Reversible and spatiotemporal control of colloidal structure formation

Tuning colloidal structure formation is a powerful approach to building functional materials, as a wide range of optical and viscoelastic properties can be accessed by the choice of individual building blocks and their interactions. Precise control is achieved by DNA specificity, depletion forces, or geometric constraints and results in a variety of complex structures. Due to the lack of control and reversibility of the interactions, an autonomous oscillating system on a mesoscale without external driving was not feasible until now. Here, we show that tunable DNA reaction circuits controlling linker strand concentrations can drive the dynamic and fully reversible assembly of DNA-functionalized micron-sized particles. The versatility of this approach is demonstrated by programming colloidal interactions in sequential and spatial order to obtain an oscillatory structure formation process on a mesoscopic scale. The experimental results represent an approach for the development of active materials by using DNA reaction networks to scale up the dynamic control of colloidal self-organization.

Structural basis for Cas9 off-target activity

The target DNA specificity of the CRISPR-associated genome editor nuclease Cas9 is determined by complementarity to a 20-nucleotide segment in its guide RNA. However, Cas9 can bind and cleave partially complementary off-target sequences, which raises safety concerns for its use in clinical applications. Here we report crystallographic structures of Cas9 bound to bona fide off-target substrates, revealing that off-target binding is enabled by a range of non- canonical base pairing interactions and preservation of base stacking within the guide-off-target heteroduplex. Off-target sites containing single-nucleotide deletions relative to the guide RNA are accommodated by base skipping rather than RNA bulge formation. Additionally, PAM-distal mismatches result in duplex unpairing and induce a conformational change of the Cas9 REC lobe that perturbs its conformational activation. Together, these insights provide a structural rationale for the off-target activity of Cas9 and contribute to the improved rational design of guide RNAs and off-target prediction algorithms.

Structural basis of ATP-dependent high-fidelity epigenome maintenance

Epigenetic evolution occurs over million-year timescales in Cryptococcus neoformans and is mediated by DNMT5, the first maintenance-type cytosine methyltransferase identified in the fungal or protist kingdoms. DNMT5 requires ATP and displays exquisite hemimethyl-DNA specificity. To understand these novel properties, we solved cryo-EM structures of CnDNMT5 in three states. These studies reveal an elaborate allosteric cascade in which hemimethylated DNA first activates the SNF2 ATPase domain by a large rigid body rotation while the target cytosine partially flips out the DNA duplex. ATP binding then triggers a striking structural reconfiguration of the methyltransferase catalytic pocket that enables cofactor binding, completion of base-flipping, and catalysis. Unmethylated DNA binding fails to open cofactor pocket and subsequent ATP binding triggers its ejection to ensure fidelity. This chaperone-like, enzyme-remodeling role of the SNF2 domain illuminates how energy can be used to enable faithful epigenetic memory.

DNA specificity in two Hedysarum sections, Hedysarum and Multicaulia (Siberia, Russia) inferred from ETS sequence data

Based on sequence data of the nuclear ETS markers of 20 species, the relationships of sections Hedysarum and Multicaulia were assessed. Phylogenetic analysis was performed on the complete sequences using the Neighbor-Joining methods. The nuclear marker ETS is investigated for the first time in the most species excluding H. hedysaroides, H. inundatum, H. ferganense, and H. neglectum. The length of sequences varies from 349 to 357 nucleotides. It is noteworthy that ETS data significantly discriminate H. ferganense from both sections, Hedysarum and Multicaulia. Moreover, our results did not support the subsectional division of Multicaulia section. Therefore, the ETS sequence data obtained in our study for 20 taxa of Hedysarum evidence the nonmonophyly of section Multicaulia.

Rewiring the specificity of extracytoplasmic function sigma factors

Bacterial genomes are being sequenced at an exponentially increasing rate, but our inability to decipher their transcriptional wiring limits our ability to derive new biology from these sequences. De novo determination of regulatory interactions requires accurate prediction of regulators’ DNA binding and precise determination of biologically significant binding sites. Here we address these challenges by solving the DNA-specificity code of extracytoplasmic function sigma factors (ECF σs), a major family of bacterial regulators, and determining their putative regulons. We generated an aligned collection of ECF σs and their promoters by leveraging the autoregulatory nature of ECF σs as a means of promoter discovery and analyzed it to identify and characterize the conserved amino acid–nucleotide interactions that determine promoter specificity. This enabled de novo prediction of ECF σ specificity, which we combined with a statistically rigorous phylogenetic footprinting pipeline based on precomputed orthologs to predict the direct targets of ∼67% of ECF σs. This global survey indicated that some ECF σs are conserved global regulators controlling many genes throughout the genome, which are important under many conditions, while others are local regulators, controlling a few closely linked genes in response to specific stimuli in select species. This analysis reveals important organizing principles of bacterial gene regulation and presents a conceptual and computational framework for deciphering gene regulatory networks.

Integrating genome sequence and structural data for statistical learning to predict transcription factor binding sites

We report an approach to predict DNA specificity of the tetracycline repressor (TetR) family transcription regulators (TFRs). First, a genome sequence-based method was streamlined with quantitative P-values defined to filter out reliable predictions. Then, a framework was introduced to incorporate structural data and to train a statistical energy function to score the pairing between TFR and TFR binding site (TFBS) based on sequences. The predictions benchmarked against experiments, TFBSs for 29 out of 30 TFRs were correctly predicted by either the genome sequence-based or the statistical energy-based method. Using P-values or Z-scores as indicators, we estimate that 59.6% of TFRs are covered with relatively reliable predictions by at least one of the two methods, while only 28.7% are covered by the genome sequence-based method alone. Our approach predicts a large number of new TFBs which cannot be correctly retrieved from public databases such as FootprintDB. High-throughput experimental assays suggest that the statistical energy can model the TFBSs of a significant number of TFRs reliably. Thus the energy function may be applied to explore for new TFBSs in respective genomes. It is possible to extend our approach to other transcriptional factor families with sufficient structural information.

Rewiring the specificity of extra-cytoplasmic function sigma factors

SUMMARYBacterial genomes are being sequenced at an exponentially increasing rate, but our inability to decipher their transcriptional wiring limits our ability to derive new biology from these sequences. De novo determination of regulatory interactions requires accurate prediction of regulators’ DNA binding and precise determination of biologically significant binding sites. Here, we address these challenges by solving the DNA-specificity code of extra-cytoplasmic function sigma factors (ECF σs), a major family of bacterial regulators, and determining their regulons. We generated an aligned collection of ECF σs and their promoters by leveraging the auto-regulatory nature of ECF σs as a means of promoter discovery and analyzed it to identify and characterize the conserved amino acid – nucleotide interactions that determine promoter specificity. This enabled de novo prediction of ECF σ specificity, which we combined with a statistically rigorous phylogenetic foot-printing pipeline based on precomputed orthologs to predict the direct targets of ∼67% of ECF σs. This global survey indicated that ECF σs play varied roles: some are global regulators controlling many genes throughout the genome that are important under many conditions, while others are local regulators, controlling few closely linked genes in response to specific stimuli. This analysis reveals important organizing principles of bacterial gene regulation and presents a conceptual and computational framework for deciphering gene regulatory networks.