Selection, characterization, and biosensing applications of DNA aptamers targeting cyanotoxin BMAA.

Scientists have established a connection between environmental exposure to toxins like ß-N-methylamino-l-alanine (BMAA) and a heightened risk of neurodegenerative disorders. BMAA is a byproduct from certain strains of cyanobacteria that are present in ecosystems worldwide and is renowned for its bioaccumulation and biomagnification in seafood. The sensitivity, selectivity, and reproducibility of the current analytical techniques are insufficient to support efforts regarding food safety and environment monitoring adequately. This work outlines the in vitro selection of BMAA-specific DNA aptamers via the systematic evolution of ligands through exponential enrichment (SELEX). Screening and characterization of the full-length aptamers was achieved using the SYBR Green (SG) fluorescence displacement assay. Aptamers BMAA_159 and BMAA_165 showed the highest binding affinities, with dissociation constants (Kd) of 2.2 ± 0.1 µM and 0.32 ± 0.02 µM, respectively. After truncation, the binding affinity was confirmed using a BMAA-conjugated fluorescence assay. The Kd values for BMAA_159_min and BMAA_165_min were 6 ± 1 µM and 0.63 ± 0.02 µM, respectively. Alterations in the amino proton region studied using solution nuclear magnetic resonance (NMR) provided further evidence of aptamer-target binding. Additionally, circular dichroism (CD) spectroscopy revealed that BMAA_165_min forms hybrid G-quadruplex (G4) structures. Finally, BMAA_165_min was used in the development of an electrochemical aptamer-based (EAB) sensor that accomplished sensitive and selective detection of BMAA with a limit of detection (LOD) of 1.13 ± 0.02 pM.

Decoding Non-coding Variants: Recent Approaches to Studying Their Role in Gene Regulation and Human Diseases.

Genome-wide association studies (GWAS) have mapped over 90% of disease- and quantitative-trait-associated variants within the non-coding genome. Non-coding regulatory DNA (e.g., promoters and enhancers) and RNA (e.g., 5' and 3' UTRs and splice sites) are essential in regulating temporal and tissue-specific gene expressions. Non-coding variants can potentially impact the phenotype of an organism by altering the molecular recognition of the cis-regulatory elements, leading to gene dysregulation. However, determining causality between non-coding variants, gene regulation, and human disease has remained challenging. Experimental and computational methods have been developed to understand the molecular mechanism involved in non-coding variant interference at the transcriptional and post-transcriptional levels. This review discusses recent approaches to evaluating disease-associated single-nucleotide variants (SNVs) and determines their impact on transcription factor (TF) binding, gene expression, chromatin conformation, post-transcriptional regulation, and translation.

Prioritizing cardiovascular disease-associated variants altering NKX2-5 and TBX5 binding through an integrative computational approach.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are heavily influenced by genetic factors. Genome-wide association studies have mapped >90% of CVD-associated variants within the noncoding genome, which can alter the function of regulatory proteins, such as transcription factors (TFs). However, due to the overwhelming number of single-nucleotide polymorphisms (SNPs) (>500,000) in genome-wide association studies, prioritizing variants for in vitro analysis remains challenging. In this work, we implemented a computational approach that considers support vector machine (SVM)-based TF binding site classification and cardiac expression quantitative trait loci (eQTL) analysis to identify and prioritize potential CVD-causing SNPs. We identified 1535 CVD-associated SNPs within TF footprints and putative cardiac enhancers plus 14,218 variants in linkage disequilibrium with genotype-dependent gene expression in cardiac tissues. Using ChIP-seq data from two cardiac TFs (NKX2-5 and TBX5) in human-induced pluripotent stem cell-derived cardiomyocytes, we trained a large-scale gapped k-mer SVM model to identify CVD-associated SNPs that altered NKX2-5 and TBX5 binding. The model was tested by scoring human heart TF genomic footprints within putative enhancers and measuring in vitro binding through electrophoretic mobility shift assay. Five variants predicted to alter NKX2-5 (rs59310144, rs6715570, and rs61872084) and TBX5 (rs7612445 and rs7790964) binding were prioritized for in vitro validation based on the magnitude of the predicted change in binding and are in cardiac tissue eQTLs. All five variants altered NKX2-5 and TBX5 DNA binding. We present a bioinformatic approach that considers tissue-specific eQTL analysis and SVM-based TF binding site classification to prioritize CVD-associated variants for in vitro analysis.

Prioritizing Cardiovascular Disease-Associated Variants Altering NKX2-5 Binding through an Integrative Computational Approach.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are heavily influenced by genetic factors. Genome-wide association studies (GWAS) have mapped > 90% of CVD-associated variants within the non-coding genome, which can alter the function of regulatory proteins, like transcription factors (TFs). However, due to the overwhelming number of GWAS single nucleotide polymorphisms (SNPs) (>500,000), prioritizing variants for in vitro analysis remains challenging. In this work, we implemented a computational approach that considers support vector machine (SVM)-based TF binding site classification and cardiac expression quantitative trait loci (eQTL) analysis to identify and prioritize potential CVD-causing SNPs. We identified 1,535 CVD-associated SNPs that occur within human heart footprints/enhancers and 9,309 variants in linkage disequilibrium (LD) with differential gene expression profiles in cardiac tissue. Using hiPSC-CM ChIP-seq data from NKX2-5 and TBX5, two cardiac TFs essential for proper heart development, we trained a large-scale gapped k-mer SVM (LS-GKM-SVM) predictive model that can identify binding sites altered by CVD-associated SNPs. The computational predictive model was tested by scoring human heart footprints and enhancers in vitro through electrophoretic mobility shift assay (EMSA). Three variants (rs59310144, rs6715570, and rs61872084) were prioritized for in vitro validation based on their eQTL in cardiac tissue and LS-GKM-SVM prediction to alter NKX2-5 DNA binding. All three variants altered NKX2-5 DNA binding. In summary, we present a bioinformatic approach that considers tissue-specific eQTL analysis and SVM-based TF binding site classification to prioritize CVD-associated variants for in vitro experimental analysis.

Hidden modes of DNA binding by human nuclear receptors.

Human nuclear receptors (NRs) are a superfamily of ligand-responsive transcription factors that have central roles in cellular function. Their malfunction is linked to numerous diseases, and the ability to modulate their activity with synthetic ligands has yielded 16% of all FDA-approved drugs. NRs regulate distinct gene networks, however they often function from genomic sites that lack known binding motifs. Here, to annotate genomic binding sites of known and unexamined NRs more accurately, we use high-throughput SELEX to comprehensively map DNA binding site preferences of all full-length human NRs, in complex with their ligands. Furthermore, to identify non-obvious binding sites buried in DNA-protein interactomes, we develop MinSeq Find, a search algorithm based on the MinTerm concept from electrical engineering and digital systems design. The resulting MinTerm sequence set (MinSeqs) reveal a constellation of binding sites that more effectively annotate NR-binding profiles in cells. MinSeqs also unmask binding sites created or disrupted by 52,106 single-nucleotide polymorphisms associated with human diseases. By implicating druggable NRs as hidden drivers of multiple human diseases, our results not only reveal new biological roles of NRs, but they also provide a resource for drug-repurposing and precision medicine.

CREPE: a Shiny app for transcription factor cataloguing.

Summary: Transcription factors (TFs) are proteins that directly interpret the genome to regulate gene expression and determine cellular phenotypes. TF identification is a common first step in unraveling gene regulatory networks. We present CREPE, an R Shiny app to catalogue and annotate TFs. CREPE was benchmarked against curated human TF datasets. Next, we use CREPE to explore the TF repertoires of Heliconius erato and Heliconius melpomene butterflies. Availability and implementation: CREPE is available as a Shiny app package available at GitHub (github.com/dirostri/CREPE). Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Disease-associated non-coding variants alter NKX2-5 DNA-binding affinity.

Genome-wide association studies (GWAS) have mapped over 90 % of disease- or trait-associated variants within the non-coding genome, like cis-regulatory elements (CREs). Non-coding single nucleotide polymorphisms (SNPs) are genomic variants that can change how DNA-binding regulatory proteins, like transcription factors (TFs), interact with the genome and regulate gene expression. NKX2-5 is a TF essential for proper heart development, and mutations affecting its function have been associated with congenital heart diseases (CHDs). However, establishing a causal mechanism between non-coding genomic variants and human disease remains challenging. To address this challenge, we identified 8475 SNPs predicted to alter NKX2-5 DNA-binding using a position weight matrix (PWM)-based predictive model. Five variants were prioritized for in vitro validation; four of them are associated with traits and diseases that impact cardiovascular health. The impact of these variants on NKX2-5 binding was evaluated with electrophoretic mobility shift assay (EMSA) using purified recombinant NKX2-5 homeodomain. Binding curves were constructed to determine changes in binding between variant and reference alleles. Variants rs7350789, rs7719885, rs747334, and rs3892630 increased binding affinity, whereas rs61216514 decreased binding by NKX2-5 when compared to the reference genome. Our findings suggest that differential TF-DNA binding affinity can be key in establishing a causal mechanism of pathogenic variants.

A Laser-Activated Membrane Introduction Mass Spectrometry Study of Proton Spillover Promoted Alkane Dehydrogenation.

Operando high-throughput evaluation of heterogeneous catalysts by laser-activated membrane introduction mass spectrometry (LAMIMS) elucidates the Pt loading dependence of methylcyclohexane dehydrogenation on platinized γ-alumina beads. A CO2 marking laser rapidly and sequentially heats catalyst beads positioned on a heat-dissipating carbon paper support that overlays a silicone membrane, separating the bead library reaction zone from a quadrupole mass analyzer. The toluene m/z peak varies logarithmically with Pt loading, suggesting that reactivity includes factors that are negatively correlated to Pt loading. These factors may include the Pt/γ-Al2O3 surface interfacial region as one component of a heterogeneous catalytically active surface area/mass. This work demonstrates LAMIMS as a broadly applicable high-throughput operando screening method for heterogeneous catalysts.

De novo design of programmable inducible promoters.

Ligand-responsive allosteric transcription factors (aTF) play a vital role in genetic circuits and high-throughput screening because they transduce biochemical signals into gene expression changes. Programmable control of gene expression from aTF-regulated promoter is important because different downstream effector genes function optimally at different expression levels. However, tuning gene expression of native promoters is difficult due to complex layers of homeostatic regulation encoded within them. We engineered synthetic promoters de novo by embedding operator sites with varying affinities and radically reshaped binding preferences within a minimal, constitutive Escherichia coli promoter. Multiplexed cell-based screening of promoters for three TetR-like aTFs generated with this approach gave rich diversity of gene expression levels, dynamic ranges and ligand sensitivities and were 50- to 100-fold more active over their respective native promoters. Machine learning on our dataset revealed that relative position of the core motif and bases flanking the core motif play an important role in modulating induction response. Our generalized approach yields customizable and programmable aTF-regulated promoters for engineering cellular pathways and enables the discovery of new small molecule biosensors.

Flexibility and structure of flanking DNA impact transcription factor affinity for its core motif.

Spatial and temporal expression of genes is essential for maintaining phenotype integrity. Transcription factors (TFs) modulate expression patterns by binding to specific DNA sequences in the genome. Along with the core binding motif, the flanking sequence context can play a role in DNA-TF recognition. Here, we employ high-throughput in vitro and in silico analyses to understand the influence of sequences flanking the cognate sites in binding of three most prevalent eukaryotic TF families (zinc finger, homeodomain and bZIP). In vitro binding preferences of each TF toward the entire DNA sequence space were correlated with a wide range of DNA structural parameters, including DNA flexibility. Results demonstrate that conformational plasticity of flanking regions modulates binding affinity of certain TF families. DNA duplex stability and minor groove width also play an important role in DNA-TF recognition but differ in how exactly they influence the binding in each specific case. Our analyses further reveal that the structural features of preferred flanking sequences are not universal, as similar DNA-binding folds can employ distinct DNA recognition modes.

Specificity landscapes unmask submaximal binding site preferences of transcription factors.

We have developed Differential Specificity and Energy Landscape (DiSEL) analysis to comprehensively compare DNA-protein interactomes (DPIs) obtained by high-throughput experimental platforms and cutting edge computational methods. While high-affinity DNA binding sites are identified by most methods, DiSEL uncovered nuanced sequence preferences displayed by homologous transcription factors. Pairwise analysis of 726 DPIs uncovered homolog-specific differences at moderate- to low-affinity binding sites (submaximal sites). DiSEL analysis of variants of 41 transcription factors revealed that many disease-causing mutations result in allele-specific changes in binding site preferences. We focused on a set of highly homologous factors that have different biological roles but "read" DNA using identical amino acid side chains. Rather than direct readout, our results indicate that DNA noncontacting side chains allosterically contribute to sculpt distinct sequence preferences among closely related members of transcription factor families.

Aptamer-Based Impedimetric Assay of Arsenite in Water: Interfacial Properties and Performance.

In this work, we explore the use of electrochemical methods (i.e., impedance) along with the arsenic-specific aptamer (ArsSApt) to fabricate and study the interfacial properties of an arsenic (As(III)) sensor. The ArsSApt layer was self-assembled on a gold substrate, and upon binding of As(III), a detectable change in the impedimetric signal was recorded because of conformational changes at the interfacial layer. These interfacial changes are linearly correlated with the concentration of arsenic present in the system. This target-induced signal was utilized for the selective detection of As(III) with a linear dynamic range of 0.05-10 ppm and minimum detectable concentrations of ca. 0.8 µM. The proposed system proved to be successful mainly because of the combination of a highly sensitive electrochemical platform and the recognized specificity of the ArsSApt toward its target molecule. Also, the interaction between the ArsSApt and the target molecule (i.e., arsenic) was explored in depth. The obtained results in this work are aimed at proving the development of a simple and environmentally benign sensor for the detection of As(III) as well as in elucidating the possible interactions between the ArsSApt and arsenic molecules.

Combinatorial bZIP dimers display complex DNA-binding specificity landscapes.

How transcription factor dimerization impacts DNA-binding specificity is poorly understood. Guided by protein dimerization properties, we examined DNA binding specificities of 270 human bZIP pairs. DNA interactomes of 80 heterodimers and 22 homodimers revealed that 72% of heterodimer motifs correspond to conjoined half-sites preferred by partnering monomers. Remarkably, the remaining motifs are composed of variably-spaced half-sites (12%) or 'emergent' sites (16%) that cannot be readily inferred from half-site preferences of partnering monomers. These binding sites were biochemically validated by EMSA-FRET analysis and validated in vivo by ChIP-seq data from human cell lines. Focusing on ATF3, we observed distinct cognate site preferences conferred by different bZIP partners, and demonstrated that genome-wide binding of ATF3 is best explained by considering many dimers in which it participates. Importantly, our compendium of bZIP-DNA interactomes predicted bZIP binding to 156 disease associated SNPs, of which only 20 were previously annotated with known bZIP motifs.

Synthetic genome readers target clustered binding sites across diverse chromatin states.

Targeting the genome with sequence-specific DNA-binding molecules is a major goal at the interface of chemistry, biology, and precision medicine. Polyamides, composed of N-methylpyrrole and N-methylimidazole monomers, are a class of synthetic molecules that can be rationally designed to "read" specific DNA sequences. However, the impact of different chromatin states on polyamide binding in live cells remains an unresolved question that impedes their deployment in vivo. Here, we use cross-linking of small molecules to isolate chromatin coupled to sequencing to map the binding of two bioactive and structurally distinct polyamides to genomes directly within live H1 human embryonic stem cells. This genome-wide view from live cells reveals that polyamide-based synthetic genome readers bind cognate sites that span a range of binding affinities. Polyamides can access cognate sites within repressive heterochromatin. The occupancy patterns suggest that polyamides could be harnessed to target loci within regions of the genome that are inaccessible to other DNA-targeting molecules.

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC (Crosslinking of Small Molecules to Isolate Chromatin).

The genome is the target of some of the most effective chemotherapeutics, but most of these drugs lack DNA sequence specificity, which leads to dose-limiting toxicity and many adverse side effects. Targeting the genome with sequence-specific small molecules may enable molecules with increased therapeutic index and fewer off-target effects. N-methylpyrrole/N-methylimidazole polyamides are molecules that can be rationally designed to target specific DNA sequences with exquisite precision. And unlike most natural transcription factors, polyamides can bind to methylated and chromatinized DNA without a loss in affinity. The sequence specificity of polyamides has been extensively studied in vitro with cognate site identification (CSI) and with traditional biochemical and biophysical approaches, but the study of polyamide binding to genomic targets in cells remains elusive. Here we report a method, the crosslinking of small molecules to isolate chromatin (COSMIC), that identifies polyamide binding sites across the genome. COSMIC is similar to chromatin immunoprecipitation (ChIP), but differs in two important ways: (1) a photocrosslinker is employed to enable selective, temporally-controlled capture of polyamide binding events, and (2) the biotin affinity handle is used to purify polyamide-DNA conjugates under semi-denaturing conditions to decrease DNA that is non-covalently bound. COSMIC is a general strategy that can be used to reveal the genome-wide binding events of polyamides and other genome-targeting chemotherapeutic agents.

Cooperativity in RNA-protein interactions: global analysis of RNA binding specificity.

The control and function of RNA are governed by the specificity of RNA binding proteins. Here, we describe a method for global unbiased analysis of RNA-protein interactions that uses in vitro selection, high-throughput sequencing, and sequence-specificity landscapes. The method yields affinities for a vast array of RNAs in a single experiment, including both low- and high-affinity sites. It is reproducible and accurate. Using this approach,we analyzed members of the PUF (Pumilio and FBF) family of eukaryotic mRNA regulators. Our data identify effects of a specific protein partner on PUF-RNA interactions, reveal subsets of target sites not previously detected, and demonstrate that designer PUF proteins can precisely alter specificity. The approach described here is, in principle, broadly applicable for analysis of any molecule that binds RNA, including proteins, nucleic acids, and small molecules.

Two-step nanoprecipitation for the production of protein-loaded PLGA nanospheres.

One of the first methods to encapsulate drugs within polymer nanospheres was developed by Fessi and coworkers in 1989 and consisted of one-step nanoprecipitation based on solvent displacement. However, proteins are poorly encapsulated within polymer nanoparticles using this method because of their limited solubility in organic solvents. To overcome this limitation, we developed a two-step nanoprecipitation method and encapsulated various proteins with high efficiency into poly(lactic-co-glycolic)acid (PLGA) nanospheres (NP). In this method, a protein nanoprecipitation step is used first followed by a second polymer nanoprecipitation step. Two model enzymes, lysozyme and α-chymotrypsin, were used for the optimization of the method. We obtained encapsulation efficiencies of >70%, an amount of buffer-insoluble protein aggregates of typically <2%, and a high residual activity of typically >90%. The optimum conditions identified for lysozyme were used to successfully encapsulate cytochrome c(Cyt-c), an apoptosis-initiating basic protein of similar size, to verify reproducibility of the encapsulation procedure. The size of the Cyt-c loaded-PLGA nanospheres was around 300-400 nm indicating the potential of the delivery system to passively target tumors. Cell viability studies, using a human cervical cancer cell line (HeLa), demonstrate excellent biocompatibility of the PLGA nanoparticles. PLGA nanoparticles carrying encapsulated Cyt-c were not efficient in causing apoptosis presumably because PLGA nanoparticles are not efficiently taken up by the cells. Future systems will have to be optimized to ascertain efficient cellular uptake of the nanoparticles by, e.g., surface modification with receptor ligands.

Prevention of benzyl alcohol-induced aggregation of chymotrypsinogen by PEGylation.

OBJECTIVES: Addition of the antimicrobial preservative benzyl alcohol to reconstitution buffer promotes the formation of undesirable aggregates in multidose protein formulations. Herein we investigated the efficiency of PEGylation (attachment of poly(ethylene glycol)) to prevent benzyl alcohol-induced aggregation of the model protein α-chymotrypsinogen A (aCTgn). METHODS: Various PEG-aCTgn conjugates were prepared using PEG with a molecular weight of either 700 or 5000 Da by varying the PEG-to-protein ratio during synthesis and the formation of insoluble aggregates was studied. The effect of benzyl alcohol on the thermodynamic stability and tertiary structure of aCTgn was also examined. KEY FINDINGS: When the model protein was reconstituted in buffer containing 0.9% benzyl alcohol, copious amounts of buffer-insoluble aggregates formed within 24 h (>10%). Benzyl alcohol-induced aggregation was completely prevented when two or five molecules of PEG with a molecular weight of 5000 Da were attached to the protein, whereas two or four molecules of bound 700 Da PEG were completely inefficient in preventing aggregation. Mechanistic investigations excluded prevention of structural perturbations or increased thermodynamic stability by PEGylation from being responsible for the prevention of aggregation. Simple addition of PEG to the buffer was also inefficient and PEG had to be covalently linked to the protein to be efficient. CONCLUSIONS: The most likely explanation for the protective effect of the 5000 Da PEG is shielding of exposed hydrophobic protein surface area and prevention of protein-protein contacts (molecular spacer effect).

Small-molecule regulators that mimic transcription factors.

Transcription factors (TFs) are responsible for decoding and expressing the information stored in the genome, which dictates cellular function. Creating artificial transcription factors (ATFs) that mimic endogenous TFs is a major goal at the interface of biology, chemistry, and molecular medicine. Such molecular tools will be essential for deciphering and manipulating transcriptional networks that lead to particular cellular states. In this minireview, the framework for the design of functional ATFs is presented and current challenges in the successful implementation of ATFs are discussed.

Nucleating the assembly of macromolecular complexes.

Nature constructs intricate complexes containing numerous binding partners in order to direct a variety of cellular processes. Researchers have taken a cue from these events to develop synthetic molecules that can nucleate natural and unnatural interactions for a diverse set of applications. These molecules can be designed to drive protein dimerization or to modulate the interactions between proteins, lipids, DNA, or RNA and thereby alter cellular pathways. A variety of components within the cellular machinery can be recruited with or replaced by synthetic compounds. Directing the formation of multicomponent complexes with new synthetic molecules can allow unprecedented control over the cellular machinery.