Protein Sequence Analysis Research Articles

Development of a Novel Biomarker for an early detection of Alzheimer disease

BackgroundAlzheimer’s disease (AD), a neurodegenerative disease, is the most common form of dementia among older patients and is the 6th leading cause of death in the US. Almost 1 in 10 people over the age of 65 have AD and every 65 second someone in the US develop AD. Worldwide 30 million people have AD, and 5.8 million American are living with this disease where by 2050, it is projected to be 14 million. Problems in AD and other forms of dementia involve an irreversible brain tissue damage and destruction, leading to progressive cognitive impairment led difficulty of performing simple tasks. In 2019, AD and other dementia in US costed $290 billion. By 2050, these costs could rise as high as 1.1 trillion. Due to technological advancements in artificial intelligence, the computer can not only plan & predict the path or course for a robot, but for multiple proteins and their metabolites. Several digital models and simulations can determine the interactions and commonality between proteins of all sorts. The goal of this project is to identify biological markers by metabolomic meta‐analysis that correlate with the progression of AD and be integrated to a prototype biosensor capable of detecting the stable biomarker for an early detection of dementia. This project analyzes the commonalties in dementia related proteins through data mining and analysis of the cerebrospinal fluid and blood metabolome to see (when altered in Alzheimer disease) the metabolic reactions that could potentially relate to phenotypes detectable for an early onset Alzheimer's. Along with that, the project utilizes the novel findings to assemble a detection system via electrochemical analysis by observing the difference in the relative resistance between varying solution of key analyte changed in Alzheimer’s patient.Material and MethodsPlastic straw, Hydrogel, Electrical resistant measuring machine and specialized Electrode. Protein sequences analysis: Information on the proteins that are associated with the Alzheimer diseases were obtained from PubMed; Amino acid sequences of these proteins (in FASTA format) were obtained through ExPASy. The amino acid sequences of proteins in FASTA format were obtained from the UniProt database in Expasy. Clastalw‐Multiple Alignment: The commonality in the protein sequences was deduced obtained by aligning multiple protein sequences through the Clustal‐W.Results and ConclusionBioinformatics tools and computer algorithms shows three dimensional structures of Alzheimer’s disease associated proteins where majority of them were associated with the membrane. Mutational analysis indicated that most of them in AD fall into transmembrane regions of the protein which may be due to change in lipid composition of the cells. Metabolomics studies indicated that the relative abundance of lipid metabolites was relatively low in the blood of AD compared to healthy or MCI. In contrast, the cerebrospinal fluid levels of lipid metabolites were higher in AD/dementia patients compared to their healthy counterparts. Increased lipid metabolomic disturbances in CSF also correlated with enlarged ventricle filled with CSF in AD patients. Digital models and simulations studies of this project demonstrated the interactions and commonality between proteins of AD and demonstrated their folding. Analysis of the CSF and blood metabolome provided a strong AD phenotypes detectability for early onset Alzheimer and may be useful as detectable marker for the cognitive impairment.

Isolation and expression of a new gene <italic>HvMEL1 AGO</italic> in Tibetan hulless barley under leaf stripe stress

<p id="C3">To explore <italic>AGO</italic> genes related to leaf stripe in Tibetan hulless barley (BLS), we obtained a differentially expressed <italic>HvMEL1 AGO </italic>gene from the transcriptional sequencing in normal and diseased leaves from resistant Tibetan hulless barley variety Kunlun 14 and the susceptible variety 1141. The <italic>HvMEL1 AGO</italic> gene was 3462 bp in length, of which the CDS (coding domain sequence) was 100% consistent in Kunlun 14 and 1141 varieties. The length of <italic>HvMEL1 AGO</italic> gene was 3161 bp without intron, contained a 3129 bp open reading frame, encoded 1043 amino acids, had a theoretical isoelectric point of 9.33, and has a predicted molecular weight of 115,865.58 Da. Protein sequence analysis showed that HvMEL1 AGO was a hydrophilic unstable acidic protein with highly conserved structural domains of DUF1785, PAZ and PIWI, belonging to <italic>AGO</italic> gene family. Phylogenetic tree analysis showed that HvMEL1 AGO belonged to the AGO1 class in <italic>Arabidopsis</italic> AGO family phylogenetic tree with HvAGO12, HvAGO18, HvAGO1D and HvAGO1B in barley AGO family, and were closely related to HvAGO12. The predicted protein interactions showed that the known proteins that acted closely with MEL1 in rice were the DCL classes, DCL1, DCL2A, DCL3A, DCL3B and DCL4, respectively. Semi-quantitative and quantitative PCR results indicated that the relative expression levels of <italic>HvMEL1 AGO</italic> gene were significantly down-regulated in 1141 and Kunlun 14 under BLS. We hypothesized that <italic>HvMEL1 AGO</italic> gene played an important role in the streak resistance mechanism of barley. This study lays the foundation for exploring the role and regulatory mechanism of <italic>HvMEL1 AGO</italic> in the process of BLS resistance.

Phylogenetic Marker Selection and Protein Sequence Analysis of the ORF5 Gene Product of Grapevine Virus A.

Grapevine virus A (GVA), the type species of the Vitivirus genus, is one of the causal agents of the Kober stem grooving disease of the rugose wood complex and one of the most frequently detected viruses in grapevine. There is little information on GVA gene(s) marker useful for phylogenetic analysis. To this aim, a total of 403 leaf samples were collected from vineyards of East and West Azarbaijan provinces in the Northwestern provinces of Iran during 2014–2016 and tested by DAS-ELISA and RT-PCR using ORF5-specific primers. GVA was detected in 56 symptomatic samples, corresponding to 14% of infection, while it was not detected in asymptomatic samples. The ORF5 (p10) protein sequence of eight Iranian isolates was compared to other vitiviruses, showing that the most conserved region resides in the N-terminus, carrying an arginine-rich motif followed by a zinc-finger motif. Next, to define a robust phylogenetic marker representative of the whole genome sequence suitable for phylogenetic and evolutionary studies, phylogenetic trees based on the full genome sequences of all the available GVA isolates and on individual genomic regions were constructed and compared. ORF1, which encodes the RNA-dependent RNA polymerase, was found to be the best phylogenetic marker for GVA classification and evolution studies. These results can be used for further research on phylogenetic analyses, evolution history, epidemiology, and etiology of rugose wood complex, and to identify control measures against GVA and other vitiviruses.

Molecular detection and phylogenetic analysis of porcine circovirus type 3 in Tibetan pigs on the Qinghai-Tibet Plateau of China

BackgroundPorcine circovirus type 3 (PCV3) has been confirmed to infect pigs, posing a health risk and making pigs more susceptible to other pathogens. After the first report of PCV3 infection in the United States, its prevalence was determined in pigs suffering from clinical digestive or respiratory diseases in several other regions, including the Sichuan and Gansu provinces of China. In this study, we describe the frequency of PCV3 detection in Tibetan pigs inhabiting three different provinces surrounding the Qinghai-Tibet Plateau of China.MethodsA total of 316 samples from diarrheic animals and 182 samples from healthy animals were collected in a randomized manner. Conventional PCR was applied for PCV3 DNA detection. The conserved regions of the PCV3 gene were analyzed with MEGA 7.1 software to design specific primers to sequence entire Cap genes in PCV3 strains, and the sequences were then used to confirm the subtypes of PCV3 in the positive samples. Prediction of the amino acid sequences by nucleotide sequence translation was also performed to compare the point mutations in the entire Cap protein. Twenty PCV3 whole-genomic sequences were used for genome phylogenetic analyses of PCV3 and sequence alignments with 22 other reference strains.ResultsWe found that the prevalence of the virus was significantly higher in samples from pigs with diarrhoea than that in samples from healthy pigs. Phylogenetic analysis of Cap proteins demonstrated that the 20 PCV3 strains formed three clades, including PCV3a (8/20, 40.00%), PCV3b (5/20, 25%) and PCV3c (7/20, 35.00%). The complete genome sequence revealed that these strains formed one branch in the phylogenetic tree. Sequence analysis showed that the Cap proteins of the 20 different viral strains shared between 95.84 and 99.18% nucleotide identity. Cap protein sequence analyses showed that the positivity rate of PCV3a was highest in the samples from pigs with diarrhoea. In comparison, PCV3c was the most elevated subtype in the healthy samples. There was no mutation at a specific site in the amino acid sequences of the entire Cap protein from different PCV3 subtype strains from heathy samples. There was a mutation at site 113 in PCV3a, site 129 in PCV3b, and site 116 in PCV3c.ConclusionOur present data provide evidence that PCV3 is prevalent in Tibetan pigs at high altitudes in China, and the higher prevalence rates of the PCV3a and PCV3b subtypes in samples from pigs with diarrhoea further indicate that the genotypes should not be neglected during surveys of the pathogenicity of PCV3. Phylogenetic and genetic diversity analyses suggested that the continuous evolution, adaptation and mechanisms of pathogenicity of PCV3 in Tibetan pigs living in this special environment should be further studied.

PyPAn: An Automated Graphical User Interface for Protein Sequence and Structure Analyses

Protein sequence and structure analyses have been essential components of bioinformatics and structural biology. They provide a deeper insight into the physicochemical properties, structure, and subsequent functions of a protein. Advanced computational approaches and bioinformatics utilities help solve several issues related to protein analysis. Still, beginners and non-professional may struggle when encountering a wide variety of computational tools and the sheer number of input parameter variables required by each tool. We introduce a free-to-access graphical user interface (GUI) named PyPAn 'Python-based Protein Analysis' for varieties of protein sequence/structure analyses. PyPAn serves as a universal platform to analyze protein sequences, structure, and their properties. PyPAn facilitates onboard analysis of each task in just a single click. It can be used to calculate the physicochemical properties, including instability index and molar extinction coefficient, for a protein. PyPAn is one of the few computational tools that allow users to generate a Ramachandran plot and calculate solvent accessibility and the radius of gyration (Rg) of proteins at once. In addition, it can refine the protein model along with computation and minimization of its energy. Above all, it can generate a recommendation for an appropriate structure modelling method to employ for a query protein sequence. To summarize, PyPAn is one of the few, if not the only, Python-based computational GUI tools with an array of options for the user to employ as they see fit. PyPAn aims to unify many successful academically significant proteomic applications, and is freely available for academic and industrial research uses at https://hassanlab.org/pypan </p>.

Incidence and Distribution of Barley yellow dwarf virus Infecting Oats in Korea

A survey of Barley yellow dwarf virus (BYDV) was conducted in major oat-growing areas of Korea in 2020. BYDV is an economically important pathogen of cereal crops that can be transmitted by aphids. The present study evaluated the genetic composition of BYDV in oat from eight geographical areas in Korea. Multiplex reverse transcription-polymerase chain reaction was used to screen 322 oat leaf samples for six BYDV strains (PAV, MAV, SGV, PAS, RPV, and RMV). The 125 samples (~39%) tested positive for BYDV. BYDV-PAV, BYDV-SGV, BYDV-PAS, and BYDV-RPV were detected from oat in different areas. Most of the BYDV-infected samples were assigned to subgroup I (n=112). The results indicate that BYDV-PAV could be dominant throughout Korea. Also, the phylogenetic analysis of coat protein sequences indicated that 23 BYDV isolates from Korea could be separated into two clades, which exhibited high nucleotide sequence similarity. In conclusion, the present survey provides a BYDV infection assessment for domestic oat varieties in Korea and basic information for the development of BYDV control measures in Korea’s oat industry.

Conserved protein targets for developing pan-coronavirus drugs based on sequence and 3D structure similarity analyses

There are 7 known human pathogenic coronaviruses, which are HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1, MERS-CoV, SARS-CoV and SARS-CoV-2. While SARS-CoV-2 is currently caused a severe epidemic, experts believe that new pathogenic coronavirus would emerge in the future. Therefore, developing broad-spectrum anti-coronavirus drugs is of great significance. In this study, we performed protein sequence and three-dimensional structure analyses for all the 20 virus-encoded proteins across all the 7 coronaviruses, with the purpose to identify highly conserved proteins and binding sites for developing pan-coronavirus drugs. We found that nsp5, nsp10, nsp12, nsp13, nsp14, and nsp16 are highly conserved both in protein sequences (with average identity percentage higher than 52%, average amino acid conservation scores higher than 5.2) and binding pockets (with average amino acid conservation scores higher than 5.8). We also performed the similarity comparison between these 6 proteins and all the human proteins, and found that all the 6 proteins have similarity less than 25%, indicating that the drugs targeting the 6 proteins should have little interference of human protein function. Accordingly, we suggest that nsp5, nsp10, nsp12, nsp13, nsp14, and nsp16 are potential targets for pan-coronavirus drug development.

Conserved Targets to Prevent Emerging Coronaviruses.

Novel coronaviruses emerged as zoonotic outbreaks in humans in 2003 (SARS), 2012 (MERS), and notably in 2019 (SARS2), which resulted in the COVID-19 pandemic, causing worldwide health and economic disaster. Vaccines provide the best protection against disease but cannot be developed and engineered quickly enough to prevent emerging viruses, zoonotic outbreaks, and pandemics. Antivirals are the best first line of therapeutic defense against novel emerging viruses. Coronaviruses are plus sense, single stranded, RNA genome viruses that undergo frequent genetic mutation and recombination, allowing for the emergence of novel coronavirus strains and variants. The molecular life cycle of the coronavirus family offers many conserved activities to be exploited as targets for antivirals. Here, we review the molecular life cycle of coronaviruses and consider antiviral therapies, approved and under development, that target the conserved activities of coronaviruses. To identify additional targets to inhibit emerging coronaviruses, we carried out in silico sequence and structure analysis of coronavirus proteins isolated from bat and human hosts. We highlight conserved and accessible viral protein domains and residues as possible targets for the development of viral inhibitors. Devising multiple antiviral therapies that target conserved viral features to be used in combination is the best first line of therapeutic defense to prevent emerging viruses from developing into outbreaks and pandemics.

Deep Learning Model for Protein Disease Classification

Background: Protein sequence analysis helps in the prediction of protein functions. As the number of proteins increases, it gives the bioinformaticians a challenge to analyze and study the similarity between them. Most of the existing protein analysis methods use Support Vector Machine. Deep learning did not receive much attention regarding protein analysis as it is noted that little work focused on studying the protein diseases classification. Objective: The contribution of this paper is to present a deep learning approach that classifies protein diseases based on protein descriptors. Methods: Different protein descriptors are used and decomposed into modified feature descriptors. Uniquely, we introduce using the Convolutional Neural Network model to learn and classify protein diseases. The modified feature descriptors are fed to the Convolutional Neural Network model on a dataset of 1563 protein sequences classified into 3 different disease classes: AIDS, Tumor suppressor, and Proto-oncogene. Results: The usage of the modified feature descriptors shows a significant increase in the performance of the Convolutional Neural Network model over Support Vector Machine using different kernel functions. One modified feature descriptor improved by 19.8%, 27.9%, 17.6%, 21.5%, 17.3%, and 22% for evaluation metrics: Area Under the Curve, Matthews Correlation Coefficient, Accuracy, F1-score, Recall, and Precision, respectively. Conclusion: Results show that the prediction of the proposed CNN model trained by modified feature descriptors significantly surpasses that of Support Vector Machine model.

First report of Pepper mottle virus in Iran

Pepper mottle virus is a member of genus Potyvirus and infects many plants worldwide. Bell pepper (Capsicum annuum) leaves with virus symptoms were collected, and after using RT-PCR amplification using pepper mottle virus-specific primers for the coat protein, amplicons were sequenced. Sequences revealed the presence of pepper mottle virus (PeMV) for the first time in Iran. Phylogenetic analysis of the coat protein sequences showed that Iranian isolates shared greatest pairwise identities (98.6%) with those from Korea, and lowest identities (91.5%) with those from Cuba.

Insights from the protein sequence and structure analysis of PgHsc70 and OsHsp70 genes.

Heat shock proteins are induced in a wide range of abiotic and biotic stresses. They are well known for cellular chaperone activities and play an important role in protecting plants through regulation of homeostasis and survival. A comprehensive characterization and comparative analysis of the Hsp70 family members within the closely related plant species helps in better interpretation of these proteins' contribution to cell function and response to specific environmental stresses. Therefore, it is of interest to glean insights from the protein sequence analysis of PgHsc 70 and OsHsp70 genes. Thus, we document data from the sequence and structure analysis of PgHsc 70 and OsHsp 70 gene a.

Distinct Expansion of Group II Introns During Evolution of Prokaryotes and Possible Factors Involved in Its Regulation.

Group II introns (G2Is) are ribozymes that have retroelement characteristics in prokaryotes. Although G2Is are suggested to have been an important evolutionary factor in the prokaryote-to-eukaryote transition, comprehensive analyses of these introns among the tens of thousands of prokaryotic genomes currently available are still limited. Here, we developed a bioinformatic pipeline that systematically collects G2Is and applied it to prokaryotic genomes. We found that in bacteria, 25% (447 of 1,790) of the total representative genomes had an average of 5.3 G2Is, and in archaea, 9% (28 of 296) of the total representative genomes had an average of 3.0 G2Is. The greatest number of G2Is per genome was 101 in Arthrospira platensis (phylum Cyanobacteriota). A comprehensive sequence analysis of the intron-encoded protein (IEP) in each G2I sequence was conducted and resulted in the addition of three new IEP classes (U1–U3) to the previous classification. This analysis suggested that about 30% of all IEPs are non-canonical IEPs. The number of G2Is per genome was defined almost at the phylum level, and at least in the following two phyla, Firmicutes, and Cyanobacteriota, the type of IEP was largely associated as a factor in the G2I increase, i.e., there was an explosive increase in G2Is with bacterial C-type IEPs, mainly in the phylum Firmicutes, and in G2Is with CL-type IEPs, mainly in the phylum Cyanobacteriota. We also systematically analyzed the relationship between genomic signatures and the mechanism of these increases in G2Is. This is the first study to systematically characterize G2Is in the prokaryotic phylogenies.

Isolation and phylogenetic analysis of goose astrovirus type 1 from goslings with gout in Jiangxi province, China

Goose astrovirus (GoAstV) is a new Avastrovirus of the genus astrovirus causing gout, hemorrhage, and swellings of kidneys that have affected goslings around the major goose-producing regions in China. The GoAstV is divided into goose astrovirus type 1 (GoAstV-1) and goose astrovirus type 2 (GoAstV-2). Although GoAstV-2 is known to be the causative agent of goose gout, little published information about the relationship between GoAstV-1 and goose gout is unknown. In this study, we investigated the presence of GoAstV-1 in 293 visceral tissue/dead embryos samples with gout on different farms in Jiangxi province, China. A survey result indicated that the mono-infection of GoAstV-1 (32.08%) and co-infection of GoAstV-1 (12.28%) with GoAstV-2 in gout goslings in Jiangxi, China. JXGZ, a GoAstV-1 strain, was effectively isolated from the visceral tissue of gosling gout and serially propagated for more than 25 passages in a goose embryo. The JXGZ strain's whole genome was sequenced and investigated. Phylogenetic analysis of complete genome and capsid protein sequences of JXGZ strain show that it was more closely related to GoAstV-1 strain than GoAstV-2 strain and was grouped within the GoAstV-1 cluster. These findings will aid in the development of efficient diagnostic reagents and possible vaccinations by providing insight into the prevalence and genetic evolution of GoAstV-1 in China.

Diarrhea outbreak associated with coronavirus infection in adult dairy goats.

BackgroundInfection by coronaviruses cause gastrointestinal disease in many species. Little is known about its prevalence and importance in goats.ObjectiveIdentify the etiology, demographics, and clinical features of an outbreak of diarrhea in adult goats.HypothesisBovine coronavirus (BCoV) PCR would detect viral material in feces of goats in the herds involved in the diarrhea outbreak.AnimalsTwelve herds with 4 to 230 adult goats were affected. Goats sampled for fecal PCR were ≥1‐year‐old: 25 from affected herds and 6 from a control herd.MethodsThis is a cross‐sectional descriptive study of an outbreak of diarrheal disease in adult goats. BCoV PCR primers for the spike (S) or nucleocapsid (N) proteins were used to test fecal material from affected goats. The N protein sequencing and phylogenetic analysis was performed. Herd records and owner surveys were used to characterize morbidity, clinical signs, and treatment.ResultsIn 2 affected herds 18/25 of animals had at least 1 positive BCoV PCR test. Goats from affected herds were significantly more likely to be PCR positive than the control herd (OR 8.75, 95% CI 1.11‐104, P = .05). The most common clinical signs were change in fecal consistency (19/20) and decreased milk production (14/15). Phylogenetic analysis of the N protein showed this virus was closely related to a bovine‐like coronavirus isolated from a giraffe.Conclusions and Clinical ImportanceBovine coronavirus primers detected nucleic acids of the N and S proteins in feces of goats in affected herds. Coronavirus shedding frequency was temporally associated with the outbreak.

NQMaker: Estimating Time Nonreversible Amino Acid Substitution Models.

Amino acid substitution models are a key component in phylogenetic analyses of protein sequences. All commonly used amino acid models available to date are time-reversible, an assumption designed for computational convenience but not for biological reality. Another significant downside to time-reversible models is that they do not allow inference of rooted trees without outgroups. In this article, we introduce a maximum likelihood approach nQMaker, an extension of the recently published QMaker method, that allows the estimation of time nonreversible amino acid substitution models and rooted phylogenetic trees from a set of protein sequence alignments. We show that the nonreversible models estimated with nQMaker are a much better fit to empirical alignments than pre-existing reversible models, across a wide range of data sets including mammals, birds, plants, fungi, and other taxa, and that the improvements in model fit scale with the size of the data set. Notably, for the recently published plant and bird trees, these nonreversible models correctly recovered the commonly estimated root placements with very high-statistical support without the need to use an outgroup. We provide nQMaker as an easy-to-use feature in the IQ-TREE software (http://www.iqtree.org), allowing users to estimate nonreversible models and rooted phylogenies from their own protein data sets. The data sets and scripts used in this article are available at https://doi.org/10.5061/dryad.3tx95x6hx. [amino acid sequence analyses; amino acid substitution models; maximum likelihood model estimation; nonreversible models; phylogenetic inference; reversible models.]

Dynamic Patterns of Sex Chromosome Evolution in Neognath Birds: Many Independent Barriers to Recombination at the ATP5F1A Locus

Avian sex chromosomes evolved after the divergence of birds and crocodilians from their common ancestor, so they are younger than the better-studied chromosomes of mammals. It has long been recognized that there may have been several stages to the evolution of avian sex chromosomes. For example, the CHD1 undergoes recombination in paleognaths but not neognaths. Genome assemblies have suggested that there may be variation in the timing of barriers to recombination among Neognathae, but there remains little understanding of the extent of this variability. Here, we look at partial sequences of ATP5F1A, which is on the avian Z and W chromosomes. It is known that recombination of this gene has independently ceased in Galliformes, Anseriformes, and at least five neoavian orders, but whether there are other independent cessations of recombination among Neoaves is not understood. We analyzed a combination of data extracted from published chromosomal-level genomes with data collected using PCR and cloning to identify Z and W copies in 22 orders. Our results suggest that there may be at least 19 independent cessations of recombination within Neognathae, and 3 clades that may still be undergoing recombination (or have only recently ceased recombination). Analyses of ATP5F1A protein sequences revealed an increased amino acid substitution rate for W chromosome gametologs, suggesting relaxed purifying selection on the W chromosome. Supporting this hypothesis, we found that the increased substitution rate was particularly pronounced for buried residues, which are expected to be more strongly constrained by purifying selection. This highlights the dynamic nature of avian sex chromosomes, and that this level of variation among clades means they should be a good system to understand sex chromosome evolution.

Genome-Wide Identification and Expression Analysis of the 14-3-3 Gene Family in Mango (Mangifera indica L.).

Members of the Mi14-3-3 gene family interact with target proteins that are widely involved in plant hormone signal transduction and physiology-related metabolism and play important roles in plant growth, development and stress responses. In this study, 14-3-3s family members are identified by the bioinformatic analysis of the mango (Mangifera indica L.) genome. The gene structures, chromosomal distributions, genetic evolution, and expression patterns of these genes and the physical and chemical properties and conserved motifs of their proteins are analysed systematically. The results identified 16 members of the 14-3-3 genes family in the mango genome. The members were not evenly distributed across the chromosomes, and the gene structure analysis showed that the gene sequence length and intron number varied greatly among the different members. Protein sequence analysis showed that the Mi14-3-3 proteins had similar physical and chemical properties and secondary and tertiary structures, and protein subcellular localization showed that the Mi14-3-3 family proteins were localized to the nucleus. The sequence analysis of the Mi14-3-3s showed that all Mi14-3-3 proteins contain a typical conserved PFAM00244 domain, and promoter sequence analysis showed that the Mi14-3-3 promoters contain multiple hormone-, stress-, and light-responsive cis-regulatory elements. Expression analysis showed that the 14-3-3 genes were expressed in all tissues of mango, but that their expression patterns were different. Drought, salt and low temperature stresses affected the expression levels of 14-3-3 genes, and different 14-3-3 genes had different responses to these stresses. This study provides a reference for further studies on the function and regulation of Mi14-3-3 family members.

Refining the domain architecture model of the replication origin firing factor Treslin/TICRR.

Faithful genome duplication requires appropriately controlled replication origin firing. The metazoan origin firing regulation hub Treslin/TICRR and its yeast orthologue Sld3 share the Sld3-Treslin domain and the adjacent TopBP1/Dpb11 interaction domain. We report a revised domain architecture model of Treslin/TICRR. Protein sequence analyses uncovered a conserved Ku70-homologous β-barrel fold in the Treslin/TICRR middle domain (M domain) and in Sld3. Thus, the Sld3-homologous Treslin/TICRR core comprises its three central domains, M domain, Sld3-Treslin domain, and TopBP1/Dpb11 interaction domain, flanked by non-conserved terminal domains, the CIT (conserved in Treslins) and the C terminus. The CIT includes a von Willebrand factor type A domain. Unexpectedly, MTBP, Treslin/TICRR, and Ku70/80 share the same N-terminal domain architecture, von Willebrand factor type A and Ku70-like β-barrels, suggesting a common ancestry. Binding experiments using mutants and the Sld3-Sld7 dimer structure suggest that the Treslin/Sld3 and MTBP/Sld7 β-barrels engage in homotypic interactions, reminiscent of Ku70-Ku80 dimerization. Cells expressing Treslin/TICRR domain mutants indicate that all Sld3-core domains and the non-conserved terminal domains fulfil important functions during origin firing in human cells. Thus, metazoa-specific and widely conserved molecular processes cooperate during metazoan origin firing.

Identification and analysis of iron transporters from the fission yeast Schizosaccharomyces pombe.

Iron is an essential trace metal ion required for all living organisms, and is taken up by iron transporters. Here, we identified and characterized three-candidate high-affinity (Fio1, Frp1 and Frp2) and two-candidate low-affinity iron transporters (Fet4 and Pdt1) from the fission yeast Schizosaccharomyces pombe. Protein sequence analyses revealed that Fio1 is a multicopper oxidase that contains three cupredoxin domains with eleven candidate iron-binding ligands, whereas Frp1 harbors a ferric reductase domain with three-candidate heme-binding ligands. Protein sequence analyses also revealed that Fet4 and Pdt1 are integral membrane proteins with 10 and 11 transmembrane regions, respectively. Deletion of fio1 and, to a lesser extent, frp1 impaired growth under iron-depleted conditions, whereas deletion of frp1 and, to a lesser extent, frp2 inhibited growth under iron-replete conditions. Deletion of fet4 and pdt1 did not affect the growth of cells under iron-depleted and iron-replete conditions. Deletion of fio1 or frp1 also increased the sensitivity of cells to other transition metals. The copper sensitivity of Δfio1 cells could be rescued by iron, suggesting that the addition of iron mightdecrease the uptake of potentially toxic copper in Δfio1 cells. The copper sensitivity of Δfio1 cells could also be rescued by deletion of frp1, suggesting that Fio1 and Frp1 may function together in iron and copper uptakes in S. pombe. Our results revealed that iron and copper uptake systems may be partially overlapped in S. pombe.

Quantification of the Potential Impact of Glyphosate-Based Products on Microbiomes

Glyphosate-based products (GBP) are the most common broad-spectrum herbicides worldwide. The target of glyphosate is the enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in the shikimate pathway, which is virtually universal in plants. The inhibition of the enzyme stops the production of three essential amino acids: phenylalanine, tyrosine, and tryptophan. EPSPS is also present in fungi and prokaryotes, such as archaea and bacteria; thus, the use of GBP may have an impact on the microbiome composition of soils, plants, herbivores, and secondary consumers. This article aims to present general guidelines to assess the effect of GBP on microbiomes from field experiments to bioinformatics analyses and provide a few testable hypotheses. Two field experiments are presented to test the GBP on non-target organisms. First, plant-associated microbes from 10 replicated control and GBP treatment plots simulating no-till cropping are sampled and analyzed. In the second experiment, samples from experimental plots fertilized by either poultry manure containing glyphosate residues or non-treated control manure were obtained. Bioinformatics analysis of EPSPS protein sequences is utilized to determine the potential sensitivity of microbes to glyphosate. The first step in estimating the effect of GBP on microbiomes is to determine their potential sensitivity to the target enzyme (EPSPS). Microbial sequences can be obtained either from public repositories or by means of PCR amplification. However, in the majority of field studies, microbiome composition has been determined based on universal DNA markers such as the 16S rRNA and the internal transcribed spacer (ITS). In these cases, sensitivity to glyphosate can only be estimated through a probabilistic analysis of EPSPS sequences using closely related species. The quantification of the potential sensitivity of organisms to glyphosate, based on the EPSPS enzyme, provides a robust approach for further experiments to study target and non-target resistant mechanisms.