Defined single-gene and multi-gene deletion mutant collections in Salmonella enterica sv Typhimurium.

We constructed two collections of targeted single gene deletion (SGD) mutants and two collections of targeted multi-gene deletion (MGD) mutants in Salmonella enterica sv Typhimurium 14028s. The SGD mutant collections contain (1), 3517 mutants in which a single gene is replaced by a cassette containing a kanamycin resistance (KanR) gene oriented in the sense direction (SGD-K), and (2), 3376 mutants with a chloramphenicol resistance gene (CamR) oriented in the antisense direction (SGD-C). A combined total of 3773 individual genes were deleted across these SGD collections. The MGD collections contain mutants bearing deletions of contiguous regions of three or more genes and include (3), 198 mutants spanning 2543 genes replaced by a KanR cassette (MGD-K), and (4), 251 mutants spanning 2799 genes replaced by a CamR cassette (MGD-C). Overall, 3476 genes were deleted in at least one MGD collection. The collections with different antibiotic markers permit construction of all viable combinations of mutants in the same background. Together, the libraries allow hierarchical screening of MGDs for different phenotypic followed by screening of SGDs within the target MGD regions. The mutants of these collections are stored at BEI Resources (www.beiresources.org) and publicly available.

Evolutionary Genomics of Salmonella enterica Subspecies.

ABSTRACT Six subspecies are currently recognized in Salmonella enterica. Subspecies I (subspecies enterica) is responsible for nearly all infections in humans and warm-blooded animals, while five other subspecies are isolated principally from cold-blooded animals. We sequenced 21 phylogenetically diverse strains, including two representatives from each of the previously unsequenced five subspecies and 11 diverse new strains from S. enterica subspecies enterica, to put this species into an evolutionary perspective. The phylogeny of the subspecies was partly obscured by abundant recombination events between lineages and a relatively short period of time within which subspeciation took place. Nevertheless, a variety of different tree-building methods gave congruent evolutionary tree topologies for subspeciation. A total of 285 gene families were identified that were recruited into subspecies enterica, and most of these are of unknown function. At least 2,807 gene families were identified in one or more of the other subspecies that are not found in subspecies I or Salmonella bongori. Among these gene families were 13 new candidate effectors and 7 new candidate fimbrial clusters. A third complete type III secretion system not present in subspecies enterica (I) isolates was found in both strains of subspecies salamae (II). Some gene families had complex taxonomies, such as the type VI secretion systems, which were recruited from four different lineages in five of six subspecies. Analysis of nonsynonymous-to-synonymous substitution rates indicated that the more-recently acquired regions in S. enterica are undergoing faster fixation rates than the rest of the genome. Recently acquired AT-rich regions, which often encode virulence functions, are under ongoing selection to maintain their high AT content. IMPORTANCE We have sequenced 21 new genomes which encompass the phylogenetic diversity of Salmonella, including strains of the previously unsequenced subspecies arizonae, diarizonae, houtenae, salamae, and indica as well as new diverse strains of subspecies enterica. We have deduced possible evolutionary paths traversed by this very important zoonotic pathogen and identified novel putative virulence factors that are not found in subspecies I. Gene families gained at the time of the evolution of subspecies enterica are of particular interest because they include mechanisms by which this subspecies adapted to warm-blooded hosts.

Distinct DNA methylation profiles between adenocarcinoma and squamous cell carcinoma of human uterine cervix.

Alterations in DNA methylation offer unique prospects as tumor markers. The big limitation in cervical cancer research is that it is too hard to obtain the pure normal tissue from a cervical cancer mass. So, we first profile type-specific DNA methylation of major two types of human uterine cervical cancer, adenocarcinoma (ACA) and squamous cell carcinoma (SCC), to establish a precise source of marker research. To assess the DNA methylation status of promoter regions in human uterine cervical ACAs and SCCs, fresh frozen tissues were obtained from bulky tumor masses to minimize the contamination from normal tissues and two array platforms using digestion with methylation-sensitive restriction-enzyme HpaII, ligation, and PCR were performed: an array of 11,994 (approximately 1.5 kb) PCR products from 10,445 promoter regions, and an array of 355,264 oligonucleotides for 18,212 HpaII fragments in 12,617 promoter regions. Loci near 21 genes showed significant differences between six ACA and four SCC from the analysis of two array data. Real-time PCR-based validation was performed on 13 loci using other nearby candidate methylation targets in the same promoter. Methylation patterns of 11 of 13 linked loci concurred with the microarray results. Four loci were further studied using tissues from additional patients (23 ACA and 24 SCC). Hypermethylation of loci in PAK6 and NOGOR most strongly correlated with ACA. Therefore, we have identified the 21 genes with differential methylation pattern between ACA and SCC and, furthermore, we found that PAK6 and NOGOR could be useful markers of ACA to be distinct from SCC.

Evaluating oligonucleotide properties for DNA microarray probe design.

Most current microarray oligonucleotide probe design strategies are based on probe design factors (PDFs), which include probe hybridization free energy (PHFE), probe minimum folding energy (PMFE), dimer score, hairpin score, homology score and complexity score. The impact of these PDFs on probe performance was evaluated using four sets of microarray comparative genome hybridization (aCGH) data, which included two array manufacturing methods and the genomes of two species. Since most of the hybridizing DNA is equimolar in CGH data, such data are ideal for testing the general hybridization properties of almost all candidate oligonucleotides. In all our data sets, PDFs related to probe secondary structure (PMFE, hairpin score and dimer score) are the most significant factors linearly correlated with probe hybridization intensities. PHFE, homology and complexity score are correlating significantly with probe specificities, but in a non-linear fashion. We developed a new PDF, pseudo probe binding energy (PPBE), by iteratively fitting dinucleotide positional weights and dinucleotide stacking energies until the average residue sum of squares for the model was minimized. PPBE showed a better correlation with probe sensitivity and a better specificity than all other PDFs, although training data are required to construct a PPBE model prior to designing new oligonucleotide probes. The physical properties that are measured by PPBE are as yet unknown but include a platform-dependent component. A practical way to use these PDFs for probe design is to set cutoff thresholds to filter out bad quality probes. Programs and correlation parameters from this study are freely available to facilitate the design of DNA microarray oligonucleotide probes.

Genome sequence of Cronobacter sakazakii BAA-894 and comparative genomic hybridization analysis with other Cronobacter species.

BACKGROUND: The genus Cronobacter (formerly called Enterobacter sakazakii) is composed of five species; C. sakazakii, C. malonaticus, C. turicensis, C. muytjensii, and C. dublinensis. The genus includes opportunistic human pathogens, and the first three species have been associated with neonatal infections. The most severe diseases are caused in neonates and include fatal necrotizing enterocolitis and meningitis. The genetic basis of the diversity within the genus is unknown, and few virulence traits have been identified. METHODOLOGY/PRINCIPAL FINDINGS: We report here the first sequence of a member of this genus, C. sakazakii strain BAA-894. The genome of Cronobacter sakazakii strain BAA-894 comprises a 4.4 Mb chromosome (57% GC content) and two plasmids; 31 kb (51% GC) and 131 kb (56% GC). The genome was used to construct a 387,000 probe oligonucleotide tiling DNA microarray covering the whole genome. Comparative genomic hybridization (CGH) was undertaken on five other C. sakazakii strains, and representatives of the four other Cronobacter species. Among 4,382 annotated genes inspected in this study, about 55% of genes were common to all C. sakazakii strains and 43% were common to all Cronobacter strains, with 10-17% absence of genes. CONCLUSIONS/SIGNIFICANCE: CGH highlighted 15 clusters of genes in C. sakazakii BAA-894 that were divergent or absent in more than half of the tested strains; six of these are of probable prophage origin. Putative virulence factors were identified in these prophage and in other variable regions. A number of genes unique to Cronobacter species associated with neonatal infections (C. sakazakii, C. malonaticus and C. turicensis) were identified. These included a copper and silver resistance system known to be linked to invasion of the blood-brain barrier by neonatal meningitic strains of Escherichia coli. In addition, genes encoding for multidrug efflux pumps and adhesins were identified that were unique to C. sakazakii strains from outbreaks in neonatal intensive care units.

Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis.

Replicate mass spectrometry (MS) measurements and the use of multiple analytical methods can greatly expand the comprehensiveness of shotgun proteomic profiling of biological samples. However, the inherent biases and variations in such data create computational and statistical challenges for quantitative comparative analysis. We developed and tested a normalized, label-free quantitative method termed the normalized spectral index (SI(N)), which combines three MS abundance features: peptide count, spectral count and fragment-ion (tandem MS or MS/MS) intensity. SI(N) largely eliminated variances between replicate MS measurements, permitting quantitative reproducibility and highly significant quantification of thousands of proteins detected in replicate MS measurements of the same and distinct samples. It accurately predicts protein abundance more often than the five other methods we tested. Comparative immunoblotting and densitometry further validate our method. Comparative quantification of complex data sets from multiple shotgun proteomics measurements is relevant for systems biology and biomarker discovery.

Development of a DNA microarray to detect antimicrobial resistance genes identified in the National Center for Biotechnology Information database.

To understand the mechanisms and epidemiology of antimicrobial resistance (AR), the genetic elements responsible must be identified. Due to the myriad of possible genes, a high-density genotyping technique is needed for initial screening. To achieve this, AR genes in the National Center for Biotechnology Information GenBank database were identified by their annotations and compiled into a nonredundant list of 775 genes. A DNA microarray was constructed of 70mer oligonucelotide probes designed to detect these genes encoding resistances to aminoglycosides, beta-lactams, chloramphenicols, glycopeptides, heavy metals, lincosamides, macrolides, metronidazoles, polyketides, quaternary ammonium compounds, streptogramins, sulfonamides, tetracyclines, and trimethoprims as well as resistance transfer genes. The microarray was validated with two fully sequenced control strains of Salmonella enterica: Typhimurium LT2 (sensitive) and Typhi CT18 (multidrug resistance [MDR]). All resistance genes encoded on the MDR plasmid, pHCM1, harbored by CT18 were detected in that strain, whereas no resistance genes were detected in LT2. The microarray was also tested with a variety of bacteria, including MDR Salmonella enterica serovars, Escherichia coli, Campylobacter spp., Enterococcus spp., methicillin-resistant Staphylococcus aureus, Listeria spp., and Clostridium difficile. The results presented here demonstrate that a microarray can be designed to detect virtually all AR genes found in the National Center for Biotechnology Information database, thus reducing the subsequent assays necessary to identify specific resistance gene alleles.

Analysis of pools of targeted Salmonella deletion mutants identifies novel genes affecting fitness during competitive infection in mice.

Pools of mutants of minimal complexity but maximal coverage of genes of interest facilitate screening for genes under selection in a particular environment. We constructed individual deletion mutants in 1,023 Salmonella enterica serovar Typhimurium genes, including almost all genes found in Salmonella but not in related genera. All mutations were confirmed simultaneously using a novel amplification strategy to produce labeled RNA from a T7 RNA polymerase promoter, introduced during the construction of each mutant, followed by hybridization of this labeled RNA to a Typhimurium genome tiling array. To demonstrate the ability to identify fitness phenotypes using our pool of mutants, the pool was subjected to selection by intraperitoneal injection into BALB/c mice and subsequent recovery from spleens. Changes in the representation of each mutant were monitored using T7 transcripts hybridized to a novel inexpensive minimal microarray. Among the top 120 statistically significant spleen colonization phenotypes, more than 40 were mutations in genes with no previously known role in this model. Fifteen phenotypes were tested using individual mutants in competitive assays of intraperitoneal infection in mice and eleven were confirmed, including the first two examples of attenuation for sRNA mutants in Salmonella. We refer to the method as Array-based analysis of cistrons under selection (ABACUS).

Enhancing identifications of lipid-embedded proteins by mass spectrometry for improved mapping of endothelial plasma membranes in vivo.

Lipid membranes structurally define the outer surface and internal organelles of cells. The multitude of proteins embedded in lipid bilayers are clearly functionally important, yet they remain poorly defined. Even today, integral membrane proteins represent a special challenge for current large scale shotgun proteomics methods. Here we used endothelial cell plasma membranes isolated directly from lung tissue to test the effectiveness of four different mass spectrometry-based methods, each with multiple replicate measurements, to identify membrane proteins. In doing so, we substantially expanded this membranome to 1,833 proteins, including >500 lipid-embedded proteins. The best method combined SDS-PAGE prefractionation with trypsin digestion of gel slices to generate peptides for seamless and continuous two-dimensional LC/MS/MS analysis. This three-dimensional separation method outperformed current widely used two-dimensional methods by significantly enhancing protein identifications including single and multiple pass transmembrane proteins; >30% are lipid-embedded proteins. It also profoundly improved protein coverage, sensitivity, and dynamic range of detection and substantially reduced the amount of sample and the number of replicate mass spectrometry measurements required to achieve 95% analytical completeness. Such expansion in comprehensiveness requires a trade-off in heavy instrument time but bodes well for future advancements in truly defining the ever important membranome with its potential in network-based systems analysis and the discovery of disease biomarkers and therapeutic targets. This analytical strategy can be applied to other subcellular fractions and should extend the comprehensiveness of many future organellar proteomics pursuits.

Salmonella serovar identification using PCR-based detection of gene presence and absence.

There are more than 2,500 known Salmonella serovars, and some of these can be further subclassified into groups of strains that differ profoundly in their gene content. We refer to these groups of strains as "genovars." A compilation of comparative genomic hybridization data on 291 Salmonella isolates, including 250 S. enterica subspecies I strains from 32 serovars (52 genovars), was used to select a panel of 384 genes whose presence and absence among serovars and genovars was of potential taxonomic value. A subset of 146 genes was used for real-time PCR to successfully identify 12 serovars (16 genovars) in 24 S. enterica strains. A further subset of 64 genes was used to identify 8 serovars (9 genovars) in 12 multiplex PCR mixes on 11 S. enterica strains. These gene panels distinguish all tested S. enterica subspecies I serovars and their known genovars, almost all by two or more informative markers. Thus, a typing methodology based on these predictive genes would generally alert users if there is an error, an unexpected polymorphism, or a potential new genovar.

DNA microarray detection of antimicrobial resistance genes in diverse bacteria.

High throughput genotyping is essential for studying the spread of multiple antimicrobial resistance. A test oligonucleotide microarray designed to detect 94 antimicrobial resistance genes was constructed and successfully used to identify antimicrobial resistance genes in control strains. The microarray was then used to assay 51 distantly related bacteria, including Gram-negative and Gram-positive isolates, resulting in the identification of 61 different antimicrobial resistance genes in these bacteria. These results were consistent with their known gene content and resistance phenotypes. Microarray results were confirmed by polymerase chain reaction and Southern blot analysis. These results demonstrate that this approach could be used to construct a microarray to detect all sequenced antimicrobial resistance genes in nearly all bacteria.

"Promoter array" studies identify cohorts of genes directly regulated by methylation, copy number change, or transcription factor binding in human cancer cells.

DNA microarrays of promoter sequences have been developed in order to identify the profile of genes bound and activated by DNA regulatory proteins such as the transcription factors c-Jun and ATF2 as well as DNA-modifying methylases. The arrays contain 3083 unique human promoter sequences from +500 to -1000 nts from the transcription start site. Cisplatin-induced DNA damage rapidly leads to specific activation of the Jun kinase pathway leading to increased phosphorylation of c-Jun and ATF2-DNA complexes at hundreds of sites within 3 hours. Using three statistical criteria, approximately 269 most commonly phosphorylated c-Jun/ATF2-DNA complexes were identified and representative cases were verified by qPCR measurement of ChIP-captured DNA. Expression was correlated at the mRNA and protein levels. The largest functional cohort was 24 genes of known DNA repair function, most of which exhibited increased protein expression indicated coordinate gene regulation. In addition, cell lines of prostate cancer exhibit stable methylation or copy number changes that reflect the alterations of the corresponding primary tumors. 504 (18.5%) promoters showed differential hybridization between immortalized control prostate epithelial and cancer cell lines. Among candidate hypermethylated genes in cancer-derived lines, eight had previously been observed in prostate cancer, and 13 were previously determined methylation targets in other cancers. The vast majority of genes that appear to be both differentially methylated and differentially regulated between prostate epithelial and cancer cell lines are novel methylation targets, including PAK6, RAD50, TLX3, PIR51, MAP2K5, INSR, FBN1, GG2-1, representing a rich new source of candidate genes to study the role of DNA methylation in prostate tumors. Earlier studies using prototype promoter arrays examine approximately 7% of the proximal regulatory sequences while the current gene regulatory events surveyed here occur on a large scale and may rapidly effect the coordinated expression of a large number of genes.