Multiple Secondary Structures Research Articles

Prediction of the effects of the top 10 synonymous mutations from 26645 SARS-CoV-2 genomes

Background The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple works had been done to study nonsynonymous mutations, which change protein sequences. However, there is little study on the effects of SARS-CoV-2 synonymous mutations, which may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome. Methods A total of 26645 SARS-CoV-2 genomic sequences retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database were aligned using MAFFT. Then, the mutations and their respective frequency were identified. Multiple RNA secondary structures prediction tools, namely RNAfold, IPknot++ and MXfold2 were applied to predict the effect of the mutations on RNA secondary structure and their base pair probabilities was estimated using MutaRNA. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2. Results A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a. Of these top 10 highest frequency synonymous mutations, C913U, C3037U, U16176C and C18877U mutants show pronounced changes between wild type and mutant in all 3 RNA secondary structure prediction tools, suggesting these mutations may have some biological impact on viral fitness. These four mutations show changes in base pair probabilities. All mutations except U16176C change the codon to a more preferred codon, which may result in higher translation efficiency. Conclusion Synonymous mutations in SARS-CoV-2 genome may affect RNA secondary structure, changing base pair probabilities and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

Classifying tetraspanins: A universal system for numbering residues and a proposal for naming structural motifs and subfamilies

All tetraspanins have four transmembrane domains (TMs). The large extracellular loop (LEL) that connects the third and fourth TMs contains multiple secondary structures together with the family's signature Cys-Cys-Gly motif. These intriguing membrane proteins are involved in diverse and incompletely understood cellular processes including cell adhesion, tissue differentiation, immune cell maturation and host-parasite interactions. Here we present a classification system that accurately describes the position of each amino acid within its primary sequence based on both sequence and topological conservation of the TMs and LEL. This builds on the numbering systems that have been used in the G protein-coupled receptor (GPCR) field for nearly three decades and which have aided the understanding of GPCR structure/activity relationships and ligand interactions. The high-resolution structures of the tetraspanins CD81, CD9, CD53 and Tspan15 were used to validate the structural relevance of our new tetraspanin classification system. Modelling of all tetraspanin LELs highlighted flexibility in LEL disulfide bonding across the family and suggests that the structural arrangement of tetraspanin LELs is more complex than previously thought. We therefore propose a new subfamily naming system that addresses this added complexity and facilitates the systematic classification of human tetraspanins, shedding light on all structural motifs within the family. We anticipate that our universal tetraspanin classification system will enable progress in defining how sequence and structure inform function.

G-quadruplexes of KSHV oriLyt play important roles in promoting lytic DNA replication.

Kaposi's sarcoma-associated herpesvirus (KSHV) utilizes distinct origins of DNA replication (origin of replications) during the latent and lytic phases of its life cycle. Lytic DNA replication requires the participation of cellular and viral proteins to initiate replication at a specific region in the KSHV genome, oriLyt. These regions contain multiple secondary structures and binding sites for viral and cellular proteins. We discovered the presence of G-quadruplex (G4) sites in the oriLyt region. G-quadruplexes are secondary structures in nucleic acid sequences that are considered regulators of multiple biological processes, such as transcription, translation, and replication initiation. Importantly, herpesviruses have a high density of putative quadruplex sequence or formation sites in their genome, including in the regulatory regions, which control replication and transcription. The binding of RecQ1 to the oriLyt region of KSHV and its ability to unwind the G4 structures led us to speculate that G-quadruplex sites play an important role in lytic DNA replication. In this study, we confirmed the formation of stable G-quadruplexes through biochemical and biophysical assays. We further demonstrated that RecQ1, a helicase, associates with the G-quadruplex forming sites of the oriLyt. The functional significance of G4 sites and RecQ1 was confirmed through the stabilization of G4 and depletion of RecQ1 levels through shRNA. Furthermore, the detection of replication initiation through single-molecule analysis of the replicated DNA demonstrated that G4 stabilization leads to subdued replication initiation at the oriLyt. This confirmed the role of the G-quadruplex in regulating viral DNA replication, which can be used to control virus growth.IMPORTANCEBiological processes originating from the DNA and RNA can be regulated by the secondary structures present in the stretch of nucleic acids, and the G-quadruplexes are shown to regulate transcription, translation, and replication. In this study, we identified the presence of multiple G-quadruplex sites in the region (oriLyt) of Kaposi's sarcoma-associated herpesvirus (KSHV) DNA, which is essential for DNA replication during the lytic cycle. We demonstrated the roles of these G-quadruplexes through multiple biochemical and biophysical assays in controlling replication and efficient virus production. We demonstrated that KSHV achieves this by recruiting RecQ1 (helicase) at those G-quadruplex sites for efficient viral DNA replication. Analysis of the replicated DNA through nucleoside labeling and immunostaining showed a reduced initiation of DNA replication in cells with a pharmacologic stabilizer of G-quadruplexes. Overall, this study confirmed the role of the G-quadruplex in regulating viral DNA replication, which can be exploited for controlling viral DNA replication.

Machine learning coarse-grained potentials of protein thermodynamics

A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach this problem by constructing coarse-grained molecular potentials based on artificial neural networks and grounded in statistical mechanics. For training, we build a unique dataset of unbiased all-atom molecular dynamics simulations of approximately 9 ms for twelve different proteins with multiple secondary structure arrangements. The coarse-grained models are capable of accelerating the dynamics by more than three orders of magnitude while preserving the thermodynamics of the systems. Coarse-grained simulations identify relevant structural states in the ensemble with comparable energetics to the all-atom systems. Furthermore, we show that a single coarse-grained potential can integrate all twelve proteins and can capture experimental structural features of mutated proteins. These results indicate that machine learning coarse-grained potentials could provide a feasible approach to simulate and understand protein dynamics.

Polymer Containing Multiple Secondary Structures—A Competition between Helical Induction and C‐T Complexation

AbstractThough “foldamers” have greatly developed, molecules that fold beyond 2° structures are less common. The design and synthesis of triblock copolymers of the “A‐B‐A” type containing two types of helix formation blocks are presented. Two blocks (A and B) are chosen, with one comprised of L‐polyproline as block “A” and the other block (B) comprised with three naphthalene diimide‐derivatives separated by two proline residues. Block (B) is carefully designed to serve as a bifunctional initiator for the ring‐opening polymerization of proline‐N‐carboxy anhydride as well as to encapsulate an electron‐rich aromatic species by charge transfer complexation (C‐T). As a result of (C‐T) complexation with dialkoxy pyrene, the native helical structure of the middle block is transformed into a 1D columnar structure without affecting the 2° structure of the polyproline block. In this way, the initial helix1‐b‐helix2‐b‐helix1 structure of the block copolymers is transformed into a helix1‐b‐columnar‐b‐helix1 structure. The C‐T complexation and related structural changes of the block copolymers are characterized using UV‐vis, fluorescence, and circular dichroism spectroscopy.

Bioinformatics-based prediction and screening of immunogenic epitopes of Toxoplasma gondii rhoptry proteins 7, 21 and 22 as candidate vaccine target

IntroductionToxoplasmosis is a well-known zoonotic disease caused by Toxoplasma gondii. The main causes of the disease range from eating undercooked or contaminated meat and shellfish to cleaning litter trays into which cats that excreted toxoplasma via faeces. This pathogen can live for a very long time, possibly a lifetime, within the bodies of humans and other animals. Aims and objectivesThis study aimed to predict and analyse candidate immunogenic epitopes for vaccine development by evaluating the physio-chemical properties, multiple sequence alignment, secondary and tertiary structures, phosphorylation sites, transmembrane domains, and signal peptides, of T. gondii rhoptry proteins ROP7, ROP21, and ROP22 using bioinformatics tools. MethodsTo find immunogenic epitopes of rhoptry proteins, numerous bioinformatics web servers were used containing multiple sequence alignment, physiochemical properties, antigenicity and allergenicity, post-translational modification sites (PTMs), signal peptides, transmembrane domains, secondary and tertiary structures, and screening of predicted epitopes. We evaluated immunogenic linear B-cell epitopes as candidate proteins for vaccine development. ResultsNine epitopes were identified for each protein, and analysis of immunogenicity, revealed three candidate epitopes for ROP7, one for ROP21, and four for ROP22. Among all candidate epitopes, ROP22 contained the most immunogenic epitopes with immunogenicity score of 0.50575. ConclusionWe acquired detailed information on predicted immunogenic epitopes using in-silico methods. The results provide a foundation for further experimental analysis of toxoplasmosis, and potential vaccine development.

AmiP from hyperthermophilic Thermus parvatiensis prophage is a thermoactive and ultrathermostable peptidoglycan lytic amidase.

Bacteriophages encode a wide variety of cell wall disrupting enzymes that aid the viral escape in the final stages of infection. These lytic enzymes have accumulated notable interest due to their potential as novel antibacterials for infection treatment caused by multiple-drug resistant bacteria. Here, the detailed functional and structural characterization of Thermus parvatiensis prophage peptidoglycan lytic amidase AmiP, a globular Amidase_3 type lytic enzyme adapted to high temperatures is presented. The sequence and structure comparison with homologous lytic amidases reveals the key adaptation traits that ensure the activity and stability of AmiP at high temperatures. The crystal structure determined at a resolution of 1.8Å displays a compact α/β-fold with multiple secondary structure elements omitted or shortened compared with protein structures of similar proteins. The functional characterization of AmiP demonstrates high efficiency of catalytic activity and broad substrate specificity toward thermophilic and mesophilic bacteria strains containing Orn-type or DAP-type peptidoglycan. The here presented AmiP constitutes the most thermoactive and ultrathermostable Amidase_3 type lytic enzyme biochemically characterized with a temperature optimum at 85°C. The extraordinary high melting temperature Tm 102.6°C confirms fold stability up to approximately 100°C. Furthermore, AmiP is shown to be more active over the alkaline pH range with pH optimum at pH8.5 and tolerates NaCl up to 300 mM with the activity optimum at 25 mM NaCl. This set of beneficial characteristics suggests that AmiP can be further exploited in biotechnology.

Molecular characterization of a teleost-specific toll-like receptor 22 (tlr22) gene from yellow catfish (Pelteobagrus fulvidraco) and its transcriptional change in response to poly I:C and Aeromonas hydrophila stimuli

Toll-like receptors (TLRs) are a class of pattern recognition receptors (PRRs) that can recognize pathogen-associated molecular patterns (PMPs) and play important roles in the innate immune system in vertebrates. In this study, we identified a teleost-specific tlr22 gene from yellow catfish (Pelteobagrus fulvidraco) and its immune roles in response to different pathogens were also determined. The open reading frame (ORF) of the tlr22 was 2892 bp in length, encoding a protein of 963 amino acids. Multiple protein sequences alignment, secondary and three-dimensional structure analyses revealed that TLR22 is highly conserved among different fish species. Phylogenetic analysis showed that the phylogenetic topology was divided into six families of TLR1, TLR3, TLR4, TLR5, TLR7 and TLR11, and TLR22 subfamily was clustered into TLR11 family. Meanwhile, synteny and gene structure comparisons revealed functional and evolutionary conservation of the tlr22 gene in teleosts. Furthermore, tlr22 gene was shown to be widely expressed in detected tissues except barbel and eye, with highest expression level in liver. The transcription of tlr22 was significantly increased in spleen, kidney, liver and gill tissues at different timepoints after Poly I:C infection, suggesting TLR22 plays critical roles in defensing virus invasion. Similarly, the transcription of tlr22 was also dramatically up-regulated in spleen, kidney and gill tissues with different patterns after Aeromonas hydrophila infection, indicating that TLR22 is also involved in resisting bacteria invasion. Our findings will provide a solid basis for the investigation the immune functions of tlr22 gene in teleosts, as well as provide useful information for disease control and treatment for yellow catfish.

Label-Free Detection of β-Sheet Polymorphism.

The ability to detect and characterize multiple secondary structures or polymorphs within peptide and protein aggregates is crucial to treatment and prevention of amyloidogenic diseases, production of novel biomaterials, and many other applications. Here we report a label-free method to distinguish multiple β-sheet configurations within a single peptide aggregate using two-dimensional infrared spectroscopy. By calculating the transition dipole strength (TDS) spectrum from the ratio of linear and two-dimensional signals, we can extract maximum TDS values which provide higher sensitivity to vibrational coupling, and thus specifics of protein structure, than vibrational frequency alone. TDS spectra of AcKFE8 aggregates reveal two distinct β-sheet structures within fibers that appear homogeneous by other techniques. Furthermore, TDS spectra taken during early stages of aggregation show additional peaks that may indicate the presence of more weakly coupled β-sheet structures. These results demonstrate a unique and powerful spectroscopic method capable of distinguishing multiple oligomeric and polymorphic motifs throughout the aggregation using only native vibrational modes.

Prediction of the effects of the top 10 synonymous mutations from 26645 SARS-CoV-2 genomes

Background: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple works had been done to study nonsynonymous mutations, which change protein sequences. However, there is little study on the effects of SARS-CoV-2 synonymous mutations, which may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome. Methods: A total of 26645 SARS-CoV-2 genomic sequences retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database were aligned using MAFFT. Then, the mutations and their respective frequency were identified. Multiple RNA secondary structures prediction tools, namely RNAfold, IPknot++ and MXfold2 were applied to predict the effect of the mutations on RNA secondary structure and their base pair probabilities was estimated using MutaRNA. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2. Results: A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a.. Of these top 10 highest frequency synonymous mutations, C913U, C3037U, U16176C and C18877U mutants show pronounced changes between wild type and mutant in all 3 RNA secondary structure prediction tools, suggesting these mutations may have some biological impact on viral fitness. These four mutations show changes in base pair probabilities. All mutations except U16176C change the codon to a more preferred codon, which may result in higher translation efficiency. Conclusion: Synonymous mutations in SARS-CoV-2 genome may affect RNA secondary structure, changing base pair probabilities and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

Axl Expression in Renal Mesangial Cells Is Regulated by Sp1, Ap1, MZF1, and Ep300, and the IL-6/miR-34a Pathway.

Axl receptor tyrosine kinase expression in the kidney contributes to a variety of inflammatory renal disease by promoting glomerular proliferation. Axl expression in the kidney is negligible in healthy individuals but upregulated under inflammatory conditions. Little is known about Axl transcriptional regulation. We analyzed the 4.4 kb mouse Axl promoter region and found that many transcription factor (TF)-binding sites and regulatory elements are located within a 600 bp fragment proximal to the translation start site. Among four TFs (Sp1, Ap1, MZF1, and Ep300) identified, Sp1 was the most potent TF that promotes Axl expression. Luciferase assays confirmed the siRNA results and revealed additional mechanisms that regulate Axl expression, including sequences encoding a 5′-UTR mini-intron and potential G-quadruplex forming regions. Deletion of the Axl 5′-UTR mini-intron resulted in a 3.2-fold increases in luciferase activity over the full-length UTR (4.4 kb Axl construct). The addition of TMPyP4, a G-quadruplex stabilizer, resulted in a significantly decreased luciferase activity. Further analysis of the mouse Axl 3′-UTR revealed a miRNA-34a binding site, which inversely regulates Axl expression. The inhibitory role of miRNA-34a in Axl expression was demonstrated in mesangial cells using miRNA-34a mimicry and in primary kidney cells with IL-6 stimulated STAT3 activation. Taken together, Axl expression in mouse kidney is synergistically regulated by multiple factors, including TFs and secondary structures, such as mini-intron and G-quadruplex. A unique IL6/STAT3/miRNA-34a pathway was revealed to be critical in inflammatory renal Axl expression.

AlphaFold2 fails to predict protein fold switching.

AlphaFold2 has revolutionized protein structure prediction by leveraging sequence information to rapidly model protein folds with atomic-level accuracy. Nevertheless, previous work has shown that these predictions tend to be inaccurate for structurally heterogeneous proteins. To systematically assess factors that contribute to this inaccuracy, we tested AlphaFold2's performance on 98-fold-switching proteins, which assume at least two distinct-yet-stable secondary and tertiary structures. Topological similarities were quantified between five predicted and two experimentally determined structures of each fold-switching protein. Overall, 94% of AlphaFold2 predictions captured one experimentally determined conformation but not the other. Despite these biased results, AlphaFold2's estimated confidences were moderate-to-high for 74% of fold-switching residues, a result that contrasts with overall low confidences for intrinsically disordered proteins, which are also structurally heterogeneous. To investigate factors contributing to this disparity, we quantified sequence variation within the multiple sequence alignments used to generate AlphaFold2's predictions of fold-switching and intrinsically disordered proteins. Unlike intrinsically disordered regions, whose sequence alignments show low conservation, fold-switching regions had conservation rates statistically similar to canonical single-fold proteins. Furthermore, intrinsically disordered regions had systematically lower prediction confidences than either fold-switching or single-fold proteins, regardless of sequence conservation. AlphaFold2's high prediction confidences for fold switchers indicate that it uses sophisticated pattern recognition to search for one most probable conformer rather than protein biophysics to model a protein's structural ensemble. Thus, it is not surprising that its predictions often fail for proteins whose properties are not fully apparent from solved protein structures. Our results emphasize the need to look at protein structure as an ensemble and suggest that systematic examination of fold-switching sequences may reveal propensities for multiple stable secondary and tertiary structures.

ENNGene: an Easy Neural Network model building tool for Genomics

BackgroundThe recent big data revolution in Genomics, coupled with the emergence of Deep Learning as a set of powerful machine learning methods, has shifted the standard practices of machine learning for Genomics. Even though Deep Learning methods such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are becoming widespread in Genomics, developing and training such models is outside the ability of most researchers in the field.ResultsHere we present ENNGene—Easy Neural Network model building tool for Genomics. This tool simplifies training of custom CNN or hybrid CNN-RNN models on genomic data via an easy-to-use Graphical User Interface. ENNGene allows multiple input branches, including sequence, evolutionary conservation, and secondary structure, and performs all the necessary preprocessing steps, allowing simple input such as genomic coordinates. The network architecture is selected and fully customized by the user, from the number and types of the layers to each layer's precise set-up. ENNGene then deals with all steps of training and evaluation of the model, exporting valuable metrics such as multi-class ROC and precision-recall curve plots or TensorBoard log files. To facilitate interpretation of the predicted results, we deploy Integrated Gradients, providing the user with a graphical representation of an attribution level of each input position. To showcase the usage of ENNGene, we train multiple models on the RBP24 dataset, quickly reaching the state of the art while improving the performance on more than half of the proteins by including the evolutionary conservation score and tuning the network per protein.ConclusionsAs the role of DL in big data analysis in the near future is indisputable, it is important to make it available for a broader range of researchers. We believe that an easy-to-use tool such as ENNGene can allow Genomics researchers without a background in Computational Sciences to harness the power of DL to gain better insights into and extract important information from the large amounts of data available in the field.

Polymorphic and Higher-Order G-Quadruplexes as Possible Transcription Regulators: Novel Perspectives for Future Anticancer Therapeutic Applications.

In the past two decades, significant efforts have been put into designing small molecules to target selected genomic sites where DNA conformational rearrangements control gene expression. G-rich sequences at oncogene promoters are considered good points of intervention since, under specific environmental conditions, they can fold into non-canonical tetrahelical structures known as G-quadruplexes. However, emerging evidence points to a frequent lack of correlation between small molecule targeting of G-quadruplexes at gene promoters and the expression of the associated protein, which hampers pharmaceutical applications. The wide genomic localization of G-quadruplexes along with their highly polymorphic behavior may account for this scenario, suggesting the need for more focused drug design strategies. Here, we will summarize the G4 structural features that can be considered to fulfill this goal. In particular, by comparing a telomeric sequence with the well-characterized G-rich domain of the KIT promoter, we will address how multiple secondary structures might cooperate to control genome architecture at a higher level. If this holds true, the link between drug–DNA complex formation and the associated cellular effects will need to be revisited.

RfaRm: An R client-side interface to facilitate the analysis of the Rfam database of RNA families.

rfaRm is an R package providing a client-side interface for the Rfam database of non-coding RNA and other structured RNA elements. The package facilitates the search of the Rfam database by keywords or sequences, as well as the retrieval of all available information about specific Rfam families, such as member sequences, multiple sequence alignments, secondary structures and covariance models. By providing such programmatic access to the Rfam database, rfaRm enables genomic workflows to incorporate information about non-coding RNA, whose potential cannot be fully exploited just through interactive access to the database. The features of rfaRm are demonstrated by using it to analyze the SARS-CoV-2 genome as an example case.

The Molecular Mechanism of Domain Swapping of the C-Terminal Domain of the SARS-Coronavirus Main Protease

In three-dimensional domain swapping, two protein monomers exchange a part of their structures to form an intertwined homodimer, whose subunits resemble the monomer. Several viral proteins domain swap to increase their structural complexity or functional avidity. The main protease (Mpro) of the severe acute respiratory syndrome (SARS) coronavirus proteolyzes viral polyproteins and has been a target for anti-SARS drug design. Domain swapping in the α-helical C-terminal domain of Mpro (MproC) locks Mpro into a hyperactive octameric form that is hypothesized to promote the early stages of viral replication. However, in the absence of a complete molecular understanding of the mechanism of domain swapping, investigations into the biological relevance of this octameric Mpro have stalled. Isolated MproC can exist as a monomer or a domain-swapped dimer. Here, we investigate the mechanism of domain swapping of MproC using coarse-grained structure-based models and molecular dynamics simulations. Our simulations recapitulate several experimental features of MproC folding. Further, we find that a contact between a tryptophan in the MproC domain-swapping hinge and an arginine elsewhere forms early during folding, modulates the folding route, and promotes domain swapping to the native structure. An examination of the sequence and the structure of the tryptophan containing hinge loop shows that it has a propensity to form multiple secondary structures and contacts, indicating that it could be stabilized into either the monomer- or dimer-promoting conformations by mutations or ligand binding. Finally, because all residues in the tryptophan loop are identical in SARS-CoV and SARS-CoV-2, mutations that modulate domain swapping may provide insights into the role of octameric Mpro in the early-stage viral replication of both viruses.

Characterization of bZIP transcription factors from Dimocarpus longan Lour. and analysis of their tissue-specific expression patterns and response to heat stress

Members of the bZIP transcription factor family play crucial roles in the regulation of plant development, biosynthesis of secondary metabolites, and response to abiotic and biotic stresses. To date, multiple bZIPs have been identified and investigated in numerous plant species. However, few studies have characterized bZIPs from Dimocarpus longan Lour. In this study, nine bZIPs from D. longan were identified from RNA-Seq data and further verified using the NCBI conserved domain search tool and Pfam database. Bioinformatics tools were used to systematically analyse the physicochemical properties, protein structures, multiple sequence alignment, motif compositions, evolutionary relationships, secondary structures, subcellular localization, phosphorylation sites, signal peptides, GO annotations and protein-protein interactions of the DlbZIPs. The expression patterns of the nine DlbZIPs were evaluated by qRT-PCR in roots and leaves and in response to varying durations of a 38°C heat treatment. DlbZIP3, DlbZIP5, DlbZIP6 and DlbZIP7 were differentially expressed between root and leaf tissues. All nine DlbZIPs responded to heat treatment in both roots and leaves, but their specific expression levels differed. DlbZIP4 and DlbZIP8 were highly expressed in roots after heat treatment, whereas DlbZIP1 and DlbZIP5 were highly expressed in leaves after heat treatment. These findings lay a foundation for increasing active secondary metabolite content and improving abiotic stress tolerance in D. longan using transgenic technology.

An Insight into Oligopeptide Transporter 3 (OPT3) Family Proteins.

OPT3s are involved in the transport of Fe from xylem to phloem, in loading Fe into phloem, and in the transmission of shoot-to-root iron signaling. Yet, apart from Arabidopsis, little is known about these transporters'functions in other plant species. OPT3 proteins of several plant species were characterized using bioinformatical tools. Also, a probable Fe chelating protein, GSH, was used in docking analyses to shed light on the interactions of ligand binding sites of OPT3s. The multiple sequence alignment (MSA) analysis, protein secondary and tertiary structure analyses, molecular phylogeny analysis, transcription factor binding site analyses, co-expression and docking analyses were performed using up-to-date bioinformatical tools. All OPT3s in this study appear to be transmembrane proteins. They appear to have broad roles and substrate specificities in different metabolic processes. OPT3 gene structures were highly conserved. Promoter analysis showed that bZIP, WRKY, Dof and AT-Hook Transcription factors (TFs) may regulate the expression of OPT3 genes. Consequently, they seemed to be taking part in both biotic and abiotic stress responses as well as growth and developmental processes. The results showed that OPT3 proteins are involved in ROS regulation, plant stress responses, and basal pathogen resistance. They have species-specific roles in biological processes. Lastly, the transport of iron through OPT3s may occur with GSH according to the binding affinity results of the docking analyses.

The Bacterial Tubulin Homolog FtsZ Forms 2D-sheets that Sustain Electrical Oscillations

FtsZ, a major cytoskeletal protein present in all bacteria and archaea forms a cytokinetic ring, the Z ring, at the site of septation, which directs cytokinesis. Multiple sequence alignment and secondary structure predictions indicate that bacterial FtsZ is a homolog of the eukaryotic tubulins which, as their mammalian counterpart, binds guanine nucleotides, has GTPase activity, and is able to assemble into protofilamental structures in a GTP-dependent manner. Previous studies from our laboratory demonstrated that microtubule (MTs) structures isolated from murine, bovine and apian brains spontaneously generate electrical oscillations and bursts of electrical activity similar to action potentials. Although the electrical behavior of brain MTs may have important implication in eukaryotic cell function, no information is available as to whether FtsZ may share similar properties. Therefore, the aim of the present study was to explore whether FtsZ protofilamental sheets may sustain electrical activity. FtsZ protein from E. coli ATCC 25922 was purified by ammonium sulfate precipitation, and assembled into protofilamental sheets by incubation with a polymerization buffer. 2D FtsZ sheets were voltage-clamped, and gigaseals obtained in most experiments (n = 7). Subsequently, electrical recordings from output currents were obtained, showing a complex oscillatory behavior with several peak frequencies between 7 and 110 Hz in the power spectra. As a result, it was observed that FtsZ 2D sheets had a much wider range of frequencies compared to MTs sheets from eukaryotic origin. The findings demonstrate that FtsZ protofilamental sheets are capable of generating electrical signals and behave as electrical oscillators that may be relevant to the cell division process and/or yet unknown signaling mechanisms.

Genetic diversity of Paramecium species on the basis of multiple loci analysis and ITS secondary structure models.

Among ciliates, Paramecium has become a privileged model for the study of "species problem" particularly in the case of the "Paramecium aurelia complex" that has been intensely investigated. Despite extensive studies, the taxonomy of Paramecium is still challenging. The major problem is an uneven sampling of Paramecium with relatively few representatives of each species. To investigate species from the less discovered region (Pakistan), 10 isolates of Paramecium species including a standing-alone FT8 strain previously isolated by some of us were subjected to molecular characterization. Fragments of 18S recombinant DNA (rDNA), ITS1-5.8S-ITS2-5'LSU rDNA, cytochrome c oxidase subunit II, and hsp70 genes were used as molecular markers for phylogenetic analysis of particular isolates. The nucleotide sequences of polymerase chain reaction products of all markers were compared with the available sequences of relevant markers of other Paramecium species from GenBank. Phylogenetic trees based on all molecular markers showed that all the nine strains had a very close relationship with Paramecium primaurelia except for the FT8 strain. FT8 consistently showed its unique position in comparison to all other species in the phylogenetic trees. Available sequences of internal transcribed spacer 1 (ITS1) and ITS2 and some other ciliate sequences from GenBank were used for the construction of secondary models. Two highly conserved helices supported by compensatory base changes among all ciliates of ITS2 secondary structures were found similar to other eukaryotes. Therefore, the most conserved 120 to 180 base pairs regions were identified for their comparative studies. We found that out of the three helices in ITS1 structure, helix B was more conserved in Paramecium species. Despite various substitutions in the primary sequence, it was observed that secondary structures of ITS1 and ITS2 could be helpful in interpreting the phylogenetic relationships both at species as well as at generic level.