Escherichia coli is a model laboratory bacterium, a species that is widely distributed in the environment, as well as a mutualist and pathogen in its human hosts. As such, E. coli represents an attractive organism to study how environment impacts microbial genome structure and function. Uropathogenic E. coli (UPEC) must adapt to life in several microbial communities in the human body, and has a complex life cycle in the bladder when it causes acute or recurrent urinary tract infection (UTI). Several studies designed to identify virulence factors have focused on genes that are uniquely represented in UPEC strains, whereas the role of genes that are common to all E. coli has received much less attention. Here we describe the complete 5,065,741-bp genome sequence of a UPEC strain recovered from a patient with an acute bladder infection and compare it with six other finished E. coli genome sequences. We searched 3,470 ortholog sets for genes that are under positive selection only in UPEC strains. Our maximum likelihood-based analysis yielded 29 genes involved in various aspects of cell surface structure, DNA metabolism, nutrient acquisition, and UTI. These results were validated by resequencing a subset of the 29 genes in a panel of 50 urinary, periurethral, and rectal E. coli isolates from patients with UTI. These studies outline a computational approach that may be broadly applicable for studying strain-specific adaptation and pathogenesis in other bacteria.uropathogenic Escherichia coli ͉ ecogenomics

Salmonella enterica serovars often have a broad host range, and some cause both gastrointestinal and systemic disease. But the serovars Paratyphi A and Typhi are restricted to humans and cause only systemic disease. It has been estimated that Typhi arose in the last few thousand years. The sequence and microarray analysis of the Paratyphi A genome indicates that it is similar to the Typhi genome but suggests that it has a more recent evolutionary origin. Both genomes have independently accumulated many pseudogenes among their approximately 4,400 protein coding sequences: 173 in Paratyphi A and approximately 210 in Typhi. The recent convergence of these two similar genomes on a similar phenotype is subtly reflected in their genotypes: only 30 genes are degraded in both serovars. Nevertheless, these 30 genes include three known to be important in gastroenteritis, which does not occur in these serovars, and four for Salmonella-translocated effectors, which are normally secreted into host cells to subvert host functions. Loss of function also occurs by mutation in different genes in the same pathway (e.g., in chemotaxis and in the production of fimbriae).

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Multiple myeloma (MM) is an incurable, B-cell malignancy, characterized by the clonal proliferation and accumulation of malignant plasma cells in bone marrow. Despite recent advances in understanding of genomic aberrations, a comprehensive catalogue of clinically actionable mutations in MM is just beginning to emerge. The tyrosine kinase (TK) and RAS oncogenes, which encode important regulators of various signaling pathways, are among the most frequently altered gene families in cancer. To clarify the role of TK and RAS genes in pathogenesis of MM, we performed a systematic, targeted screening of mutations on prioritized RAS and TK genes, in CD138 sorted bone marrow specimens from 42 untreated patients. We identified a total of 24 mutations in KRAS, PIK3CA, INSR, LTK and MERTK genes. In particular, seven novel mutations in addition to known KRAS mutations were observed. Prediction analysis tools, PolyPhen and SIFT were used to assess the functional significance of these novel mutations. Our analysis predicted that these mutations may have a deleterious effect, resulting in functional alteration of proteins involved in the pathogenesis of myeloma. While further investigation is needed to determine the functional consequences of these proteins, mutational testing of the RAS and TK genes in larger myeloma cohorts might be also useful to establish the recurrent nature of these mutations.

The sequence of any genome becomes most useful for biological experimentation when a complete and accurate gene set is available. Gene prediction programs offer an efficient way to generate an automated gene set. Manual annotation, when performed by experienced annotators, is more accurate and complete than automated annotation. However, it is a laborious and expensive process, and by its nature, introduces a degree of variability not found with automated annotation. EAnnot (Electronic Annotation) is a program originally developed for manually annotating the human genome. It combines the latest bioinformatics tools to extract and analyze a wide range of publicly available data in order to achieve fast and reliable automatic gene prediction and annotation. EAnnot builds gene models based on mRNA, EST, and protein alignments to genomic sequence, attaches supporting evidence to the corresponding genes, identifies pseudogenes, and locates poly(A) sites and signals. Here, we compare manual annotation of human chromosome 6 with annotation performed by EAnnot in order to assess the latter's accuracy. EAnnot can readily be applied to manual annotation of other eukaryotic genomes and can be used to rapidly obtain an automated gene set