The Burkholderia cepacia complex (Bcc) are a group of closely related species known for their intrinsic multidrug resistance, large multipart genomes and ability to infect people with cystic fibrosis. The clinical relevance of the Bcc and their large multipart genomes make the study of their essential genes of broad interest. Essential genes are those required for survival in standard laboratory conditions this makes them potential targets for novel antibiotics against a group of species where few existing antibiotics are effective. Furthermore, while essential gene studies have been carried out in a number of bacterial species, only one of these species had multiple chromosomes and none had a genome as large as the Bcc. In my research I identified essential genes in B. cenocepacia K56-2, a member of the Bcc, by using transposon mutagenesis to deliver a rhamnose inducible promoter randomly into the genome and screening for a conditional growth (CG) phenotype. The utility of the CG mutant library was confirmed by showing that, when grown in suboptimal concentrations of rhamnose, only mutants that under-expressed the target of the antibiotic were hypersensitive. The CG mutant library included transposon insertions upstream from widely conserved, well-characterized essential genes suggesting that the system is capable of recovering essential gene mutants. A number of genes with either no or mixed records of essentiality in other microorganisms were also recovered. Among these was one of the three electron transfer flavoproteins (ETFs) in B. cenocepacia. The ETFs are a family of proteins found in a large number of eukaryotic, archaeal and bacterial species, which are required for the metabolism of specific substrates or for symbiotic nitrogen fixation in some bacteria. Despite these non-essential functions, high throughput screens have identified ETFs as putatively essential in several species. I showed that ETF expression is required for both viability and growth both on complex media and on media containing a variety of single carbon sources. Furthermore, cells depleted of ETF were determined to be nonviable and the morphologic shape of the cells changed from short rods to small spheres. In depth studies of essential genes are only possible for organisms with sequenced genomes. Of the 18 named species that currently comprise the Bcc, only 7 have been sequenced limiting the possibility of cross species comparative genomics. Therefore, I have assembled the first draft genomes of B. contaminans isolates, a species that has emerged as the dominant Bcc species recovered from the CF populations of Argentina and Spain. Identifying and characterizing essential genes in the Bcc, and sequencing additional Bcc species for comparative genomics are important first steps in understanding these clinically important bacteria. / February 2016

Indiana University-Purdue University Indianapolis (IUPUI) / Chlamydia trachomatis is the leading cause of bacterial sexually transmitted disease. Chlamydia spp. are all obligate intracellular organisms that undergo a biphasic developmental cycle within a vacuole termed the inclusion. Infectious, non metabolically active elementary bodies (EBs) are endocytosed and differentiate into non infectious, metabolically active reticulate bodies (RBs) before re-differentiating back into EBs. The chlamydial factors that mediate these differentiation events are mostly unknown. Comparative genomics revealed that Chlamydia spp. have small, highly conserved genomes, suggesting that many of their genes may be essential. Genetic manipulation strategies for Chlamydia spp. are in their infancy, and most of these cannot be used to inactivate essential genes. We generated a clonal ethyl methanesulfonate (EMS)-mutagenized C. trachomatis library and screened it for temperature sensitive (TS) mutants that produced fewer inclusions at either 32°C or 40°C compared to 37°C. Because EMS mutagenesis elicited multiple mutations in most of the library isolates, we also developed a novel lateral gene transfer strategy for mapping mutations linked to TS phenotypes. We identified TS alleles of genes that are essential in other bacteria and that are involved in diverse biological processes including DNA replication, protein synthesis, carbohydrate metabolism, fatty acid biosynthesis, and energy generation, as well as in highly conserved chlamydial hypothetical genes. TS DNA polymerase (dnaEts) and glutamyl-tRNA synthestase (gltXts) mutants were characterized further. Both the dnaEts and gltXts mutants failed to replicate their genomes at 40°C but exhibited unique signs of stress. Chlamydial DNA replication begins by 12 hpi and protein synthesis begins by 2 hpi. However, inclusion expansion and replication of both of the mutants could be rescued by shifting to them to 37°C prior to mid-late development. Since gltXts is likely unable to produce aminoacyl-tRNAs at 40°C, our observation suggests that de novo chlamydial translation uses a pre-existing pool of aminoacyl-tRNA in EBs. Genetic suppressor analysis indicated that the inability of the dnaEts mutant to replicate its genome at 40°C might be linked to an inability of mutant DnaE to bind the DNA template. The tools and mutants we have identified will be invaluable assets for investigating many essential aspects of chlamydial biology.

The continuing emergence of multi-drug resistant Mycobacterium tuberculosis is threatening the ability to treat tuberculosis (TB) worldwide. The development of new anti-TB drugs requires new approaches and new drug targets. In this study, a mariner-based transposon, TnQuoVadis, was constructed to identify essential genes as potential drug targets. This transposon has an outward-facing anhydrotetracycline (ATc)-inducible promoter at each end. A mutant with TnQuoVadis inserted upstream of an essential gene may display normal growth in the presence of ATc, but exhibit no growth or severely diminished growth in the absence of ATc. TnQuoVadis was placed onto a vector with a temperature sensitive replication origin for more efficient mutagenesis of mycobacteria. In a preliminary genetic screen using the model organism Mycobacterium smegmatis, 13 mutants with ATc-dependent growth were identified. Identification of the insertion sites by cloning and sequencing indicated that there were nine genetic loci containing transposon insertions upstream of essential gene candidates in M. smegmatis. Further analysis of these genes indicated that many were previously known essential in both M. smegmatis and M. tuberculosis. These results demonstrate that TnQuoVadis and its delivery system can be utilized for the identification of essential genes in mycobacteria / Master of Science

Campylobacter jejuni is a major cause of bacterial gastroenteritis in the developed world; however, many aspects of its biology remain poorly understood, including its colonization of the mucus layer lining the gastrointestinal tract. In this study, we utilized microarray transposon tracking to compile a list of 195 genes essential for the growth of C. jejuni in vitro under microaerophilic conditions. Then we characterized C. jejuni growing in an extracted intestinal mucus medium. We found that C. jejuni will grow efficiently in a medium comprised of either chick and piglet intestinal mucus, and that these media have a dramatic impact on its transcriptome. Within the genes identified as differentially expressed during growth in a mucus medium, we identified a single operon, (cj0481-cj0490), which we have subsequently characterized as being responsible for both the uptake and metabolism of L-fucose. This represents the first observation of carbohydrate metabolism by the otherwise asaccharolytic C. jejuni. We further found that the inability to utilize L-fucose puts C. jejuni at a competitive disadvantage when colonizing the piglet intestine, but not the chick cecum. Finally, we examined C. jejuni’s ability to utilize mucins as a carbon source while growing within the mucus layer. We found that despite mucins being a major source of L-fucose and amino acids within the intestine, C. jejuni has a minimal ability to degrade and utilize mucins on its own. However, close proximity to mucolytic bacteria within the microbiota of the intestine, allows for increased C. jejuni growth. Together, this paints the picture of an organism that is well adapted to survival within the mucus lining of the intestine and establishing itself as part of the intestinal microbiota.

Campylobacter jejuni is a major cause of bacterial gastroenteritis in the developed world; however, many aspects of its biology remain poorly understood, including its colonization of the mucus layer lining the gastrointestinal tract. In this study, we utilized microarray transposon tracking to compile a list of 195 genes essential for the growth of C. jejuni in vitro under microaerophilic conditions. Then we characterized C. jejuni growing in an extracted intestinal mucus medium. We found that C. jejuni will grow efficiently in a medium comprised of either chick and piglet intestinal mucus, and that these media have a dramatic impact on its transcriptome. Within the genes identified as differentially expressed during growth in a mucus medium, we identified a single operon, (cj0481-cj0490), which we have subsequently characterized as being responsible for both the uptake and metabolism of L-fucose. This represents the first observation of carbohydrate metabolism by the otherwise asaccharolytic C. jejuni. We further found that the inability to utilize L-fucose puts C. jejuni at a competitive disadvantage when colonizing the piglet intestine, but not the chick cecum. Finally, we examined C. jejuni’s ability to utilize mucins as a carbon source while growing within the mucus layer. We found that despite mucins being a major source of L-fucose and amino acids within the intestine, C. jejuni has a minimal ability to degrade and utilize mucins on its own. However, close proximity to mucolytic bacteria within the microbiota of the intestine, allows for increased C. jejuni growth. Together, this paints the picture of an organism that is well adapted to survival within the mucus lining of the intestine and establishing itself as part of the intestinal microbiota.

Essential genes constitute the minimal gene set of an organism that is indispensable for its survival under most favorable conditions. The problem of accurately identifying and predicting genes essential for survival of an organism has both theoretical and practical relevance in genome biology and medicine. From a theoretical perspective it provides insights in the understanding of the minimal requirements for cellular life and plays a key role in the emerging field of synthetic biology; from a practical perspective, it facilitates efficient identification of potential drug targets (e.g., antibiotics) in novel pathogens. However, characterizing essential genes of an organism requires sophisticated experimental studies that are expensive and time consuming. The goal of this research study was to investigate machine learning methods to accurately classify/predict "essential genes" in newly sequenced microbial genomes based solely on their genomic sequence data. This study formulates the predication of essential genes problem as a binary classification problem and systematically investigates applicability of three different supervised classification methods for this task. In particular, Decision Tree (DT), Support Vector Machine (SVM), and Artificial Neural Network (ANN) based classifier models were constructed and trained on genomic features derived solely from gene sequence data of 14 experimentally validated microbial genomes whose essential genes are known. A set of 52 relevant genomic sequence derived features (including gene and protein sequence features, protein physio-chemical features and protein sub-cellular features) was used as input for the learners to learn the classifier models. The training and test datasets used in this study reflected between-class imbalance (i.e. skewed majority class vs. minority class) that is intrinsic to this data domain and essential genes prediction problem. Two imbalance reduction techniques (homology reduction and random under sampling of 50% of the majority class) were devised without artificially balancing the datasets and compromising classifier generalizability. The classifier models were trained and evaluated using 10-fold stratified cross validation strategy on both the full multi-genome datasets and its class imbalance reduced variants to assess their predictive ability of discriminating essential genes from non-essential genes. In addition, the classifiers were also evaluated using a novel blind testing strategy, called LOGO (Leave-One-Genome-Out) and LOTO (Leave-One-Taxon group-Out) tests on carefully constructed held-out datasets (both genome-wise (LOGO) and taxonomic group-wise (LOTO)) that were not used in training of the classifier models. Prediction performance metrics, accuracy, sensitivity, specificity, precision and area under the Receiver Operating Characteristics (AU-ROC) were assessed for DT, SVM and ANN derived models. Empirical results from 10 X 10-fold stratified cross validation, Leave-One-Genome-Out (LOGO) and Leave-One-Taxon group-Out (LOTO) blind testing experiments indicate SVM and ANN based models perform better than Decision Tree based models. On 10 X 10-fold cross validations, the SVM based models achieved an AU-ROC score of 0.80, while ANN and DT achieved 0.79 and 0.68 respectively. Both LOGO (genome-wise) and LOTO (taxonwise) blind tests revealed the generalization extent of these classifiers across different genomes and taxonomic orders. This study empirically demonstrated the merits of applying machine learning methods to predict essential genes in microbial genomes by using only gene sequence and features derived from it. It also demonstrated that it is possible to predict essential genes based on features derived from gene sequence without using homology information. LOGO and LOTO Blind test results reveal that the trained classifiers do generalize across genomes and taxonomic boundaries and provide first critical estimate of predictive performance on microbial genomes. Overall, this study provides a systematic assessment of applying DT, ANN and SVM to this prediction problem. An important potential application of this study will be to apply the resultant predictive model/approach and integrate it as a genome annotation pipeline method for comparative microbial genome and metagenome analysis resources such as the Integrated Microbial Genome Systems (IMG and IMG/M).

No description available.

<p>The <em>Sinorhizobium meliloti</em> genome consists of 6204 predicted protein-coding regions of which approximately 2000 are proteins of unknown function (PUFs). To identify functions of <em>S. meliloti</em> PUFs, we employed the FRT/Flp recombination system to delete large gene clusters and then screened for phenotypes. Large-scale deletions have been mainly used to define minimal gene sets that contain only those genes that are essential and sufficient to sustain a functioning cell. To adapt FRT/Flp for use in <em>S. meliloti</em>, we used an already constructed pTH1522-derived integration gene library of the <em>S. meliloti</em> genome (pTH1522 carries a single FRT site). A second FRT site was inserted at defined locations in the genome through integration of a second plasmid (pTH1937) that also carries a single FRT site. Here we outline how this Flp/FRT system was used to delete defined regions and hence generate multiple gene knock-out mutants. This system was used to delete 32 and 56 defined regions from the 1340 Kb pSymA and 1678 Kb pSymB megaplasmid, respectively. The structures of the resulting megaplasmid deletion mutants were confirmed by PCR analysis. Carbohydrate and nitrogen utilization phenotypes were associated with the deletion of specific regions. Deleting large, regions of the genome helped us to identify phenotypes such as inability to grow on minimal media with fucose, maltotriose, maltitol, trehalose, palatinose, lactulose and galactosamine as sole carbon source. For several FRT-flanked regions, few or no recombinants were recovered which suggested the presence of essential genes. Through this strategy, two essential genes <em>tRNA^arg </em>and<em> engA</em> located on the pSymB and three toxin/antitoxin-like systems, <em>sma0471</em>/<em>sma0473</em>, <em>sma2105</em> and <em>sma2230</em>/<em>sma2231</em> on pSymA megaplasmid were identified.</p> / Doctor of Philosophy (PhD)

No description available.

Infectious diseases are the top leading cause of death worldwide. Identifying essential genes, genes indispensable for survival, has been proven indispensable in defining new therapeutic targets against pathogens, major elements of the minimal set genome to be harnessed in synthetic biology, and determinants of evolutionary relationships of phylogenetically distant species. Thus, essentiality studies promise valuable revenues that can decipher much of biological complexities. Taking advantage of the available microbial sequences and the essentiality studies conducted in various microbial models, we proposed a framework for the prediction of essential genes based on our experimentally verified knowledge of the pathways involved in three essential xiv functions: genetic information processing, cell wall biosynthesis, and energy metabolism. We investigated physiological pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG) database and developed a bioinformatics approach to predict essential genes in 13 different microbial species. Our in silico findings matched to a high degree the experimental data derived from essentiality studies conducted on the same microbial models, providing insights about the microbial lifestyles, including energy resources, cell wall structure, and ecological preferences, but not virulence tools and mechanisms. Furthermore, we believe that essential genes have survived the evolutionary purifying selection due to their evolved capacity to re-wire genetic and protein networks in response to any emerging stress. In this sense, an environmental specificity (stress) provides a dominant determinant of an essential gene set. The new challenge was understanding the contribution of the essential genome in S. sanguinis to the coping mechanisms to different clinically relevant stress factors, namely temperature elevation (43oC) and sub-inhibitory concentration of ampicillin, an abundantly prescribed antibiotic for prophylaxis and treatment against S. sanguinis. The current project investigated the transcriptomic and proteomic profiles of essential genes and proteins, using RNA-seq and mass spectrometry respectively, under the impact of the two stressors separately, to elucidate the essential genome and proteome dynamics on a temporal basis and define “pathogenesis signatures” as potential therapeutic targets. We believe that the current findings will help characterize a bacterial model for studying the dynamics of essential genes and assist in designing evidence-based guidelines for drug prescription in clinical practice.