Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data.

Summary Aminoglycoside antibiotics directly target the ribosome, yet the mechanisms by which they induce cell death are not fully understood. Recently, oxidative stress has been implicated as one of the mechanisms whereby bactericidal antibiotics kill bacteria. Here we work out, using systems-level approaches and phenotypic analyses, the pathway whereby aminoglycosides ultimately trigger hydroxyl radical formation. We show, by disabling systems which facilitate membrane protein traffic, that mistranslation and misfolding of membrane proteins are central to aminoglycoside-induced oxidative stress and cell death. We also demonstrate that signaling through the envelope stress response two-component system is a key player in this process, and highlight an associated role for the redox-responsive two-component system. Additionally, we show that these two-component systems play a general role in bactericidal antibiotic-mediated oxidative stress and cell death, expanding our understanding of the common mechanism of killing induced by bactericidal antibiotics.

Saccharomyces cerevisiae centromeres have a characteristic 120-base-pair region consisting of three distinct centromere DNA sequence elements (CDEI, CDEII, and CDEIII). We have generated a series of 26 CEN mutations in vitro (including 22 point mutations, 3 insertions, and 1 deletion) and tested their effects on mitotic chromosome segregation by using a new vector system. The yeast transformation vector pYCF5 was constructed to introduce wild-type and mutant CEN DNAs onto large, linear chromosome fragments which are mitotically stable and nonessential. Six point mutations in CDEI show increased rates of chromosome loss events per cell division of 2-to 10-fold. Twenty mutations in CDEIH exhibit chromosome loss rates that vary from wild type (10-4) to nonfunctional (>10-'). These results directly identify nucleotides within CDEI and CDEIII that are required for the specification of a functional centromere and show that the degree of conservation of an individual base does not necessarily reflect its importance in mitotic CEN function.Since the first isolation (8) of a DNA clone containing a centromere of the yeast Saccharomyces cerevisiae, a major goal has been the identification of those DNA sequences that are important for the assembly of functional yeast centromeres. Potential candidates are nucleotides within a characteristic 120-base-pair (bp) DNA segment, which was found by sequence comparisons of cloned DNA from the centromere regions (CEN DNA) of 12 S. cerevisiae chromosomes (13,19,21,29,41).Deletion analysis of CEN3, CEN6, and CEN11 DNA has demonstrated that the presence of the 120-bp conserved sequence is necessary and sufficient for complete centromere activity in vivo (1,17,35,40). Several segments of highly conserved base pairs within the CEN region contribute to palindromic structures (see Fig. 2A and B). The completely conserved uTCACuTG (u = purine) at the left end (CDEI) was recently shown to bind to a protein in cell extracts (3; L. Panzeri, personal communication), although there is at present no evidence that this protein binds CDEI in the centromere DNA in vivo. Deletions at the left end, including all or major parts of CDEI, lead to a substantial decrease in centromere activity (40).

No abstract

No abstract