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The complete nucleic acid sequence of the Penaeus monodon densovirus (PmDNV) from India was characterized. Analysis of the whole genome, consisting of 6310 bp revealed the presence of three open reading frames (ORFs), comprising 1281 bp, 1734 bp and 2460 bp, respectively. The complete genome and amino acid sequences of three proteins viz., NS1, NS2 and VP were compared with PmDNV from Thailand, PmergDNV from Australia and other partial sequences in GenBank, respectively. Highest nucleotide similarity was observed with the Thai strain (88%), while 33, 32 and 91 amino acid substitutions were observed in the NS2, NS1 and VP, respectively. Phylogenetic analysis of shrimp, insect and vertebrate parvovirus sequences revealed that the Indian PmDNV is more closely related to Thai isolates than all other parvoviruses reported so far.
A group of intrinsically disordered, hydrophilic proteins-Late Embryogenesis Abundant (LEA) proteins-has been linked to survival in plants and animals in periods of stress, putatively through safeguarding enzymatic function and prevention of aggregation in times of dehydration/heat. Yet despite decades of effort, the molecular-level mechanisms defining this protective function remain unknown. A recent effort to understand LEA functionality began with the unique application of phage display, wherein phage display and biopanning over recombinant Seed Maturation Protein homologs from Arabidopsis thaliana and Glycine max were used to retrieve client proteins at two different temperatures, with one intended to represent heat stress. From this previous study, we identified 21 client proteins for which clones were recovered, sometimes repeatedly. Here, we use sequence analysis and homology modeling of the client proteins to ascertain common sequence and structural properties that may contribute to binding affinity with the protective LEA protein. Our methods uncover what appears to be a predilection for protein-nucleic acid interactions among LEA client proteins, which is suggestive of subcellular residence. The results from this initial computational study will guide future efforts to uncover the protein protective mechanisms during heat stress, potentially leading to phage-display-directed evolution of synthetic LEA molecules.
Translin is a highly conserved RNA- and DNA-binding protein that plays essential roles in eukaryotic cells. Human translin functions as an octamer, but in the octameric crystallographic structure, the residues responsible for nucleic acid binding are not accessible. Moreover, electron microscopy data reveal very different octameric configurations. Consequently, the functional assembly and the mechanism of nucleic acid binding by the protein remain unclear. Here, we present an integrative study combining small-angle X-ray scattering (SAXS), site-directed mutagenesis, biochemical analysis and computational techniques to address these questions. Our data indicate a significant conformational heterogeneity for translin in solution, formed by a lesser-populated compact octameric state resembling the previously solved X-ray structure, and a highly populated open octameric state that had not been previously identified. On the other hand, our SAXS data and computational analyses of translin in complex with the RNA oligonucleotide (GU)12 show that the internal cavity found in the octameric assemblies can accommodate different nucleic acid conformations. According to this model, the nucleic acid binding residues become accessible for binding, which facilitates the entrance of the nucleic acids into the cavity. Our data thus provide a structural basis for the functions that translin performs in RNA metabolism and transport.
Protein-RNA and protein-DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein-nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein-nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein-DNA and protein-RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein-nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.
Mitochondrial DNA (mtDNA) deletions are a common cause of mitochondrial disorders. Large mtDNA deletions can lead to a broad spectrum of clinical features with different age of onset, ranging from mild mitochondrial myopathies (MM), progressive external ophthalmoplegia (PEO), and Kearns-Sayre syndrome (KSS), to severe Pearson syndrome. The aim of this study is to investigate the molecular signatures surrounding the deletion breakpoints and their association with the clinical phenotype and age at onset. MtDNA deletions in 67 patients were characterized using array comparative genomic hybridization (aCGH) followed by PCR-sequencing of the deletion junctions. Sequence homology including both perfect and imperfect short repeats flanking the deletion regions were analyzed and correlated with clinical features and patients' age group. In all age groups, there was a significant increase in sequence homology flanking the deletion compared to mtDNA background. The youngest patient group (<6 years old) showed a diffused pattern of deletion distribution in size and locations, with a significantly lower sequence homology flanking the deletion, and the highest percentage of deletion mutant heteroplasmy. The older age groups showed rather discrete pattern of deletions with 44% of all patients over 6 years old carrying the most common 5 kb mtDNA deletion, which was found mostly in muscle specimens (22/41). Only 15% (3/20) of the young patients (<6 years old) carry the 5 kb common deletion, which is usually present in blood rather than muscle. This group of patients predominantly (16 out of 17) exhibit multisystem disorder and/or Pearson syndrome, while older patients had predominantly neuromuscular manifestations including KSS, PEO, and MM. In conclusion, sequence homology at the deletion flanking regions is a consistent feature of mtDNA deletions. Decreased levels of sequence homology and increased levels of deletion mutant heteroplasmy appear to correlate with earlier onset and more severe disease with multisystem involvement.
Barnacles adhere by producing a mixture of cement proteins (CPs) that organize into a permanently bonded layer displayed as nanoscale fibers. These cement proteins share no homology with any other marine adhesives, and a common sequence-basis that defines how nanostructures function as adhesives remains undiscovered. Here we demonstrate that a significant unidentified portion of acorn barnacle cement is comprised of low complexity proteins; they are organized into repetitive sequence blocks and found to maintain homology to silk motifs. Proteomic analysis of aggregate bands from PAGE gels reveal an abundance of Gly/Ala/Ser/Thr repeats exemplified by a prominent, previously unidentified, 43 kDa protein in the solubilized adhesive. Low complexity regions found throughout the cement proteome, as well as multiple lysyl oxidases and peroxidases, establish homology with silk-associated materials such as fibroin, silk gum sericin, and pyriform spidroins from spider silk. Distinct primary structures defined by homologous domains shed light on how barnacles use low complexity in nanofibers to enable adhesion, and serves as a starting point for unraveling the molecular architecture of a robust and unique class of adhesive nanostructures.
Sequence database searches followed by homology-based function transfer form one of the oldest and most popular approaches for predicting protein functions, such as Gene Ontology (GO) terms. Although sequence search tools are the basis of homology-based protein function prediction, previous studies have scarcely explored how to select the optimal sequence search tools and configure their parameters to achieve the best function prediction. In this paper, we evaluate the effect of using different options from among popular search tools, as well as the impacts of search parameters, on protein function prediction. When predicting GO terms on a large benchmark dataset, we found that BLASTp and MMseqs2 consistently exceed the performance of other tools, including DIAMOND - one of the most popular tools for function prediction - under default search parameters. However, with the correct parameter settings, DIAMOND can perform comparably to BLASTp and MMseqs2 in function prediction. This study emphasizes the critical role of search parameter settings in homology-based function transfer.
Most eukaryotic genomes contain substantial amounts of repetitive DNA organized in the form of constitutive heterochromatin and associated with repressive epigenetic modifications, such as H3K9me3 and C5 cytosine methylation (5mC). In the fungus Neurospora crassa, H3K9me3 and 5mC are catalyzed, respectively, by a conserved SUV39 histone methyltransferase, DIM-5, and a DNMT1-like cytosine methyltransferase, DIM-2. Here we show that DIM-2 can also mediate repeat-induced point mutation (RIP) of repetitive DNA in N. crassa. We further show that DIM-2-dependent RIP requires DIM-5, HP1, and other known heterochromatin factors, implying a role for a repeat-induced heterochromatin-related process. Our previous findings suggest that the mechanism of repeat recognition for RIP involves direct interactions between homologous double-stranded DNA (dsDNA) segments. We thus now propose that, in somatic cells, homologous dsDNA-dsDNA interactions between a small number of repeat copies can nucleate a transient heterochromatic state, which, on longer repeat arrays, may lead to the formation of constitutive heterochromatin.
eurygaster integriceps Puton, commonly known as sunn pest, is a major pest of wheat in Northern Africa, the Middle East and Eastern Europe. This insect injects a prolyl endoprotease into the wheat, destroying the gluten. The purpose of this study was to clone the full length cDNA of the sunn pest prolyl endoprotease (spPEP) for expression in E. coli and to compare the amino acid sequence of the enzyme to other known PEPs in both phylogeny and potential tertiary structure. Sequence analysis shows that the 5ꞌ UTR contains several putative transcription factor binding sites for transcription factors known to be expressed in Drosophila that might be useful targets for inhibition of the enzyme. The spPEP was first identified as a prolyl endoprotease by Darkoh et al., 2010. The enzyme is a unique serine protease of the S9A family by way of its substrate recognition of the gluten proteins, which are greater than 30 kD in size. At 51% maximum identity to known PEPs, homology modeling using SWISS-MODEL, the porcine brain PEP (PDB: 2XWD) was selected in the database of known PEP structures, resulting in a predicted tertiary structure 99% identical to the porcine brain PEP structure. A Km for the recombinant spPEP was determined to be 210 ± 53 µM for the zGly-Pro-pNA substrate in 0.025 M ethanolamine, pH 8.5, containing 0.1 M NaCl at 37 °C with a turnover rate of 172 ± 47 µM Gly-Pro-pNA/s/µM of enzyme.
The Sac10b protein family is regarded as a group of nucleic acid-binding proteins that are highly conserved and widely distributed within archaea. All reported members of this family are basic proteins that exist as homodimers in solution and bind to DNA and/or RNA without apparent sequence specificity in vitro. Here, we reported a unique member of the family, Mth10b from Methanobacterium thermoautotrophicum ΔH, whose amino acid sequence shares high homology with other Sac10b family proteins. However, unlike those proteins, Mth10b is an acidic protein; its potential isoelectric point is only 4.56, which is inconsistent with the characteristics of a nucleic acid-binding protein. In this study, Mth10b was expressed in Escherichia coli and purified using a three-column chromatography purification procedure. Biochemical characterization indicated that Mth10b should be similar to typical Sac10b family proteins with respect to its secondary and tertiary structure and in its preferred oligomeric forms. However, an electrophoretic mobility shift analysis (EMSA) showed that neither DNA nor RNA bound to Mth10b in vitro, indicating that either Mth10b likely has a physiological function that is distinct from those of other Sac10b family members or nucleic acid-binding ability may not be a fundamental factor to the actual function of the Sac10b family.
In eukaryotes, RNA-binding proteins that contain multiple K homology (KH) domains play a key role in coordinating the different steps of RNA synthesis, metabolism and localization. Understanding how the different KH modules participate in the recognition of the RNA targets is necessary to dissect the way these proteins operate. We have designed a KH mutant with impaired RNA-binding capability for general use in exploring the role of individual KH domains in the combinatorial functional recognition of RNA targets. A double mutation in the hallmark GxxG loop (GxxG-to-GDDG) impairs nucleic acid binding without compromising the stability of the domain. We analysed the impact of the GDDG mutations in individual KH domains on the functional properties of KSRP as a prototype of multiple KH domain-containing proteins. We show how the GDDG mutant can be used to directly link biophysical information on the sequence specificity of the different KH domains of KSRP and their role in mRNA recognition and decay. This work defines a general molecular biology tool for the investigation of the function of individual KH domains in nucleic acid binding proteins.
We describe a general binding score for predicting the nucleic acid binding probability in proteins. The score is directly derived from physicochemical and evolutionary features and integrates a residue neighboring network approach. Our process achieves stable and high accuracies on both DNA- and RNA-binding proteins and illustrates how the main driving forces for nucleic acid binding are common. Because of the effective integration of the synergetic effects of the network of neighboring residues and the fact that the prediction yields a hierarchical scoring on the protein surface, energy funnels for nucleic acid binding appear on protein surfaces, pointing to the dynamic process occurring in the binding of nucleic acids to proteins.
Profiling the nucleic acid-binding proteins (NABPs) during aging process is critical to elucidate its roles in biological systems as well as transcriptional and translational regulation. Here, we developed a comprehensive strategy to survey the NABPs of mouse immune organs by using single cell preparation and selective capture technology-based proteomics. Our approach provided a global view of tissue NABPs from different organs under normal physiological conditions with extraction specificity of 70 to 90%. Through quantitative proteomics analysis of mouse spleen and thymus at 1, 4, 12, 24, 48, and 72 weeks, we investigated the molecular features of aging-related NABPs. A total of 2674 proteins were quantified in all six stages, demonstrating distinct and time-specific expression pattern of NABPs. Thymus and spleen exhibited unique aging signatures, and differential proteins and pathways were enriched across the mouse lifespan. Three core modules and 16 hub proteins associated with aging were revealed through weighted gene correlation network analysis. Significant candidates were screened for immunoassay verification, and six hub proteins were confirmed. The integrated strategy pertains the capability to decipher the dynamic functions of NABPs in aging physiology and benefit further mechanism research.
Function annotation efforts provide a foundation to our understanding of cellular processes and the functioning of the living cell. This motivates high-throughput computational methods to characterize new protein members of a particular function. Research work has focused on discriminative machine-learning methods, which promise to make efficient, de novo predictions of protein function. Furthermore, available function annotation exists predominantly for individual proteins rather than residues of which only a subset is necessary for the conveyance of a particular function. This limits discriminative approaches to predicting functions for which there is sufficient residue-level annotation, e.g., identification of DNA-binding proteins or where an excellent global representation can be divined. Complete understanding of the various functions of proteins requires discovery and functional annotation at the residue level. Herein, we cast this problem into the setting of multiple-instance learning, which only requires knowledge of the protein's function yet identifies functionally relevant residues and need not rely on homology. We developed a new multiple-instance leaning algorithm derived from AdaBoost and benchmarked this algorithm against two well-studied protein function prediction tasks: annotating proteins that bind DNA and RNA. This algorithm outperforms certain previous approaches in annotating protein function while identifying functionally relevant residues involved in binding both DNA and RNA, and on one protein-DNA benchmark, it achieves near perfect classification.
Lipopolyamines (LPAs) are cationic lipids; they interact spontaneously with nucleic acids to form lipoplexes used for gene delivery. The main hurdle to using lipoplexes in gene therapy lies in their immunostimulatory properties, so far attributed to the nucleic acid cargo, while cationic lipids were considered as inert to the immune system. Here we demonstrate for the first time that di-C18 LPAs trigger pro-inflammatory responses through Toll-like receptor 2 (TLR2) activation, and this whether they are bound to nucleic acids or not. Molecular docking experiments suggest potential TLR2 binding modes reminiscent of bacterial lipopeptide sensing. The di-C18 LPAs share the ability of burying their lipid chains in the hydrophobic cavity of TLR2 and, in some cases, TLR1, at the vicinity of the dimerization interface; the cationic headgroups form multiple hydrogen bonds, thus crosslinking TLRs into functional complexes. Unravelling the molecular basis of TLR1 and TLR6-driven heterodimerization upon LPA binding underlines the highly collaborative and promiscuous ligand binding mechanism. The prevalence of non-specific main chain-mediated interactions demonstrates that potentially any saturated LPA currently used or proposed as transfection agent is likely to activate TLR2 during transfection. Hence our study emphasizes the urgent need to test the inflammatory properties of transfection agents and proposes the use of docking analysis as a preliminary screening tool for the synthesis of new non-immunostimulatory nanocarriers.
Interactions between nuclide acids (RNA/DNA) play important roles in many basic cellular activities like transcription regulation, RNA processing, and protein synthesis. Therefore, determining the complex structures between RNAs/DNAs is crucial to understand the molecular mechanism of related RNA/DNA-RNA/DNA interactions. Here, we have presented HNADOCK, a user-friendly web server for nucleic acid (NA)-nucleic acid docking to model the 3D complex structures between two RNAs/DNAs, where both sequence and structure inputs are accepted for RNAs, while only structure inputs are supported for DNAs. HNADOCK server was tested through both unbound structure and sequence inputs on the benchmark of 60 RNA-RNA complexes and compared with the state-of-the-art algorithm SimRNA. For structure input, HNADOCK server achieved a high success rate of 71.7% for top 10 predictions, compared to 58.3% for SimRNA. For sequence input, HNADOCK server also obtained a satisfactory performance and gave a success rate of 83.3% when the bound RNA templates are included or 53.3% when excluding those bound RNA templates. It was also found that inclusion of the inter-RNA base-pairing information from RNA-RNA interaction prediction can significantly improve the docking accuracy, especially for the top prediction. HNADOCK is fast and can normally finish a job in about 10 minutes. The HNADOCK web server is available at http://huanglab.phys.hust.edu.cn/hnadock/.
An Universal Stress Protein (USP) expressed under acid stress condition by Listeria innocua ATCC 33090 was investigated. The USP was up-regulated not only in the stationary phase but also during the exponential growth phase. The three dimensional (3D) structure of USP was predicted using a combined proteomic and bioinformatics approach. Phylogenetic analysis showed that the USP from Listeria detected in our study was distant from the USPs of other bacteria (such as Pseudomonas spp., Escherichia coli, Salmonella spp.) and clustered in a separate and heterogeneous class including several USPs from Listeria spp. and Lactobacillus spp. An important information on the studied USP was obtained from the 3D-structure established through the homology modeling procedure. In detail, the Model_USP-691 suggested that the investigated USP had a homo-tetrameric quaternary structure. Each monomer presented an architecture analogous to the Rossmann-like α/β-fold with five parallel β-strands, and four α-helices. The analysis of monomer-monomer interfaces and quality of the structure alignments confirmed the model reliability. In fact, the structurally and sequentially conserved hydrophobic residues of the β-strand 5 (in particular the residues V146 and V148) were involved in the inter-chains contact. Moreover, the highly conserved residues I139 and H141 in the region α4 were involved in the dimer association and functioned as hot spots into monomer-monomer interface assembly. The hypothetical assembly of dimers was also supported by the large interface area and by the negative value of solvation free energy gain upon interface interaction. Finally, the structurally conserved ATP-binding motif G-2X-G-9X-G(S/T-N) suggested for a putative role of ATP in stabilizing the tetrameric assembly of the USP. Therefore, the results obtained from a multiple approach, consisting in the application of kinetic, proteomic, phylogenetic and modeling analyses, suggest that Listeria USP could be considered a new type of ATP-binding USP involved in the response to acid stress condition during the exponential growth phase.
While protein-nucleic acid interactions are pivotal for many crucial biological processes, limited experimental data has made the development of computational approaches to characterise these interactions a challenge. Consequently, most approaches to understand the effects of missense mutations on protein-nucleic acid affinity have focused on single-point mutations and have presented a limited performance on independent data sets. To overcome this, we have curated the largest dataset of experimentally measured effects of mutations on nucleic acid binding affinity to date, encompassing 856 single-point mutations and 141 multiple-point mutations across 155 experimentally solved complexes. This was used in combination with an optimized version of our graph-based signatures to develop mmCSM-NA (http://biosig.unimelb.edu.au/mmcsm_na), the first scalable method capable of quantitatively and accurately predicting the effects of multiple-point mutations on nucleic acid binding affinities. mmCSM-NA obtained a Pearson's correlation of up to 0.67 (RMSE of 1.06 Kcal/mol) on single-point mutations under cross-validation, and up to 0.65 on independent non-redundant datasets of multiple-point mutations (RMSE of 1.12 kcal/mol), outperforming similar tools. mmCSM-NA is freely available as an easy-to-use web-server and API. We believe it will be an invaluable tool to shed light on the role of mutations affecting protein-nucleic acid interactions in diseases.
The JC virus (JCV) control region contains AGGGAAGGGA, the tandem pentanucleotide repeat element (Pnt2). Several proteins specifically interacted via Pnt2 to regulate the expression of JCV early promoter-enhancer (JCV(E)) or late promoter-enhancer (JCV(L)). In this study, a JCV Pnt2 oligonucleotide probe was used to screen a cDNA expression library from glial P19 mouse embryonal carcinoma cells. A cDNA clone was isolated by Southwestern blot assay and it produced a protein that reproducibly and specifically bound to Pnt2. This cDNA had 100% homology to one of three previously identified mouse cDNAs called cellular nucleic acid binding proteins (Cnbps). Cnbps are a highly homologous family of eukaryotic genes implicated in functional interactions with cytoplasmic RNA and regulatory DNA elements. An mRNA of 2.2 kb of Pnt2-interacting Cnbp (PCnbp) was seen in undifferentiated, muscle or glial P19 cells. When expressed from a cDNA expression vector as a fusion protein that also contained 115 kDa from beta-galactosidase, a Pnt2 binding protein (PCNBP) specifically bound to Pnt2 in Southwestern blots as a 30 kDa component of the 145 kDa fusion protein. Furthermore, JCV(E) expression was negatively regulated by PCnbp produced in vivo from the cDNA expression vector. Regulation of JCV(L) was unaffected. We suggest a novel role for CNBP as a PCNBP that interacts with Pnt2 in the negative transcriptional regulation of JCV(E).
Detection of disease-associated, cell-free nucleic acids in body fluids enables early diagnostics, genotyping and personalized therapy, but is challenged by the low concentrations of clinically significant nucleic acids and their sequence homology with abundant wild-type nucleic acids. We describe a novel approach, dubbed NAVIGATER, for increasing the fractions of Nucleic Acids of clinical interest Via DNA-Guided Argonaute from Thermus thermophilus (TtAgo). TtAgo cleaves specifically guide-complementary DNA and RNA with single nucleotide precision, greatly increasing the fractions of rare alleles and, enhancing the sensitivity of downstream detection methods such as ddPCR, sequencing, and clamped enzymatic amplification. We demonstrated 60-fold enrichment of the cancer biomarker KRAS G12D and ∼100-fold increased sensitivity of Peptide Nucleic Acid (PNA) and Xenonucleic Acid (XNA) clamp PCR, enabling detection of low-frequency (<0.01%) mutant alleles (∼1 copy) in blood samples of pancreatic cancer patients. NAVIGATER surpasses Cas9-based assays (e.g. DASH, Depletion of Abundant Sequences by Hybridization), identifying more mutation-positive samples when combined with XNA-PCR. Moreover, TtAgo does not require targets to contain any specific protospacer-adjacent motifs (PAM); is a multi-turnover enzyme; cleaves ssDNA, dsDNA and RNA targets in a single assay; and operates at elevated temperatures, providing high selectivity and compatibility with polymerases.
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