Project description:Phosphorus (P) deficiency is a major limitation for legume crop production. Although overall adaptations of plant roots to P deficiency have been extensively studied, fragmentary information is available in regards to root nodule responses to P deficiency. In this study, genome wide transcriptome analysis was conducted using RNA-seq analysis to investigate molecular mechanisms underlying soybean (Glycine max) nodule adaptation to phosphate (Pi) starvation. Phosphorus deficiency significantly decreased soybean nodule growth and nitrogenase activity. Nodule Pi concentrations declined by 49% in response to P deficiency, but this was well below the 87% and 88% decreases observed in shoots and roots, respectively. Nodule transcript profiling revealed that a total of 2,055 genes exhibited differential expression patterns between Pi sufficient and deficient conditions. A set of DEGs appeared to be involved in maintaining Pi homeostasis in soybean nodules, including 8 Pi transporters (PTs), 8 proteins containing the SYG1/PHO81/XPR1 domain (SPXs), and 16 purple acid phosphatases (PAPs). The results suggest that a complex transcriptional regulatory network participates in soybean nodule adaption to Pi starvation, most notable a Pi signaling pathway specifically involved in maintaining Pi homeostasis in nodules.
Project description:In agroecosystems, a plant-usable form of nitrogen is mainly generated by legume-based biological nitrogen fixation, a process that requires phosphorus (P) as an essential nutrient. To investigate the physiological mechanism whereby phosphorus influences soybean nodule nitrogen fixation, soybean root nodules were exposed to four phosphate levels: 1 mg/L (P stress), 11 mg/L (P stress), 31 mg/L (Normal P), 61 mg/L (High P) then proteome analysis of nodules was conducted to identify phosphorus-associated proteome changes. We found that phosphorus stress-induced ribosomal protein structural changes were associated with altered key root nodule protein synthesis profiles. Importantly, up-regulated expression of peroxidase was observed as an important phosphorus stress-induced nitrogen fixation-associated adaptation that supported two nodule-associated activities: scavenging of reactive oxygen species (ROS) and cell wall growth. In addition, phosphorus transporter (PT) and purple acid phosphatase (PAPs) were up-regulated that regulated phosphorus transport and utilisation to maintain phosphorus balance and nitrogen fixation function in phosphorus-stressed root nodules.
Project description:The TRAP-seq process is dependent on the expression of a cell layer-specific His-FLAG-tagged ribosomal protein L18 (HF-GmRPL 18), which allows for the immunoprecipitation of ribosomes with their corresponding mRNA to produce tissue-specific translatomes (Zanetti et al., 2005; Castro‐Guerrero et al., 2016).To capture events occurring in the cortex during the early stages of infection and initial cortical cell divisions, we inoculated plants and performed a time-course collection of root samples at 72- and 96-hour post inoculation (hpi) followed by TRAP-seq. Immunoblot analysis indicated that an adequate amount of protein was present for immunoprecipitation. To study rhizobial-induced transcriptional changes in the cortex during early nodule development, we identified a soybean promoter (Glyma.18g53890, Figure 1B) expressed exclusively in the cortex cells using LCM (Kerk et al., 2003; Casson et al., 2008) followed by transcriptional analysis. The cortex-specific promoter was used to drive the expression of GmRPL18 in soybean hairy roots. To capture events occurring in the cortex during the early stages of infection and initial cortical cell divisions, we inoculated plants and performed a time-course collection of root samples at 72- and 96-hour post inoculation (hpi) followed by TRAP-seq. Immunoblot analysis indicated that an adequate amount of protein was present for immunoprecipitation (Figure 1C). Taken together, time-course cortex-specific TRAP-seq was established for studying of early nodule development in soybean.
Project description:Common bean (Phaseolus vulgaris) and soybean (Glycine max) both belong to the Phaseoleae tribe and share significant coding sequence homology. To evaluate the utility of the soybean GeneChip for transcript profiling of common bean, we hybridized cRNAs purified from nodule, leaf, and root of common bean and soybean in triplicate to the soybean GeneChip. Initial data analysis showed a decreased sensitivity and specificity in common bean cross-species hybridization (CSH) GeneChip data compared to that of soybean. We employed a method that masked putative probes targeting inter-species variable (ISV) regions between common bean and soybean. A masking signal intensity threshold was selected that optimized both sensitivity and specificity. After masking for ISV regions, the number of differentially-expressed genes identified in common bean was increased by about 2.8-fold reflecting increased sensitivity. Quantitative RT-PCR analysis of a total of 20 randomly selected genes and purine-ureides pathway genes demonstrated an increased specificity after masking for ISV regions. We also evaluated masked probe frequency per probe set to gain insight into the sequence divergence pattern between common bean and soybean. The results from this study suggested that transcript profiling in common bean can be done using the soybean GeneChip. However, a significant decrease in sensitivity and specificity can be expected. Problems associated with CSH GeneChip data can be mitigated by masking probes targeting ISV regions. In addition to transcript profiling CSH of the GeneChip in combination with masking probes in the ISV regions can be used for comparative ecological and/or evolutionary genomics studies. We hybridized cRNA purified from nodule, leaf, and root of common bean and soybean in, triplicate, to the soybean GeneChip (18 GeneChip hybridizations = 2 species x 3 organs x 3 replicates).
Project description:Legumes perform symbiotic nitrogen fixation through rhizobial bacteroids housed in specialised root nodules. The biochemical process is energy‐intensive and consumes a huge carbon source to generate sufficient reducing power. To maintain the symbiosis, malate is supplied by legume nodules to bacteroids as their major carbon and energy source in return for ammonium ions and nitrogenous compounds. To sustain the carbon supply to bacteroids, nodule cells undergo drastic reorganisation of carbon metabolism. Here, a comprehensive quantitative comparison of the mitochondrial proteomes between root nodules and uninoculated roots was performed using data‐independent acquisition proteomics, revealing the modulations in nodule mitochondrial proteins and pathways in response to carbon reallocation. Corroborated our findings with that from the literature, we believe nodules preferably allocate cytosolic phosphoenolpyruvates towards malate synthesis in lieu of pyruvate synthesis, and nodule mitochondria prefer malate over pyruvate as the primary source of NADH for ATP production. Moreover, the differential regulation of respiratory chain‐associated proteins suggests that nodule mitochondria could enhance the efficiencies of complexes I and IV for ATP synthesis. This study highlighted a quantitative proteomic view of the mitochondrial adaptation in soybean nodules.
Project description:Common bean (Phaseolus vulgaris) and soybean (Glycine max) both belong to the Phaseoleae tribe and share significant coding sequence homology. To evaluate the utility of the soybean GeneChip for transcript profiling of common bean, we hybridized cRNAs purified from nodule, leaf, and root of common bean and soybean in triplicate to the soybean GeneChip. Initial data analysis showed a decreased sensitivity and specificity in common bean cross-species hybridization (CSH) GeneChip data compared to that of soybean. We employed a method that masked putative probes targeting inter-species variable (ISV) regions between common bean and soybean. A masking signal intensity threshold was selected that optimized both sensitivity and specificity. After masking for ISV regions, the number of differentially-expressed genes identified in common bean was increased by about 2.8-fold reflecting increased sensitivity. Quantitative RT-PCR analysis of a total of 20 randomly selected genes and purine-ureides pathway genes demonstrated an increased specificity after masking for ISV regions. We also evaluated masked probe frequency per probe set to gain insight into the sequence divergence pattern between common bean and soybean. The results from this study suggested that transcript profiling in common bean can be done using the soybean GeneChip. However, a significant decrease in sensitivity and specificity can be expected. Problems associated with CSH GeneChip data can be mitigated by masking probes targeting ISV regions. In addition to transcript profiling CSH of the GeneChip in combination with masking probes in the ISV regions can be used for comparative ecological and/or evolutionary genomics studies.
2010-03-01 | GSE18822 | GEO
Project description:Soybean root nodule and rhizosphere microbiome
Project description:Global bottom-up proteomics analysis of proteins purified from soybean root nodules infected with either WT or nifH- mutant Bradyrhizobium japonicum. Nine glycoproteins containing Lewis-a N-glycans, with 3 distinct Lewis-a epitopes (Hex:5 HexNAc:4 dHex:3 Pent:1, Hex:4 HexNAc:4 dHex:2 Pent:1, and Hex:4 HexNAc:3 dHex:2 Pent:1) were observed. Proteins purified from WT and nifH- infected soybean root nodules (five biological replicates each) were reduced using dithiothreitol, alkylated with iodoacetamide and trypsin digested followed by C18 SPE clean-up and LC-MS/MS analysis. Raw data files were processed using FragPipe v17.1, then output files 'combined_modified_peptide.tsv' and 'combined_protein.tsv' were used to identify glycopeptides and for global protein quantitation. These files, along with Excel files containing global quantitation analysis files for soybean nodule (Glycine max) and bacterial (Bradyrhizobium), are available in directory 'Quantification/MSFragger_results'. Glycopeptide data were also processed with PMI Byonic, and Excel file results are available in directory 'Quantification/PMI_Byonic_results'.