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.

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.

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.

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.

Genomic insights into tuberculosis.

Prevalent since pre-history, human tuberculosis - caused by the pathogen Mycobacterium tuberculosis - remains a major source of death worldwide. Moreover, increasing drug resistance poses the threat of disease resurgence. However, the expanding application of genomic techniques is providing new avenues for combating this old foe. Whole-genome sequencing, comparative genomics and systems biology are generating new insights into the origins and ongoing evolution of M. tuberculosis, as well as the molecular basis for its pathogenicity. These have important implications for our perspective of the disease, development of new drugs and vaccines, and treatment of patients using existing therapeutics.

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.

The Mycobacterium tuberculosis regulatory network and hypoxia.

We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub.

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.

Characterization of a cAMP responsive transcription factor, Cmr (Rv1675c), in TB complex mycobacteria reveals overlap with the DosR (DevR) dormancy regulon.

Mycobacterium tuberculosis (Mtb) Cmr (Rv1675c) is a CRP/FNR family transcription factor known to be responsive to cAMP levels and during macrophage infections. However, Cmr's DNA binding properties, cellular targets and overall role in tuberculosis (TB) complex bacteria have not been characterized. In this study, we used experimental and computational approaches to characterize Cmr's DNA binding properties and identify a putative regulon. Cmr binds a 16-bp palindromic site that includes four highly conserved nucleotides that are required for DNA binding. A total of 368 binding sites, distributed in clusters among ~200 binding regions throughout the Mycobacterium bovis BCG genome, were identified using ChIP-seq. One of the most enriched Cmr binding sites was located upstream of the cmr promoter, and we demonstrated that expression of cmr is autoregulated. cAMP affected Cmr binding at a subset of DNA loci in vivo and in vitro, including multiple sites adjacent to members of the DosR (DevR) dormancy regulon. Our findings of cooperative binding of Cmr to these DNA regions and the regulation by Cmr of the DosR-regulated virulence gene Rv2623 demonstrate the complexity of Cmr-mediated gene regulation and suggest a role for Cmr in the biology of persistent TB infection.

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.

Role of intragenic binding of cAMP responsive protein (CRP) in regulation of the succinate dehydrogenase genes Rv0249c-Rv0247c in TB complex mycobacteria.

Bacterial pathogens adapt to changing environments within their hosts, and the signaling molecule adenosine 3', 5'-cyclic monophosphate (cAMP) facilitates this process. In this study, we characterized in vivo DNA binding and gene regulation by the cAMP-responsive protein CRP in M. bovis BCG as a model for tuberculosis (TB)-complex bacteria. Chromatin immunoprecipitation followed by deep-sequencing (ChIP-seq) showed that CRP associates with ∼900 DNA binding regions, most of which occur within genes. The most highly enriched binding region was upstream of a putative copper transporter gene (ctpB), and crp-deleted bacteria showed increased sensitivity to copper toxicity. Detailed mutational analysis of four CRP binding sites upstream of the virulence-associated Rv0249c-Rv0247c succinate dehydrogenase genes demonstrated that CRP directly regulates Rv0249c-Rv0247c expression from two promoters, one of which requires sequences intragenic to Rv0250c for maximum expression. The high percentage of intragenic CRP binding sites and our demonstration that these intragenic DNA sequences significantly contribute to biologically relevant gene expression greatly expand the genome space that must be considered for gene regulatory analyses in mycobacteria. These findings also have practical implications for an important bacterial pathogen in which identification of mutations that affect expression of drug target-related genes is widely used for rapid drug resistance screening.

Analysis of clock-regulated genes in Neurospora reveals widespread posttranscriptional control of metabolic potential.

Neurospora crassa has been for decades a principal model for filamentous fungal genetics and physiology as well as for understanding the mechanism of circadian clocks. Eukaryotic fungal and animal clocks comprise transcription-translation-based feedback loops that control rhythmic transcription of a substantial fraction of these transcriptomes, yielding the changes in protein abundance that mediate circadian regulation of physiology and metabolism: Understanding circadian control of gene expression is key to understanding eukaryotic, including fungal, physiology. Indeed, the isolation of clock-controlled genes (ccgs) was pioneered in Neurospora where circadian output begins with binding of the core circadian transcription factor WCC to a subset of ccg promoters, including those of many transcription factors. High temporal resolution (2-h) sampling over 48 h using RNA sequencing (RNA-Seq) identified circadianly expressed genes in Neurospora, revealing that from ∼10% to as much 40% of the transcriptome can be expressed under circadian control. Functional classifications of these genes revealed strong enrichment in pathways involving metabolism, protein synthesis, and stress responses; in broad terms, daytime metabolic potential favors catabolism, energy production, and precursor assembly, whereas night activities favor biosynthesis of cellular components and growth. Discriminative regular expression motif elicitation (DREME) identified key promoter motifs highly correlated with the temporal regulation of ccgs. Correlations between ccg abundance from RNA-Seq, the degree of ccg-promoter activation as reported by ccg-promoter-luciferase fusions, and binding of WCC as measured by ChIP-Seq, are not strong. Therefore, although circadian activation is critical to ccg rhythmicity, posttranscriptional regulation plays a major role in determining rhythmicity at the mRNA level.

A genome-wide map of diversity in Plasmodium falciparum.

Genetic variation allows the malaria parasite Plasmodium falciparum to overcome chemotherapeutic agents, vaccines and vector control strategies and remain a leading cause of global morbidity and mortality. Here we describe an initial survey of genetic variation across the P. falciparum genome. We performed extensive sequencing of 16 geographically diverse parasites and identified 46,937 SNPs, demonstrating rich diversity among P. falciparum parasites (pi = 1.16 x 10(-3)) and strong correlation with gene function. We identified multiple regions with signatures of selective sweeps in drug-resistant parasites, including a previously unidentified 160-kb region with extremely low polymorphism in pyrimethamine-resistant parasites. We further characterized 54 worldwide isolates by genotyping SNPs across 20 genomic regions. These data begin to define population structure among African, Asian and American groups and illustrate the degree of linkage disequilibrium, which extends over relatively short distances in African parasites but over longer distances in Asian parasites. We provide an initial map of genetic diversity in P. falciparum and demonstrate its potential utility in identifying genes subject to recent natural selection and in understanding the population genetics of this parasite.

Reconstruction and validation of a genome-scale metabolic model for the filamentous fungus Neurospora crassa using FARM.

The filamentous fungus Neurospora crassa played a central role in the development of twentieth-century genetics, biochemistry and molecular biology, and continues to serve as a model organism for eukaryotic biology. Here, we have reconstructed a genome-scale model of its metabolism. This model consists of 836 metabolic genes, 257 pathways, 6 cellular compartments, and is supported by extensive manual curation of 491 literature citations. To aid our reconstruction, we developed three optimization-based algorithms, which together comprise Fast Automated Reconstruction of Metabolism (FARM). These algorithms are: LInear MEtabolite Dilution Flux Balance Analysis (limed-FBA), which predicts flux while linearly accounting for metabolite dilution; One-step functional Pruning (OnePrune), which removes blocked reactions with a single compact linear program; and Consistent Reproduction Of growth/no-growth Phenotype (CROP), which reconciles differences between in silico and experimental gene essentiality faster than previous approaches. Against an independent test set of more than 300 essential/non-essential genes that were not used to train the model, the model displays 93% sensitivity and specificity. We also used the model to simulate the biochemical genetics experiments originally performed on Neurospora by comprehensively predicting nutrient rescue of essential genes and synthetic lethal interactions, and we provide detailed pathway-based mechanistic explanations of our predictions. Our model provides a reliable computational framework for the integration and interpretation of ongoing experimental efforts in Neurospora, and we anticipate that our methods will substantially reduce the manual effort required to develop high-quality genome-scale metabolic models for other organisms.

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.

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.

How accurate can genetic predictions be?

BACKGROUND: Pre-symptomatic prediction of disease and drug response based on genetic testing is a critical component of personalized medicine. Previous work has demonstrated that the predictive capacity of genetic testing is constrained by the heritability and prevalence of the tested trait, although these constraints have only been approximated under the assumption of a normally distributed genetic risk distribution. RESULTS: Here, we mathematically derive the absolute limits that these factors impose on test accuracy in the absence of any distributional assumptions on risk. We present these limits in terms of the best-case receiver-operating characteristic (ROC) curve, consisting of the best-case test sensitivities and specificities, and the AUC (area under the curve) measure of accuracy. We apply our method to genetic prediction of type 2 diabetes and breast cancer, and we additionally show the best possible accuracy that can be obtained from integrated predictors, which can incorporate non-genetic features. CONCLUSION: Knowledge of such limits is valuable in understanding the implications of genetic testing even before additional associations are identified.

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.

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.

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.