Transcriptomic Analysis of Cyclamen persicum to Identify Invovled Genes in Triterpene Secondary Metabolites Pathway.

Saponins are considered as a diverse group of natural active compounds, which are widely found in crops. Mevalonate pathway (MVA) is regarded as the main pathway for synthesis of saponins in crops. This study aims to compare transcriptome of the leaf with tuber of crop including tubers and roots. First, more than 166 million reads were generated. The existence of 36,678 unigenes in the two samples out of 48,936 assembled ones showed a significant difference in expression. Finally, 310 and 290 highly up-regulated genes in leaf and tuber were selected for the next analysis. In addition, the expression profiles of 13 key genes in the MVA pathway were compared in RNA sequencing and reverse transcription-quantitative polymerase chain reaction analysis. The results indicated that cyclamen tuber has a higher level of expression of MVA pathway genes. The topological analysis for gene co-expression network involved in triterpenoid synthesis represented that the genes at the beginning of such pathway play a critical role so that the reduction of their expression challenges triterpenoid synthesis severely. The tuber of the cyclamen appears to be the major site of triterpene synthesis, and transfer of excess Isopentenyl pyrophosphate (IPP) from tuber to leaf activates downstream genes in leaf of crop.

Transcriptomic analysis of alternative splicing events for different stages of growth and development in Sistan Yaghooti grape clusters.

Sistan Yaghooti grape variety, despite characteristics such as early ripening, is vulnerable to cluster rot due to small berries and dense clusters. In this regard, AS may serve as a regulatory mechanism during developmental processes and in response to environmental signals. RNA-Seq analysis was performed to measure gene expression and the extent of AS events in the cluster growth and development stages of Sistan Yaghooti grape. The number of AS events increased during stages, suggesting that it contributes to the grapevine's adaptability to various stresses. In addition, DEG and DAS genes showed little overlap in cluster growth stages. Functional analysis of 19,194 DAS -gene sets showed that VIT_06s0004g06670 gene is involved in the activation of calcium channels (Ca2+) through the activation of 5 PLC biosynthetic pathways. Among the 27,229 DEG -sets, VIT_07s0005g05320 gene showed higher expression. Interestingly, this gene is involved in the synthesis of an EF -hand domain-containing protein capable of binding to Ca2+ by activating 4 biochemical pathways. These genes increase cytosolic Ca2+ concentration, enhancing plant stress tolerance and resistance to cracking. These results show that AS can respond independently to different types of stress. Among the other DAS genes, the GA2ox gene (VvGA2ox) showed an increase in AS events during cluster development. This gene is critical for initiating the degradation process of GA and plays a crucial role in different stages of seed development. Therefore, it is very likely that this gene is one of the main factors responsible for the density and seedlessness of Sistan Yaghooti grape.

Lipid-Based Delivery Systems for Flavonoids and Flavonolignans: Liposomes, Nanoemulsions, and Solid Lipid Nanoparticles.

Herbal chemicals with a long history in medicine have attracted a lot of attention. Flavonolignans and flavonoids are considered as two classes of the above-mentioned compounds with different functional groups which exhibit several therapeutic capabilities such as antimicrobial, anti-inflammatory, antioxidant, antidiabetic, and anticancer activities. Based on the studies, high hydrophobic properties of the aforementioned compounds limit their bioavailability inside the human body and restrict their wide application. Nanoscale formulations such as solid lipid nanoparticles, liposomes, and other types of lipid-based delivery systems have been introduced to overcome the above-mentioned challenges. This approach allows the aforementioned hydrophobic therapeutic compounds to be encapsulated between hydrophobic structures, resulting in improving their bioavailability. The above-mentioned enhanced delivery system improves delivery to the targeted sites and reduces the daily required dosage. Lowering the required daily dose improves the performance of the drug by diminishing its side effects on non-targeted tissues. The present study aims to highlight the recent improvements in implementing lipid-based nanocarriers to deliver flavonolignans and flavonoids.

A study of the interaction space of two lactate dehydrogenase isoforms (LDHA and LDHB) and some of their inhibitors using proteochemometrics modeling.

Lactate dehydrogenase (LDH) is a tetramer enzyme that converts pyruvate to lactate reversibly. This enzyme becomes important because it is associated with diseases such as cancers, heart disease, liver problems, and most importantly, corona disease. As a system-based method, proteochemometrics does not require knowledge of the protein's three-dimensional structure, but rather depends on the amino acid sequence and protein descriptors. Here, we applied this methodology to model a set of LDHA and LDHB isoenzyme inhibitors. To implement the proteochemetrics method, the camb package in the R Studio Server programming environment was used. The activity of 312 compounds of LDHA and LDHB isoenzyme inhibitors from the valid Binding DB database was retrieved. The proteochemometrics method was applied to three machine learning algorithms gradient amplification model, random forest, and support vector machine as regression methods to find the best model. Through the combination of different models into an ensemble (greedy and stacking optimization), we explored the possibility of improving the performance of models. For the RF best ensemble model of inhibitors of LDHA and LDHB isoenzymes, and were 0.66 and 0.62, respectively. LDH inhibitory activation is influenced by Morgan fingerprints and topological structure descriptors.

Characterization of sucrose binding protein as a seed-specific promoter in transgenic tobacco Nicotiana tabacum L.

Seed-specific expression using appropriate promoters is a recommended strategy for the efficiently producing valuable metabolites in transgenic plants. In the present study, we investigated the sequence of sucrose binding protein (SBP) as a seed-specific promoter to find the cis-acting elements specific to gene expression in seeds. The 1860 bp SBP sequence was analyzed using Plant Care and PLACE databases to find cis-acting elements, which resulted in a finding of 22 cis-acting elements required for seed expression. In addition, we have discovered cis- acting elements that are indirectly involved in triacylglycerol synthesis (GATABOX, DOFCOREZM, CACGTGMOTIF). The seed specificity of SBP was analyzed by generating a stable transgenic tobacco plant harboring ß-glucuronidase (GUS) reporter gene under the control of the SBP promoter. Histochemical analysis of these transgenic tobacco plants indicated decreasing GUS activity in the leaves during the vegetative stage. However, the mature seeds of transgenic plants showed GUS activity. Moreover, the SBP promoter function in the seed oil content was evaluated by the expression of DGAT1. The expression analysis of DGAT1 in SBP-DGAT1 transgenic tobacco seeds using quantitative real-time PCR revealed a 7.8-fold increase in DGAT1 than in non-transgenic plants. Moreover, oil content increased up to 2.19 times more than in non-transgenic plants. And the oil content of the SBP-DGAT1 transgenic tobacco leaves did not change compared to the control plant. Therefore, we suggested that the SBP promoter could be used as a seed-specific promoter for targeted expression of desired genes in the metabolite engineering of oilseed crops.

Differentiation of an Iranian resistance chickpea line to Ascochyta blight from a susceptible line using a functional SNP.

Identification of resistant sources to Ascochyta blight (AB) has been considered as a main purpose in most chickpea breeding programs. Achievements to molecular markers related to resistance to Ascochyta rabiei allows selection programs to be developed more accurately and efficiently. The aim of this study was to investigate the applicability of a functional SNP in differentiating Iranian resistant cultivars to be used in selection programs. Amplification of SNP-containing fragment with specific primer pair and its sequencing resulted in tracking and determining the allelic pattern of SNP18, SNP18-2147, SNP18-2491 and SNP18-2554 loci belong to GSH118 gene in ILC263 (sensitive) and MCC133 (resistant) chickpea lines. Mutations in SNP18 and SNP18-2147 occur at the protein level at positions 499 and 554. Bioinformatics studies have shown that the GSH118 gene is a Lucien-rich repeat receptor kinases (LRR-RKs) and encodes a membrane protein which can be involved in recognizing microorganisms and initiating immune signaling pathways in plants. Additional studies to determine the function of this gene and its interaction with other proteins can be effective in gaining more knowledge about the molecular basis of resistance against AB.

Expression of BMP2-Hydrophobin fusion protein in the tobacco plant and molecular dynamic evaluation of its simulated model.

Plants are one of the ideal models for therapeutic protein production, however the recombinant protein purification problems in them must be overcome. Bone Morphogenetic Protein2 (BMP2) is employed for the restoration and construction of bone tissues. Hydrophobin is a fungal based protein with high hydrophobic characteristics. Due to this specificity, it is suitable for the purification of chimer protein from complex solutions when is fused to a protein utilizing an aqueous two-phase (A2P) technique. The plant optimized mature human BMP2 gene was designed and evaluated by in silico method. This process involves simulating molecular dynamics using the RMSD, RMSF and Gyration radius indexes. The synthesized Hyd-BMP2 gene was cloned into a pTRAkc-ERH plasmid and Transferred into Agrobacterium (Gv3101). The Nicotiana benthamiana plant leaves were co-agroinfiltrated with HA-Hyd-BMP2 and P19-pCambia1304 containing silencing suppressor. After purification of plant extract utilizing the A2P method, the sample was subjected to SDS-PAGE and Western-blot. By in silico study, the simulated fusion protein profitably shows reasonable protein compactness and the effect of amino acid substitution on protein-protein interaction is not remarkable. Western-blotting using anti HA tag has shown that the A2P technique partially purified the two 22 kDa and 44 kDa forms of Hydrophobin-BMP2. These results confirmed the presence of monomer and dimer forms of Hydrophobin-BMP2 proteins. Moreover, the expression level of the protein using P19 silencing suppressor increased six times and to 0.018% as shown by ELISA. This study presents a fast and easy technique for the purification of transient expressed pharmaceutical proteins from plants.

Bioinformatic tools for DNA methylation and histone modification: A survey.

Epigenetic inheritance occurs due to different mechanisms such as chromatin and histone modifications, DNA methylation and processes mediated by non-coding RNAs. It leads to changes in gene expressions and the emergence of new traits in different organisms in many diseases such as cancer. Recent advances in experimental methods led to the identification of epigenetic target sites in various organisms. Computational approaches have enabled us to analyze mass data produced by these methods. Next-generation sequencing (NGS) methods have been broadly used to identify these target sites and their patterns. By using these patterns, the emergence of diseases could be prognosticated. In this study, target site prediction tools for two major epigenetic mechanisms comprising histone modification and DNA methylation are reviewed. Publicly accessible databases are reviewed as well. Some suggestions regarding the state-of-the-art methods and databases have been made, including examining patterns of epigenetic changes that are important in epigenotypes detection.

Chromosomal abnormality, laboratory techniques, tools and databases in molecular Cytogenetics.

Cytogenetics is concerned with the structure and number of chromosomes (Karyotyping) and their abnormalities not only in congenital but also in acquired genetic disorders. Chromosomal abnormalities can form when there is an error occurred in chromosome number and, or their structural changes. Such changes happen by itself or inductively by environmental agents like chemical reagents, radiation, etc. Cytogenetics techniques used to understand chromosomal disorders and their relationship to health and disease provide not only valuable clues about chromosome breakage and DNA repair mechanisms but also a more proper understanding of their relationship to cause various illnesses. In this sense, to evaluate chromosomal imbalance and rearrangement, alternative experimental methods have been expanded. Currently, Cytogenetics evolves into a multidimensional science that led to promoting both theoretically and technologically advanced molecular biology, flow cytometry, bioinformatics, and phylogeny. This study investigates the unique laboratory Cytogenetics methods, databases, algorithms, and software used molecular Cytogenetics to identify various chromosomal abnormalities.

Protein complex prediction: A survey.

Protein complexes are one of the most important functional units for deriving biological processes within the cell. Experimental methods have provided valuable data to infer protein complexes. However, these methods have inherent limitations. Considering these limitations, many computational methods have been proposed to predict protein complexes, in the last decade. Almost all of these in-silico methods predict protein complexes from the ever-increasing protein-protein interaction (PPI) data. These computational approaches usually use the PPI data in the format of a huge protein-protein interaction network (PPIN) as input and output various sub-networks of the given PPIN as the predicted protein complexes. Some of these methods have already reached a promising efficiency in protein complex detection. Nonetheless, there are challenges in prediction of other types of protein complexes, specially sparse and small ones. New methods should further incorporate the knowledge of biological properties of proteins to improve the performance. Additionally, there are several challenges that should be considered more effectively in designing the new complex prediction algorithms in the future. This article not only reviews the history of computational protein complex prediction but also provides new insight for improvement of new methodologies. In this article, most important computational methods for protein complex prediction are evaluated and compared. In addition, some of the challenges in the reconstruction of the protein complexes are discussed. Finally, various tools for protein complex prediction and PPIN analysis as well as the current high-throughput databases are reviewed.

Gibberellin causes wide transcriptional modifications in the early stage of grape cluster development.

Yaghooti grape of Sistan is seedless, early ripening but has compact clusters. To study gibberellin effect on cluster compactness of Yaghooti grape, it has been studied transcriptomic changes in three developmental stages (cluster formation, berry formation and final size of cluster). We found out that 5409 of 22,756 genes in cluster tissue showed significant changes under gibberellin. Finally, it was showed that 2855, 2862 and 497 genes have critically important role on above developmental stages, respectively. GO enrichment analysis showed that gibberellin enhances biochemical pathways activity. Moreover, genes involved in ribosomal structure and photosynthesis rate in cluster tissue were up- and down- regulated, respectively. In addition, we observed location of metabolomic activities was transferred from nucleus to cytoplasm and from cytoplasm to cell wall and intercellular spaces during cluster development; but there is not such situation in gibberellin treated samples.

Beneficial effects of rutin in diabetes-induced deficits in acquisition learning, retention memory and pain perception in rats.

Objectives: Cognitive impairment and hyperalgesia are among the common manifestations of diabetes. Hyperglycemia may contribute to their developments but the exact pathophysiology underlying these complications is not fully understood. Flavonoids from plants original have beneficial effects on diabetes by improving glycemic control. Rutin (RUT) is a bioflavonoid found in many plants and foods with many biological activities including neuroprotective and antidiabetic effects. In this study, we hypothesized that administration of RUT (10, 25 and 50 mg/kg, i.g.) for 30 days in rats would affect on hyperglycemia, cognitive dysfunction and hyperalgesia, which are common complications of diabetes type I. Methods: Diabetes was induced by streptozotocin (STZ) injection which destroys ß-cells and induces clinical features in animals that resemble those in diabetes type I in humans. Therefore, STZ-treated animals are used for the evaluation of novel antidiabetic drugs. The animals received vehicle or RUT (10, 25 and 50 mg/kg, i.g., once daily) at the onset of hyperglycemia for 30 days. Learning and memory was assessed by passive avoidance learning and memory test in streptozocin-induced diabetic and non-diabetic rats. Chemical hyperalgesia was evaluated by the formalin test. Results: Diabetes-induced deficits in acquisition and retrieval processes. RUT (25 and 50 mg/kg) reversed learning and memory deficits in diabetic rats. These doses of RUT reversed chemical hyperalgesia during both phases of the formalin test in diabetic rats and induced antinociceptive effects in healthy animals. RUT 10 mg/kg did not alter behaviors in control and diabetic groups. RUT 50 mg/kg induced significant hypoglycemic effects in both diabetic and non-diabetic rats. Discussion: Prolonged oral administration of RUT (25 and 50 mg/kg) induced cognitive enhancing and antinociceptive effects in both control and diabetic rats. Therefore, it may represent a potential therapeutic option against diabetic neurological disorders which deserves consideration and further examination.

Salinity-associated microRNAs and their potential roles in mediating salt tolerance in rice colonized by the endophytic root fungus Piriformospora indica.

Piriformospora indica (P. indica), an endophytic root fungus, supports the growth and enhanced tolerance of plants to biotic and abiotic stresses. Several recent studies showed the significant role of small RNA (sRNA) molecules including microRNAs (miRNAs) in plant adaption to environmental stress, but little is known concerning the symbiosis-mediated salt stress tolerance regulated at miRNAs level. The overarching goal of this research is to elucidate the impact of miRNAs in regulating the P. indica-mediated salt tolerance in rice. Applying sRNA-seq analysis led to identify a set of 547 differentially abundant miRNAs in response to P. indica inoculation and salt stress. These included 206 rice-specific and 341 previously known miRNAs from other plant species. In silico analysis of miRNAs predictions of the differentially abundant miRNAs led to identifying of 193 putatively target genes, most of which were encoded either genes or transcription factors involved in nutrient uptake, sodium ion transporters, growth regulators, and auxin- responsive proteins. The rice-specific miRNAs targeted the transcription factors involved in the import of potassium ions into the root cells, the export of sodium ions, and plant growth and development. Interestingly, P. indica affected the differential abundance of miRNAs regulated genes and transcription factors linked to salt stress tolerance. Our data helps to understand the molecular basis of salt stress tolerance mediated by symbionts in plant and the potential impact of miRNAs for genetic improvement of rice varieties for tolerance to salt stress.

DNA-protein interaction: identification, prediction and data analysis.

Life in living organisms is dependent on specific and purposeful interaction between other molecules. Such purposeful interactions make the various processes inside the cells and the bodies of living organisms possible. DNA-protein interactions, among all the types of interactions between different molecules, are of considerable importance. Currently, with the development of numerous experimental techniques, diverse methods are convenient for recognition and investigating such interactions. While the traditional experimental techniques to identify DNA-protein complexes are time-consuming and are unsuitable for genome-scale studies, the current high throughput approaches are more efficient in determining such interaction at a large-scale, but they are clearly too costly to be practice for daily applications. Hence, according to the availability of much information related to different biological sequences and clearing different dimensions of conditions in which such interactions are formed, with the developments related to the computer, mathematics, and statistics motivate scientists to develop bioinformatics tools for prediction the interaction site(s). Until now, there has been much progress in this field. In this review, the factors and conditions governing the interaction and the laboratory techniques for examining such interactions are addressed. In addition, developed bioinformatics tools are introduced and compared for this reason and, in the end, several suggestions are offered for the promotion of such tools in prediction with much more precision.

Identification, Prediction and Data Analysis of Noncoding RNAs: A Review.

BACKGROUND: Noncoding RNAs (ncRNAs) which play an important role in various cellular processes are important in medicine as well as in drug design strategies. Different studies have shown that ncRNAs are dis-regulated in cancer cells and play an important role in human tumorigenesis. Therefore, it is important to identify and predict such molecules by experimental and computational methods, respectively. However, to avoid expensive experimental methods, computational algorithms have been developed for accurately and fast prediction of ncRNAs. OBJECTIVE: The aim of this review was to introduce the experimental and computational methods to identify and predict ncRNAs structure. Also, we explained the ncRNA's roles in cellular processes and drugs design, briefly. METHOD: In this survey, we will introduce ncRNAs and their roles in biological and medicinal processes. Then, some important laboratory techniques will be studied to identify ncRNAs. Finally, the state-of-the-art models and algorithms will be introduced along with important tools and databases. RESULTS: The results showed that the integration of experimental and computational approaches improves to identify ncRNAs. Moreover, the high accurate databases, algorithms and tools were compared to predict the ncRNAs. CONCLUSION: ncRNAs prediction is an exciting research field, but there are different difficulties. It requires accurate and reliable algorithms and tools. Also, it should be mentioned that computational costs of such algorithm including running time and usage memory are very important. Finally, some suggestions were presented to improve computational methods of ncRNAs gene and structural prediction.

afpCOOL: A tool for antifreeze protein prediction.

Various cold-adapted organisms produce antifreeze proteins (AFPs), which prevent the freezing of cell fluids by inhibiting the growth of ice crystals. AFPs are currently being recognized in various organisms, living in extremely low temperatures. AFPs have several important applications in increasing freeze tolerance of plants, maintaining the tissue in frozen conditions and producing cold-hardy plants by applying transgenic technology. Substantial differences in the sequence and structure of the AFPs, pose a challenge for researchers to identify these proteins. In this paper, we proposed a novel method to identify AFPs, using supportive vector machine (SVM) by incorporating 4 types of features. Results of the two used benchmark datasets, revealed the strength of the proposed method in AFP prediction. According to the results of an independent test setup, our method outperformed the current state-of-the-art methods. In addition, the comparison results of the discrimination power of different feature types revealed that physicochemical descriptors are the most contributing features in AFP detection. This method has been implemented as a stand-alone tool, named afpCOOL, for various operating systems to predict AFPs with a user friendly graphical interface.

Unraveling the transcriptional complexity of compactness in sistan grape cluster.

Yaghooti grape of Sistan is the earliest ripening grape in Iran, harvested every May annually. It is adapted to dry conditions in Sistan region and its water requirement is less than the other grape cultivars. The transcriptional complexity of this grape was studied in three stages of cluster development. Totally, 24121 genes were expressed in different cluster development steps (step 1: cluster formation, step 2: berry formation, step 3: final size of cluster) of which 3040 genes in the first stage, 2381 genes in the second stage and 2400 genes in the third stage showed a significant increase in expression. GO analysis showed that when the clusters are ripening, the activity of the nucleus, cytoplasmic, cytosol, membrane and chloroplast genes in the cluster architecture cells decreases. In contrast, the activity of the endoplasmic reticulum, vacuole and extracellular region genes enhances. When Yaghooti grape is growing and developing, some of metabolic pathways were activated in the response to biotic and abiotic stresses. Gene co-expression network reconstruction showed that AGAMOUS is a key gene in compactness of Sistan grape cluster, because it influences on expression of GA gene which leads to increase cluster length and berries size.

Leaf proteomics of drought-sensitive and -tolerant genotypes of fennel.

Fennel is attracted attention as a useful resource as researching medicinal plant for drought tolerance. To elucidate the response mechanism in drought-sensitive and -tolerant genotypes of fennel leaf, a gel-free/label-free proteomic technique was used. Fifty-day-old plants were subjected to drought stress for 60days. The relative water and proline contents were decreased and increased in sensitive genotypes, respectively; however, they were not a big change in tolerant genotypes. Photosynthesis was decreased in the sensitive genotypes under drought; however, it was increased in the tolerant genotype. In both drought-sensitive and -tolerant genotypes, proteins related to protein metabolism and cell organization were predominately affected under drought stress. The abundance of phosphoribulokinase and phosphoglycerate kinase enzymes were decreased and increased in drought-sensitive and -tolerant genotypes, respectively; however, the abundance of RuBisCO and glyceraldehyde-3-phosphate dehydrogenase enzymes were increased and decreased in drought-sensitive and -tolerant genotypes, respectively. Under drought stress, the abundance of glycolysis-related proteins was decreased in sensitive genotypes; however, they were increased in tolerance genotypes. Commonly changed proteins with polyethylene glycol fractionation such as cobalamin-independent methionine synthase were decreased and increased in drought-sensitive and -tolerant genotypes, respectively. These results suggest that cobalamin-independent methionine synthetase is involved in the tolerance of drought-tolerant fennel leaf under drought stress.

Rosmarinic acid protects against chronic ethanol-induced learning and memory deficits in rats.

OBJECTIVES: Ethanol consumption induces neurological disorders including cognitive dysfunction. Oxidative damage is considered a likely cause of cognitive deficits. We aimed to investigate the effects of rosmarinic acid (RA) in different doses for 30 days on chronic ethanol-induced cognitive dysfunction using the passive avoidance learning (PAL) and memory task in comparison with donepezil, a reference drug. We also evaluated the levels of superoxide dismutase (SOD), catalase (CAT), and lipid peroxidation in hippocampus as possible mechanisms. METHODS: Memory impairment was induced by 15% w/v ethanol (2 g/kg, i.g.) administration for 30 days. RA (8, 16, and 32 mg/kg, i.g.) or donepezil (2 mg/kg, i.g.) was administered 30 minutes before ethanol. The acquisition trial was done 1 hour after the last administration of RA and donepezil. At the end, animals were weighed and hippocami were isolated for analyzing of oxidant/antioxidant markers. RESULTS: Ethanol caused cognition deficits in the PAL and memory task. While RA 16 and 32 mg/kg improved cognition in control rats, it prevented learning and memory deficits of alcoholic groups. RA 8 mg/kg did not influence cognitive function in both control and alcoholic rats. RA 32 mg/kg had comparable effects with donepezil in prevention of acquisition and retention memory impairment. The higher doses of RA not only prevented increased lipid peroxidation and nitrite content but also decreased SOD, CAT, GSH, and FRAP levels in alcoholic groups and exerted antioxidant effects in non-alcoholic rats. DISCUSSION: We showed that RA administration dose-dependently prevented cognitive impairment induced by chronic ethanol in PAL and memory and disturbed oxidant/antioxidant status as a possible mechanism. The antioxidant, anticholinesterase, and neuroprotective properties of RA may be involved in the observed effects. Therefore, RA represents a potential therapeutic option against chronic ethanol-induced amnesia which deserves consideration and further examination.

Preventive effects of Salvia officinalis L. against learning and memory deficit induced by diabetes in rats: Possible hypoglycaemic and antioxidant mechanisms.

Learning and memory impairment occurs in diabetes. Salvia officinalis L. (SO) has been used in Iranian traditional medicine as a remedy against diabetes. We hypothesized that chronic administration of SO (400, 600 and 800mg/kg, p.o.) and its principal constituent, rosmarinic acid, would affect on passive avoidance learning (PAL) and memory in streptozocin-induced diabetic and non-diabetic rats. We also explored hypoglycemic and antioxidant activities of SO as the possible mechanisms. Treatments were begun at the onset of hyperglycemia. PAL was assessed 30days later. Retention test was done 24h after training. At the end, animals were weighed and blood samples were drawn for further analyzing of glucose and oxidant/antioxidant markers. Diabetes induced deficits in acquisition and retrieval processes. SO (600 and 800mg/kg) and rosmarinic acid reversed learning and memory deficits induced by diabetes and improved cognition of healthy rats. While the dose of 400mg/kg had no effect, the higher doses and rosmarinic acid inhibited hyperglycemia and lipid peroxidation as well as enhanced the activity of antioxidant enzymes superoxide dismutase and catalase. SO prevented diabetes-induced acquisition and memory deficits through inhibiting hyperglycemia, lipid peroxidation as well as enhancing antioxidant defense systems. Therefore, SO and its principal constituent rosmarinic acid represent a potential therapeutic option against diabetic memory impairment which deserves consideration and further examination.