Comparative proximity biotinylation implicates the small GTPase RAB18 in sterol mobilization and biosynthesis

Loss of functional RAB18 causes the autosomal recessive condition Warburg Micro syndrome. To better understand this disease, we used proximity biotinylation to generate an inventory of potential RAB18 effectors. A restricted set of 28 RAB18 interactions were dependent on the binary RAB3GAP1–RAB3GAP2 RAB18–guanine nucleotide exchange factor complex. Twelve of these 28 interactions are supported by prior reports, and we have directly validated novel interactions with SEC22A, TMCO4, and INPP5B. Consistent with a role for RAB18 in regulating membrane contact sites, interactors included groups of microtubule/membrane-remodeling proteins, membrane-tethering and docking proteins, and lipid-modifying/transporting proteins. Two of the putative interactors, EBP and OSBPL2/ORP2, have sterol substrates. EBP is a Δ8-Δ7 sterol isomerase, and ORP2 is a lipid transport protein. This prompted us to investigate a role for RAB18 in cholesterol biosynthesis. We found that the cholesterol precursor and EBP-product lathosterol accumulates in both RAB18-null HeLa cells and RAB3GAP1-null fibroblasts derived from an affected individual. Furthermore, de novo cholesterol biosynthesis is impaired in cells in which RAB18 is absent or dysregulated or in which ORP2 expression is disrupted. Our data demonstrate that guanine nucleotide exchange factor–dependent Rab interactions are highly amenable to interrogation by proximity biotinylation and may suggest that Micro syndrome is a cholesterol biosynthesis disorder

Simulation and prediction of soybean growth and development under field conditions

Thermal unit is often used as the main driving force in crop simulation models. However, simulation models built with this approach often do not lead to a satisfactory accuracy of prediction when it regards to soybean; mainly due to strong photoperiod influence on soybean and complicated interactions between photoperiod and temperature. This study tried to simulate and predict soybean phenological growth using calendar-day based approach. Field experiments were conducted at the Delta Research and Extension Center, Stoneville, Mississippi, USA. Five year (1998-2002) field data were used with 24 sowing dates from maturity groups (MG) III to MG VI soybean varieties. Three methods, artificial neural network (ANN), k- nearest neighbor (kNN) and regression were used to construct prediction models. Vegetative and reproductive growth stages were modeled separately. Results indicated that calendar-based prediction model in soybean growth calculation is a feasible approach. All three methods achieved the acceptable prediction accuracy. On average, prediction errors of ANN, kNN and Regression methods were 3.6, 2.8 and 3.6 days for vegetative stage and 4.4, 3.5 and 4.7 days for reproductive stages, respectively

Draft genome sequence of agrobacterium deltaense strain CNPSo 3391, isolated from a soybean nodule in Mozambique.

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Naturalised populations of mesorhizobia in chickpea (Cicer arietinum L.) cropping soils: effects on nodule occupancy and productivity of commercial chickpea

Background and aims: Chickpea rhizobia did not occur naturally in Australian cropping soils, necessitating inoculation at sowing. Now, after more than 30 years of chickpea cultivation using a single inoculant strain, CC1192, it is likely that chickpea rhizobia are established in 1.0-1.5 Mha cropping land. The aims of this study were to examine effects of the naturalised chickpea rhizobia on nodulation and productivity (total crop N, crop N fixed and grain yield) of commercial chickpea. Methods: Soil was sampled from 26 fields to estimate chickpea rhizobial numbers, relate numbers to edaphic factors and years since previous chickpea crop, determine the proportions of CC1192 and novel strains using RAPD-PCR and subject a subset of novel strains from one site to 16S rRNA analysis. Nodules were harvested from 15 inoculated, commercial chickpea crops to determine occupancy by CC1192. The symbiotic effectiveness of a second subset of novel strains was assessed. Results: The mean number of rhizobia in the soils varied from log 0.08 to log 5.16 rhizobia g soil⁻¹ with population size positively correlated with soil moisture content and negatively correlated with salt concentration (ECe). RAPD-PCR analysis of 570 strains of chickpea rhizobia isolated from the soils indicated only 14 % with molecular fingerprints similar to CC1192. Occupancy by CC1192 of nodules harvested from commercial crops ranged 0-100 %, with an average of 53 %. Occupancy by CC1192 declined by an average 17 % with each log unit increase in numbers of novel chickpea rhizobia. Conclusions: We found no evidence that the novel mesorhizobia in the chickpea soils compromised N₂ fixation or productivity of commercial chickpea crops, even though individual strains had generally reduced symbiotic effectiveness relative to CC1192