Functional assessment of AtPAP17; encoding a purple acid phosphatase involved in phosphate metabolism in Arabidopsis thaliana.

PURPOSE: Purple acid phosphatases (PAPs) includ the largest classes of non-specific plant acid phosphatases. Most characterized PAPs were found to play physiological functions in phosphorus metabolism. In this study, we investigated the function of AtPAP17 gene encoding an important purple acid phosphatase in Arabidopsis thaliana. METHODS: The full-length cDNA sequence of AtPAP17 gene under the control of CaMV-35S promoter was transferred to the A. thaliana WT plant. The generated homozygote AtPAP17-overexpressed plants were compared by the types of analyses with corresponding homozygote atpap17-mutant plant and WT in both + P (1.2 mM) and - P (0 mM) conditions. RESULTS: In the + P condition, the highest and the lowest amount of Pi was observed in AtPAP17-overexpressed plants and atpap17-mutant plants by 111% increase and 38% decrease compared with the WT plants, respectively. Furthermore, under the same condition, APase activity of AtPAP17-overexpressed plants increased by 24% compared to the WT. Inversely, atpap17-mutant plant represented a 71% fall compared to WT plants. The comparison of fresh weight and dry weight in the studied plants showed that the highest and the lowest amount of absorbed water belonged to OE plants (with 38 and 12 mg plant-1) and Mu plants (with 22 and 7 mg plant-1) in + P and - P conditions, respectively. CONCLUSION: The lack of AtPAP17 gene in the A. thaliana genome led to a remarkable reduction in the development of root biomass. Thus, AtPAP17 could have an important role in the root but not shoot developmental and structural programming. Consequently, this function enables them to absorb more water and eventually associated with more phosphate absorption.

RAV transcription factor regulatory function in response to salt stress in two Iranian wheat landraces.

Amongst the transcription factor groups, the AP2/ERF (Apetala2/Ethylene Response Factor) superfamily is one of the main groups in plants and plays an essential role in tolerating abiotic and biotic stresses. The AP2/ERF superfamily consists of ERF, AP2, RAV, and Soloist families based on the AP2 domain number. The RAV (Related to ABI3/VP1) family members have been revealed to be stimulate by a number of biotic and abiotic environmental incentives; including pathogen infection, salicylic acid, osmotic stress, cold, high salinity, wounding, and exogenous hormone application. However, limited data are available on the contributions of RAV transcription factors in wheat (Triticum aestivum L.). In the present study, a total of 26 RAV genes were identified in wheat from a genome-wide search against the latest wheat genome data. Phylogenetic and sequence alignment analyses divided the wheat RAV genes into 4 clusters, I, II, III and IV. Chromosomal distribution, gene structure and motif composition were subsequently investigated. The 26 TaRAV genes were unevenly distributed on 21 chromosomes. After cloning and sequencing of 7 TaRAVs candidate genes the expression levels of two TaRAVs, TaRAV4 and TaRAV5, were validated through qPCR analyses in two salt-tolerant Iranian landraces of wheat. Our results showed that the TaRAV4 and TaRAV5 were co-expressed in wheat tissues and were highly correlated to salt tolerance indices such as the K+/Na+ ratio. Protein interaction revealed that the TaRAV4 and TaRAV5 were related to vital proteins such as PK4 and PP2C, and MYB and Zinc finger transcription factors, and Gigantea proteins. This study improved our knowledge of the RAV gene family function in wheat and the probable role of RAVs in salt tolerance mechanisms to improve crop production under changing environments. Also, the two relatively salt-tolerant landraces of wheat that were examined in this study could be suitable candidates for future breeding studies.

A Comprehensive Review of the Key Characteristics of the Genus Mentha, Natural Compounds and Biotechnological Approaches for the Production of Secondary Metabolites.

Context: The genus Mentha is one of the most aromatic and well-known members of the Lamiaceae family. A wide range of bioactive compounds has been reported in mints. Regarding the high economic importance of Mentha plants due to the presence of valuable metabolites, the demand for their products is growing exponentially. Therefore, to supply such demand, new strategies should be adopted to improve the yield and medicinal quality of the products. Evidence Acquisition: The current review is written based on scientific literature obtained from online databases, including Google Scholar, PubMed, Scopus, and Web of Science regarding the characteristic features of some species of the genus Mentha, their distribution and cultivation, main uses and benefits, phytochemical composition, biotechnological approaches for the production of secondary metabolites, and strategies for enhanced production of mints secondary metabolites. Results: In this article, we offer an overview of the key characteristics, natural compounds, biological properties, and medicinal uses of the genus Mentha. Current research describes biotechnological techniques such as in vitro culture methods for the production of high-value secondary metabolites. This review also highlights the strategies such as elicitation, genetic, and metabolic engineering to improve the secondary compounds production level in mint plants. Overall, it can be concluded that identifying the biosynthetic pathways, leading to the accumulation of pharmaceutically important bioactive compounds, has paved the way for developing highly productive mint plants with improved phytochemical profiles.

Critical assessment of genome-scale metabolic models of Arabidopsis thaliana.

Genome-scale metabolic models (GEMs) have enabled researchers to perform systems-level studies of living organisms. Flux balance analysis (FBA), as a constraint-based technique, enables computation of reaction fluxes and prediction of the metabolic phenotypes of a cell under a set of specified conditions. The quality of a GEM is important for obtaining accurate predictions. In this study, we evaluated the quality of five available GEMs for Arabidopsis thaliana from various points of views. To do this, we inspected some of their important features, including the number of reactions with well-defined gene-protein-reaction rules, number of blocked reactions, mass-unbalanced reactions, prediction accuracy in the simulation of key metabolic functions and existence of erroneous energy generating cycles (EGCs). All of the models were found to include some mass-unbalanced reactions. Moreover, four out of five models were found to include EGCs. However, Aracell includes the maximum number of blocked reactions, which suggests the presence of several incomplete pathways. These results clearly show that simulation by using these models may result in erroneous predictions and all of the publicly available GEMs for A. thaliana require extensive curations before being applied in practice.

Meta-Analysis of EGF-Stimulated Normal and Cancer Cell Lines to Discover EGF-Associated Oncogenic Signaling Pathways and Prognostic Biomarkers.

Background: Although epidermal growth factor (EGF) controls many crucial processes in the human body, it can increase the risk of developing cancer when overexpresses. Objectives: This study focused on detecting cancer-associated genes that are dysregulated by EGF overexpression. Materials and Methods: To identify differentially expressed genes (DEGs), two independent meta-analyses with normal and cancer RNA-Seq samples treated by EGF were conducted. The new DEGs detected only via two meta-analyses were used in all downstream analyses. To reach count data, the tools of FastQC, Trimmomatic, HISAT2, SAMtools, and HTSeq-count were employed. DEGs in each individual RNA-Seq study and the meta-analysis of RNA-Seq studies were identified using DESeq2 and metaSeq R package, respectively. MCODE detected densely interconnected top clusters in the protein-protein interaction (PPI) network of DEGs obtained from normal and cancer datasets. The DEGs were then introduced to Enrichr and ClueGO/CluePedia, and terms, pathways, and hub genes enriched in Gene Ontology (GO) and KEGG and Reactome were detected. Results: The meta-analysis of normal and cancer datasets revealed 990 and 541 new DEGs, all upregulated. A number of DEGs were enriched in protein K48-linked deubiquitination, ncRNA processing, ribosomal large subunit binding, and protein processing in endoplasmic reticulum. Hub genes overexpression (DHX33, INTS8, NMD3, OTUD4, P4HB, RPS3A, SEC13, SKP1, USP34, USP9X, and YOD1) in tumor samples were validated by TCGA and GTEx databases. Overall survival and disease-free survival analysis also confirmed worse survival in patients with hub genes overexpression. Conclusions: The detected hub genes could be used as cancer biomarkers when EGF overexpresses.

Enhanced inulin production by hairy root cultures of Cichorium intybus in response to Pi and Fe starvation.

Cichorium intybus is rich in inulin and has several pharmacological applications. Hairy roots culture is a valuable biotechnological tool used to produce plant secondary metabolites. Agrobacterium rhizogenes-mediated genetic transformation of chicory to hairy roots was investigated using Agrobacterium Strains A4, A13, A7, and ATCC15834. Several hairy roots were tested, from which 17 lines were selected based on their fast-growing characteristics. Results of PCR analysis revealed foreign DNA integration into the selected transgenic hairy root lines. Finally, four Adventitious roots that contained the highest ratio of total sugar to total weight (µg/gr DW), were selected. This study investigated the effects of various levels of minerals and sucrose on the production of inulin in Cichorium hairy root culture. Different levels of sucrose, phosphate (Pi) and Iron (Fe) were evaluated, separately. It was found that an increase in sucrose levels from 3 to 5% could decrease the root growth; however, 60 g/l sucrose remarkably enhanced the inulin production rate in all the examined lines. The highest biomass was achieved by applying 3.75 mM Pi but it ended in the decreasing the inulin content per unit weight. In contrast, the highest inulin accumulation and the lowest amount of biomass were observed in 0.5 mM Pi. Fe starvation caused the biomass decrease and a significant increase in inulin accumulation. Results of this study suggest a successfully optimized culture medium to initiate the induction of Cichorium intybus hairy root cells to produce inulin as a valuable medicinal secondary metabolite.

In silico prediction of enzymatic reactions catalyzed by acid phosphatases.

In present work, we describe a methodology for prediction of an enzymatic reaction for which no experimental data are available except for a gene sequence. As a challenging case, we have developed the method for identifying the putative substrates of monoester phosphatases, commonly known as acid phosphatase enzymes, which have no strong substrate specificity. Finding a preferable substrate for each one is an important task to unravel pathways involved in plant phosphate metabolism. Having used an Arabidopsis thaliana haloacid dehalogenase (HAD)-related acid phosphatases, HRP9, with an experimentally known structure and preferred substrate as an instance, we firstly predicted the 3 D-structure of HRP1 for subsequent analysis. Then, molecular docking was used to find the best protein interaction with a ligand existing in a set of possible substrates compiled from genome scale metabolic networks of A. thaliana based on binding energy, binding mode as well as the distance between phosphoric ester and cofactor, Mg2+, localized in the active site of HRP1. Molecular dynamics simulation ratified stable protein-ligand complex model. Our analysis predicted HRP1 preferably bind to pyridoxamine-5'-phosphate (PMP). Thus, it is deduced that the conversion of PMP to pyridoxamine must be catalyzed by HRP1. This procedure is expected to make a reliable pipeline to predict the enzymatic reactions catalyzed by acid phosphatases. Taken as a whole, it could be applicable for discovery of the interacting ligands, inhibitors as well as interacting proteins which limits lab works or used for gap filling in biosystems.Communicated by Ramaswamy H. Sarma.

Evaluation of the Effectiveness of Herbal Components Based on Their Regulatory Signature on Carcinogenic Cancer Cells.

Predicting cancer cells' response to a plant-derived agent is critical for the drug discovery process. Recently transcriptomes advancements have provided an opportunity to identify regulatory signatures to predict drug activity. Here in this study, a combination of meta-analysis and machine learning models have been used to determine regulatory signatures focusing on differentially expressed transcription factors (TFs) of herbal components on cancer cells. In order to increase the size of the dataset, six datasets were combined in a meta-analysis from studies that had evaluated the gene expression in cancer cell lines before and after herbal extract treatments. Then, categorical feature analysis based on the machine learning methods was applied to examine transcription factors in order to find the best signature/pattern capable of discriminating between control and treated groups. It was found that this integrative approach could recognize the combination of TFs as predictive biomarkers. It was observed that the random forest (RF) model produced the best combination rules, including AIP/TFE3/VGLL4/ID1 and AIP/ZNF7/DXO with the highest modulating capacity. As the RF algorithm combines the output of many trees to set up an ultimate model, its predictive rules are more accurate and reproducible than other trees. The discovered regulatory signature suggests an effective procedure to figure out the efficacy of investigational herbal compounds on particular cells in the drug discovery process.

Toward more specific inhibitor for Solanum tuberosum polyphenol oxidase through a structural insight into its activities and inhibition.

To prevent enzymatic browning, applying a polyphenol oxidase (PPO) inhibitor is more desirable, especially when the freshness of the product matters. Most of the inhibition studies were done on mushroom tyrosinase (MT) while the literature indicates that MT and PPO of Solanum tuberosum (PPOsol ) respond differently to the same modulator despite their similar active sites. This research was conducted to deepen our knowledge about PPOsol and introduce a more specific inhibitor for this enzyme to be used in controlling the enzymatic browning of potatoes. A modified procedure was developed for PPOsol purification. The enzyme was subjected to some essential physicochemical and kinetics studies. In parallel to the comparable physicochemical properties, homology modeling revealed high structural similarity between Solanum lycopersicum PPO (PPOsly ) and PPOsol except for their active site pockets. Accordingly, PPOsol showed 5.1- and 34-fold higher affinity toward chlorogenic acid compared with two PPOsly isozymes. Alike PPOsly , PPOsol showed monophenolase activity but it was inactive toward L-tyrosine and p-coumaric acid. Based on structural criteria, phthalic acid, cinnamic acid, ferulic acid, and vanillin were selected and thoroughly examined for inhibition of the catecholase activity of PPOsol . Although all these substances inhibited PPOsol in mixed-inhibition mode, the results were strongly in favor of vanillin with IC50 < 1.37 mM and Ki < 1.2 mM. PRACTICAL APPLICATIONS: There are subtle structural differences in the active site pockets of polyphenol oxidase (PPOs) of various fruits, vegetables, and crops. Consequently, to introduce an efficient inhibitor for hindering enzymatic browning of crop products, it is essential to have detailed knowledge about the structure and activity of its PPO as the main player of this undesirable phenomenon. Results of this study not only shed light on the physicochemical properties of PPOsol but can also be used in making various formulations for safe controlling enzymatic browning of potatoes, especially fresh-cut and minimally processed products, and similar crops products during postharvest and the processes of products preparations.

The Effect of Endogenous Hormones, Total Antioxidant and Total Phenol Changes on Regeneration of Barley Cultivars.

BACKGROUND: Barley (Hordeum vulgar L.) is a valuable platform for producing recombinant proteins. Before using different barley cultivars as an efficient platform for molecular farming, optimization of cultural conditions and studying the effective factors on the tissue culture are critical. OBJECTIVES: In this study, we evaluated callus induction, plant regeneration and changes in the levels of total antioxidant, total phenol and endogenous hormones of three Iranian barley cultivars (Reyhan, Yousef and Bahman) and Golden Promise cultivar. MATERIALS AND METHODS: We used immature embryos as explants on MS-based medium containing 3 mg.L-1 2,4-D for callus induction. Calluses were transferred to regeneration media with 2 mg.L-1 BAP. The levels of endogenous hormones were measured using High-Performance Liquid Chromatography system and total antioxidant and total phenols were determined using a spectrophotometer. RESULTS: We demonstrated that callus formation was very high in all cultivars (about 91%) and all immature embryo explants had the potential to produce embryogenic calluses. The present study also showed that the regeneration rates among the studied cultivars were very different and the Iranian cultivars showed lower regeneration percentages (about 1.4%) compared to Golden Promise cultivar (about 72.5%). The levels of endogenous hormones in Iranian cultivars and Golden Promise varied distinctly and significant differences in terms of total antioxidants and total phenols were found in the two groups. CONCLUSIONS: Accumulated evidence suggests that for successful regeneration of recalcitrant cultivars, external treatments should be done in a way to reduce the inhibitory effects of internal factors.

Production of phenolic acids in hairy root cultures of medicinal plant Mentha spicata L. in response to elicitors.

In this study, hairy root induction in leaf and stem explants of Mentha spicata using various Agrobacterium rhizogenes strains was established for the first time. Although inoculation of explants by immersion method resulted in tissue necrosis, direct injection of explants by all examined strains (A13,R318,A4,GMI 9534 and ATCC15834) was effective. All different parts of the stem were susceptible to A. rhizogenes infection. However, the middle and lower internodes showed a higher rate of transformation. Among the different strains, the strain A13 exhibited the highest infection efficiency (almost 75% of the explants). A13 and R318-infected hairy roots showed the highest biomass production (close to 60 mg/flask), while infection with GMI 9534 produced the highest content of phenolic acids. Finally, the effect of phytohormone elicitation on hairy root growth and phenolic acid biosynthesis was investigated. A substantial increase in root growth and phenolic acids accumulation was obtained followed by 0.3 mg L-1 IBA and 100 µM MeJA treatment, respectively.

A Study to Assess the Role of Gluten Encoded Genes and Their Regulatory Elements in Bread Making Quality of Wheat.

BACKGROUND: Quality of bread baking is affected by gluten genes and balance between their expressions. Hence, it is necessary for a comprehensive research to study and compare all gluten genes and their regulating elements simultaneously. OBJECTIVES: The aim of this study was to evaluate the molecular mechanism of bread quality at the level of coding genes and regulating elements via comparative transcriptome analysis of two extreme wheat cultivars. MATERIALS AND METHODS: RNAs were extracted from the grain of two wheat cultivars with high (Pishtaz) and low (Navid) bread making qualities, collected during endosperm development at five stages. mRNAs were sequenced and gluten transcripts were assessed to find differentially expressed genes. Then, transcription factors interacting with gluten genes were detected and evaluated for expression. RESULTS: Results showed that Ɣ-gliadin and LMW-GS genes had a higher expression in Pishtaz and Navid, respectively. Most identified transcription factors were active at the early stage of growth and it seemed that NAC and ERF transcription factors had significant roles in regulating genes with different expressions. There was no significant difference in the expression level of NACs between two cultivars. It is proposed that the ERF transcription factor which classified as BREB2C transcription factor could control the expression of LMW-GS genes in two cultivars and functionally act as a repressor for their target genes. CONCLUSION: The priority of Pishtaz wheat cultivar in bread quality originated from high expression levels of Ɣ-gliadin gene and ERF transcription factor.

Functional Assessment of an Overexpressed Arabidopsis Purple Acid Phosphatase Gene (AtPAP26) in Tobacco Plants.

BACKGROUND: Overexpression of known genes encoding key phosphate (Pi)-metabolizing enzymes, such as acid phosphatases (APases), is presumed to help plants with Pi availability and absorption as they are mostly exposed to suboptimal environmental conditions for this vital element. OBJECTIVES: In this study, the overexpression effect of AtPAP26, one of the main contributors in retrieving Pi from intracellular and extracellular compounds, was evaluated from various viewes in tobacco plant. MATERIALS AND METHODS: As a heterologous expression system, the encoding cDNA sequence of AtPAP26 was transferred into tobacco plants. RESULTS: A high growth rate of the transgenic lines was observed which could be due to an increased APase activity, leading to the high total phosphorus as well as the free Pi content of the transgenic plants. Interestingly, a significant increased activity of the other APases was also noticed, indicating a networking among them. These were accompanied by less branched and short primary roots and a decreased lateral root numbers grown in Pi-starvation condition compared to the wild type seedlings. Besides, a delayed germination and dwarf phenotype indicates the possible reduction in gibberellic acid biosynthesis in the transgenic lines. CONCLUSIONS: Such transgenic plants are of interest not only for increased yield but also for the reduced need for chemical fertilizers and removal of excessive Pi accumulation in soils as a consequence of fertilizers' or poultry wastes' over-usage.

Expression pattern and subcellular localization of Arabidopsis purple acid phosphatase AtPAP9.

Purple acid phosphatase (PAP; EC 3.1.3.2) enzymes are metallophosphoesterases that hydrolysis phosphate ester bonds in a wide range of substrates. Twenty-nine PAP-encoding loci have been identified in the Arabidopsis genome, many of which have multiple transcript variants expressed in response to diverse environmental conditions. Having analyzed T-DNA insertion mutants, we have provided strong pieces of evidence that AtPAP9 locus encodes at least two types of transcripts, designated as AtPAP9-1 and AtPAP9-2. These transcript variants expressed distinctly during the course of growth in medium containing sufficient phosphate or none. Further histochemical analysis by the use of AtPAP9-1 promoter fused to ß-glucuronidase reporter gene indicated the expression of this gene is regulated in a tissue-specific manner. AtPAP9-1 was highly expressed in stipule and vascular tissue, particularly in response to fungal infection. Subcellular localization of AtPAP9-1:green fluorescent fusion protein showed that it must be involved in plasma membrane and cell wall adhesion.

Hybrid-controlled neurofuzzy networks analysis resulting in genetic regulatory networks reconstruction.

Reverse engineering of gene regulatory networks (GRNs) is the process of estimating genetic interactions of a cellular system from gene expression data. In this paper, we propose a novel hybrid systematic algorithm based on neurofuzzy network for reconstructing GRNs from observational gene expression data when only a medium-small number of measurements are available. The approach uses fuzzy logic to transform gene expression values into qualitative descriptors that can be evaluated by using a set of defined rules. The algorithm uses neurofuzzy network to model genes effects on other genes followed by four stages of decision making to extract gene interactions. One of the main features of the proposed algorithm is that an optimal number of fuzzy rules can be easily and rapidly extracted without overparameterizing. Data analysis and simulation are conducted on microarray expression profiles of S. cerevisiae cell cycle and demonstrate that the proposed algorithm not only selects the patterns of the time series gene expression data accurately, but also provides models with better reconstruction accuracy when compared with four published algorithms: DBNs, VBEM, time delay ARACNE, and PF subjected to LASSO. The accuracy of the proposed approach is evaluated in terms of recall and F-score for the network reconstruction task.