Global Transposon Mutagenesis and Essential Gene Analysis of Helicobacter pylori

Abstract

We have constructed a genome-saturating mutant library of the human gastric pathogen Helicobacter pylori. Microarray tracking of transposon mutants (MATT) allowed us to map the position of 5,363 transposon mutants in our library. While we generally found insertions well distributed throughout the genome, 344 genes had no detectable transposon insertions, and this list is predicted to be highly enriched for essential genes. Comparison to the essential gene set of other bacteria revealed a surprisingly limited overlap with all organisms tested (11%), while 55% were essential in some organisms but not others. We independently verified the essentiality of several gene products, including an HtrA family serine protease, a hypothetical protein with putative phospholipase D activity, and a riboflavin specific deaminase. A limited screen for motility mutants allowed us to estimate that 4.5% of the genome is dedicated to this virulence-associated phenotype.

Identification of Campylobacter jejuni Genes Contributing to Acid Adaptation by Transcriptional Profiling and Genome-Wide Mutagenesis

“…74,2008 STEADY-STATE ACID STRESS RESPONSE OF C. JEJUNI 1601 suffers from two major weaknesses: mRNA abundance may not always correlate with the expression of functional proteins, and protein expression may not always correlate with its functional requirement. In particular, the up-regulation of a gene under a given stress condition does not necessarily indicate it is required for survival under that condition (11).…”

“…Chromosomal DNA was extracted from the Tn mutants impaired for growth at low pH using standard protocols. This DNA was used as the template for either a single-primer PCR amplification (24,45) or a semidegenerate PCR amplification (19,74). PCR amplification using a single primer (also called RATE, for random amplification of transposon ends) was performed using 0.4 mM dNTPs, 0.8 M of either primer Ori1 (5Ј CCATGAGGGTTTAGTTCGTTAAA 3Ј) or SqFP (5Ј GCCA ACGACTACGCACTAGCCAAC 3Ј), which binds within the transposon, 4.4 mM MgCl 2 , and 5 U Taq DNA polymerase (hot start).…”

“…Semidegenerate PCR amplification required two separate amplification steps. In the first step, primer Ori1 or SqFP (which binds within the transposon) and primer CEKG2C (5Ј GGCCACGCGTCGAC TAGTACNNNNNNNNNNGATAT 3Ј) (a semidegenerate primer with a 5Ј overhang) (74) were used to amplify a portion of the transposon and flanking chromosomal DNA. The product of the first amplification reaction was diluted 10-fold, and 1 l was used as the template for the second amplification reaction, which was carried out using a nested primer that binds within the transposon (SqFP or AR54 [5Ј AGAGCTTAGTACGTTAAACATGA 3Ј]) and a primer (CEKG4; 5Ј GGCCACGCGTCGACTAGTAC 3Ј) (74) complementary to the overhang sequence in CEKG2C.…”

“…This second step is designed to further amplify the DNA of interest. The reaction mixture for both amplification reactions contained 0.2 mM dNTPs, 0.4 M each primer, 4.4 mM MgCl 2 , and 2.5 U Taq polymerase, and the cycling conditions were those used by Salama and coworkers (74). The PCR product amplified using either strategy was sequenced using a nested transposon-specific primer (SqFP or AR54), and the transposon insertion site was identified by BLAST analysis of the DNA sequence immediately flanking the mosaic end of the transposon.…”

Building the blueprint of life

“…These problems can be overcome by integrating many taxonomically diverse gene essentiality datasets into the analysis with a focus on the biological functions that are conserved across multiple datasets. This approach has been applied previously using essentiality datasets from five different organisms [29], but now we expanded the study to the 13 currently available datasets [19,[30][31][32][33][34][35][36][37][38][39][40][41][42][43]. We began our analysis by comparing the lists of SEED functional roles associated with the essential genes in each of the 13 datasets to identify the biological functions that are conserved across multiple datasets.…”