Elfamycins are a relatively understudied group of antibiotics that target the essential process of translation through impairment of EF-Tu function. For the most part, the utility of these compounds has been as laboratory tools for the study of EF-Tu and the ribosome, as their poor pharmacokinetic profile and solubility has prevented implementation as therapeutic agents. However, due to the slowing of the antibiotic pipeline and the rapid emergence of resistance to approved antibiotics, this group is being reconsidered. Some researchers are using screens for novel naturally produced variants, while others are making directed, systematic chemical improvements on publically disclosed compounds. As an example of the latter approach, a GE2270 A derivative, LFF571, has completed phase 2 clinical trials, thus demonstrating the potential for elfamycins to become more prominent antibiotics in the future.

, and the sequence data generally yield a consensus sequence. Here we describe valuable data that are missing from consensus sequences, variable effects on sequence data generated from nonidentical 16S rRNA amplicons, and the appearance of data displayed by different software programs. These effects are illustrated by analysis of 16S rRNA genes from 50 strains of the Bacillus cereus group, i.e., Bacillus anthracis, Bacillus cereus, Bacillus mycoides, and Bacillus thuringiensis. These species have 11 to 14 rRNA operons, and sequence variability occurs among the multiple 16S rRNA genes. A single nucleotide polymorphism (SNP) previously reported to be specific to B. anthracis was detected in some B. cereus strains. However, a different SNP, at position 1139, was identified as being specific to B. anthracis, which is a biothreat agent with high mortality rates. Compared with visual analysis of the electropherograms, basecaller software frequently missed gene sequence variations or could not identify variant bases due to overlapping basecalls. Accurate detection of 16S rRNA gene sequences that include intragenomic variations can improve discrimination among closely related species, improve the utility of 16S rRNA databases, and facilitate rapid bacterial identification by targeted DNA sequence analysis or by whole-genome sequencing performed by clinical or reference laboratories. In 1977, Woese and his colleagues introduced the 16S rRNA gene sequence for phylogenetic studies and, based on that sequence, proposed a Tree of Life composed of three domains of living organisms, i.e., Archaea, Bacteria, and Eukarya (1, 2). The domain of bacteria is by far the largest and continues to expand as diverse environments are analyzed (3). Bacterial 16S rRNA genes are located within the rRNA operons, which also contain genes for 23S rRNA, 5S rRNA, tRNA, and associated intergenic spacer regions. Since rRNAs are essential for survival, these operons are expected to be found on the chromosome. However, a recent report by Anda et al. (4) described a clade within the genus Aureimonas for which the sole rRNA operon is located on a small plasmid, which suggests that there is still more to be learned about rRNA in bacterial species. Although the DNA sequences of various rRNA genes and intergenic spacer regions have been used for identification to the genus or species level, the 16S rRNA gene is usually preferred. In addition to being universally distributed among bacteria, this gene contains both highly conserved and hypervariable regions, and there are large and constantly expanding databases of 16S rRNA gene sequences for comparison.Widespread use of DNA sequencing technologies in clinical, public health, and research laboratories has resulted in rapid and accurate molecular diagnostic methods. A bacterial isolate can now be identified more rapidly by 16S rRNA sequence analysis than by conventional methods. In addition to novel or unculturable bacteria, gene sequence analysis has been employed for identification of bacteria with unusual...

The seeds of the Ricinus communis (Castor bean) plant are the source of the economically important commodity castor oil. Castor seeds also contain the proteins ricin and R. communis agglutinin (RCA), two toxic lectins that are hazardous to human health. Radial immunodiffusion (RID) and the enzyme linked immunosorbent assay (ELISA) are two antibody-based methods commonly used to quantify ricin and RCA; however, antibodies currently used in these methods cannot distinguish between ricin and RCA due to the high sequence homology of the respective proteins. In this study, a technique combining antibody-based affinity capture with liquid chromatography and multiple reaction monitoring (MRM) mass spectrometry (MS) was used to quantify the amounts of ricin and RCA independently in extracts prepared from the seeds of eighteen representative cultivars of R. communis which were propagated under identical conditions. Additionally, liquid chromatography and MRM-MS was used to determine rRNA N-glycosidase activity for each cultivar and the overall activity in these cultivars was compared to a purified ricin standard. Of the cultivars studied, the average ricin content was 9.3 mg/g seed, the average RCA content was 9.9 mg/g seed, and the enzymatic activity agreed with the activity of a purified ricin reference within 35% relative activity.

An automated high-throughput immunomagnetic separation (IMS) method for diagnosing exposure to the organophosphorus nerve agents (OPNAs) sarin (GB), cyclohexylsarin (GF), VX, and Russian VX (RVX) was developed to increase sample processing capacity for emergency response applications. Diagnosis of exposure to OPNAs was based on the formation of OPNA adducts to butyrylcholinesterase (BuChE). Data reported with this method represent a ratio of the agent-specific BuChE adduct concentration, relative to the total BuChE peptide concentration that provides a nonactivity measurement expressed as percent adducted. All magnetic bead transfer steps and washes were performed using instrumentation in a 96-well format allowing for simultaneous extraction of 86 clinical samples plus reference materials. Automating extractions increased sample throughput 50-fold, as compared to a previously reported manual method. The limits of detection, determined using synthetic peptides, were 1 ng/mL for unadducted BuChE and GB-, GF-, VX-, and RVX-adducted BuChE. The automated method was characterized using unexposed serum and serum pools exposed to GB, GF, VX, or RVX. Variation for the measurement of percent adducted was <12% for all characterized quality control serum pools. Twenty-six (26) serum samples from individuals asymptomatic for cholinesterase inhibitor exposure were analyzed using this method, and no background levels of OPNA exposure were observed. Unexposed BuChE serum concentrations measured using this method ranged from 2.8 μg/mL to 10.6 μg/mL, with an average concentration of 6.4 μg/mL.