challenges in accurately discerning essential proteins, primarily relying on information derived from protein-protein interaction (PPI) networks. Despite attempts by some researchers to integrate biological data and PPI networks for predicting essential proteins, designing effective integration methods remains a challenge. In response to these challenges, this paper presents the ACDMBI model, specifically designed to overcome the aforementioned issues. ACDMBI is comprised of two key modules: feature extraction and classification. In terms of capturing relevant information, we draw insights from three distinct data sources. Initially, structural features of proteins are extracted from the PPI network through community division. Subsequently, these features are further optimized using Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT). Moving forward, protein features are extracted from gene expression data utilizing Bidirectional Long Short-Term Memory networks (BiLSTM) and a multi-head self-attention mechanism. Finally, protein features are derived by mapping subcellular localization data to a one-dimensional vector and processing it through fully connected layers. In the classification phase, we integrate features extracted from three different data sources, crafting a multi-layer deep neural network (DNN) for protein classification prediction. Experimental results on brewing yeast data showcase the ACDMBI model's superior performance, with AUC reaching 0.9533 and AUPR reaching 0.9153. Ablation experiments further reveal that the effective integration of features from diverse biological information significantly boosts the model's performance.

ECDEP: identifying essential proteins based on evolutionary community discovery and subcellular localization

BACKGROUND

In cellular activities, essential proteins play a vital role and are instrumental in comprehending fundamental biological necessities and identifying pathogenic genes. Current deep learning approaches for predicting essential proteins underutilize the potential of gene expression data and are inadequate for the exploration of dynamic networks with limited evaluation across diverse species.

RESULTS

We introduce ECDEP, an essential protein identification model based on evolutionary community discovery. ECDEP integrates temporal gene expression data with a protein-protein interaction (PPI) network and employs the 3-Sigma rule to eliminate outliers at each time point, constructing a dynamic network. Next, we utilize edge birth and death information to establish an interaction streaming source to feed into the evolutionary community discovery algorithm and then identify overlapping communities during the evolution of the dynamic network. SVM recursive feature elimination (RFE) is applied to extract the most informative communities, which are combined with subcellular localization data for classification predictions. We assess the performance of ECDEP by comparing it against ten centrality methods, four shallow machine learning methods with RFE, and two deep learning methods that incorporate multiple biological data sources on Saccharomyces. Cerevisiae (S. cerevisiae), Homo sapiens (H. sapiens), Mus musculus, and Caenorhabditis elegans. ECDEP achieves an AP value of 0.86 on the H. sapiens dataset and the contribution ratio of community features in classification reaches 0.54 on the S. cerevisiae (Krogan) dataset.

CONCLUSIONS

Our proposed method adeptly integrates network dynamics and yields outstanding results across various datasets. Furthermore, the incorporation of evolutionary community discovery algorithms amplifies the capacity of gene expression data in classification.

The application of an applied electrical potential to generate electrical fields and forces to enhance affinity biosensors

Affinity biosensors play a crucial role in clinical diagnosis, pharmaceuticals, immunology, and other areas of human health. Affinity biosensors rely on the specific binding between target analytes and biological ligands such as antibodies, nucleic acids, aptamers, or other receptors to primarily generate electrochemical or optical signals. Considerable effort has been put into improving the performance of the affinity technologies to make them more sensitive, efficient and reproducible, of the many approaches electrokinetic phenomena are a viable option. In this perspective, studies that combine electrokinetic phenomena with affinity biosensor are discussed about their promise for achieving higher sensitivity and lower detection limit.

Gold Nanoparticle-Bridge Array to Improve DNA Hybridization Efficiency of SERS Sensors

The interfacial mass transfer rate of a target has a significant impact on the sensing performance. The surface reaction forms a concentration gradient perpendicular to the surface, wherein a slow mass transfer process decreases the interfacial reaction rate. In this work, we self-assembled gold nanoparticles (AuNPs) in the gap of a SiO₂ opal array to form a AuNP-bridge array. The diffusion paths of vertical permeability and a microvortex effect provided by the AuNP-bridge array synergistically improved the target mass transfer efficiency. As a proof of concept, we used DNA hybridization efficiency as a research model, and the surface-enhanced Raman spectroscopy (SERS) signal acted as a readout index. The experimental verification and theoretical simulation show that the AuNP-bridge array exhibited rapid mass transfer and high sensitivity. The DNA hybridization efficiency of the AuNP-bridge array was 15-fold higher than that of the AuNP-planar array. We believe that AuNP-bridge arrays can be potentially applied for screening drug candidates, genetic variations, and disease biomarkers.

A deep learning framework for identifying essential proteins based on multiple biological information

Background

Essential Proteins are demonstrated to exert vital functions on cellular processes and are indispensable for the survival and reproduction of the organism. Traditional centrality methods perform poorly on complex protein–protein interaction (PPI) networks. Machine learning approaches based on high-throughput data lack the exploitation of the temporal and spatial dimensions of biological information.

Results

We put forward a deep learning framework to predict essential proteins by integrating features obtained from the PPI network, subcellular localization, and gene expression profiles. In our model, the node2vec method is applied to learn continuous feature representations for proteins in the PPI network, which capture the diversity of connectivity patterns in the network. The concept of depthwise separable convolution is employed on gene expression profiles to extract properties and observe the trends of gene expression over time under different experimental conditions. Subcellular localization information is mapped into a long one-dimensional vector to capture its characteristics. Additionally, we use a sampling method to mitigate the impact of imbalanced learning when training the model. With experiments carried out on the data of Saccharomyces cerevisiae, results show that our model outperforms traditional centrality methods and machine learning methods. Likewise, the comparative experiments have manifested that our process of various biological information is preferable.

Conclusions

Our proposed deep learning framework effectively identifies essential proteins by integrating multiple biological data, proving a broader selection of subcellular localization information significantly improves the results of prediction and depthwise separable convolution implemented on gene expression profiles enhances the performance.

Oligonucleotide Synthesis on Porous Glass Resins Containing Activators

For the advancement of nucleic acid-related research, high-efficiency, low-cost synthesis of high-purity oligonucleotides is necessary. Herein, we introduced hydroxybenzotriazole (HOBt) activators on controlled pore glass resins to improve the efficiency of chain elongation (the synthesis efficiency increased from 48% without an activator to 92% with an activator). In particular, the use of the resin containing 6-trifluoromethyl HOBt with a linker of lauric acid and succinic acid significantly improved the synthesis efficiency for both DNA and RNA syntheses.

Synthesis and J-Dimer Formation of Tetrapyrazinoporphyrazines with Different Functional Groups for Potential Biomolecular Probe Applications

Though tetrapyrazinoporphyrazines (TPyzPzs) are generally presented as universal dark quenchers for oligonucleotide probes, the availability of TPyzPzs bearing different functional groups suitable for attachment to 3', and 5' ends or intrastrand positions remains rather limited. Therefore, a synthetic route to hexa(bis(2-methoxyethyl)amino) or hexa(diethylamino) TPyzPzs functionalized by an azide, hydroxy, or carboxy group or their combinations was developed. Studies of self-assembly into J-dimers in nonpolar solvents and their stability upon titration with pyridine (association constants, K_P values, ranging 0.32-12.7×10²  M^-1 ) revealed that smaller peripheral substituents and functionalization of TPyzPzs improves the stability of J-dimers. Φ_Δ and Φ_F were low for the monomers (Φ_F <0.0001, Φ_Δ <0.008, DMF) due to quenching by intramolecular charge transfer; however, they increased in nonpolar solvents and after self-assembly into J-dimer (up to Φ_F =0.027, Φ_Δ =0.28).

M2-like polarization of THP-1 monocyte-derived macrophages under chronic iron overload

Macrophages are characterized by phenotypical and functional heterogeneity. In different microenvironments, macrophages can polarize into two types: classically activated macrophages (M1) or alternatively activated macrophages (M2). M1 macrophages are a well-known bacteriostatic macrophage, and conversely, M2 macrophages may play an important role in tumor growth and tissue remodeling. M1 macrophages have been reported to have high intracellular iron stores, while M2 macrophages contain lower intracellular iron. It has been well-described that disturbances of iron homeostasis are associated with altered immune function. Thus, it is important to investigate if chronic iron overload is capable of polarizing macrophages. Human monocytic leukemia THP-1 cells were maintained in culture medium that contained 100 μM ferrous sulfate heptahydrate (FeSO₄) (I-THP-1) and differentiated into THP-1-derived macrophages (I-TDMs) by induction with phorbol 12-myristate 13-acetate (PMA). We characterized that I-TDMs not only enhanced the surface expression of CD163 and CD206 but also increased arginase and decreased iNOS protein expression. I-TDMs enhanced pSTAT6 expression and decreased pSTAT1 and NF-κB expressions. Furthermore, the gene expression profile of I-TDMs was comparable with M2 macrophages by performing human oligonucleotide DNA microarray analysis. Finally, functional assays demonstrated I-TDMs secreted higher levels of IL-10 but not M1 cytokines. Additionally, the conditional medium of I-TDMs had enhanced migration and increased invasion of A375 melanoma cells which was similar to the characteristics of tumor-associated macrophages. Taken together, we demonstrated that THP-1-derived macrophages polarized to a phenotype of M2-like characteristics when subjected to chronic iron overload.

Hydrogel based protein biochip for parallel detection of biomarkers for diagnosis of a Systemic Inflammatory Response Syndrome (SIRS) in human serum

The Systemic Inflammatory Response Syndrome (SIRS), a sepsis related inflammatory state, is a self-defense mechanism against specific and nonspecific stimuli. The six most extensively studied inflammatory biomarkers for the clinical diagnosis of SIRS are interleukin 4 (hIL-4), interleukin 6 (hIL-6), interleukin 10 (hIL-10), tumor necrosis factor alpha (hTNF-α), interferon gamma (hIFN-γ) and procalcitonin (hPCT). These biomarkers are naturally present (but usually only at low concentration) in SIRS infected patients [1, 2] and thus the development of a highly sensitive detection method is of major clinical interest. However, the existing analytical techniques are lacking in required analytical sensitivity and parallel determination of these biomarkers. We developed a fast, easy and cost-efficient protein microarray biochip where the capture molecules are attached on hydrogel spots, enabling SIRS diagnosis by parallel detection of these six clinically relevant biomarkers with a sample volume of 25 μl. With our hydrogel based protein microarray biochip we achieved a limit of detection for hIL-4 of 75.2 pg/ml, for hIL-6 of 45.1 pg/ml, for hIL-10 of 71.5 pg/ml, for hTNF-α of 56.7 pg/ml, for IFN-γ of 46.4 pg/ml and for hPCT of 1.1 ng/ml in spiked human serum demonstrating sufficient sensitivity for clinical usage. Additionally, we demonstrated successful detection of two relevant SIRS biomarkers in clinical patient samples with a turnaround time of the complete analysis from sample-to-answer in less than 200 minutes.

Biophysical Stimuli: A Review of Electrical and Mechanical Stimulation in Hyaline Cartilage

OBJECTIVE

Hyaline cartilage degenerative pathologies induce morphologic and biomechanical changes resulting in cartilage tissue damage. In pursuit of therapeutic options, electrical and mechanical stimulation have been proposed for improving tissue engineering approaches for cartilage repair. The purpose of this review was to highlight the effect of electrical stimulation and mechanical stimuli in chondrocyte behavior.

DESIGN

Different information sources and the MEDLINE database were systematically revised to summarize the different contributions for the past 40 years.

RESULTS

It has been shown that electric stimulation may increase cell proliferation and stimulate the synthesis of molecules associated with the extracellular matrix of the articular cartilage, such as collagen type II, aggrecan and glycosaminoglycans, while mechanical loads trigger anabolic and catabolic responses in chondrocytes.

CONCLUSION

The biophysical stimuli can increase cell proliferation and stimulate molecules associated with hyaline cartilage extracellular matrix maintenance.

Methicillin-Resistant Staphylococcus aureus: Molecular Characterization, Evolution, and Epidemiology

Staphylococcus aureus, a major human pathogen, has a collection of virulence factors and the ability to acquire resistance to most antibiotics. This ability is further augmented by constant emergence of new clones, making S. aureus a "superbug." Clinical use of methicillin has led to the appearance of methicillin-resistant S. aureus (MRSA). The past few decades have witnessed the existence of new MRSA clones. Unlike traditional MRSA residing in hospitals, the new clones can invade community settings and infect people without predisposing risk factors. This evolution continues with the buildup of the MRSA reservoir in companion and food animals. This review focuses on imparting a better understanding of MRSA evolution and its molecular characterization and epidemiology. We first describe the origin of MRSA, with emphasis on the diverse nature of staphylococcal cassette chromosome mec (SCCmec). mecA and its new homologues (mecB, mecC, and mecD), SCCmec types (13 SCCmec types have been discovered to date), and their classification criteria are discussed. The review then describes various typing methods applied to study the molecular epidemiology and evolutionary nature of MRSA. Starting with the historical methods and continuing to the advanced whole-genome approaches, typing of collections of MRSA has shed light on the origin, spread, and evolutionary pathways of MRSA clones.

New Contributions to Asarum Powder on Immunology Related Toxicity Effects in Lung

Objective. Asarum is widely used in clinical practice of Chinese medicine in the treatment of respiratory diseases. Many toxic ingredients (safrole, etc.) had been found in Asarum that show multiple visceral toxicities. In this study, we performed systematic investigation of expression profiles of genes to take a new insight into unclear mechanism of Asarum toxicities in lung. Methods. mRNAs were extracted from lungs of rats after intragastric administration with/without Asarum powders, and microarray assays were applied to investigate gene expression profiles. Differentially expressed genes with significance were selected to carry out GO analysis. Subsequently, quantitative PCRs were performed to verify the differential expression of Tmprss6, Prkag3, Nptx2, Antxr11, Klk11, Rag2, Olr77, Cd7, Il20, LOC69, C6, Ccl20, LOC68, and Cd163 in lung. Changes of Ampk, Bcl2, Caspase 3, Il1, Il20, Matriptase2, Nfκb, Nptx2, and Rag2 in the lung on protein level were verified by western blotting and immunohistochemistry. Results. Compared with control group, the estimated organ coefficients were relatively increased in Asarum group. Results of GO analysis showed that a group of immune related genes in lung were expressed abnormally. The result of PCRs showed that Ccl20 was downregulated rather than other upregulated genes in the Asarum group. Western blotting and immunohistochemistry images showed that Asarum can upregulate the expression of Ampk, Caspase 3, Il1, Il20, Matriptase2, Nfκb, and Rag2 and downregulate the expression of Bcl2 in lung. Conclusion. Our data suggest that expressions of immune related genes in lung were selectively altered by Asarum. Therefore, inflammatory response was active, by regulating Caspase 3, Il1, Il20, Matriptase2, Nfκb, Rag2, Tmprss6, Prkag3, Nptx2, Antxr1, Klk11, Olr77, Cd7, LOC69, C6, LOC68, Cd163, Ampk, Bcl2, and Ccl20. Our study indicated that inflammatory factors take effect in lung toxicity caused by Asarum, which provides a new insight into molecular mechanism of Asarum toxicities in lung.

A rapid and concise setup for the fast screening of FRET pairs using bioorthogonalized fluorescent dyes

One of the most popular means to follow interactions between bio(macro)molecules is Förster resonance energy transfer (FRET). There is large interest in widening the selection of fluorescent FRET pairs especially in the region of the red/far red range, where minimal autofluorescence is encountered. A set of bioorthogonally applicable fluorescent dyes, synthesized recently in our lab, were paired (Cy3T/Cy5T; Cy1A/Cy3T and Cy1A/CBRD1A) based on their spectral characteristics in order to test their potential in FRET applications. For fast elaboration of the selected pairs we have created a bioorthogonalized platform based on complementary 17-mer DNA oligomers. The cyclooctynylated strands were modified nearly quantitatively with the fluorophores via bioorthogonal chemistry steps, using azide- (Cy1; CBRD1) or tetrazine-modified (Cy3; Cy5) dyes. Reactions were followed by capillary electrophoresis using a method specifically developed for this project. FRET efficiencies of the fluorescent dye pairs were compared both in close proximity (5' and 3' matched) and at larger distance (5' and 5' matched). The specificity of FRET signals was further elaborated by denaturation and competition studies. Cy1A/Cy3T and Cy1A/CBRD1A introduced here as novel FRET pairs are highly recommended for FRET applications based on the significant changes in fluorescence intensities of the donor and acceptor peaks. Application of one of the FRET pairs was demonstrated in live cells, transfected with labeled oligos. Furthermore, the concise installation of the dyes allows for efficient fluorescence modification of any selected DNA strands as was demonstrated in the construction of Cy3T labeled oligomers, which were used in the FISH-based detection of Helicobacter pylori.

Innovations in biomedical nanoengineering: nanowell array biosensor

Nanostructured biosensors have pioneered biomedical engineering by providing highly sensitive analyses of biomolecules. The nanowell array (NWA)-based biosensing platform is particularly innovative, where the small size of NWs within the array permits extremely profound sensing of a small quantity of biomolecules. Undoubtedly, the NWA geometry of a gently-sloped vertical wall is critical for selective docking of specific proteins without capillary resistances, and nanoprocessing has contributed to the fabrication of NWA electrodes on gold substrate such as molding process, e-beam lithography, and krypton-fluoride (KrF) stepper semiconductor method. The Lee group at the Mara Nanotech has established this NW-based biosensing technology during the past two decades by engineering highly sensitive electrochemical sensors and providing a broad range of detection methods from large molecules (e.g., cells or proteins) to small molecules (e.g., DNA and RNA). Nanosized gold dots in the NWA enhance the detection of electrochemical biosensing to the range of zeptomoles in precision against the complementary target DNA molecules. In this review, we discuss recent innovations in biomedical nanoengineering with a specific focus on novel NWA-based biosensors. We also describe our continuous efforts in achieving a label-free detection without non-specific binding while maintaining the activity and stability of immobilized biomolecules. This research can lay the foundation of a new platform for biomedical nanoengineering systems.

Transcriptomic Studies of the Effect of nod Gene-Inducing Molecules in Rhizobia: Different Weapons, One Purpose

Simultaneous quantification of transcripts of the whole bacterial genome allows the analysis of the global transcriptional response under changing conditions. RNA-seq and microarrays are the most used techniques to measure these transcriptomic changes, and both complement each other in transcriptome profiling. In this review, we exhaustively compiled the symbiosis-related transcriptomic reports (microarrays and RNA sequencing) carried out hitherto in rhizobia. This review is specially focused on transcriptomic changes that takes place when five rhizobial species, Bradyrhizobium japonicum (=diazoefficiens) USDA 110, Rhizobium leguminosarum biovar viciae 3841, Rhizobium tropici CIAT 899, Sinorhizobium (=Ensifer) meliloti 1021 and S. fredii HH103, recognize inducing flavonoids, plant-exuded phenolic compounds that activate the biosynthesis and export of Nod factors (NF) in all analysed rhizobia. Interestingly, our global transcriptomic comparison also indicates that each rhizobial species possesses its own arsenal of molecular weapons accompanying the set of NF in order to establish a successful interaction with host legumes.

Real-time reliable determination of binding kinetics of DNA hybridization using a multi-channel graphene biosensor

Reliable determination of binding kinetics and affinity of DNA hybridization and single-base mismatches plays an essential role in systems biology, personalized and precision medicine. The standard tools are optical-based sensors that are difficult to operate in low cost and to miniaturize for high-throughput measurement. Biosensors based on nanowire field-effect transistors have been developed, but reliable and cost-effective fabrication remains a challenge. Here, we demonstrate that a graphene single-crystal domain patterned into multiple channels can measure time- and concentration-dependent DNA hybridization kinetics and affinity reliably and sensitively, with a detection limit of 10 pM for DNA. It can distinguish single-base mutations quantitatively in real time. An analytical model is developed to estimate probe density, efficiency of hybridization and the maximum sensor response. The results suggest a promising future for cost-effective, high-throughput screening of drug candidates, genetic variations and disease biomarkers by using an integrated, miniaturized, all-electrical multiplexed, graphene-based DNA array.

Monitoring DNA binding and single-base mismatches accurately in real time is difficult, especially for miniaturized devices. Here the authors report a graphene field-effect transistor array capable of reliably measuring DNA hybridization kinetics and affinity at the picomolar level.

Gene Expression Profiling in Fish Toxicology: A Review

In this review, we present an overview of transcriptomic responses to chemical exposures in a variety of fish species. We have discussed the use of several molecular approaches such as northern blotting, differential display reverse transcription-polymerase chain reaction (DDRT-PCR), suppression subtractive hybridization (SSH), real time quantitative PCR (RT-qPCR), microarrays, and next-generation sequencing (NGS) for measuring gene expression. These techniques have been mainly used to measure the toxic effects of single compounds or simple mixtures in laboratory conditions. In addition, only few studies have been conducted to examine the biological significance of differentially expressed gene sets following chemical exposure. Therefore, future studies should focus more under field conditions using a multidisciplinary approach (genomics, proteomics and metabolomics) to understand the synergetic effects of multiple environmental stressors and to determine the functional significance of differentially expressed genes. Nevertheless, recent developments in NGS technologies and decreasing costs of sequencing holds the promise to uncover the complexity of anthropogenic impacts and biological effects in wild fish populations.

Emergence through delicate balance between the steric factor and molecular orientation: a highly bright and photostable DNA marker for real-time monitoring of cell growth dynamics

A bright and biostable molecular fluorogenic material for real-time monitoring of in vitro cellular growth dynamics.

Real-time, label-free characterization of oligosaccharide-binding proteins using carbohydrate microarrays and an ellipsometry-based biosensor

Carbohydrates present on cell surfaces mediate cell behavior through interactions with other biomolecules. Due to their structural complexity, diversity, and heterogeneity, it is difficult to fully characterize a variety of carbohydrates and their binding partners. As a result, novel technologies for glycomics applications have been developed, including carbohydrate microarrays and label-free detection methods. In this paper, we report using the combination of oligosaccharide microarrays and the label-free oblique-incidence reflectivity difference (OI-RD) microscopy for real-time characterization of oligosaccharide binding proteins. Aminated human milk oligosaccharides were immobilized on epoxy-coated glass substrates as microarrays for reactions with Family 1 of solute binding proteins from Bifidobacterium longum subsp. infantis (B. infantis). Binding affinities of these protein-oligosaccharide interactions showed preferences of Family 1 of solute binding proteins to host glycans, which helps in characterizing the complex process of human milk oligosaccharides foraging by B. infantis.

Clickable Polymeric Coating for Glycan Microarrays

The interaction of carbohydrates with a variety of biological targets, including antibodies, proteins, viruses, and cells are of utmost importance in many aspects of biology. Glycan microarrays are increasingly used to determine the binding specificity of glycan-binding proteins. In this study, a novel microarray support is reported for the fabrication of glycan arrays that combines the higher sensitivity of a layered Si-SiO₂ surface with a novel polymeric coating easily modifiable by subsequent click reaction. The alkyne-containing copolymer, adsorbed from an aqueous solution, produces a coating by a single step procedure and serves as a soft, tridimensional support for the oriented immobilization of carbohydrates via azide/alkyne Cu (I) catalyzed "click" reaction. The advantages of a functional 3D polymer coating making use of a click chemistry immobilization are combined with the high fluorescence sensitivity and superior signal-to-noise ratio of a Si-SiO₂ substrate. The proposed approach enables the attachment of complex sugars on a silicon oxide surface by a method that does not require skilled personnel and chemistry laboratories.

Hybrid Valve Structure for High-Throughput, Low-Volume Liquid-Handling Applications

A hybrid valve that integrates precision microfluidics for fluid routing, high-speed valving for fluid switching, and reagent-jetting devices for metering the fluid dispenses is described. The hybrid valve enables parallel switching between aspiration and dispense modes for multiple sample streams. This unique valve structure addresses many of the concerns with handling microscale volumes, including efficient use of samples, degradation of ink jet valves and speed of operation. A broad range of volumes can be manipulated with excellent reproducibility. The hybrid valve can be configured for a variety of applications. Pick-and-place aspiration and dispensing of unique reagents and rapid dispensing of a common reagent are possible. Together these features lead to higher-speed transfer of smaller volumes of reagent.

The unexpected complexity of bacterial genomes

Gene organization and control are described by models conceived in the 1960s. These models explain basic gene regulatory mechanisms and underpin current genome annotation. However, such models struggle to explain recent genome-scale observations. For example, accounts of RNA synthesis initiating within genes, widespread antisense transcription and non-canonical DNA binding by gene regulatory proteins are difficult to reconcile with traditional thinking. As a result, unexpected observations have often been dismissed and downstream consequences ignored. In this paper I will argue that, to fully understand the biology of bacterial chromosomes, we must embrace their hidden layers of complexity.

Selenium Incorporated Cationic Organochalcogen: Live Cell Compatible and Highly Photostable Molecular Stain for Imaging and Localization of Intracellular DNA

Successful integration of selenium unit into a newly designed cationic chemical architecture led to the development of a highly photostable molecular maker PA5 to be used in fluorescence microscopy as cellular nucleus staining agent for longer duration imaging under continuous laser illumination. Adaptation of a targeted single-atom modification strategy led to the development of a series of proficient DNA light-up probes (PA1-PA5). Further, their comparative photophysical studies in the presence of DNA revealed the potential of electron rich heteroatoms of chalcogen family in improving binding efficiency and specificity of molecular probes toward DNA. The findings of cell studies confirmed the outstanding cell compatibility of probe PA5 in terms of cell permeability, biostability, and extremely low cytotoxicity. Moreover, the photostability experiment employing continuous laser illumination in solution phase as well as in cell assay (both fixed and live cells) revealed the admirable photobleaching resistance of PA5. Finally, while investigating the phototoxicity of PA5, the probe was found not to exhibit light-induced toxicity even when irradiated for longer duration. All these experimental results demonstrated the promising standing of PA5 as a futuristic cell compatible potential stain for bioimaging and temporal profiling of DNA.

A microarray-based approach to evaluate the functional significance of protein-binding motifs

Intracellular proteins comprise numerous peptide motifs that interact with protein-binding domains. However, using sequence information alone, the identification of functionally relevant interaction motifs remains a challenge. Here, we present a microarray-based approach for the evaluation of peptides as protein-binding motifs. To this end, peptides corresponding to protein interaction motifs were spotted as a microarray. First, peptides were titrated with a pan-specific binder and the apparent K_d value of this binder for each peptide was determined. For phosphotyrosine-containing peptides, an anti-phosphotyrosine antibody was employed. Then, in the presence of the pan-specific binder, arrays were competitively titrated with cell lysate and competition constants were determined. Using the Cheng-Prusoff equation, binding constants for the pan-specific binder and inhibition constants for the lysates were converted into affinity constants for the lysate. We experimentally validate this method using a phosphotyrosine-binding SH2 domain as a further reference. Furthermore, strong binders correlated with binding motifs engaging in numerous interactions as predicted by Scansite. This method provides a highly parallel and robust approach to identify peptides corresponding to interaction motifs with strong binding capacity for proteins in the cell lysate.

Graphical Abstract

An anti-fouling aptasensor for detection of thrombin by dual polarization interferometry

An anti-fouling surface was designed to effectively resist nonspecific protein adsorption using dual polarization interferometry, based on which the aptasensor for detection of thrombin was fabricated according to the specific interaction between thrombin and its 15-mer aptamer.

Biomolecular recognition at the cellular level: geometrical and chemical functionality dependence of a low phototoxic cationic probe for DNA imaging

Potential application of a biocompatible and low phototoxic cationic stain with semilunar geometry for longer duration visualization of cellular DNA is reported.

Platforms Formed from a Three-Dimensional Cu-Based Zwitterionic Metal-Organic Framework and Probe ss-DNA: Selective Fluorescent Biosensors for Human Immunodeficiency Virus 1 ds-DNA and Sudan Virus RNA Sequences

We herein report a water-stable three-dimensional Cu-based metal-organic framework (MOF) 1 supported by a tritopic quaternized carboxylate and 4,4'-dipyridyl sulfide as an ancillary ligand. This MOF exhibits unique pore shapes with aromatic rings, positively charged pyridinium and unsaturated Cu(II) cation centers, free carboxylates, tessellating H2O, and coordinating SO4(2-) on the pore surface. Compound 1 can interact with two carboxyfluorescein (FAM)-labeled single-stranded DNA sequences (probe ss-DNA, delineated as P-DNA) through electrostatic, π-stacking, and/or hydrogen-bonding interactions to form two P-DNA@1 systems, and thus quench the fluorescence of FAM via a photoinduced electron-transfer process. These P-DNA@1 systems can be used as effective fluorescent sensors for human immunodeficiency virus 1 double-stranded DNA and Sudan virus RNA sequences, respectively, with detection limits of 196 and 73 pM, respectively.

Oligonucleotide Immobilization and Hybridization on Aldehyde-Functionalized Poly(2-hydroxyethyl methacrylate) Brushes

DNA biosensing requires high oligonucleotide binding capacity interface chemistries that can be tuned to maximize probe presentation as well as hybridization efficiency. This contribution investigates the feasibility of aldehyde-functionalized poly(2-hydroxyethyl methacrylate) (PHEMA) brush-based interfaces for oligonucleotide binding and hybridization. These polymer brushes, which allow covalent immobilization of oligonucleotides, are prepared by surface-initiated atom transfer radical polymerization (SI-ATRP) of HEMA followed by a postpolymerization oxidation step to generate side chain aldehyde groups. A series of polymer brushes covering a range of film thicknesses and grafting densities was investigated with regard to their oligonucleotide binding capacity as well as their ability to support oligonucleotide hybridization. Densely grafted brushes were found to have probe oligonucleotide binding capacities of up to ∼30 pmol/cm(2). Increasing the thickness of these densely grafted brush films, however, resulted in a decrease in the oligonucleotide binding capacity. Less densely grafted brushes possess binding capacities of ∼10 pmol/cm(2), which did not significantly depend on film thickness. The oligonucleotide hybridization efficiencies, however, were highest (93%) on those brushes that present the lowest surface concentration of the probe oligonucleotide. These results highlight the importance of optimizing the probe oligonucleotide surface concentration and binding interface chemistry. The versatility and tunability of the PHEMA-based brushes presented herein makes these films a very attractive platform for the immobilization and hybridization of oligonucleotides.

PNA Molecular Beacons Assembled by Post-Synthetic Click Chemistry Functionalization

To avoid the tedious synthesis of functionalized peptide nucleic acid (PNA) monomers for probe development, we proposed a simple approach to modify PNA oligomers by post-synthetic on-resin click chemistry. PNA molecular beacons (MBs) were prepared by incorporation of azide-containing monomers into the oligomer by automatic solid-phase peptide synthesis and subsequent derivatization with pyrene moieties by copper-catalyzed azide-alkyne cycloaddition. Two pyrene-based quencher-free PNA molecular beacons, a stemless MB and one possessing a stem-loop structure, targeting a portion of the cystic fibrosis gene, were successfully synthesized by using this method. Fluorescence studies showed that the stem-loop MB exhibited better discrimination of changes in excimer/monomer ratios as compared to the stemless MB construct.

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.

Focused upon hybridization: rapid and high sensitivity detection of DNA using isotachophoresis and peptide nucleic acid probes

We present a novel assay for rapid and high sensitivity detection of nucleic acids without amplification. Utilizing the neutral backbone of peptide nucleic acids (PNA), our method is based on the design of low electrophoretic mobility PNA probes, which do not focus under isotachophoresis (ITP) unless bound to their target sequence. Thus, background noise associated with free probes is entirely eliminated, significantly improving the signal-to-noise ratio while maintaining a simple single-step assay requiring no amplification steps. We provide a detailed analytical model and experimentally demonstrate the ability to detect targets as short as 17 nucleotides (nt) and a limit of detection of 100 fM with a dynamic range of 5 decades. We also demonstrate that the assay can be successfully implemented for detection of DNA in human serum without loss of signal. The assay requires 15 min to complete, and it could potentially be used in applications where rapid and highly sensitive amplification-free detection of nucleic acids is desired.

Structural Characterization of Single-Stranded DNA Monolayers Using Two-Dimensional Sum Frequency Generation Spectroscopy

DNA-covered materials are important in technological applications such as biosensors and microarrays, but obtaining structural information on surface-bound biomolecules is experimentally challenging. In this paper, we structurally characterize single-stranded DNA monolayers of poly(thymine) from 10 to 25 bases in length with an emerging surface technique called two-dimensional sum frequency generation (2D SFG) spectroscopy. These experiments are carried out by adding a mid-IR pulse shaper to a femtosecond broad-band SFG spectrometer. Cross peaks and 2D line shapes in the 2D SFG spectra provide information about structure and dynamics. Because the 2D SFG spectra are heterodyne detected, the monolayer spectra can be directly compared to 2D infrared (2D IR) spectra of poly(thymine) in solution, which aids interpretation. We simulate the 2D SFG spectra using DFT calculations and an excitonic Hamiltonian that relates the molecular geometry to the vibrational coupling. Intrabase cross peaks help define the orientation of the bases and interbase cross peaks, created by coupling between bases, and resolves features not observed in 1D SFG spectra that constrain the relative geometries of stacked bases. We present a structure for the poly(T) oligomer that is consistent with the 2D SFG data. These experiments provide insight into the DNA monolayer structure and set precedent for studying complex biomolecules on surfaces with 2D SFG spectroscopy.

Straightforward Micropatterning of Oligonucleotides in Microfluidics by Novel Spin-On ZrO₂ Surfaces

DNA biochip assays often require immobilization of bioactive molecules on solid surfaces. A simple biofunctionalization protocol and precise spatial binding represent the two major challenges in order to obtain localized region specific biopatterns into lab-on-a-chip (LOC) systems. In this work, a simple strategy to anchor oligonucleotides on microstructured areas and integrate the biomolecules patterns within microfluidic channels is reported. A photosensitive ZrO2 system is proposed as an advanced platform and versatile interface for specific positioning and oriented immobilization of phosphorylated DNA. ZrO2 sol-gel structures were easily produced on fused silica by direct UV lithography, allowing a simple and fast patterning process with different geometries. A thermal treatment at 800 °C was performed to crystallize the structures and maximize the affinity of DNA to ZrO2. Fluorescent DNA strands were selectively immobilized on the crystalline patterns inside polydimethylsiloxane (PDMS) microchannels, allowing high specificity and rapid hybridization kinetics. Hybridization tests confirmed the correct probe anchoring and the bioactivity retention, while denaturation experiments demonstrated the possibility of regenerating the surface.

DNA-Based Nanobiosensors as an Emerging Platform for Detection of Disease

Detection of disease at an early stage is one of the biggest challenges in medicine. Different disciplines of science are working together in this regard. The goal of nanodiagnostics is to provide more accurate tools for earlier diagnosis, to reduce cost and to simplify healthcare delivery of effective and personalized medicine, especially with regard to chronic diseases (e.g., diabetes and cardiovascular diseases) that have high healthcare costs. Up-to-date results suggest that DNA-based nanobiosensors could be used effectively to provide simple, fast, cost-effective, sensitive and specific detection of some genetic, cancer, and infectious diseases. In addition, they could potentially be used as a platform to detect immunodeficiency, and neurological and other diseases. This review examines different types of DNA-based nanobiosensors, the basic principles upon which they are based and their advantages and potential in diagnosis of acute and chronic diseases. We discuss recent trends and applications of new strategies for DNA-based nanobiosensors, and emphasize the challenges in translating basic research to the clinical laboratory.

Carbon Substrates: A Stable Foundation for Biomolecular Arrays

Since their advent in the early 1990s, microarray technologies have developed into a powerful and ubiquitous platform for biomolecular analysis. Microarrays consist of three major elements: the substrate upon which they are constructed, the chemistry employed to attach biomolecules, and the biomolecules themselves. Although glass substrates and silane-based attachment chemistries are used for the vast majority of current microarray platforms, these materials suffer from severe limitations in stability, due to hydrolysis of both the substrate material itself and of the silyl ether linkages employed for attachment. These limitations in stability compromise assay performance and render impossible many potential microarray applications. We describe here a suite of alternative carbon-based substrates and associated attachment chemistries for microarray fabrication. The substrates themselves, as well as the carbon-carbon bond-based attachment chemistries, offer greatly increased chemical stability, enabling a myriad of novel applications.

A Novel Multipeptide Microarray for the Specific and Sensitive Mapping of Linear IgE-Binding Epitopes of Food Allergens

BACKGROUND

The identification of B-cell epitopes of food allergens can possibly lead to novel diagnostic tools and therapeutic reagents for food allergy. We sought to develop a flexible, low-tech, cost-effective and reproducible multipeptide microarray for the research environment to enable large-scale screening of IgE epitopes of food allergens.

METHODS

Overlapping peptides (15-mer, 4 amino acid offset) covering the primary sequence of either peanut allergen Ara h 1 or all 3 subunits of the soybean allergen Gly m 5 were simultaneously synthesized in-house on a porous cellulose matrix. Identical peptide microarrays created with up to 384 duplicate peptide-cellulose microspots each were investigated for specificity and sensitivity in IgE immunodetection and in direct experimental comparison to the formerly established SPOT™ membrane technique.

RESULTS

The in-house microarray identified with 98% reproducibility the same IgE-binding peptides as the SPOT™ membrane technique. Additional IgE-binding peptides were identified using the microarray. While the sensitivity was increased between 2- and 20-fold, the amount of human serum required was reduced by at least two thirds over the SPOT™ membrane technique using the microarray. After subtraction of the potential background, we did not observe non-specific binding to the presented peptides on microarray.

CONCLUSIONS

The novel peptide microarray allows simple and cost-effective screening for potential epitopes of large allergenic legume seed storage proteins, and it could be adapted for other food allergens as well, to study allergenic epitopes at the individual subject level in large paediatric and adult study groups of food allergic subjects.

Correcting positional correlations in Affymetrix® genome chips

We report and model a previously undescribed systematic error causing spurious excess correlations that depend on the distance between probes on Affymetrix® microarrays. The phenomenon affects pairs of features with large chip separations, up to over 100 probes apart. The effect may have a significant impact on analysis of correlations in large collections of expression data, where the systematic experimental errors are repeated in many data sets. Examples of such studies include analysis of functions and interactions in groups of genes, as well as global properties of genomes. We find that the average correlations between probes on Affymetrix microarrays are larger for smaller chip distances, which points out to a previously undescribed positional artifact. The magnitude of the artifact depends on the design of the chip, and we find it to be especially high for the yeast S98 microarray, where spurious excess correlations reach 0.1 at a distance of 50 probes. We have designed an algorithm to correct this bias and provide new data sets with the corrected expression values. This algorithm was successfully implemented to remove the positional artifact from the S98 chip data while preserving the integrity of the data.

Fabrication of micropatterned polymeric nanowire arrays for high-resolution reagent localization and topographical cellular control

Herein, we present a novel approach for the fabrication of micropatterned polymeric nanowire arrays that addresses the current need for scalable and customizable polymer nanofabrication. We describe two variations of this approach for the patterning of nanowire arrays on either flat polymeric films or discrete polymeric microstructures and go on to investigate biological applications for the resulting polymeric features. We demonstrate that the micropatterned arrays of densely packed nanowires facilitate rapid, low-waste drug and reagent localization with micron-scale resolution as a result of their high wettability. We also show that micropatterned nanowire arrays provide hierarchical cellular control by simultaneously directing cell shape on the micron scale and influencing focal adhesion formation on the nanoscale. This nanofabrication approach has potential applications in scaffold-based cellular control, biological assay miniaturization, and biomedical microdevice technology.

Microarrays for identifying binding sites and probing structure of RNAs

Oligonucleotide microarrays are widely used in various biological studies. In this review, application of oligonucleotide microarrays for identifying binding sites and probing structure of RNAs is described. Deep sequencing allows fast determination of DNA and RNA sequence. High-throughput methods for determination of secondary structures of RNAs have also been developed. Those methods, however, do not reveal binding sites for oligonucleotides. In contrast, microarrays directly determine binding sites while also providing structural insights. Microarray mapping can be used over a wide range of experimental conditions, including temperature, pH, various cations at different concentrations and the presence of other molecules. Moreover, it is possible to make universal microarrays suitable for investigations of many different RNAs, and readout of results is rapid. Thus, microarrays are used to provide insight into oligonucleotide sequences potentially able to interfere with biological function. Better understanding of structure-function relationships of RNA can be facilitated by using microarrays to find RNA regions capable to bind oligonucleotides. That information is extremely important to design optimal sequences for antisense oligonucleotides and siRNA because both bind to single-stranded regions of target RNAs.