Modification of seed oil content and acyl composition in the brassicaceae by expression of a yeast sn-2 acyltransferase gene.

A putative yeast sn-2 acyltransferase gene (SLC1-1), reportedly a variant acyltransferase that suppresses a genetic defect in sphingolipid long-chain base biosynthesis, has been expressed in a yeast SLC deletion strain. The SLC1-1 gene product was shown in vitro to encode an sn-2 acyltransferase capable of acylating sn-1 oleoyl-lysophosphatidic acid, using a range of acyl-CoA thioesters, including 18:1-, 22:1-, and 24:0-CoAs. The SLC1-1 gene was introduced into Arabidopsis and a high erucic acid-containing Brassica napus cv Hero under the control of a constitutive (tandem cauliflower mosaic virus 35S) promoter. The resulting transgenic plants showed substantial increases of 8 to 48% in seed oil content (expressed on the basis of seed dry weight) and increases in both overall proportions and amounts of very-long-chain fatty acids in seed triacylglycerols (TAGs). Furthermore, the proportion of very-long-chain fatty acids found at the sn-2 position of TAGs was increased, and homogenates prepared from developing seeds of transformed plants exhibited elevated lysophosphatidic acid acyltransferase (EC 2.3.1.51) activity. Thus, the yeast sn-2 acyltransferase has been shown to encode a protein that can exhibit lysophosphatidic acid acyltransferase activity and that can be used to change total fatty acid content and composition as well as to alter the stereospecific acyl distribution of fatty acids in seed TAGs.     

II. In vitro studies of antibacterial activity

One hundred and forty isolates of beta-hemolytic streptococcus cultured from patients with clinical pharyngitis were studied by disc diffusion for antibiotic sensitivity to lincomycin, erythromycin, cephalexin and penicillin and by agar dilution to cephalexin and penicillin. All isolates were sensitive to ≤ 0.1 μg./ml. penicillin and ≤ 1.56 μg./ml. cephalexin. The disc-diffusion test was reliable in predicting the sensitivities in vitro. One strain of group A betahemolytic streptococcus was resistant to erythromycin by disc diffusion. When compared to Lancefield grouping 18% of strains were incorrectly identified as group A by the bacitracin-disc test. Cephalexin was uniformly effective in vitro in inhibiting beta-hemolytic streptococci and the 30 μg. cephalexin disc was reliable in predicting these sensitivities.     

Principal stratification designs to estimate input data missing due to death

We consider studies of cohorts of individuals after a critical event, such as an injury, with the following characteristics. First, the studies are designed to measure "input" variables, which describe the period before the critical event, and to characterize the distribution of the input variables in the cohort. Second, the studies are designed to measure "output" variables, primarily mortality after the critical event, and to characterize the predictive (conditional) distribution of mortality given the input variables in the cohort. Such studies often possess the complication that the input data are missing for those who die shortly after the critical event because the data collection takes place after the event. Standard methods of dealing with the missing inputs, such as imputation or weighting methods based on an assumption of ignorable missingness, are known to be generally invalid when the missingness of inputs is nonignorable, that is, when the distribution of the inputs is different between those who die and those who live. To address this issue, we propose a novel design that obtains and uses information on an additional key variable-a treatment or externally controlled variable, which if set at its "effective" level, could have prevented the death of those who died. We show that the new design can be used to draw valid inferences for the marginal distribution of inputs in the entire cohort, and for the conditional distribution of mortality given the inputs, also in the entire cohort, even under nonignorable missingness. The crucial framework that we use is principal stratification based on the potential outcomes, here mortality under both levels of treatment. We also show using illustrative preliminary injury data that our approach can reveal results that are more reasonable than the results of standard methods, in relatively dramatic ways. Thus, our approach suggests that the routine collection of data on variables that could be used as possible treatments in such studies of inputs and mortality should become common.