Re-Assembly of the Genome of Francisella tularensis Subsp. holarctica OSU18

Francisella tularensis is a highly infectious human intracellular pathogen that is the causative agent of tularemia. It occurs in several major subtypes, including the live vaccine strain holarctica (type B). F. tularensis is classified as category A biodefense agent in part because a relatively small number of organisms can cause severe illness. Three complete genomes of subspecies holarctica have been sequenced and deposited in public archives, of which OSU18 was the first and the only strain for which a scientific publication has appeared [1]. We re-assembled the OSU18 strain using both de novo and comparative assembly techniques, and found that the published sequence has two large inversion mis-assemblies. We generated a corrected assembly of the entire genome along with detailed information on the placement of individual reads within the assembly. This assembly will provide a more accurate basis for future comparative studies of this pathogen

TTFields alone and in combination with chemotherapeutic agents effectively reduce the viability of MDR cell sub-lines that over-express ABC transporters

<p>Abstract</p> <p>Background</p> <p>Exposure of cancer cells to chemotherapeutic agents may result in reduced sensitivity to structurally unrelated agents, a phenomenon known as multidrug resistance, MDR. The purpose of this study is to investigate cell growth inhibition of wild type and the corresponding MDR cells by Tumor Treating Fields - TTFields, a new cancer treatment modality that is free of systemic toxicity. The TTFields were applied alone and in combination with paclitaxel and doxorubicin.</p> <p>Methods</p> <p>Three pairs of wild type/MDR cell lines, having resistivity resulting from over-expression of ABC transporters, were studied: a clonal derivative (C11) of parental Chinese hamster ovary AA8 cells and their emetine-resistant sub-line Emt^R1; human breast cancer cells MCF-7 and their mitoxantrone-resistant sub lines MCF-7/Mx and human breast cancer cells MDA-MB-231 and their doxorubicin resistant MDA-MB-231/Dox cells. TTFields were applied for 72 hours with and without the chemotherapeutic agents. The numbers of viable cells in the treated cultures and the untreated control groups were determined using the XTT assay. Student t-test was applied to asses the significance of the differences between results obtained for each of the three cell pairs.</p> <p>Results</p> <p>TTFields caused a similar reduction in the number of viable cells of wild type and MDR cells. Treatments by TTFields/drug combinations resulted in a similar increased reduction in cell survival of wild type and MDR cells. TTFields had no effect on intracellular doxorubicin accumulation in both wild type and MDR cells.</p> <p>Conclusions</p> <p>The results indicate that TTFields alone and in combination with paclitaxel and doxorubicin effectively reduce the viability of both wild type and MDR cell sub-lines and thus can potentially be used as an effective treatment of drug resistant tumors.</p

A proteogenomic update to Yersinia: enhancing genome annotation

<p>Abstract</p> <p>Background</p> <p>Modern biomedical research depends on a complete and accurate proteome. With the widespread adoption of new sequencing technologies, genome sequences are generated at a near exponential rate, diminishing the time and effort that can be invested in genome annotation. The resulting gene set contains numerous errors in even the most basic form of annotation: the primary structure of the proteins.</p> <p>Results</p> <p>The application of experimental proteomics data to genome annotation, called proteogenomics, can quickly and efficiently discover misannotations, yielding a more accurate and complete genome annotation. We present a comprehensive proteogenomic analysis of the plague bacterium, <it>Yersinia pestis KIM</it>. We discover non-annotated genes, correct protein boundaries, remove spuriously annotated ORFs, and make major advances towards accurate identification of signal peptides. Finally, we apply our data to 21 other <it>Yersinia </it>genomes, correcting and enhancing their annotations.</p> <p>Conclusions</p> <p>In total, 141 gene models were altered and have been updated in RefSeq and Genbank, which can be accessed seamlessly through any NCBI tool (e.g. blast) or downloaded directly. Along with the improved gene models we discover new, more accurate means of identifying signal peptides in proteomics data.</p

Feature-by-Feature – Evaluating De Novo Sequence Assembly

The whole-genome sequence assembly (WGSA) problem is among one of the most studied problems in computational biology. Despite the availability of a plethora of tools (i.e., assemblers), all claiming to have solved the WGSA problem, little has been done to systematically compare their accuracy and power. Traditional methods rely on standard metrics and read simulation: while on the one hand, metrics like N50 and number of contigs focus only on size without proportionately emphasizing the information about the correctness of the assembly, comparisons performed on simulated dataset, on the other hand, can be highly biased by the non-realistic assumptions in the underlying read generator. Recently the Feature Response Curve (FRC) method was proposed to assess the overall assembly quality and correctness: FRC transparently captures the trade-offs between contigs' quality against their sizes. Nevertheless, the relationship among the different features and their relative importance remains unknown. In particular, FRC cannot account for the correlation among the different features. We analyzed the correlation among different features in order to better describe their relationships and their importance in gauging assembly quality and correctness. In particular, using multivariate techniques like principal and independent component analysis we were able to estimate the “excess-dimensionality” of the feature space. Moreover, principal component analysis allowed us to show how poorly the acclaimed N50 metric describes the assembly quality. Applying independent component analysis we identified a subset of features that better describe the assemblers performances. We demonstrated that by focusing on a reduced set of highly informative features we can use the FRC curve to better describe and compare the performances of different assemblers. Moreover, as a by-product of our analysis, we discovered how often evaluation based on simulated data, obtained with state of the art simulators, lead to not-so-realistic results

Evolution of Highly Pathogenic H5N1 Avian Influenza Viruses in Vietnam between 2001 and 2007

Highly pathogenic avian influenza (HPAI) H5N1 viruses have caused dramatic economic losses to the poultry industry of Vietnam and continue to pose a serious threat to public health. As of June 2008, Vietnam had reported nearly one third of worldwide laboratory confirmed human H5N1 infections. To better understand the emergence, spread and evolution of H5N1 in Vietnam we studied over 300 H5N1 avian influenza viruses isolated from Vietnam since their first detection in 2001. Our phylogenetic analyses indicated that six genetically distinct H5N1 viruses were introduced into Vietnam during the past seven years. The H5N1 lineage that evolved following the introduction in 2003 of the A/duck/Hong Kong/821/2002-like viruses, with clade 1 hemagglutinin (HA), continued to predominate in southern Vietnam as of May 2007. A virus with a clade 2.3.4 HA newly introduced into northern Vietnam in 2007, reassorted with pre-existing clade 1 viruses, resulting in the emergence of novel genotypes with neuraminidase (NA) and/or internal gene segments from clade 1 viruses. A total of nine distinct genotypes have been present in Vietnam since 2001, including five that were circulating in 2007. At least four of these genotypes appear to have originated in Vietnam and represent novel H5N1 viruses not reported elsewhere. Geographic and temporal analyses of H5N1 infection dynamics in poultry suggest that the majority of viruses containing new genes were first detected in northern Vietnam and subsequently spread to southern Vietnam after reassorting with pre-existing local viruses in northern Vietnam. Although the routes of entry and spread of H5N1 in Vietnam remain speculative, enhanced poultry import controls and virologic surveillance efforts may help curb the entry and spread of new HPAI viral genes

SuRankCo: supervised ranking of contigs in de novo assemblies

Background: Evaluating the quality and reliability of a de novo assembly and of single contigs in particular is challenging since commonly a ground truth is not readily available and numerous factors may influence results. Currently available procedures provide assembly scores but lack a comparative quality ranking of contigs within an assembly. Results: We present SuRankCo, which relies on a machine learning approach to predict quality scores for contigs and to enable the ranking of contigs within an assembly. The result is a sorted contig set which allows selective contig usage in downstream analysis. Benchmarking on datasets with known ground truth shows promising sensitivity and specificity and favorable comparison to existing methodology. Conclusions: SuRankCo analyzes the reliability of de novo assemblies on the contig level and thereby allows quality control and ranking prior to further downstream and validation experiments

Enhanced repair of DNA interstrand crosslinking in ovarian cancer cells from patients following treatment with platinum-based chemotherapy

Despite high tumour response rates to platinum-based chemotherapy in ovarian cancer survival is poor due to the emergence of drug resistance. Mechanistic studies in clinical material have been hampered by the unavailability of sensitive methods to detect the critical drug-induced effects in individual cells. A modification of the single cell gel electrophoresis (comet) assay allows the sensitive detection of DNA interstrand crosslinking in both tumour and normal cells derived directly from clinical material. Tumour cells isolated from 50 ovarian cancer patients were treated ex vivo with 100 μM cisplatin for 1 h and crosslink formation and repair (unhooking) measured. No significant difference in the peak level of crosslinking in tumour cells was observed between patients who were either newly diagnosed or previously treated with platinum-based therapy, or between tumour and mesothelial cells from an individual patient. This indicates no difference in cellular mechanisms such as drug transport or detoxification. In contrast, the percentage repair (unhooking) of DNA interstrand crosslinks was much greater in the group of treated patients. At 24 h in the 36 newly diagnosed patient tumour samples, only one gave >50% repair and 23 gave <10% repair; however, 19 out of 22 treated patient samples gave >10% repair and 14 showed >50% repair. The estimated median difference (newly diagnosed minus treated) was −52 (95% CI −67 to −28), and the P-value from a Mann–Whitney test was <0.001. In eight patients, it was possible to obtain tumour samples prior to any chemotherapy, and also on relapse or at interval debulking surgery following platinum-based chemotherapy. In these patients, the mean % repair prior to therapy was 2.85 rising to 71.23 following treatment. These data demonstrate increased repair of DNA interstrand crosslinks in ovarian tumour cells following platinum therapy which may contribute to clinical acquired resistance

Efficient oligonucleotide probe selection for pan-genomic tiling arrays

Background: Array comparative genomic hybridization is a fast and cost-effective method for detecting, genotyping, and comparing the genomic sequence of unknown bacterial isolates. This method, as with all microarray applications, requires adequate coverage of probes targeting the regions of interest. An unbiased tiling of probes across the entire length of the genome is the most flexible design approach. However, such a whole-genome tiling requires that the genome sequence is known in advance. For the accurate analysis of uncharacterized bacteria, an array must query a fully representative set of sequences from the species' pan-genome. Prior microarrays have included only a single strain per array or the conserved sequences of gene families. These arrays omit potentially important genes and sequence variants from the pan-genome. Results: This paper presents a new probe selection algorithm (PanArray) that can tile multiple whole genomes using a minimal number of probes. Unlike arrays built on clustered gene families, PanArray uses an unbiased, probe-centric approach that does not rely on annotations, gene clustering, or multi-alignments. Instead, probes are evenly tiled across all sequences of the pangenome at a consistent level of coverage. To minimize the required number of probes, probes conserved across multiple strains in the pan-genome are selected first, and additional probes are used only where necessary to span polymorphic regions of the genome. The viability of the algorithm is demonstrated by array designs for seven different bacterial pan-genomes and, in particular, the design of a 385,000 probe array that fully tiles the genomes of 20 different Listeria monocytogenes strains with overlapping probes at greater than twofold coverage. Conclusion: PanArray is an oligonucleotide probe selection algorithm for tiling multiple genome sequences using a minimal number of probes. It is capable of fully tiling all genomes of a species on a single microarray chip. These unique pan-genome tiling arrays provide maximum flexibility for the analysis of both known and uncharacterized strains.https://doi.org/10.1186/1471-2105-10-29