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Localized arrays of proteins cooperatively assemble onto chromosomes to control DNA activity in many contexts. Binding cooperativity is often mediated by specific protein-protein interactions, but cooperativity through DNA structure is becoming increasingly recognized as an additional mechanism. During the site-specific DNA recombination reaction that excises phage λ from the chromosome, the bacterial DNA architectural protein Fis recruits multiple λ-encoded Xis proteins to the attR recombination site. Here, we report X-ray crystal structures of DNA complexes containing Fis + Xis, which show little, if any, contacts between the two proteins. Comparisons with structures of DNA complexes containing only Fis or Xis, together with mutant protein and DNA binding studies, support a mechanism for cooperative protein binding solely by DNA allostery. Fis binding both molds the minor groove to potentiate insertion of the Xis β-hairpin wing motif and bends the DNA to facilitate Xis-DNA contacts within the major groove. The Fis-structured minor groove shape that is optimized for Xis binding requires a precisely positioned pyrimidine-purine base-pair step, whose location has been shown to modulate minor groove widths in Fis-bound complexes to different DNA targets.
Bacteria encode homooligomeric single-stranded (ss) DNA-binding proteins (SSBs) that coat and protect ssDNA intermediates formed during genome maintenance reactions. The prototypical Escherichia coli SSB tetramer can bind ssDNA using multiple modes that differ by the number of bases bound per tetramer and the magnitude of the binding cooperativity. Our understanding of the mechanisms underlying cooperative ssDNA binding by SSBs has been hampered by the limited amount of structural information available for interfaces that link adjacent SSB proteins on ssDNA. Here we present a crystal structure of Bacillus subtilis SsbA bound to ssDNA. The structure resolves SsbA tetramers joined together by a ssDNA "bridge" and identifies an interface, termed the "bridge interface," that links adjacent SSB tetramers through an evolutionarily conserved surface near the ssDNA-binding site. E. coli SSB variants with altered bridge interface residues bind ssDNA with reduced cooperativity and with an altered distribution of DNA binding modes. These variants are also more readily displaced from ssDNA by RecA than wild-type SSB. In spite of these biochemical differences, each variant is able to complement deletion of the ssb gene in E. coli. Together our data suggest a model in which the bridge interface contributes to cooperative ssDNA binding and SSB function but that destabilization of the bridge interface is tolerated in cells.
The ARID (A-T Rich Interaction Domain) is a helix-turn-helix motif-based DNA-binding domain, conserved in all eukaryotes and diagnostic of a family that includes 15 distinct human proteins with important roles in development, tissue-specific gene expression and proliferation control. The 15 human ARID family proteins can be divided into seven subfamilies based on the degree of sequence identity between individual members. Most ARID family members have not been characterized with respect to their DNA-binding behavior, but it is already apparent that not all ARIDs conform to the pattern of binding AT-rich sequences. To understand better the divergent characteristics of the ARID proteins, we undertook a survey of DNA-binding properties across the entire ARID family. The results indicate that the majority of ARID subfamilies (i.e. five out of seven) bind DNA without obvious sequence preference. DNA-binding affinity also varies somewhat between subfamilies. Site-specific mutagenesis does not support suggestions made from structure analysis that specific amino acids in Loop 2 or Helix 5 are the main determinants of sequence specificity. Most probably, this is determined by multiple interacting differences across the entire ARID structure.
Despite their diverse biochemical characteristics and functions, all DNA-binding proteins share the ability to accurately locate their target sites among the vast excess of non-target DNA. Toward identifying universal mechanisms of the target search, we used single-molecule tracking of 11 diverse DNA-binding proteins in living Escherichia coli. The mobility of these proteins during the target search was dictated by DNA interactions rather than by their molecular weights. By generating cells devoid of all chromosomal DNA, we discovered that the nucleoid is not a physical barrier for protein diffusion but significantly slows the motion of DNA-binding proteins through frequent short-lived DNA interactions. The representative DNA-binding proteins (irrespective of their size, concentration, or function) spend the majority (58%-99%) of their search time bound to DNA and occupy as much as ∼30% of the chromosomal DNA at any time. Chromosome crowding likely has important implications for the function of all DNA-binding proteins.
DNA-binding proteins are key players in the regulation of gene expression and, hence, are essential for cell function. Chimeric proteins composed of DNA-binding domains and DNA modifying domains allow for precise genome manipulation. A key prerequisite is the specific recognition of a particular nucleotide sequence. Here, we quantitatively assess the binding affinity of DNA-binding proteins by molecular dynamics-based alchemical free energy simulations. A computational framework was developed to automatically set up in silico screening assays and estimate free energy differences using two independent procedures, based on equilibrium and non-equlibrium transformation pathways. The influence of simulation times on the accuracy of both procedures is presented. The binding specificity of a zinc-finger transcription factor to several sequences is calculated, and agreement with experimental data is shown. Finally we propose an in silico screening strategy aiming at the derivation of full specificity profiles for DNA-binding proteins.
Characterization and prediction of the DNA-biding regions in proteins are essential for our understanding of how proteins recognize/bind DNA. We analyze the unbound (U) and the bound (B) forms of proteins from the protein-DNA docking benchmark that contains 66 binary protein-DNA complexes along with their unbound counterparts. Proteins binding DNA undergo greater structural changes on complexation (in particular, those in the enzyme category) than those involved in protein-protein interactions (PPI). While interface atoms involved in PPI exhibit an increase in their solvent-accessible surface area (ASA) in the bound form in the majority of the cases compared to the unbound interface, protein-DNA interactions indicate increase and decrease in equal measure. In 25% structures, the U form has missing residues which are located in the interface in the B form. The missing atoms contribute more toward the buried surface area compared to other interface atoms. Lys, Gly and Arg are prominent in disordered segments that get ordered in the interface on complexation. In going from U to B, there may be an increase in coil and helical content at the expense of turns and strands. Consideration of flexibility cannot distinguish the interface residues from the surface residues in the U form.
The process of protein-DNA binding has an essential role in the biological processing of genetic information. We use relational machine learning to predict DNA-binding propensity of proteins from their structures. Automatically discovered structural features are able to capture some characteristic spatial configurations of amino acids in proteins.
Sequence-specific DNA-binding proteins (DBPs) play critical roles in biology and biotechnology, and there has been considerable interest in the engineering of DBPs with new or altered specificities for genome editing and other applications. While there has been some success in reprogramming naturally occurring DBPs using selection methods, the computational design of new DBPs that recognize arbitrary target sites remains an outstanding challenge. We describe a computational method for the design of small DBPs that recognize specific target sequences through interactions with bases in the major groove, and employ this method in conjunction with experimental screening to generate binders for 5 distinct DNA targets. These binders exhibit specificity closely matching the computational models for the target DNA sequences at as many as 6 base positions and affinities as low as 30-100 nM. The crystal structure of a designed DBP-target site complex is in close agreement with the design model, highlighting the accuracy of the design method. The designed DBPs function in both Escherichia coli and mammalian cells to repress and activate transcription of neighboring genes. Our method is a substantial step towards a general route to small and hence readily deliverable sequence-specific DBPs for gene regulation and editing.
Sequence-specific DNA-binding proteins play a key role in many fundamental biological processes, such as transcription, DNA replication and recombination. Very often, these DNA-binding proteins introduce structural changes to the target DNA-binding sites including DNA bending, twisting or untwisting and wrapping, which in many cases induce a linking number change (Delta Lk) to the DNA-binding site. Due to the lack of a feasible approach, Delta Lk induced by sequence-specific DNA-binding proteins has not been fully explored. In this paper we successfully constructed a series of DNA plasmids that carry many tandem copies of a DNA-binding site for one sequence-specific DNA-binding protein, such as lambda O, LacI, GalR, CRP and AraC. In this case, the protein-induced Delta Lk was greatly amplified and can be measured experimentally. Indeed, not only were we able to simultaneously determine the protein-induced Delta Lk and the DNA-binding constant for lambda O and GalR, but also we demonstrated that the protein-induced Delta Lk is an intrinsic property for these sequence-specific DNA-binding proteins. Our results also showed that protein-mediated DNA looping by AraC and LacI can induce a Delta Lk to the plasmid DNA templates. Furthermore, we demonstrated that the protein-induced Delta Lk does not correlate with the protein-induced DNA bending by the DNA-binding proteins.
Bacillus subtilis phage Φ29 has a linear, double-stranded DNA 19 kb long with an inverted terminal repeat of 6 nucleotides and a protein covalently linked to the 5' ends of the DNA. This protein, called terminal protein (TP), is the primer for the initiation of replication, a reaction catalyzed by the viral DNA polymerase at the two DNA ends. The DNA polymerase further elongates the nascent DNA chain in a processive manner, coupling strand displacement with elongation. The viral protein p5 is a single-stranded DNA binding protein (SSB) that binds to the single strands generated by strand displacement during the elongation process. Viral protein p6 is a double-stranded DNA binding protein (DBP) that preferentially binds to the origins of replication at the Φ29 DNA ends and is required for the initiation of replication. Both SSB and DBP are essential for Φ29 DNA amplification. This review focuses on the role of these phage DNA-binding proteins in Φ29 DNA replication both in vitro and in vivo, as well as on the implication of several B. subtilis DNA-binding proteins in different processes of the viral cycle. We will revise the enzymatic activities of the Φ29 DNA polymerase: TP-deoxynucleotidylation, processive DNA polymerization coupled to strand displacement, 3'-5' exonucleolysis and pyrophosphorolysis. The resolution of the Φ29 DNA polymerase structure has shed light on the translocation mechanism and the determinants responsible for processivity and strand displacement. These two properties have made Φ29 DNA polymerase one of the main enzymes used in the current DNA amplification technologies. The determination of the structure of Φ29 TP revealed the existence of three domains: the priming domain, where the primer residue Ser232, as well as Phe230, involved in the determination of the initiating nucleotide, are located, the intermediate domain, involved in DNA polymerase binding, and the N-terminal domain, responsible for DNA binding and localization of the TP at the bacterial nucleoid, where viral DNA replication takes place. The biochemical properties of the Φ29 DBP and SSB and their function in the initiation and elongation of Φ29 DNA replication, respectively, will be described.
Members of transcription factor families typically have similar DNA binding specificities yet execute unique functions in vivo. Transcription factors often bind DNA as multiprotein complexes, raising the possibility that complex formation might modify their DNA binding specificities. To test this hypothesis, we developed an experimental and computational platform, SELEX-seq, that can be used to determine the relative affinities to any DNA sequence for any transcription factor complex. Applying this method to all eight Drosophila Hox proteins, we show that they obtain novel recognition properties when they bind DNA with the dimeric cofactor Extradenticle-Homothorax (Exd). Exd-Hox specificities group into three main classes that obey Hox gene collinearity rules and DNA structure predictions suggest that anterior and posterior Hox proteins prefer DNA sequences with distinct minor groove topographies. Together, these data suggest that emergent DNA recognition properties revealed by interactions with cofactors contribute to transcription factor specificities in vivo.
The binding of transcription factors to their respective DNA sites is a key component of every regulatory network. Predictions of transcription factor binding sites are usually based on models for transcription factor specificity. These models, in turn, are often based on examples of known binding sites.
Detection of DNA-binding sites in proteins is of enormous interest for technologies targeting gene regulation and manipulation. We have previously shown that a residue and its sequence neighbor information can be used to predict DNA-binding candidates in a protein sequence. This sequence-based prediction method is applicable even if no sequence homology with a previously known DNA-binding protein is observed. Here we implement a neural network based algorithm to utilize evolutionary information of amino acid sequences in terms of their position specific scoring matrices (PSSMs) for a better prediction of DNA-binding sites.
The ARID is an ancient DNA-binding domain that is conserved throughout the evolution of higher eukaryotes. The ARID consensus sequence spans about 100 amino acid residues, and structural studies identify the major groove contact site as a modified helix-turn-helix motif. ARID-containing proteins exhibit a range of cellular functions, including participation in chromatin remodeling, and regulation of gene expression during cell growth, differentiation, and development. A subset of ARID family proteins binds DNA specifically at AT-rich sites; the remainder bind DNA nonspecifically. Orthologs to each of the seven distinct subfamilies of mammalian ARID-containing proteins are found in insect genomes, indicating the minimum age for the organization of these higher metazoan subfamilies. Many of these ancestral genes were duplicated and fixed over time to yield the 15 ARID-containing genes that are found in the human, mouse, and dog genomes. This paper describes a nomenclature, recommended by the Mouse Genomic Nomenclature Committee (MGNC) and accepted by the Human Genome Organization (HUGO) Gene Nomenclature Committee, for these mammalian ARID-containing genes that reflects this evolutionary history.
The cytidine deaminase, APOBEC3A (A3A), is a prominent source of mutations in multiple cancer types. These APOBEC-signature mutations are non-uniformly distributed across cancer genomes, associating with single-stranded (ss) DNA formed during DNA replication and hairpin-forming sequences. The biochemical and cellular factors that influence these specificities are unclear. We measured A3A's cytidine deaminase activity in vitro on substrates that model potential sources of ssDNA in the cell and found that A3A is more active on hairpins containing 4 nt ssDNA loops compared to hairpins with larger loops, bubble structures, replication fork mimics, ssDNA gaps, or linear DNA. Despite pre-bent ssDNAs being expected to fit better in the A3A active site, we determined A3A favors a 4 nt hairpin substrate only 2- to fivefold over linear ssDNA substrates. Addition of whole cell lysates or purified RPA to cytidine deaminase assays more severely reduced A3A activity on linear ssDNA (45 nt) compared to hairpin substrates. These results indicate that the large enrichment of A3A-driven mutations in hairpin-forming sequences in tumor genomes is likely driven in part by other proteins that preferentially bind longer ssDNA regions, which limit A3A's access. Furthermore, A3A activity is reduced at ssDNA associated with a stalled T7 RNA polymerase, suggesting that potential protein occlusion by RNA polymerase also limits A3A activity. These results help explain the small transcriptional strand bias for APOBEC mutation signatures in cancer genomes and the general targeting of hairpin-forming sequences in the lagging strand template during DNA replication.
We report data from single molecule studies on the interaction between single DNA molecules and core histones using custom-designed horizontal magnetic tweezers. The DNA-core histone complexes were formed using λ-DNA tethers, core histones, and NAP1 and were exposed to forces ranging from ~2 pN to ~74 pN. During the assembly events, we observed the length of the DNA decrease in approximate integer multiples of ~50 nm, suggesting the binding of the histone octamers to the DNA tether. During the mechanically induced disassembly events, we observed disruption lengths in approximate integer multiples of ~50 nm, suggesting the unbinding of one or more octamers from the DNA tether. We also observed histone octamer unbinding events at forces as low as ~2 pN. Our horizontal magnetic tweezers yielded high-resolution, low-noise data on force-mediated DNA-core histone assembly and disassembly processes.
Single-stranded DNA-binding proteins (SSBs) are required for repair, recombination and replication in all organisms. Eukaryotic SSBs are regulated by phosphorylation on serine and threonine residues. To our knowledge, phosphorylation of SSBs in bacteria has not been reported. A systematic search for phosphotyrosine-containing proteins in Streptomyces griseus by immunoaffinity chromatography identified bacterial SSBs as a novel target of bacterial tyrosine kinases. Since genes encoding protein-tyrosine kinases (PTKs) have not been recognized in streptomycetes, and SSBs from Streptomyces coelicolor (ScSSB) and Bacillus subtilis (BsSSB) share 38.7% identity, we used a B.subtilis protein-tyrosine kinase YwqD to phosphorylate two cognate SSBs (BsSSB and YwpH) in vitro. We demonstrate that in vivo phosphorylation of B.subtilis SSB occurs on tyrosine residue 82, and this reaction is affected antagonistically by kinase YwqD and phosphatase YwqE. Phosphorylation of B.subtilis SSB increased binding almost 200-fold to single-stranded DNA in vitro. Tyrosine phosphorylation of B.subtilis, S.coelicolor and Escherichia coli SSBs occured while they were expressed in E.coli, indicating that tyrosine phosphorylation of SSBs is a conserved process of post-translational modification in taxonomically distant bacteria.
We developed a new approach that couples Southwestern blotting and mass spectrometry to discover proteins that bind extracellular DNA (eDNA) in bacterial biofilms. Using Staphylococcus aureus as a model pathogen, we identified proteins with known DNA-binding activity and uncovered a series of lipoproteins with previously unrecognized DNA-binding activity. We demonstrated that expression of these lipoproteins results in an eDNA-dependent biofilm enhancement. Additionally, we found that while deletion of lipoproteins had a minimal impact on biofilm accumulation, these lipoprotein mutations increased biofilm porosity, suggesting that lipoproteins and their associated interactions contribute to biofilm structure. For one of the lipoproteins, SaeP, we showed that the biofilm phenotype requires the lipoprotein to be anchored to the outside of the cellular membrane, and we further showed that increased SaeP expression correlates with more retention of high-molecular-weight DNA on the bacterial cell surface. SaeP is a known auxiliary protein of the SaeRS system, and we also demonstrated that the levels of SaeP correlate with nuclease production, which can further impact biofilm development. It has been reported that S. aureus biofilms are stabilized by positively charged cytoplasmic proteins that are released into the extracellular environment, where they make favorable electrostatic interactions with the negatively charged cell surface and eDNA. In this work we extend this electrostatic net model to include secreted eDNA-binding proteins and membrane-attached lipoproteins that can function as anchor points between eDNA in the biofilm matrix and the bacterial cell surface.IMPORTANCE Many bacteria are capable of forming biofilms encased in a matrix of self-produced extracellular polymeric substances (EPS) that protects them from chemotherapies and the host defenses. As a result of these inherent resistance mechanisms, bacterial biofilms are extremely difficult to eradicate and are associated with chronic wounds, orthopedic and surgical wound infections, and invasive infections, such as infective endocarditis and osteomyelitis. It is therefore important to understand the nature of the interactions between the bacterial cell surface and EPS that stabilize biofilms. Extracellular DNA (eDNA) has been recognized as an EPS constituent for many bacterial species and has been shown to be important in promoting biofilm formation. Using Staphylococcus aureus biofilms, we show that membrane-attached lipoproteins can interact with the eDNA in the biofilm matrix and promote biofilm formation, which suggests that lipoproteins are potential targets for novel therapies aimed at disrupting bacterial biofilms.
Recognition models for protein-DNA interactions, which allow the prediction of specificity for a DNA-binding domain based only on its sequence or the alteration of specificity through rational design, have long been a goal of computational biology. There has been some progress in constructing useful models, especially for C(2)H(2) zinc finger proteins, but it remains a challenging problem with ample room for improvement. For most families of transcription factors the best available methods utilize k-nearest neighbor (KNN) algorithms to make specificity predictions based on the average of the specificities of the k most similar proteins with defined specificities. Homeodomain (HD) proteins are the second most abundant family of transcription factors, after zinc fingers, in most metazoan genomes, and as a consequence an effective recognition model for this family would facilitate predictive models of many transcriptional regulatory networks within these genomes.
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