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Substrate recognition and cleavage by the bacterial RNase P RNA requires two domains, a specificity domain, or S-domain, and a catalytic domain, or C-domain. The S-domain binds the T stem-loop region in a pre-tRNA substrate to confer specificity for tRNA substrates. In this work, the entire S-domain of the Bacillus subtilis RNase P RNA is replaced with an artificial substrate binding module. New RNA substrates are isolated by in vitro selection using two libraries containing random regions of 60 nt. At the end of the selection, the cleavage rates of the substrate library are approximately 0.7 min(-1)in 10 mM MgCl(2)at 37 degrees C, approximately 4-fold better than the cleavage of a pre-tRNA substrate by the wild-type RNase P RNA under the same conditions. The contribution of the S-domain replacement to the catalytic efficiency is from 6- to 22 000-fold. Chemical and nuclease mapping of two ribozyme-product complexes shows that this contribution correlates with direct interactions between the S-domain replacement and the selected substrate. These results demonstrate the feasibility of design and isolation of RNase P-based, matching ribozyme-substrate pairs without prior knowledge of the sequence or structure of the interactive modules in the ribozyme or substrate.

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A multifaceted disability management program was instituted at an automotive manufacturing organization to control rising workers' compensation costs. A pilot program showed major cost savings over a 9-month period. When total and component disability leave rates were calculated as a percentage of the available workforce and tracked on a weekly basis over the subsequent 3 years, total disability leave rates fell by nearly 50%. This was largely attributable to an approximately 50% decrease in the extended (> 1-year) disability leave rate and a 75% decrease in the workers' compensation leave rate. A novel approach to biostatistical analysis showed a good fit of weekly disability leave rates to a Poisson random variable distribution with an identifiable break point at about 1 1/2 years after observation for extended disability leaves and at 2 years for workers' compensation leaves. This biostatistical approach may prove generalizable to tracking leave rates in other organizations.