An Allosteric Transcription Factor DNA-Binding Electrochemical Biosensor for Progesterone

Predictive Biophysical Neural Network Modeling of a Compendium of in vivo Transcription Factor DNA Binding Profiles for Escherichia coli

The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs using ChIP-Seq. We used these data to train BoltzNet, a novel neural network that predicts TF binding energy from DNA sequence. BoltzNet mirrors a quantitative biophysical model and provides directly interpretable predictions genome-wide at nucleotide resolution. We used BoltzNet to quantitatively design novel binding sites, which we validated with biophysical experiments on purified protein. We have generated models for 125 TFs that provide insight into global features of TF binding, including clustering of sites, the role of accessory bases, the relevance of weak sites, and the background affinity of the genome. Our paper provides new paradigms for studying TF-DNA binding and for the development of biophysically motivated neural networks.

Strategy, Design, and Fabrication of Electrochemical Biosensors: A Tutorial

Advanced healthcare requires novel technologies capable of real-time sensing to monitor acute and long-term health. The challenge relies on converting a real-time quantitative biological and chemical signal into a desired measurable output. Given the success in detecting glucose and the commercialization of glucometers, electrochemical biosensors continue to be a mainstay of academic and industrial research activities. Despite the wealth of literature on electrochemical biosensors, reports are often specific to a particular application (e.g., pathogens, cancer markers, glucose, etc.), and most fail to convey the underlying strategy and design, and if it is transferable to detection of a different analyte. Here we present a tutorial review for those entering this research area that summarizes the basic electrochemical techniques utilized as well as discusses the designs and optimization strategies employed to improve sensitivity and maximize signal output.

Double-Stranded DNA Immobilized in Lying-Flat and Upright Orientation on a PNIPAm-Coated Surface: A Theoretical Study

Surface-immobilized double-stranded DNA (dsDNA) in upright orientation plays an important role in optimizing and understanding DNA-based nanosensors and nanodevices. However, it is difficult to regulate the surface density of upright DNA due to the fact that DNA usually stands vertically at a high packing density but may lie down at a low packing density. We herein report dsDNA immobilized in upright orientation on a poly(N-isopropylacrylamide) (PNIPAm)-coated surface in theory. The theoretical results reveal that the angle of upright DNA relative to the surface is larger than that of DNA immobilized on the bare surface caused by the lying-flat DNA under proper PNIPAm surface coverage at 45 °C. The surface density of upright DNA is significantly influenced by DNA concentration and DNA length. It is envisioned that the density-regulated DNA molecules immobilized in upright orientation in the present work are well suited to bottom-up construction of complex DNA-based nanostructures and nanodevices.

Applications of Graphene in Five Senses, Nervous System, and Artificial Muscles

Graphene remains of great interest in biomedical applications because of biocompatibility. Diseases relating to human senses interfere with life satisfaction and happiness. Therefore, the restoration by artificial organs or sensory devices may bring a bright future by the recovery of senses in patients. In this review, we update the most recent progress in graphene based sensors for mimicking human senses such as artificial retina for image sensors, artificial eardrums, gas sensors, chemical sensors, and tactile sensors. The brain-like processors are discussed based on conventional transistors as well as memristor related neuromorphic computing. The brain-machine interface is introduced for providing a single pathway. Besides, the artificial muscles based on graphene are summarized in the means of actuators in order to react to the physical world. Future opportunities remain for elevating the performances of human-like sensors and their clinical applications.

IVT cell-free biosensors for tetracycline and macrolide detection based on allosteric transcription factors (aTFs)

In recent years, the issue of food safety has received a lot of attention. The Food and Drug Administration (FDA) prescribes the antibiotic's maximum residue limit (MRL) in food production. The standard detection methods of antibiotics are liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) and high-performance liquid chromatography (HPLC), with complex operations and precision instruments. In this study, allosteric transcription factor (aTF)-based in vitro transcription (IVT) cell-free biosensors were developed for tetracyclines and macrolides with nucleic acid sequence-based amplification (NASBA). Characterization of binding and dissociation processes between aTF and DNA was carried out by BIAcore assay and electrophoretic mobility shift assay (EMSA). BIAcore was innovatively used to directly observe the real-time process of binding and dissociation of aTF with DNA. The biosensors produce more fluorescence RNA when target antibiotics are added to the three-way junction dimeric Broccoli (3WJdB). Four tetracyclines and two macrolides were quantified in the 0.5-15 μM range, while erythromycin and clarithromycin were detected over a range of 0.1-15 μM. NASBA, commonly used for viral detection, was used to amplify 3WJdB RNA generated by IVT, which greatly increased the LOD for tetracyclines and macrolides to 0.01 μM. The use of biosensors in milk samples demonstrated their on-site detection performance. Overall, our proposed biosensors are simple, rapid, selective, and sensitive, with the potential for field application.