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.

Transcription-Factor-Induced Aggregation of Biomimetic Oligonucleotide-b-Protein Micelles.

Polymeric micelles and especially those based on natural diblocks are of particular interest due to their advantageous properties in terms of molecular recognition, biocompatibility, and biodegradability. We herein report a facile and straightforward synthesis of thermoresponsive elastin-like polypeptide (ELP) and oligonucleotide (ON) diblock bioconjugates, ON-b-ELP, through copper-catalyzed azide-alkyne cycloaddition. The resulting thermosensitive diblock copolymer self-assembles above its critical micelle temperature (CMT ∼30 °C) to form colloidally stable micelles of ∼50 nm diameter. The ON-b-ELP micelles hybridize with an ON complementary strand and maintain their size and stability. Next, we describe the capacity of these micelles to bind proteins, creating more complex structures using the classic biotin-streptavidin pairing and the specific recognition between a transcription factor protein and the ON strand. In both instances, the micelles are intact, form larger structures, and retain their sensitivity to temperature.

Structural Insights into the Substrate Range of a Bacterial Monoamine Oxidase.

Monoamine oxidases (MAOs) play a key role in the breakdown of primary and secondary amines. In eukaryotic organisms, these enzymes are vital to the regulation of monoamine neurotransmitters and the degradation of dietary monoamines. MAOs have also been identified in prokaryotic species, although their role in these organisms is not well understood. Here, we report the biophysical and structural properties of a promiscuous, bacterial MAO from Corynebacterium ammoniagenes (caMAO). caMAO catalyzes the oxidation of a number of monoamine substrates including dopamine and norepinephrine, as well as exhibiting some activity with polyamine substrates such as cadaverine. The X-ray crystal structures of Michaelis complexes with seven substrates show that conserved hydrophobic interactions and hydrogen-bonding pattern (for polar substrates) allow the broad specificity range. The structure of caMAO identifies an unusual cysteine (Cys424) residue in the so-called "aromatic cage", which flanks the flavin isoalloxazine ring in the active site. Site-directed mutagenesis, steady-state kinetics in air-saturated buffer, and UV-vis spectroscopy revealed that Cys424 plays a role in the pH dependence and modulation of electrostatics within the caMAO active site. Notably, bioinformatic analysis shows a propensity for variation at this site within the "aromatic cage" of the flavin amine oxidase (FAO) superfamily. Structural analysis also identified the conservation of a secondary substrate inhibition site, present in a homologous member of the superfamily. Finally, genome neighborhood diagram analysis of caMAO in the context of the FAO superfamily allows us to propose potential roles for these bacterial MAOs in monoamine and polyamine degradation and catabolic pathways related to scavenging of nitrogen.

The quantum dot vs. organic dye conundrum for ratiometric FRET-based biosensors: which one would you chose?

Förster resonance energy transfer (FRET) is a widely used and ideal transduction modality for fluorescent based biosensors as it offers high signal to noise with a visibly detectable signal. While intense efforts are ongoing to improve the limit of detection and dynamic range of biosensors based on biomolecule optimization, the selection of and relative location of the dye remains understudied. Herein, we describe a combined experimental and computational study to systematically compare the nature of the dye, i.e., organic fluorophore (Cy5 or Texas Red) vs. inorganic nanoparticle (QD), and the position of the FRET donor or acceptor on the biomolecular components. Using a recently discovered transcription factor (TF)-deoxyribonucleic acid (DNA) biosensor for progesterone, we examine four different biosensor configurations and report the quantum yield, lifetime, FRET efficiency, IC50, and limit of detection. Fitting the computational models to the empirical data identifies key molecular parameters driving sensor performance in each biosensor configuration. Finally, we provide a set of design parameters to enable one to select the fluorophore system for future intermolecular biosensors using FRET-based conformational regulation in in vitro assays and new diagnostic devices.

RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12.

Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.

An Allosteric Transcription Factor DNA-Binding Electrochemical Biosensor for Progesterone.

We describe an electrochemical strategy to transduce allosteric transcription factor (aTF) binding affinity to sense steroid hormones. Our approach utilizes square wave voltammetry to monitor changes in current output as a progesterone (PRG)-specific aTF (SRTF1) unbinds from the cognate DNA sequence in the presence of PRG. The sensor detects PRG in artificial urine samples with sufficient sensitivity suitable for clinical applications. Our results highlight the capability of using aTFs as the biorecognition elements to develop electrochemical point-of-care biosensors for the detection of small-molecule biomarkers and analytes.

Paper-Based Progesterone Sensor Using an Allosteric Transcription Factor.

Progesterone monitoring is an essential component of in vitro fertilization treatments and reproductive management of dairy cows. Gold-standard biosensors for progesterone monitoring rely on antibodies, which are expensive and difficult to procure. We have developed an alternative transcription factor-based sensor that is superior to conventional progesterone biosensors. Here, we incorporate this transcription factor-based progesterone sensor into an affordable, portable paperfluidic format to facilitate widespread implementation of progesterone monitoring at the point of care. Oligonucleotides labeled with a fluorescent dye are immobilized onto nitrocellulose via a biotin-streptavidin interaction. In the absence of progesterone, these oligonucleotides form a complex with a transcription factor that is fluorescently labeled with tdTomato. In the presence of progesterone, the fluorescent transcription factor unbinds from the immobilized DNA, resulting in a decrease in tdTomato fluorescence. The limit of detection of our system is 27 nm, which is a clinically relevant level of progesterone. We demonstrate that transcription factor-based sensors can be incorporated into paperfluidic devices, thereby making them accessible to a broader population due to the portability and affordability of paper-based devices.

Development and Clinical Validation of Iso-IMRS: A Novel Diagnostic Assay for P. falciparum Malaria.

In many countries targeting malaria elimination, persistent malaria infections can have parasite loads significantly below the lower limit of detection (LLOD) of standard diagnostic techniques, making them difficult to identify and treat. The most sensitive diagnostic methods involve amplification and detection of Plasmodium DNA by polymerase chain reaction (PCR), which requires expensive thermal cycling equipment and is difficult to deploy in resource-limited settings. Isothermal DNA amplification assays have been developed, but they require complex primer design, resulting in high nonspecific amplification, and show a decrease in sensitivity than PCR methods. Here, we have used a computational approach to design a novel isothermal amplification assay with a simple primer design to amplify P. falciparum DNA with analytical sensitivity comparable to PCR. We have identified short DNA sequences repeated throughout the parasite genome to be used as primers for DNA amplification and demonstrated that these primers can be used, without modification, to isothermally amplify P. falciparum parasite DNA via strand displacement amplification. Our novel assay shows a LLOD of ∼1 parasite/µL within a 30 min amplification time. The assay was demonstrated with clinical samples using patient blood and saliva. We further characterized the assay using direct amplicon next-generation sequencing and modified the assay to work with a visual readout. The technique developed here achieves similar analytical sensitivity to current gold standard PCR assays requiring a fraction of time and resources for PCR. This highly sensitive isothermal assay can be more easily adapted to field settings, making it a potentially useful tool for malaria elimination.

Transcription Factor Based Small-Molecule Sensing with a Rapid Cell Phone Enabled Fluorescent Bead Assay.

Recently, allosteric transcription factors (TFs) were identified as a novel class of biorecognition elements for in vitro sensing, whereby an indicator of the differential binding affinity between a TF and its cognate DNA exhibits dose-dependent responsivity to an analyte. Described is a modular bead-based biosensor design that can be applied to such TF-DNA-analyte systems. DNA-functionalized beads enable efficient mixing and spatial separation, while TF-labeled semiconductor quantum dots serve as bright fluorescent indicators of the TF-DNA bound (on bead) and unbound states. The prototype sensor for derivatives of the antibiotic tetracycline exhibits nanomolar sensitivity with visual detection of bead fluorescence. Facile changes to the sensor enable sensor response tuning without necessitating changes to the biomolecular affinities. Assay components self-assemble, and readout by eye or digital camera is possible within 5 minutes of analyte addition, making sensor use facile, rapid, and instrument-free.

Hydrogel-Embedded Quantum Dot-Transcription Factor Sensors for Quantitative Progesterone Detection.

Immobilization of biosensors in or on a functional material is critical for subsequent device development and translation to wearable technology. Here, we present the development and assessment of an immobilized quantum dot-transcription factor-nucleic acid complex for progesterone detection as a first step toward such device integration. The sensor, composed of a polyhistidine-tagged transcription factor linked to a quantum dot and a fluorophore-modified cognate DNA, is embedded within a hydrogel as an immobilization matrix. The hydrogel is optically transparent, soft, and flexible as well as traps the quantum dot-transcription factor DNA assembly but allows free passage of the analyte, progesterone. Upon progesterone exposure, DNA dissociates from the quantum dot-transcription factor DNA assembly resulting in an attenuated ratiometric fluorescence output via Förster resonance energy transfer. The sensor performs in a dose-dependent manner with a limit of detection of 55 nM. Repeated analyte measurements are similarly successful. Our approach combines a systematically characterized hydrogel as an immobilization matrix and a transcription factor-DNA assembly as a recognition/transduction element, offering a promising framework for future biosensor devices.

Surface Immobilized Nucleic Acid-Transcription Factor Quantum Dots for Biosensing.

Immobilization of biosensors on surfaces is a key step toward development of devices for real-world applications. Here the preparation, characterization, and evaluation of a surface-bound transcription factor-nucleic acid complex for analyte detection as an alternative to conventional systems employing aptamers or antibodies are described. The sensor consists of a gold surface modified with thiolated Cy5 fluorophore-labeled DNA and an allosteric transcription factor (TetR) linked to a quantum dot (QD). Upon addition of anhydrotetracycline (aTc)-the analyte-the TetR-QDs release from the surface-bound DNA, resulting in loss of the Förster resonance energy transfer signal. The sensor responds in a dose-dependent manner over the relevant range of 0-200 µm aTc with a limit of detection of 80 nm. The fabrication of the sensor and the subsequent real-time quantitative measurements establish a framework for the design of future surface-bound, affinity-based biosensors using allosteric transcription factors for molecular recognition.

Redefining fundamental concepts of transcription initiation in bacteria.

Despite enormous progress in understanding the fundamentals of bacterial gene regulation, our knowledge remains limited when compared with the number of bacterial genomes and regulatory systems to be discovered. Derived from a small number of initial studies, classic definitions for concepts of gene regulation have evolved as the number of characterized promoters has increased. Together with discoveries made using new technologies, this knowledge has led to revised generalizations and principles. In this Expert Recommendation, we suggest precise, updated definitions that support a logical, consistent conceptual framework of bacterial gene regulation, focusing on transcription initiation. The resulting concepts can be formalized by ontologies for computational modelling, laying the foundation for improved bioinformatics tools, knowledge-based resources and scientific communication. Thus, this work will help researchers construct better predictive models, with different formalisms, that will be useful in engineering, synthetic biology, microbiology and genetics.

Epigenetic competition reveals density-dependent regulation and target site plasticity of phosphorothioate epigenetics in bacteria.

Phosphorothioate (PT) DNA modifications-in which a nonbonding phosphate oxygen is replaced with sulfur-represent a widespread, horizontally transferred epigenetic system in prokaryotes and have a highly unusual property of occupying only a small fraction of available consensus sequences in a genome. Using Salmonella enterica as a model, we asked a question of fundamental importance: How do the PT-modifying DndA-E proteins select their GPSAAC/GPSTTC targets? Here, we applied innovative analytical, sequencing, and computational tools to discover a novel behavior for DNA-binding proteins: The Dnd proteins are "parked" at the G6mATC Dam methyltransferase consensus sequence instead of the expected GAAC/GTTC motif, with removal of the 6mA permitting extensive PT modification of GATC sites. This shift in modification sites further revealed a surprising constancy in the density of PT modifications across the genome. Computational analysis showed that GAAC, GTTC, and GATC share common features of DNA shape, which suggests that PT epigenetics are regulated in a density-dependent manner partly by DNA shape-driven target selection in the genome.

A Förster Resonance Energy Transfer-Based Ratiometric Sensor with the Allosteric Transcription Factor TetR.

A recent description of an antibody-free assay is significantly extended for small molecule analytes using allosteric transcription factors (aTFs) and Förster resonance energy transfer (FRET). The FRET signal indicates the differential binding of an aTF-DNA pair with a dose-dependent response to its effector molecule, i.e., the analyte. The new sensors described here, based on the well-characterized aTF TetR, demonstrate several new features of the assay approach: 1) the generalizability of the sensors to additional aTF-DNA-analyte systems, 2) sensitivity modulation through the choice of donor fluorophore (quantum dots or fluorescent proteins, FPs), and 3) sensor tuning using aTF variants with differing aTF-DNA binding affinities. While all of these modular sensors self-assemble, the design reported here based on a recombinant aTF-FP chimera with commercially available dye-labeled DNA uses readily accessible sensor components to facilitate easy adoption of the sensing approach by the broader community.

A progesterone biosensor derived from microbial screening.

Bacteria are an enormous and largely untapped reservoir of biosensing proteins. We describe an approach to identify and isolate bacterial allosteric transcription factors (aTFs) that recognize a target analyte and to develop these TFs into biosensor devices. Our approach utilizes a combination of genomic screens and functional assays to identify and isolate biosensing TFs, and a quantum-dot Förster Resonance Energy Transfer (FRET) strategy for transducing analyte recognition into real-time quantitative measurements. We use this approach to identify a progesterone-sensing bacterial aTF and to develop this TF into an optical sensor for progesterone. The sensor detects progesterone in artificial urine with sufficient sensitivity and specificity for clinical use, while being compatible with an inexpensive and portable electronic reader for point-of-care applications. Our results provide proof-of-concept for a paradigm of microbially-derived biosensors adaptable to inexpensive, real-time sensor devices.

RegulonDB v 10.5: tackling challenges to unify classic and high throughput knowledge of gene regulation in E. coli K-12.

RegulonDB, first published 20 years ago, is a comprehensive electronic resource about regulation of transcription initiation of Escherichia coli K-12 with decades of knowledge from classic molecular biology experiments, and recently also from high-throughput genomic methodologies. We curated the literature to keep RegulonDB up to date, and initiated curation of ChIP and gSELEX experiments. We estimate that current knowledge describes between 10% and 30% of the expected total number of transcription factor- gene regulatory interactions in E. coli. RegulonDB provides datasets for interactions for which there is no evidence that they affect expression, as well as expression datasets. We developed a proof of concept pipeline to merge binding and expression evidence to identify regulatory interactions. These datasets can be visualized in the RegulonDB JBrowse. We developed the Microbial Conditions Ontology with a controlled vocabulary for the minimal properties to reproduce an experiment, which contributes to integrate data from high throughput and classic literature. At a higher level of integration, we report Genetic Sensory-Response Units for 200 transcription factors, including their regulation at the metabolic level, and include summaries for 70 of them. Finally, we summarize our research with Natural language processing strategies to enhance our biocuration work.

A unified resource for transcriptional regulation in Escherichia coli K-12 incorporating high-throughput-generated binding data into RegulonDB version 10.0.

BACKGROUND: Our understanding of the regulation of gene expression has benefited from the availability of high-throughput technologies that interrogate the whole genome for the binding of specific transcription factors and gene expression profiles. In the case of widely used model organisms, such as Escherichia coli K-12, the new knowledge gained from these approaches needs to be integrated with the legacy of accumulated knowledge from genetic and molecular biology experiments conducted in the pre-genomic era in order to attain the deepest level of understanding possible based on the available data. RESULTS: In this paper, we describe an expansion of RegulonDB, the database containing the rich legacy of decades of classic molecular biology experiments supporting what we know about gene regulation and operon organization in E. coli K-12, to include the genome-wide dataset collections from 32 ChIP and 19 gSELEX publications, in addition to around 60 genome-wide expression profiles relevant to the functional significance of these datasets and used in their curation. Three essential features for the integration of this information coming from different methodological approaches are: first, a controlled vocabulary within an ontology for precisely defining growth conditions; second, the criteria to separate elements with enough evidence to consider them involved in gene regulation from isolated transcription factor binding sites without such support; and third, an expanded computational model supporting this knowledge. Altogether, this constitutes the basis for adequately gathering and enabling the comparisons and integration needed to manage and access such wealth of knowledge. CONCLUSIONS: This version 10.0 of RegulonDB is a first step toward what should become the unifying access point for current and future knowledge on gene regulation in E. coli K-12. Furthermore, this model platform and associated methodologies and criteria can be emulated for gathering knowledge on other microbial organisms.

Mycobacterium tuberculosis Whole Genome Sequences From Southern India Suggest Novel Resistance Mechanisms and the Need for Region-Specific Diagnostics.

BACKGROUND.: India is home to 25% of all tuberculosis cases and the second highest number of multidrug resistant cases worldwide. However, little is known about the genetic diversity and resistance determinants of Indian Mycobacterium tuberculosis, particularly for the primary lineages found in India, lineages 1 and 3. METHODS.: We whole genome sequenced 223 randomly selected M. tuberculosis strains from 196 patients within the Tiruvallur and Madurai districts of Tamil Nadu in Southern India. Using comparative genomics, we examined genetic diversity, transmission patterns, and evolution of resistance. RESULTS.: Genomic analyses revealed (11) prevalence of strains from lineages 1 and 3, (11) recent transmission of strains among patients from the same treatment centers, (11) emergence of drug resistance within patients over time, (11) resistance gained in an order typical of strains from different lineages and geographies, (11) underperformance of known resistance-conferring mutations to explain phenotypic resistance in Indian strains relative to studies focused on other geographies, and (11) the possibility that resistance arose through mutations not previously implicated in resistance, or through infections with multiple strains that confound genotype-based prediction of resistance. CONCLUSIONS.: In addition to substantially expanding the genomic perspectives of lineages 1 and 3, sequencing and analysis of M. tuberculosis whole genomes from Southern India highlight challenges of infection control and rapid diagnosis of resistant tuberculosis using current technologies. Further studies are needed to fully explore the complement of diversity and resistance determinants within endemic M. tuberculosis populations.