A probabilistic method for identifying start codons in bacterial genomes.

As the pace of genome sequencing has accelerated, the need for highly accurate gene prediction systems has grown. Computational systems for identifying genes in prokaryotic genomes have sensitivities of 98-99% or higher (Delcher et al., Nucleic Acids Res., 27, 4636-4641, 1999). These accuracy figures are calculated by comparing the locations of verified stop codons to the predictions. Determining the accuracy of start codon prediction is more problematic, however, due to the relatively small number of start sites that have been confirmed by independent, non-computational methods. Nonetheless, the accuracy of gene finders at predicting the exact gene boundaries at both the 5' and 3' ends of genes is of critical importance for microbial genome annotation, especially in light of the important signaling information that is sometimes found on the 5' end of a protein coding region. In this paper we propose a probabilistic method to improve the accuracy of gene identification systems at finding precise translation start sites. The new system, RBSfinder, is tested on a validated set of genes from Escherichia coli, for which it improves the accuracy of start site locations predicted by computational gene finding systems from the range 67-77% to 90% correct.     

Activation of the Murine Sarcoma Virus Genome After Infection with the Murine Leukemia Virus as Determined by Cell Agglutination

Non-virus-producing NIH/3T3 cells transformed by the murine sarcoma virus are agglutinated by conconavalin A to the same low level as normal NIH/3T3 cells. Infection with the murine leukemia virus greatly increases the agglutination of transformed cells but not that of normal cells. These data suggest that the morphological expression of cell transformation and the surface alterations associated with increased cell agglutination are controlled by the expressions of different sarcoma virus genes.     

Caffeine interaction with fluorescent calcium indicator dyes.

We report that caffeine, in millimolar concentrations, interacts strongly with four common calcium indicator dyes: mag-fura-2, magnesium green, fura-2, and fluo-3. Fluorescence intensities are either noticeably enhanced (mag-fura-2, fura-2) or diminished (magnesium green, fluo-3). The caffeine-induced changes in the fluorescence spectra are clearly distinct from those of metal ion binding at the indicator chelation sites. Binding affinities for calcium of either mag-fura-2 or magnesium green increased only slightly in the presence of caffeine. Caffeine also alters the fluorescence intensities of two other fluorescent dyes lacking a chelation site, fluorescein and sulforhodamine 101, implicating the fluorophore itself as the interaction site for caffeine. In the absence of caffeine, variation of solution hydrophobicity by means of water/dioxane mixtures yielded results similar to those for caffeine. These observations suggest that hydrophobic substances, in general, can alter dye fluorescence in a dye-specific manner. For the particular case of caffeine, and perhaps other commonly used pharmacological agents, the dye interactions can seriously distort fluorescence measurements of intracellular ion concentrations with metal indicator dyes.     

The complete genome sequence of Bacillus anthracis Ames "Ancestor"

The pathogenic bacterium Bacillus anthracis has become the subject of intense study as a result of its use in a bioterrorism attack in the United States in September and October 2001. Previous studies suggested that B. anthracis Ames Ancestor, the original Ames fully virulent plasmid-containing isolate, was the ideal reference. This study describes the complete genome sequence of that original isolate, derived from a sample kept in cold storage since 1981.     

Searching for SNPs with cloud computing

As DNA sequencing outpaces improvements in computer speed, there is a critical need to accelerate tasks like alignment and SNP calling. Crossbow is a cloud-computing software tool that combines the aligner Bowtie and the SNP caller SOAPsnp. Executing in parallel using Hadoop, Crossbow analyzes data comprising 38-fold coverage of the human genome in three hours using a 320-CPU cluster rented from a cloud computing service for about $85. Crossbow is available from .     

Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of approximately 1.3 gigabytes. Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches. Multiple processor cores can be used simultaneously to achieve even greater alignment speeds. Bowtie is open source .     

Clustering metagenomic sequences with interpolated Markov models

Background  

Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and sequenced by traditional methods. Because the output from metagenomic sequencing is a large set of reads of unknown origin, clustering reads together that were sequenced from the same species is a crucial analysis step. Many effective approaches to this task rely on sequenced genomes in public databases, but these genomes are a highly biased sample that is not necessarily representative of environments interesting to many metagenomics projects.     

Methylated DNA/RNA in Body Fluids as Biomarkers for Lung Cancer

DNA/RNA methylation plays an important role in lung cancer initiation and progression. Liquid biopsy makes use of cells, nucleotides and proteins released from tumor cells into body fluids to help with cancer diagnosis and prognosis. Methylation of circulating tumor DNA (ctDNA) has gained increasing attention as biomarkers for lung cancer. Here we briefly introduce the biological basis and detection method of ctDNA methylation, and review various applications of methylated DNA in body fluids in lung cancer screening, diagnosis, prognosis, monitoring and treatment prediction. We also discuss the emerging role of RNA methylation as biomarkers for cancer.