Crystallization and preliminary X‐ray diffraction analysis of the Pax9 paired domain bound to a DC5 enhancer DNA element

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109357/1/S2053230X14017415.pd

DNA-mediated cooperativity facilitates the co-selection of cryptic enhancer sequences by SOX2 and PAX6 transcription factors

© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. Sox2 and Pax6 are transcription factors that direct cell fate decision during neurogenesis, yet the mechanism behind how they cooperate on enhancer DNA elements and regulate gene expression is unclear. By systematically interrogating Sox2 and Pax6 interaction on minimal enhancer elements, we found that cooperative DNA recognition relies on combinatorial nucleotide switches and precisely spaced, but cryptic composite DNA motifs. Surprisingly, all tested Sox and Pax paralogs have the capacity to cooperate on such enhancer elements. NMR and molecular modeling reveal very few direct protein-protein interactions between Sox2 and Pax6, suggesting that cooperative binding is mediated by allosteric interactions propagating through DNA structure. Furthermore, we detected and validated several novel sites in the human genome targeted cooperatively by Sox2 and Pax6. Collectively, we demonstrate that Sox- Pax partnerships have the potential to substantially alter DNA target specificities and likely enable the pleiotropic and context-specific action of these cell-lineage specifiers.Link_to_subscribed_fulltex

TherMos: Estimating protein-DNA binding energies from in vivo binding profiles

Accurately characterizing transcription factor (TF)-DNA affinity is a central goal of regulatory genomics. Although thermodynamics provides the most natural language for describing the continuous range of TF-DNA affinity, traditional motif discovery algorithms focus instead on classification paradigms that aim to discriminate 'bound' and 'unbound' sequences. Moreover, these algorithms do not directly model the distribution of tags in ChIP-seq data. Here, we present a new algorithm named Thermodynamic Modeling of ChIP-seq (TherMos), which directly estimates a positionspecific binding energy matrix (PSEM) from ChIPseq/exo tag profiles. In cross-validation tests on seven genome-wide TF-DNA binding profiles, one of which we generated via ChIP-seq on a complex developing tissue, TherMos predicted quantitative TF-DNA binding with greater accuracy than five well-known algorithms. We experimentally validated TherMos binding energy models for Klf4 and Esrrb, using a novel protocol to measure PSEMs in vitro. Strikingly, our measurements revealed strong nonadditivity at multiple positions within the two PSEMs. Among the algorithms tested, only TherMos was able to model the entire binding energy landscape of Klf4 and Esrrb. Our study reveals new insights into the energetics of TF-DNA binding in vivo and provides an accurate first-principles approach to binding energy inference from ChIP-seq and ChIP-exo data. © 2013 The Author(s).Link_to_subscribed_fulltex

Deciphering the Sox-Oct partner code by quantitative cooperativity measurements

Several Sox-Oct transcription factor (TF) combinations have been shown to cooperate on diverse enhancers to determine cell fates. Here, we developed a method to quantify biochemically the Sox-Oct cooperation and assessed the pairing of the high-mobility group (HMG) domains of 11 Sox TFs with Oct4 on a series of composite DNA elements. This way, we clustered Sox proteins according to their dimerization preferences illustrating that Sox HMG domains evolved different propensities to cooperate with Oct4. Sox2, Sox14, Sox21 and Sox15 strongly cooperate on the canonical element but compete with Oct4 on a recently discovered compressed element. Sry also cooperates on the canonical element but binds additively to the compressed element. In contrast, Sox17 and Sox4 cooperate more strongly on the compressed than on the canonical element. Sox5 and Sox18 show some cooperation on both elements, whereas Sox8 and Sox9 compete on both elements. Testing rationally mutated Sox proteins combined with structural modeling highlights critical amino acids for differential Sox-Oct4 partnerships and demonstrates that the cooperativity correlates with the efficiency in producing induced pluripotent stem cells. Our results suggest selective Sox-Oct partnerships in genome regulation and provide a toolset to study protein cooperation on DNA

Novel engineered nanobodies specific for N-terminal region of alpha-synuclein recognize Lewy-body pathology and inhibit in-vitro seeded aggregation and toxicity.

Nanobodies (Nbs), the single-domain antigen-binding fragments of dromedary heavy-chain antibodies (HCAb), are excellent candidates as therapeutic and diagnostic tools in synucleinopathies because of their small size, solubility and stability. Here, we constructed an immune nanobody library specific to the monomeric form of alpha-synuclein (α-syn). Phage display screening of the library allowed the identification of a nanobody, Nbα-syn01, specific for α-syn. Unlike previously developed nanobodies, Nbα-syn01 recognized the N-terminal region which is critical for in vitro and in vivo aggregation and contains many point mutations involved in early PD cases. The affinity of the monovalent Nbα-syn01 and the engineered bivalent format BivNbα-syn01 measured by isothermal titration calorimetry revealed unexpected results where Nbα-syn01 and its bivalent format recognized preferentially α-syn fibrils compared to the monomeric form. Nbα-syn01 and BivNbα-syn01 were also able to inhibit α-syn-seeded aggregation in vitro and reduced α-syn-seeded aggregation and toxicity in cells showing their potential to reduce α-syn pathology. Moreover, both nanobody formats were able to recognize Lewy-body pathology in human post-mortem brain tissue from PD and DLB cases. Additionally, we present evidence through structural docking that Nbα-syn01 binds the N-terminal region of the α-syn aggregated form. Overall, these results highlight the potential of Nbα-syn01 and BivNbα-syn01 in developing into a diagnostic or a therapeutic tool for PD and related disorders

Structural basis for the cooperative DNA recognition by Smad4 MH1 dimers

Smad proteins form multimeric complexes consisting of the ‘common partner’ Smad4 and receptor regulated R-Smads on clustered DNA binding sites. Deciphering how pathway specific Smad complexes multimerize on DNA to regulate gene expression is critical for a better understanding of the cis-regulatory logic of TGF-β and BMP signaling. To this end, we solved the crystal structure of the dimeric Smad4 MH1 domain bound to a palindromic Smad binding element. Surprisingly, the Smad4 MH1 forms a constitutive dimer on the SBE DNA without exhibiting any direct protein–protein interactions suggesting a DNA mediated indirect readout mechanism. However, the R-Smads Smad1, Smad2 and Smad3 homodimerize with substantially decreased efficiency despite pronounced structural similarities to Smad4. Therefore, intricate variations in the DNA structure induced by different Smads and/or variant energetic profiles likely contribute to their propensity to dimerize on DNA. Indeed, competitive binding assays revealed that the Smad4/R-Smad heterodimers predominate under equilibrium conditions while R-Smad homodimers are least favored. Together, we present the structural basis for DNA recognition by Smad4 and demonstrate that Smad4 constitutively homo- and heterodimerizes on DNA in contrast to its R-Smad partner proteins by a mechanism independent of direct protein contacts

Implications for domain fusion protein-protein interactions based on structural information

Abstract Background Several in silico methods exist that were developed to predict protein interactions from the copious amount of genomic and proteomic data. One of these methods is Domain Fusion, which has proven to be effective in predicting functional links between proteins. Results Analyzing the structures of multi-domain single-chain peptides, we found that domain pairs located less than 30 residues apart on a chain are almost certain to share a physical interface. The majority of these interactions are also conserved across separate chains. We make use of this observation to improve domain fusion based protein interaction predictions, and demonstrate this by implementing it on a set of Saccharomyces cerevisiae proteins. Conclusion We show that existing structural data supports the domain fusion hypothesis. Empirical information from structural data also enables us to refine and assess domain fusion based protein interaction predictions. These interactions can then be integrated with downstream biochemical and genetic assays to generate more reliable protein interaction data sets.</p

Molecule

US7998701Granted Paten