SummaryHigh-throughput approaches for gene cloning and expression require the development of new, nonstandard tools for use by molecular biologists and biochemists. We have developed and implemented a series of methods that enable the production of expression constructs in 96-well plate format. A screening process is described that facilitates the identification of bacterial clones expressing soluble protein. Application of the solubility screen then provides a plate map that identifies the location of wells containing clones producing soluble proteins. A series of semi-automated methods can then be applied for validation of solubility and production of freezer stocks for the protein production group. This process provides an 80% success rate for the identification of clones producing soluble protein and results in a significant decrease in the level of effort required for the labor-intensive components of validation and preparation of freezer stocks. This process is customized for large-scale structural genomics programs that rely on the production of large amounts of soluble proteins for crystallization trials.
Background Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. Methodology We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derived from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. Conclusions 69% of expressed mycorrhizal JGI "best" gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.
IMP dehydrogenase, a regulatory enzyme of guanine nucleotide biosynthesis, may play a role in cell proliferation and malignancy. To assess this possibility, we examined IMP dehydrogenase expression in a series of human solid tumor tissues and tumor cell lines in comparison with their normal counterparts. Increased IMP dehydrogenase gene expression was observed in brain tumors relative to normal brain tissue and in sarcoma cells relative to normal fibroblasts. Similarly, in several B- and T-lymphoid leukemia cell lines, elevated levels of IMP dehydrogenase mRNA and cellular enzyme were observed in comparison with the levels in peripheral blood lymphocytes. These results are consistent with an association between increased IMP dehydrogenase expression and either enhanced cell proliferation or malignant transformation.
