A hypoxia-derived gene signature to suggest cisplatin-based therapeutic responses in patients with cervical cancer.

Cervical cancer remains a significant global public health concern, often exhibits cisplatin resistance in clinical settings. Hypoxia, a characteristic of cervical cancer, substantially contributes to cisplatin resistance. To evaluate the therapeutic efficacy of cisplatin in patients with cervical cancer and to identify potential effective drugs against cisplatin resistance, we established a hypoxia-inducible factor-1 (HIF-1)-related risk score (HRRS) model using clinical data from patients treated with cisplatin. Cox and LASSO regression analyses were used to stratify patient risks and prognosis. Through qRT-PCR, we validated nine potential prognostic HIF-1 genes that successfully predict cisplatin responsiveness in patients and cell lines. Subsequently, we identified fostamatinib, an FDA-approved spleen tyrosine kinase inhibitor, as a promising drug for targeting the HRRS-high group. We observed a positive correlation between the IC50 values of fostamatinib and HRRS in cervical cancer cell lines. Moreover, fostamatinib exhibited potent anticancer effects on high HRRS groups in vitro and in vivo. In summary, we developed a hypoxia-related gene signature that suggests cisplatin response prediction in cervical cancer and identified fostamatinib as a potential novel treatment approach for resistant cases.

Genetically modified soybean lines exhibit less transcriptomic variation compared to natural varieties.

Genetically modified (GM) soybeans provide a huge amount of food for human consumption and animal feed. However, the possibility of unexpected effects of transgenesis has increased food safety concerns. High-throughput sequencing profiling provides a potential approach to directly evaluate unintended effects caused by foreign genes. In this study, we performed transcriptomic analyses to evaluate differentially expressed genes (DEGs) in individual soybean tissues, including cotyledon (C), germ (G), hypocotyl (H), and radicle (R), instead of using the whole seed, from four GM and three non-GM soybean lines. A total of 3,351 DEGs were identified among the three non-GM soybean lines. When the GM lines were compared with their non-GM parents, 1,836 to 4,551 DEGs were identified. Furthermore, Gene Ontology (GO) analysis of the DEGs showed more abundant categories of GO items (199) among non-GM lines than between GM lines and the non-GM natural varieties (166). Results of Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that most KEGG pathways were the same for the two types of comparisons. The study successfully employed RNA sequencing to assess the differences in gene expression among four tissues of seven soybean varieties, and the results suggest that transgenes do not induce massive transcriptomic alterations in transgenic soybeans compared with those that exist among natural varieties. This work offers empirical evidence to investigate the genomic-level disparities induced by genetic modification in soybeans, specifically focusing on seed tissues.

High Calorific Values Boron Powder: Ignition and Combustion Mechanism, Surface Modification Strategies and Properties.

Boron powder is a kind of metal fuel with high gravimetric and volumetric calorific values, which has been widely used in military fields such as solid propellants, high-energy explosives, and pyrotechnics. However, the easily formed liquid oxide layer can adhere to the surface of boron powder and react with the hydroxyl (-OH) group of hydroxyl-terminated polybutadiene (HTPB) binder to form a gel layer that is detrimental to propellant processing and restricts the complete oxidation of boron powder. Therefore, to improve the combustion efficiency of boron powder, the ignition and combustion mechanisms of boron powder have been studied, and surface coating modification strategies have been developed by researchers worldwide, aiming to optimize the surface properties, improve the reaction activity, and promote the energy release of boron powder. In this review, recent studies on the ignition and combustion mechanisms of boron powder are discussed. Moreover, the reported boron powder coating materials are classified according to the chemical structure and reaction mechanism. Additionally, the mechanisms and characteristics of different coating materials are summarized, and the mechanism diagrams of fluoride and metal oxide are provided. Furthermore, promising directions for modification methods and the potential application prospects of boron powder are also proposed.

Proteomic and Metabolomic Evaluation of Insect- and Herbicide-Resistant Maize Seeds.

Label-free quantitative proteomic (LFQ) and widely targeted metabolomic analyses were applied in the safety evaluation of three genetically modified (GM) maize varieties, BBL, BFL-1, and BFL-2, in addition to their corresponding non-GM parent maize. A total of 76, 40, and 25 differentially expressed proteins (DEPs) were screened out in BBL, BFL-1, and BFL-2, respectively, and their abundance compared was with that in their non-GM parents. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most of the DEPs participate in biosynthesis of secondary metabolites, biosynthesis of amino acids, and metabolic pathways. Metabolomic analyses revealed 145, 178, and 88 differentially accumulated metabolites (DAMs) in the BBL/ZH58, BFL-1/ZH58, and BFL-2/ZH58×CH72 comparisons, respectively. KEGG pathway enrichment analysis showed that most of the DAMs are involved in biosynthesis of amino acids, and in arginine and proline metabolism. Three co-DEPs and 11 co-DAMs were identified in the seeds of these GM maize lines. The proteomic profiling of seeds showed that the GM maize varieties were not dramatically different from their non-GM control. Similarly, the metabolomic profiling of seeds showed no dramatic changes in the GM/non-GM maize varieties compared with the GM/GM and non-GM/non-GM maize varieties. The genetic background of the transgenic maize was found to have some influence on its proteomic and metabolomic profiles.

Detection and Diagnostic Value of Cytokines in Serum of Children with Acute Viral Encephalitis.

Acute viral encephalitis is one of the serious infectious diseases. In order to analyze the diagnostic efficacy of serum procalcitonin (PCT), C-reactive protein (CRP), and S100B protein in acute viral encephalitis, a total of 100 children with acute viral encephalitis from July 2019 to December 2021 are selected and included in the viral encephalitis group. The results show that S100B protein model has high specificity and sensitivity and is simple to operate. It provides new ideas and directions for differential diagnosis, improvement, and optimization of relevant clinical diagnosis and treatment schemes and has high clinical value.

Potential of different cells-derived exosomal microRNA cargos for treating spinal cord injury.

Spinal cord injury (SCI) is a disastrous situation that affects many patients worldwide. A profound understanding of the pathology and etiology of SCI is of great importance in inspiring new therapeutic concepts and treatment. In recent years, exosomes, which are complex lipid membrane structures secreted nearly by all kinds of plants and animal cells, can transport their valuable cargoes (e.g., proteins, lipids, RNAs) to the targeted cells and exert their communication and regulation functions, which open up a new field of treatment of SCI. Notably, the exosome's advantage is transporting the carried material to the target cells across the blood-brain barrier and exerting regulatory functions. Among the cargoes of exosomes, microRNAs, through the modulation of their mRNA targets, emerges with great potentiality in the pathological process, diagnosis and treatment of SCI. In this review, we discuss the role of miRNAs transported by different cell-derived exosomes in SCI that are poised to enhance SCI-specific therapeutic capabilities of exosomes.

High Thermal Stability and Insensitive Fused Triazole-Triazine Trifluoromethyl-Containing Explosives (TFX).

A trifluoromethyl-containing fused triazole-triazine energetic molecule, 3-nitro-7-(trifluoromethyl)-1,2,4-triazolo[5,1-c]-1,2,4-triazin-4-amine (TFX), has been synthesized in three steps from amino guanidine bicarbonate and trifluoroacetic acid. The process was found to be effective, nontoxic, and simple. The X-ray structure analysis of TFX finds that there are inter- and intramolecular hydrogen bonds and π-π interactions in the crystal lattice. TFX with a high density (1.88 g·cm-3) at room temperature, excellent thermal stability (T p = 300.3 °C), moderate energetic performance, and with insensitivity to mechanical stimulation has potential as heat-resistant energetic materials.

The emerging role of circular RNAs in spinal cord injury.

Spinal cord injury (SCI) is one kind of severe diseases with high mortality and morbidity worldwide, and lacks effective therapeutic interventions currently, which leads to not only permanent neurological impairments but also heavy social and economic burden. Recent studies have proved that circRNAs are highly expressed in neural tissues, regulating the neuronal and synaptic functions. What's more, significantly altered circRNAs expression profiles are closely associated with the pathophysiology of SCI. In this review, we summarize the current advance on the role of circRNAs in SCI, which may provide a better understanding of pathogenesis and therapeutic strategies of SCI. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: The Translational potential of this article is that A further understanding of circRNAs in the pathogenesis of SCI will promote the circRNA-based clinical applications.

Integrated proteomics and metabolomics analysis of transgenic and gene-stacked maize line seeds.

Unintended effects of genetically modified (GM) crops may pose safety issues. Omics techniques provide researchers with useful tools to assess such unintended effects. Proteomics and metabolomics analyses were performed for three GM maize varieties, 2A-7, CC-2, and 2A-7×CC-2 stacked transgenic maize, and the corresponding non-GM parent Zheng58.Proteomics revealed 120, 271 and 135 maize differentially expressed proteins (DEPs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most DEPs participated in metabolic pathways and the biosynthesis of secondary metabolite. Metabolomics revealed 179, 135 and 131 differentially accumulated metabolites (DAMs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Based on KEGG enrichment analysis, most DAMs are involved in the biosynthesis of secondary metabolite and metabolic pathways. According to integrated proteomics and metabolomics analysis, the introduction of exogenous EPSPS did not affect the expression levels of six other enzymes or the abundance of seven metabolites involved in the shikimic acid pathway in CC-2 and 2A-7×CC-2 seeds. Six co-DEPs annotated by integrated proteomics and metabolomics pathway analysis were further analyzed by qRT-PCR.This study successfully employed integrated proteomic and metabolomic technology to assess unintended changes in maize varieties. The results suggest that GM and gene stacking do not cause significantly unintended effects.

A multiplex and regenerable surface plasmon resonance (MR-SPR) biosensor for DNA detection of genetically modified organisms.

The continuous advancement of analytical technology has provided methods with increasing sensitivity and precision to detect genetically modified organisms (GMOs). Novel analytical strategy-based detection methods are alternatives to conventional polymerase chain reaction (PCR)-mediated assays, which are still the gold standard in this field. However, PCR primers and probes cannot be reused, which makes the technique uneconomical. Surface plasmon resonance (SPR) is an optical and label-free technique for studying ligand-analyte interactions, especially for DNA hybridization, and several SPR biosensors have been described for the detection of nucleic acids. Here, a multiplexed, regenerable and real-time SPR biosensor for the detection of GMOs is described. A biosensor was constructed for qualitative detection of T-nos, CaMV35S and cry1A and had good specificity and sensitivity. The limit of detection (LOD) of this biosensor was 0.1 nM without any signal amplification. Furthermore, our biosensor could be stably regenerated more than 100 times over at least 20 days and showed good reproducibility. This nucleic acid SPR biosensor has potential for application in other types of biological detection.

Synthesis of Cu2O-Modified Reduced Graphene Oxide for NO2 Sensors.

Nowadays, metal oxide semiconductors (MOS)-reduced graphene oxide (rGO) nanocomposites have attracted significant research attention for gas sensing applications. Herein, a novel composite material is synthesized by combining two p-type semiconductors, i.e., Cu2O and rGO, and a p-p-type gas sensor is assembled for NO2 detection. Briefly, polypyrrole-coated cuprous oxide nanowires (PPy/Cu2O) are prepared via hydrothermal method and combined with graphene oxide (GO). Then, the nanocomposite (rGO/PPy/Cu2O) is obtained by using high-temperature thermal reduction under Ar atmosphere. The results reveal that the as-prepared rGO/PPy/Cu2O nanocomposite exhibits a maximum NO2 response of 42.5% and is capable of detecting NO2 at a low concentration of 200 ppb. Overall, the as-prepared rGO/PPy/Cu2O nanocomposite demonstrates excellent sensitivity, reversibility, repeatability, and selectivity for NO2 sensing applications.

Preoperative Prediction of Ki-67 Status in Breast Cancer with Multiparametric MRI Using Transfer Learning.

RATIONALE AND OBJECTIVES: Ki-67 is one of the most important biomarkers of breast cancer traditionally measured invasively via immunohistochemistry. In this study, deep learning based radiomics models were established for preoperative prediction of Ki-67 status using multiparametric magnetic resonance imaging (mp-MRI). MATERIALS AND METHODS: Total of 328 eligible patients were retrospectively reviewed [training dataset (n = 230) and a temporal validation dataset (n = 98)]. Deep learning imaging features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast enhanced T1-weighted imaging (T1+C). Transfer learning techniques constructed four feature sets based on the individual three MR sequences and their combination (i.e., mp-MRI). Multilayer perceptron classifiers were trained for final prediction of Ki-67 status. Mann-Whitney U test compared the predictive performance of individual models. RESULTS: The area under curve (AUC) of models based on T2WI,T1+C,DWI and mp-MRI were 0.727, 0.873, 0.674, and 0.888 in the training dataset, respectively, and 0.706, 0.829, 0.643, and 0.875 in the validation dataset, respectively. The predictive performance of mp-MRI classification model in the AUC value was significantly better than that of the individual sequence model (all p< 0.01). CONCLUSION: In clinical practice, a noninvasive approach to improve the performance of radiomics in preoperative prediction of Ki-67 status can be provided by extracting breast cancer specific structural and functional features from mp-MRI images obtained from conventional scanning sequences using the advanced deep learning methods. This could further personalize medicine and computer aided diagnosis.

Proteomic analysis of the seeds of transgenic rice lines and the corresponding nongenetically modified isogenic variety.

BACKGROUND: An isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analysis was employed to study the seeds of two genetically modified (GM) rice lines, T2A-1 and T1C-19, and their nontransgenic isogenic variety, MH63, to investigate the unintended effects of genetic modification. RESULTS: A total of 3398 proteins were quantitatively identified. Seventy-seven differentially abundant proteins (DAPs) were identified in the T2A-1/MH63 comparison, and 70 and 7 of these DAPs were upregulated and downregulated, respectively. A pathway enrichment analysis showed that most of these DAPs participated in metabolic pathways and protein processing in endoplasmic reticulum and were ribosome components. Some 181 DAPs were identified from the T1C-19/MH63 comparison, and these included 115 upregulated proteins and 66 downregulated proteins. The subsequent pathway enrichment analysis showed that these DAPs mainly participated in protein processing in endoplasmic reticulum and carbon fixation in photosynthetic organisms and were ribosome components. None of these DAPs were identified as new unintended toxins or allergens, and only changes in abundance were detected. Fifty-four co-DAPs were identified in the seeds of the two GM rice lines, and protein-protein interaction analysis of these co-DAPs demonstrated that some interacting proteins were involved in protein processing in endoplasmic reticulum and metabolic pathways, whereas others were identified as ribosome components. Representative co-DAPs and proteins related to nutrients were analyzed using qRT-PCR to determine their transcriptional levels. CONCLUSIONS: The results suggested that the seed proteomic profiles of the two GM rice lines studied were not substantially altered from those of their natural isogenic control. © 2020 Society of Chemical Industry.

Circular RNA derived from TIMP2 functions as a competitive endogenous RNA and regulates intervertebral disc degeneration by targeting miR­185­5p and matrix metalloproteinase 2.

Intervertebral disc degeneration (IDD) is an important cause of lower back pain, although the underlying mechanisms remain poorly understood. The present study aimed to examine the role of a circular RNA derived from tissue inhibitor of metallopeptidases 2 (circ­TIMP2) in degenerative nucleus pulposus (NP) tissues, and to validate its function in cultured human NP cells. Overexpression of miR­185­5p in NP cells markedly inhibited the enhanced extracellular matrix (ECM) catabolism induced by tumor necrosis factor­α (TNF­α) and interleukin­1ß (IL­1ß) treatment. Bioinformatics analysis demonstrated that matrix metalloproteinase 2 (MMP2) was a potential target of miR­185­5p. MMP2 protein expression levels were increased following treatment with TNF­α and IL­1ß in NP cells compared with those in untreated cells, and this effect was attenuated by transfection with miR­185­5p. Compared with normal NP tissues, IDD samples exhibited higher circ­TIMP2 expression levels. In addition, overexpression of circ­TIMP2 promoted ECM catabolism and suppressed ECM anabolism. Furthermore, circ­TIMP2 sequestered miR­185­5p, which may potentially upregulate the target genes associated with ECM degradation. In conclusion, the results of the present study revealed that circ­TIMP2 promoted TNF­α­ and IL­1ß­induced NP cell imbalance between ECM anabolism and catabolism via miR­185­5p­MMP2 signaling. These findings provide a potential therapeutic option for the treatment of IDD.

Identification of a circRNA-miRNA-mRNA network to explore the effects of circRNAs on pathogenesis and treatment of spinal cord injury.

AIMS: Many studies have demonstrated that circRNAs are closely associated with human diseases. Nonetheless, the potential mechanism by which circRNAs impacts spinal cord injury (SCI) is not fully understood. The aim of this study was to explore the regulatory roles of circRNAs in SCI. MAIN METHODS: The sequencing data of circRNA, miRNA and mRNA were obtained from Gene Expression Omnibus (GEO) datasets. Candidates were identified to construct a circRNA-miRNA-mRNA network based on circRNA-miRNA interactions and miRNA-mRNA interactions. Protein-protein interactions (PPI) analysis was performed to determine hub genes, and a connectivity map (CMap) analysis was applied to determine potential therapeutic targets for SCI. KEY FINDINGS: A total of 1656 differentially expressed circRNAs (DEcircRNAs), 71 differentially expressed miRNAs (DEmiRNAs) and 2782 differentially expressed mRNAs (DEmRNAs) were identified. We integrated four overlapped circRNAs, six miRNAs and 101 target mRNAs into a circRNA-miRNA-mRNA network. We next identified two hub genes (DDIT4, EZR) based on the PPI network and identified five circRNA-miRNA-hub gene regulatory axes. In addition, we discovered three chemicals (tanespimycin, fulvestrant, carbamazepine) as potential treatment options for SCI. SIGNIFICANCE: Our study suggests a regulatory role for circRNAs in the pathogenesis and treatment of SCI from the view of a competitive endogenous RNA (ceRNA) network.

Evaluation of human epidermal growth factor receptor 2 status of breast cancer using preoperative multidetector computed tomography with deep learning and handcrafted radiomics features.

OBJECTIVE: To evaluate the human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer using multidetector computed tomography (MDCT)-based handcrafted and deep radiomics features. METHODS: This retrospective study enrolled 339 female patients (primary cohort, n=177; validation cohort, n=162) with pathologically confirmed invasive breast cancer. Handcrafted and deep radiomics features were extracted from the MDCT images during the arterial phase. After the feature selection procedures, handcrafted and deep radiomics signatures and the combined model were built using multivariate logistic regression analysis. Performance was assessed by measures of discrimination, calibration, and clinical usefulness in the primary cohort and validated in the validation cohort. RESULTS: The handcrafted radiomics signature had a discriminative ability with a C-index of 0.739 [95% confidence interval (95% CI): 0.661-0.818] in the primary cohort and 0.695 (95% CI: 0.609-0.781) in the validation cohort. The deep radiomics signature also had a discriminative ability with a C-index of 0.760 (95% CI: 0.690-0.831) in the primary cohort and 0.777 (95% CI: 0.696-0.857) in the validation cohort. The combined model, which incorporated both the handcrafted and deep radiomics signatures, showed good discriminative ability with a C-index of 0.829 (95% CI: 0.767-0.890) in the primary cohort and 0.809 (95% CI: 0.740-0.879) in the validation cohort. CONCLUSIONS: Handcrafted and deep radiomics features from MDCT images were associated with HER2 status in patients with breast cancer. Thus, these features could provide complementary aid for the radiological evaluation of HER2 status in breast cancer.

Development of a sensitive monoclonal antibody-based sandwich ELISA to detect Vip3Aa in genetically modified crops.

OBJECTIVES: To develop a sensitive monoclonal antibody-based sandwich enzyme-linked immunosorbent assay (ELISA) to detect Vip3Aa in genetically modified (GM) crops and their products. RESULTS: Vegetative insecticidal proteins (Vips) are secreted by Bacillus thuringiensis (Bt) and are known to be toxic to Lepidoptera species. Vip3Aa family proteins, Vip3Aa19 and Vip3Aa20, were successfully applied in GM crops to confer an effective and persistent insecticidal resistance. A sensitive monoclonal antibody-based sandwich ELISA was developed to detect Vip3Aa in GM crops and their products. Two monoclonal antibodies were raised against the overexpressed and purified His-Vip3Aa20, were purified from mouse ascites and characterized. A sandwich ELISA method was developed using the 2G3-1D7 monoclonal antibody for capture and the biotin-labeled 1F9-1F5 monoclonal antibody for detection of Vip3Aa20. The linear detection range of the method was found to be approximately 31.25-500 pg/ml, with a sensitivity of 10.24 pg/ml. CONCLUSIONS: The established ELISA was effective for detecting Vip3Aa family proteins other than Vip3Aa8, and was successfully applied in the detection of Vip3Aa20 and Vip3Aa19 expressed in transgenic maize and cotton.

Metformin limits osteoarthritis development and progression through activation of AMPK signalling.

OBJECTIVES: In this study, we aim to determine the effect of metformin on osteoarthritis (OA) development and progression. METHODS: Destabilisation of the medial meniscus (DMM) surgery was performed in 10-week-old wild type and AMP-activated protein kinase (AMPK)α1 knockout (KO) mice. Metformin (4 mg/day in drinking water) was given, commencing either 2 weeks before or 2 weeks after DMM surgery. Mice were sacrificed 6 and 12 weeks after DMM surgery. OA phenotype was analysed by micro-computerised tomography (µCT), histology and pain-related behaviour tests. AMPKα1 (catalytic alpha subunit of AMPK) expression was examined by immunohistochemistry and immunofluorescence analyses. The OA phenotype was also determined by µCT and MRI in non-human primates. RESULTS: Metformin upregulated phosphorylated and total AMPK expression in articular cartilage tissue. Mild and more severe cartilage degeneration was observed at 6 and 12 weeks after DMM surgery, evidenced by markedly increased Osteoarthritis Research Society International scores, as well as reduced cartilage areas. The administration of metformin, commencing either before or after DMM surgery, caused significant reduction in cartilage degradation. Prominent synovial hyperplasia and osteophyte formation were observed at both 6 and 12 weeks after DMM surgery; these were significantly inhibited by treatment with metformin either before or after DMM surgery. The protective effects of metformin on OA development were not observed in AMPKα1 KO mice, suggesting that the chondroprotective effect of metformin is mediated by AMPK signalling. In addition, we demonstrated that treatment with metformin could also protect from OA progression in a partial medial meniscectomy animal model in non-human primates. CONCLUSIONS: The present study suggests that metformin, administered shortly after joint injury, can limit OA development and progression in injury-induced OA animal models.

Deep Learning Signature Based on Staging CT for Preoperative Prediction of Sentinel Lymph Node Metastasis in Breast Cancer.

RATIONALE AND OBJECTIVES: To evaluate the noninvasive predictive performance of deep learning features based on staging CT for sentinel lymph node (SLN) metastasis of breast cancer. MATERIALS AND METHODS: A total of 348 breast cancer patients were enrolled in this study, with their SLN metastases pathologically confirmed. All patients received contrast-enhanced CT preoperative examinations and CT images were segmented and analyzed to extract deep features. After the feature selection, deep learning signature was built with the selected key features. The performance of the deep learning signatures was assessed with respect to discrimination, calibration, and clinical usefulness in the primary cohort (184 patients from January 2016 to March 2017) and then validated in the independent validation cohort (164 patients from April 2017 to December 2018). RESULTS: Ten deep learning features were automatically selected in the primary cohort to establish the deep learning signature of SLN metastasis. The deep learning signature shows favorable discriminative ability with an area under curve of 0.801 (95% confidence interval: 0.736-0.867) in primary cohort and 0.817 (95% confidence interval: 0.751-0.884) in validation cohort. To further distinguish the number of metastatic SLNs (1-2 or more than two metastatic SLN), another deep learning signature was constructed and also showed moderate performance (area under curve 0.770). CONCLUSION: We developed the deep learning signatures for preoperative prediction of SLN metastasis status and numbers (1-2 or more than two metastatic SLN) in patients with breast cancer. The deep learning signature may potentially provide a noninvasive approach to assist clinicians in predicting SLN metastasis in patients with breast cancer.

iTRAQ-based quantitative proteomic analysis of two transgenic soybean lines and the corresponding non-genetically modified isogenic variety.

To investigate the unintended effects of genetically modified (GM) crops, an isobaric tags for relative and absolute quantitation (iTRAQ)-based comparative proteomic analysis was performed with seed cotyledons of two GM soybean lines, MON87705 and MON87701×MON89788, and the corresponding non-transgenic isogenic variety A3525. Thirty-five differentially abundant proteins (DAPs) were identified in MON87705/A3525, 27 of which were upregulated and 8 downregulated. Thirty-eight DAPs were identified from the MON87701×MON89788/A3525 sample, including 29 upregulated proteins and 9 downregulated proteins. Pathway analysis showed that most of these DAPs participate in protein processing in endoplasmic reticulum and in metabolic pathways. Protein-protein interaction analysis of these DAPs demonstrated that the main interacting proteins are associated with post-translational modification, protein turnover, chaperones and signal transduction mechanisms. Nevertheless, these DAPs were not identified as new unintended toxins or allergens and only showed changes in abundance. All these results suggest that the seed cotyledon proteomic profiles of the two GM soybean lines studied were not dramatically altered compared with that of their natural isogenic control.