Rapid cell-free forward engineering of novel genetic ring oscillators

While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the 'repressilator,' a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hours. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior

A Field‐Capable Rapid Plant DNA Extraction Protocol Using Microneedle Patches for Botanical Surveying and Monitoring

Premise: A novel protocol for rapid plant DNA extraction using microneedles is proposed, which supports botanic surveys, taxonomy, and systematics. This protocol can be conducted in the field with limited laboratory skills and equipment. The protocol is validated by sequencing and comparing the results with QIAGEN spin-column DNA extractions using BLAST analyses. Methods and Results: Two sets of DNA extractions were conducted on 13 species spanning various leaf anatomies and phylogenetic lineages: (i) fresh leaves were punched with custom polymeric microneedle patches to recover genomic DNA, or (ii) QIAGEN DNA extractions. Three plastid (matK, rbcL, and trnH-psbA) and one nuclear ribosomal (ITS) DNA regions were amplified and sequenced using Sanger or nanopore technology. The proposed method reduced the extraction time to 1 min and yielded the same DNA sequences as the QIAGEN extractions. Conclusions: Our drastically faster and simpler method is compatible with nanopore sequencing and is suitable for multiple applications, including high-throughput DNA-based species identifications and monitoring

Moiré patterns in van der Waals heterostructures

© 2019 American Physical Society. Using scanning tunneling microscopy, we report the observation of moiré patterns (MPs) on van der Waals heterostructures comprised of various 2D allotropes of bismuth and antimony grown on highly ordered pyrolytic graphite and MoS2. The spatial periods of the MPs range from λ∼1 to ∼10 nm. For all the reported cases (α-bismuthene, α-antimonene, β-antimonene, and monolayer bismuthene), we model the observations using a simple superposition model (SSM). Where possible, the results obtained from the SSM are compared to analytical prediction. MPs emerging from mixed symmetry stacking (hexagonal on rectangular) are explained without requiring commensuration of the layers

A high throughput molecular force assay for protein-DNA interactions.

An accurate and genome-wide characterization of protein–DNA interactions such as transcription factor binding is of utmost importance for modern biology. Powerful screening methods emerged. But the vast majority of these techniques depend on special labels or markers against the ligand of interest and moreover most of them are not suitable for detecting low-affinity binders. In this article a molecular force assay is described based on measuring comparative unbinding forces of biomolecules for the detection of protein–DNA interactions. The measurement of binding or unbinding forces has several unique advantages in biological applications since the interaction between certain molecules and not the mere presence of one of them is detected. No label or marker against the protein is needed and only specifically bound ligands are detected. In addition the force-based assay permits the detection of ligands over a broad range of affinities in a crowded and opaque ambient environment. We demonstrate that the molecular force assay allows highly sensitive and fast detection of protein–DNA interactions. As a proof of principle, binding of the protein EcoRI to its DNA recognition sequence is measured and the corresponding dissociation constant in the sub-nanomolar range is determined. Furthermore, we introduce a new, simplified setup employing FRET pairs on the molecular level and standard epi-fluorescence for readout. Due to these advancements we can now demonstrate that a feature size of a few microns is sufficient for the measurement process. This will open a new paradigm in high-throughput screening with all the advantages of force-based ligand detection. Graphical abstract: A high throughput molecular force assay for protein–DNA interaction

Probing the Informational and Regulatory Plasticity of a Transcription Factor DNA–Binding Domain

Transcription factors have two functional constraints on their evolution: (1) their binding sites must have enough information to be distinguishable from all other sequences in the genome, and (2) they must bind these sites with an affinity that appropriately modulates the rate of transcription. Since both are determined by the biophysical properties of the DNA–binding domain, selection on one will ultimately affect the other. We were interested in understanding how plastic the informational and regulatory properties of a transcription factor are and how transcription factors evolve to balance these constraints. To study this, we developed an in vivo selection system in Escherichia coli to identify variants of the helix-turn-helix transcription factor MarA that bind different sets of binding sites with varying degrees of degeneracy. Unlike previous in vitro methods used to identify novel DNA binders and to probe the plasticity of the binding domain, our selections were done within the context of the initiation complex, selecting for both specific binding within the genome and for a physiologically significant strength of interaction to maintain function of the factor. Using MITOMI, quantitative PCR, and a binding site fitness assay, we characterized the binding, function, and fitness of some of these variants. We observed that a large range of binding preferences, information contents, and activities could be accessed with a few mutations, suggesting that transcriptional regulatory networks are highly adaptable and expandable

Discovery of a hepatitis C target and its pharmacological inhibitors by microfluidic affinity analysis

More effective therapies are urgently needed against hepatitis C virus (HCV), a major cause of viral hepatitis. We used in vitro protein expression and microfluidic affinity analysis to study RNA binding by the HCV transmembrane protein NS4B, which plays an essential role in HCV RNA replication. We show that HCV NS4B binds RNA and that this binding is specific for the 3' terminus of the negative strand of the viral genome with a dissociation constant (K(d)) of approximately 3.4 nM. A high-throughput microfluidic screen of a compound library identified 18 compounds that substantially inhibited binding of RNA by NS4B. One of these compounds, clemizole hydrochloride, was found to inhibit HCV RNA replication in cell culture that was mediated by its suppression of NS4B's RNA binding, with little toxicity for the host cell. These results yield new insight into the HCV life cycle and provide a candidate compound for pharmaceutical development

Formation of regulatory modules by local sequence duplication

Turnover of regulatory sequence and function is an important part of molecular evolution. But what are the modes of sequence evolution leading to rapid formation and loss of regulatory sites? Here, we show that a large fraction of neighboring transcription factor binding sites in the fly genome have formed from a common sequence origin by local duplications. This mode of evolution is found to produce regulatory information: duplications can seed new sites in the neighborhood of existing sites. Duplicate seeds evolve subsequently by point mutations, often towards binding a different factor than their ancestral neighbor sites. These results are based on a statistical analysis of 346 cis-regulatory modules in the Drosophila melanogaster genome, and a comparison set of intergenic regulatory sequence in Saccharomyces cerevisiae. In fly regulatory modules, pairs of binding sites show significantly enhanced sequence similarity up to distances of about 50 bp. We analyze these data in terms of an evolutionary model with two distinct modes of site formation: (i) evolution from independent sequence origin and (ii) divergent evolution following duplication of a common ancestor sequence. Our results suggest that pervasive formation of binding sites by local sequence duplications distinguishes the complex regulatory architecture of higher eukaryotes from the simpler architecture of unicellular organisms

Using a structural and logics systems approach to infer bHLH–DNA binding specificity determinants

Numerous efforts are underway to determine gene regulatory networks that describe physical relationships between transcription factors (TFs) and their target DNA sequences. Members of paralogous TF families typically recognize similar DNA sequences. Knowledge of the molecular determinants of protein–DNA recognition by paralogous TFs is of central importance for understanding how small differences in DNA specificities can dictate target gene selection. Previously, we determined the in vitro DNA binding specificities of 19 Caenorhabditis elegans basic helix-loop-helix (bHLH) dimers using protein binding microarrays. These TFs bind E-box (CANNTG) and E-box-like sequences. Here, we combine these data with logics, bHLH–DNA co-crystal structures and computational modeling to infer which bHLH monomer can interact with which CAN E-box half-site and we identify a critical residue in the protein that dictates this specificity. Validation experiments using mutant bHLH proteins provide support for our inferences. Our study provides insights into the mechanisms of DNA recognition by bHLH dimers as well as a blueprint for system-level studies of the DNA binding determinants of other TF families in different model organisms and humans.National Institute of General Medical Sciences (U.S.) (DK068429)National Institute of General Medical Sciences (U.S.) (HG003985)European Union (PROSPECTS HEALTH-F4-2008-201648

Epistasis in a Model of Molecular Signal Transduction

Biological functions typically involve complex interacting molecular networks, with numerous feedback and regulation loops. How the properties of the system are affected when one, or several of its parts are modified is a question of fundamental interest, with numerous implications for the way we study and understand biological processes and treat diseases. This question can be rephrased in terms of relating genotypes to phenotypes: to what extent does the effect of a genetic variation at one locus depend on genetic variation at all other loci? Systematic quantitative measurements of epistasis – the deviation from additivity in the effect of alleles at different loci – on a given quantitative trait remain a major challenge. Here, we take a complementary approach of studying theoretically the effect of varying multiple parameters in a validated model of molecular signal transduction. To connect with the genotype/phenotype mapping we interpret parameters of the model as different loci with discrete choices of these parameters as alleles, which allows us to systematically examine the dependence of the signaling output – a quantitative trait – on the set of possible allelic combinations. We show quite generally that quantitative traits behave approximately additively (weak epistasis) when alleles correspond to small changes of parameters; epistasis appears as a result of large differences between alleles. When epistasis is relatively strong, it is concentrated in a sparse subset of loci and in low order (e.g. pair-wise) interactions. We find that focusing on interaction between loci that exhibit strong additive effects is an efficient way of identifying most of the epistasis. Our model study defines a theoretical framework for interpretation of experimental data and provides statistical predictions for the structure of genetic interaction expected for moderately complex biological circuits