Transient receptor potential mucolipin (TRPML) protein in flies plays a pivotal role in Ca2+ ions release, resulting in membrane trafficking, autophagy and ion homeostasis. However, to date, the characterization of TRPML in agricultural pests remains unknown. Here, we firstly reported the TRPML of a destructive pest of gramineous crops, Laodelphax striatellus. The L. striatellus TRPML (Ls-TRPML) has a 1818 bp open reading frame, encoding 605 amino acid. TRPML in agricultural pests is evolutionarily conserved, and the expression of Ls-TRPML is predominately higher in the ovary than in other organs of L. striatellus at the transcript and protein level. The Bac–Bac system showed that Ls-TRPML localized in the plasma membrane, nuclear membrane and nucleus and co-localized with lysosome in Spodoptera frugiperda cells. The immunofluorescence microscopy analysis showed that Ls-TRPML localized in the cytoplasm and around the nuclei of the intestine cells or ovary follicular cells of L. striatellus. The results from the lipid-binding assay revealed that Ls-TRPML strongly bound to phosphatidylinositol-3,5-bisphosphate, as compared with other phosphoinositides. Overall, our results helped is identify and characterize the TRPML protein of L. striatellus, shedding light on the function of TRPML in multiple cellular processes in agricultural pests.

The studied reservoir is represented by complex clastic deposits located in northwest of China. From the core description, there are 15 rock types and five oil bearing gradesvarying from no oily to oil immersion. So the reservoir is very heterogeneous and it is very challenging to identify the best zones for fracturing. To mitigate this challenge, it is of utmost important to understand and evaluate the relationship between reservoir heterogeneity and oil saturation level to find out the best reservoir rock type for further completion work. At the beginning of the work, detailed analysis have been done and a very strong relationship is observed between core grain sizes and oil bearing grade. In the current study area, high resolution borehole image logs are acquired but core data is available only for short intervals. Consequently, borehole image based methodology has been developed to characterize relationship among grain size, sorting and oil saturation. Also, Reservoir Rock Type (RRT) has been computed using integrated result from shale content, effective porosity and image derived advance outputs to identify sweet zone for hydraulic fracturing. The study shows very interesting results from integrated image analysis within sandy interval, with decreasing grain size the oil bearing grade is increasing and the oil bearing grade is maximum in the medium grain sized pebbly zone. Four main reservoir rock type has been computed from clay content, effective porosity curves and image derived sorting index data. RRT result shows very good relationship with the oil bearing grade. Good RRT is dominated with oil immersion, Good to Moderate RRT is dominated with oil spot, Moderate RRT is dominated with oil stains and Poor RRT is dominated with no oily. This RRT computation method from image derived high resolution data provides very valuable information for proper evaluation of this complex reservoir and sweet spot identification. This workflow has been established as a standard workflow to be applied in other parts of the study area. Also, this work can be a very good example to follow in similar complex clastic reservoirs from any part of the world.