Metabolic and translational efficiency in microbial organisms.

Metabolic efficiency, as a selective force shaping proteomes, has been shown to exist in Escherichia coli and Bacillus subtilis and in a small number of organisms with photoautotrophic and thermophilic lifestyles. Earlier attempts at larger-scale analyses have utilized proxies (such as molecular weight) for biosynthetic cost, and did not consider lifestyle or auxotrophy. This study extends the analysis to all currently sequenced microbial organisms that are amenable to these analyses while utilizing lifestyle specific amino acid biosynthesis pathways (where possible) to determine protein production costs and compensating for auxotrophy.

Inferring the number of contributors to mixed DNA profiles.

Forensic samples containing DNA from two or more individuals can be difficult to interpret. Even ascertaining the number of contributors to the sample can be challenging. These uncertainties can dramatically reduce the statistical weight attached to evidentiary samples.

A genetic optimization approach for isolating translational efficiency bias.

The study of codon usage bias is an important research area that contributes to our understanding of molecular evolution, phylogenetic relationships, respiratory lifestyle, and other characteristics. Translational efficiency bias is perhaps the most well-studied codon usage bias, as it is frequently utilized to predict relative protein expression levels. We present a novel approach to isolating translational efficiency bias in microbial genomes.

Automated isolation of translational efficiency bias that resists the confounding effect of GC(AT)-content.

Genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale; however, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism's genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons are preferred.

Run-specific limits of detection and quantitation for STR-based DNA testing.

STR-based DNA profiling is an exceptionally sensitive analytical technique that is often used to obtain results at the very limits of its sensitivity. The challenge of reliably distinguishing between signal and noise in such situations is one that has been rigorously addressed in numerous other analytical disciplines. However, an inability to determine accurately the height of electropherogram baselines has caused forensic DNA profiling laboratories to utilize alternative approaches.

Amino acid cost and codon-usage biases in 6 prokaryotic genomes: a whole-genome analysis.

For most prokaryotic organisms, amino acid biosynthesis represents a significant portion of their overall energy budget. The difference in the cost of synthesis between amino acids can be striking, differing by as much as 7-fold. Two prokaryotic organisms, Escherichia coli and Bacillus subtilis, have been shown to preferentially utilize less costly amino acids in highly expressed genes, indicating that parsimony in amino acid selection may confer a selective advantage for prokaryotes.

Empirical analysis of the STR profiles resulting from conceptual mixtures.

Samples containing DNA from two or more individuals can be difficult to interpret. Even ascertaining the number of contributors can be challenging and associated uncertainties can have dramatic effects on the interpretation of testing results. Using an FBI genotypes dataset, containing complete genotype information from the 13 Combined DNA Index System (CODIS) loci for 959 individuals, all possible mixtures of three individuals were exhaustively and empirically computed.

Systematic differences in electropherogram peak heights reported by different versions of the GeneScan software.

DNA profiling using STRs on the 310 and 3100 Genetic Analyzers routinely generates electropherograms that are analyzed with the GeneScan software available from the instrument's manufacturer, Applied Biosystems. Users have been able to choose from three different smoothing options that have been known to result in significant differences in the peak heights that are reported. Improvements in the underlying algorithm of the most recent version of the software also result in significant and somewhat predictable differences in peak height values.