CD4(+) T-cell depletion is a characteristic of human immunodeficiency virus type 1 (HIV-1) infection. In this study, modulation of mRNA expression of 6800 genes was monitored simultaneously at eight time points in a CD4(+) T-cell line (CEM-GFP) during HIV infection. The responses to infection included: (1) >30% decrease at 72 h after infection in overall host-cell production of monitored mRNA synthesis, with the replacement of host-cell mRNA by viral mRNA, (2) suppression of the expression of selected mitochondrial and DNA repair gene transcripts, (3) increased expression of the proapoptotic gene and its gene p53-induced product Bax, and (4) activation of caspases 2, 3, and 9. The intense HIV-1 transcription resulted in the repression of much cellular RNA expression and was associated with the induction of apoptosis of infected cells but not bystander cells. This choreographed host gene response indicated that the subversion of the cell transcriptional machinery for the purpose of HIV-1 replication is akin to genotoxic stress and represents a major factor leading to HIV-induced apoptosis.
We describe a data mining method that uses indexing terms ('keywords') from the published literature linked to specific genes to present a view of the conceptual similarity of genes within a cluster or group of interest. The method takes advantage of the hierarchical nature of Medical Subject Headings used to index citations in the MEDLINE database, and the registry numbers applied to enzymes.
Biomedical text mining and other automated techniques are beginning to achieve performance which suggests that they could be applied to aid database curators. However, few studies have evaluated how these systems might work in practice. In this article we focus on the problem of annotating mutations in Protein Data Bank (PDB) entries, and evaluate the relationship between performance of two automated techniques, a text-mining-based approach (MutationFinder) and an alignment-based approach, in intrinsic versus extrinsic evaluations. We find that high performance on gold standard data (an intrinsic evaluation) does not necessarily translate to high performance for database annotation (an extrinsic evaluation). We show that this is in part a result of lack of access to the full text of journal articles, which appears to be critical for comprehensive database annotation by text mining. Additionally, we evaluate the accuracy and completeness of manually annotated mutation data in the PDB, and find that it is far from perfect. We conclude that currently the most cost-effective and reliable approach for database annotation might incorporate manual and automatic annotation methods.
Reprogramming of the somatic state to pluripotency can be induced by a defined set of transcription factors including Oct3/4, Sox2, Klf4 and c-Myc [1]. These induced pluripotent stem cells (iPSCs) hold great promise in human therapy and disease modeling. However, tumor suppressive activities of p53, which are necessary to prevent persistence of DNA damage in mammalian cells, have proven a serious impediment to formation of iPSCs [2]. We examined the requirement for downstream p53 activities in suppressing efficiency of reprogramming as well as preventing persistence of DNA damage into the early iPSCs. We discovered that the majority of the p53 activation occurred through early reprogramming-induced DNA damage with the activated expression of the apoptotic inducer Puma and the cell cycle inhibitor p21. While Puma-deficiency increases reprogramming efficiency only in the absence of c-Myc, double deficiency of Puma and p21 has achieved a level of efficiency that exceeded that of p53 deficiency alone. We further demonstrated that, in both the presence and absence of p21, Puma-deficiency was able to prevent any increase in persistent DNA damage in early iPSCs. This may be due to a compensatory cellular senescent-response to reprogramming-induced DNA damage in pre-iPSCs. Therefore, our findings provide a potentially safe approach to enhance iPSC derivation by silencing Puma and p21 without compromising genomic integrity.
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