Protection Induced by Oral Vaccination with a Recombinant Yersinia pseudotuberculosis Delivering Yersinia pestis LcrV and F1 Antigens in Mice and Rats against Pneumonic Plague.

A newly attenuated Yersinia pseudotuberculosis strain (designated Yptb1) with triple mutation Δasd ΔyopK ΔyopJ and chromosomal insertion of the Y. pestis caf1R-caf1M-caf1A-caf1 operon was constructed as a live vaccine platform. Yptb1 tailored with an Asd+ plasmid (pYA5199) (designated Yptb1[pYA5199]) simultaneously delivers Y. pestis LcrV and F1. The attenuated Yptb1(pYA5199) localized in the Peyer's patches, lung, spleen, and liver for a few weeks after oral immunization without causing any disease symptoms in immunized rodents. An oral prime-boost Yptb1(pYA5199) immunization stimulated potent antibody responses to LcrV, F1, and Y. pestis whole-cell lysate (YPL) in Swiss Webster mice and Brown Norway rats. The prime-boost Yptb1(pYA5199) immunization induced higher antigen-specific humoral and cellular immune responses in mice than a single immunization did, and it provided complete short-term and long-term protection against a high dose of intranasal Y. pestis challenge in mice. Moreover, the prime-boost immunization afforded substantial protection for Brown Norway rats against an aerosolized Y. pestis challenge. Our study highlights that Yptb1(pYA5199) has high potential as an oral vaccine candidate against pneumonic plague.

Activation of Heme Oxygenase Expression by Cobalt Protoporphyrin Treatment Prevents Pneumonic Plague Caused by Inhalation of Yersinia pestis.

Pneumonic plague, caused by the Gram-negative bacteria Yersinia pestis, is an invasive, rapidly progressing disease with poor survival rates. Following inhalation of Y. pestis, bacterial invasion of the lungs and a tissue-damaging inflammatory response allows vascular spread of the infection. Consequently, primary pneumonic plague is a multiorgan disease involving sepsis and necrosis of immune tissues and the liver, as well as bronchopneumonia and rampant bacterial growth. Given the likely role of the hyperinflammatory response in accelerating the destruction of tissue, in this work we evaluated the therapeutic potential of the inducible cytoprotective enzyme heme oxygenase 1 (HO-1) against primary pneumonic plague. On its own, the HO-1 inducer cobalt protoporphyrin IX (CoPP) provided mice protection from lethal challenge with Y. pestis CO92 with improved pulmonary bacterial clearance and a dampened inflammatory response compared to vehicle-treated mice. Furthermore, CoPP treatment combined with doxycycline strongly enhanced protection in a rat aerosol challenge model. Compared to doxycycline alone, CoPP treatment increased survival, with a 3-log decrease in median bacterial titer recovered from the lungs and the general absence of a systemic hyperinflammatory response. In contrast, treatment with the HO-1 inhibitor SnPP had no detectable impact on doxycycline efficacy. The combined data indicate that countering inflammatory toxicity by therapeutically inducing HO-1 is effective in reducing the rampant growth of Y. pestis and preventing pneumonic plague.

Complementary feature selection from alternative splicing events and gene expression for phenotype prediction.

MOTIVATION: A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via gene expression. Isoforms, however, generated from alternative splicing, may provide a novel and complementary set of transcripts for phenotype prediction. In contrast to gene expression, the number of isoforms increases significantly due to numerous alternative splicing patterns, resulting in a prioritization problem for many machine learning algorithms. This study identifies the empirically optimal methods of transcript quantification, feature engineering and filtering steps using phenotype prediction accuracy as a metric. At the same time, the complementary nature of gene and isoform data is analyzed and the feasibility of identifying isoforms as biomarker candidates is examined. RESULTS: Isoform features are complementary to gene features, providing non-redundant information and enhanced predictive power when prioritized and filtered. A univariate filtering algorithm, which selects up to the N highest ranking features for phenotype prediction is described and evaluated in this study. An empirical comparison of pipelines for isoform quantification is reported by performing cross-validation prediction tests with datasets from human non-small cell lung cancer (NSCLC) patients, human patients with chronic obstructive pulmonary disease (COPD) and amyotrophic lateral sclerosis (ALS) transgenic mice, each including samples of diseased and non-diseased phenotypes. AVAILABILITY AND IMPLEMENTATION: https://github.com/clabuzze/Phenotype-Prediction-Pipeline.git CONTACT: clabuzze@iastate.edu, antoniom@bc.edu, watsondk@musc.edu, andersonpe2@cofc.edu.

Word2Vec inversion and traditional text classifiers for phenotyping lupus.

BACKGROUND: Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text classifiers based on Natural Language Processing (NLP) techniques along with pattern recognition machine learning (ML) algorithms. The aim of this research is to evaluate the performance of traditional classifiers for identifying patients with Systemic Lupus Erythematosus (SLE) in comparison with a newer Bayesian word vector method. METHODS: We obtained clinical notes for patients with SLE diagnosis along with controls from the Rheumatology Clinic (662 total patients). Sparse bag-of-words (BOWs) and Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs) matrices were produced using NLP pipelines. These matrices were subjected to several different NLP classifiers: neural networks, random forests, naïve Bayes, support vector machines, and Word2Vec inversion, a Bayesian inversion method. Performance was measured by calculating accuracy and area under the Receiver Operating Characteristic (ROC) curve (AUC) of a cross-validated (CV) set and a separate testing set. RESULTS: We calculated the accuracy of the ICD-9 billing codes as a baseline to be 90.00% with an AUC of 0.900, the shallow neural network with CUIs to be 92.10% with an AUC of 0.970, the random forest with BOWs to be 95.25% with an AUC of 0.994, the random forest with CUIs to be 95.00% with an AUC of 0.979, and the Word2Vec inversion to be 90.03% with an AUC of 0.905. CONCLUSIONS: Our results suggest that a shallow neural network with CUIs and random forests with both CUIs and BOWs are the best classifiers for this lupus phenotyping task. The Word2Vec inversion method failed to significantly beat the ICD-9 code classification, but yielded promising results. This method does not require explicit features and is more adaptable to non-binary classification tasks. The Word2Vec inversion is hypothesized to become more powerful with access to more data. Therefore, currently, the shallow neural networks and random forests are the desirable classifiers.

Multivariate models from RNA-Seq SNVs yield candidate molecular targets for biomarker discovery: SNV-DA.

BACKGROUND: It has recently been shown that significant and accurate single nucleotide variants (SNVs) can be reliably called from RNA-Seq data. These may provide another source of features for multivariate predictive modeling of disease phenotype for the prioritization of candidate biomarkers. The continuous nature of SNV allele fraction features allows the concurrent investigation of several genomic phenomena, including allele specific expression, clonal expansion and/or deletion, and copy number variation. RESULTS: The proposed software pipeline and package, SNV Discriminant Analysis (SNV-DA), was applied on two RNA-Seq datasets with varying sample sizes sequenced at different depths: a dataset containing primary tumors from twenty patients with different disease outcomes in lung adenocarcinoma and a larger dataset of primary tumors representing two major breast cancer subtypes, estrogen receptor positive and triple negative. Predictive models were generated using the machine learning algorithm, sparse projections to latent structures discriminant analysis. Training sets composed of RNA-Seq SNV features limited to genomic regions of origin (e.g. exonic or intronic) and/or RNA-editing sites were shown to produce models with accurate predictive performances, were discriminant towards true label groupings, and were able to produce SNV rankings significantly different from than univariate tests. Furthermore, the utility of the proposed methodology is supported by its comparable performance to traditional models as well as the enrichment of selected SNVs located in genes previously associated with cancer and genes showing allele-specific expression. As proof of concept, we highlight the discovery of a previously unannotated intergenic locus that is associated with epigenetic regulatory marks in cancer and whose significant allele-specific expression is correlated with ER+ status; hereafter named ER+ associated hotspot (ERPAHS). CONCLUSION: The use of models from RNA-Seq SNVs to identify and prioritize candidate molecular targets for biomarker discovery is supported by the ability of the proposed method to produce significantly accurate predictive models that are discriminant towards true label groupings. Importantly, the proposed methodology allows investigation of mutations outside of exonic regions and identification of interesting expressed loci not included in traditional gene annotations. An implementation of the proposed methodology is provided that allows the user to specify SNV filtering criteria and cross-validation design during model creation and evaluation.

RNA-Seq analysis of seasonal and individual variation in blood transcriptomes of healthy managed bottlenose dolphins.

BACKGROUND: The blood transcriptome can reflect both systemic exposures and pathological changes in other organs of the body because immune cells recirculate through the blood, lymphoid tissues, and affected sites. In human and veterinary medicine, blood transcriptome analysis has been used successfully to identify markers of disease or pathological conditions, but can be confounded by large seasonal changes in expression. In comparison, the use of transcriptomic based analyses in wildlife has been limited. Here we report a longitudinal study of four managed bottlenose dolphins located in Waikoloa, Hawaii, serially sampled (approximately monthly) over the course of 1 year to establish baseline information on the content and variation of the dolphin blood transcriptome. RESULTS: Illumina based RNA-seq analyses were carried out using both the Ensembl dolphin genome and a de novo blood transcriptome as guides. Overall, the blood transcriptome encompassed a wide array of cellular functions and processes and was relatively stable within and between animals over the course of 1 year. Principal components analysis revealed moderate clustering by sex associated with the variation among global gene expression profiles (PC1, 22 % of variance). Limited seasonal change was observed, with < 2.5 % of genes differentially expressed between winter and summer months (FDR < 0.05). Among the differentially expressed genes, cosinor analysis identified seasonal rhythmicity for the observed changes in blood gene expression, consistent with studies in humans. While the proportion of seasonally variant genes in these dolphins is much smaller than that reported in humans, the majority of those identified in dolphins were also shown to vary with season in humans. Gene co-expression network analysis identified several gene modules with significant correlation to age, sex, or hematological parameters. CONCLUSIONS: This longitudinal analysis of healthy managed dolphins establishes a preliminary baseline for blood transcriptome analysis in this species. Correlations with hematological parameters, distinct from muted seasonal effects, suggest that the otherwise relatively stable blood transcriptome may be a useful indicator of health and exposure. A robust database of gene expression in free-ranging and managed dolphins across seasons with known adverse health conditions or contaminant exposures will be needed to establish predictive gene expression profiles suitable for biomonitoring.

High CO2 alters the hypoxia response of the Pacific whiteleg shrimp (Litopenaeus vannamei) transcriptome including known and novel hemocyanin isoforms.

Acclimation to low O2 in many organisms involves changes at the level of the transcriptome. Here we used high-throughput RNA sequencing (RNA-Seq) to explore the global transcriptomic response and specific involvement of a suite of hemocyanin (Hc) subunits to low O2 alone and in combination with high CO2, which naturally co-occurs with low O2. Hepatopancreas mRNA of juvenile L. vannamei exposed to air-saturated water, low O2, or low O2/high CO2 for 4 or 24 h was pooled, sequenced (HiSeq 2500) and assembled (Trinity: 52,190 contigs) to create a deep strand-specific reference transcriptome. Annotation of the assembly revealed sequences encoding the previously described small Hc subunit (HcS), and three full-length isoforms of the large subunit (HcL1-3). In addition to this, a previously unidentified full-length Hc subunit was discovered. Phylogenetic analysis demonstrated the subunit to be a ß-type Hc subunit (denoted HcB), making this the first report of a ß-type hemocyanin subunit in the Penaeoidea. RNAs of individual shrimp were sequenced; regulated genes identified from pairwise comparisons demonstrated a distinct pattern of regulation between prolonged low O2 and low O2/high CO2 treatments by GO term enrichment analysis (Roff-Bentzen, P < 0.0001), showcasing the stabilization of energetically costly translational machinery, mobilization of energy stores, and downregulation of the ubiquitin/proteasomal degradation machinery. Exposure to hypoxia for 24 h resulted in an increase in all of the full-length hemocyanin subunits (HcS, HcL1, HcL2, HcL3, and HcB). The addition of CO2 to hypoxia muted the transcriptomic response of all the Hc subunits to low O2, except for the ß-type subunit.

Transcriptomics of mRNA and egg quality in farmed fish: Some recent developments and future directions.

Maternal mRNA transcripts deposited in growing oocytes regulate early development and are under intensive investigation as determinants of egg quality. The research has evolved from single gene studies to microarray and now RNA-Seq analyses in which mRNA expression by virtually every gene can be assessed and related to gamete quality. Such studies have mainly focused on genes changing two- to several-fold in expression between biological states, and have identified scores of candidate genes and a few gene networks whose functioning is related to successful development. However, ever-increasing yields of information from high throughput methods for detecting transcript abundance have far outpaced progress in methods for analyzing the massive quantities of gene expression data, and especially for meaningful relation of whole transcriptome profiles to gamete quality. We have developed a new approach to this problem employing artificial neural networks and supervised machine learning with other novel bioinformatics procedures to discover a previously unknown level of ovarian transcriptome function at which minute changes in expression of a few hundred genes is highly predictive of egg quality. In this paper, we briefly review the progress in transcriptomics of fish egg quality and discuss some future directions for this field of study.

Quantitative structure-activity relationships for organophosphates binding to acetylcholinesterase.

Organophosphates are a group of pesticides and chemical warfare nerve agents that inhibit acetylcholinesterase, the enzyme responsible for hydrolysis of the excitatory neurotransmitter acetylcholine. Numerous structural variants exist for this chemical class, and data regarding their toxicity can be difficult to obtain in a timely fashion. At the same time, their use as pesticides and military weapons is widespread, which presents a major concern and challenge in evaluating human toxicity. To address this concern, a quantitative structure-activity relationship (QSAR) was developed to predict pentavalent organophosphate oxon human acetylcholinesterase bimolecular rate constants. A database of 278 three-dimensional structures and their bimolecular rates was developed from 15 peer-reviewed publications. A database of simplified molecular input line entry notations and their respective acetylcholinesterase bimolecular rate constants are listed in Supplementary Material, Table I. The database was quite diverse, spanning 7 log units of activity. In order to describe their structure, 675 molecular descriptors were calculated using AMPAC 8.0 and CODESSA 2.7.10. Orthogonal projection to latent structures regression, bootstrap leave-random-many-out cross-validation and y-randomization were used to develop an externally validated consensus QSAR model. The domain of applicability was assessed by the William's plot. Six external compounds were outside the warning leverage indicating potential model extrapolation. A number of compounds had residuals >2 or <-2, indicating potential outliers or activity cliffs. The results show that the HOMO-LUMO energy gap contributed most significantly to the binding affinity. A mean training R (2) of 0.80, a mean test set R (2) of 0.76 and a consensus external test set R (2) of 0.66 were achieved using the QSAR. The training and external test set RMSE values were found to be 0.76 and 0.88. The results suggest that this QSAR model can be used in physiologically based pharmacokinetic/pharmacodynamic models of organophosphate toxicity to determine the rate of acetylcholinesterase inhibition.

Tissue and Temperature-Specific RNA-Seq Analysis Reveals Genomic Versatility and Adaptive Potential in Wild Sea Turtle Hatchlings (Caretta caretta).

Background: Digital transcriptomics is rapidly emerging as a powerful new technology for modelling the environmental dynamics of the adaptive landscape in diverse lineages. This is particularly valuable in taxa such as turtles and tortoises (order Testudines) which contain a large fraction of endangered species at risk due to anthropogenic impacts on the environment, including pollution, overharvest, habitat degradation, and climate change. Sea turtles (family Cheloniidae) in particular invite a genomics-enabled approach to investigating their remarkable portfolio of adaptive evolution. The sex of the endangered loggerhead sea turtle (Caretta caretta) is subject to temperature-dependent sex determination (TSD), a mechanism by which exposure to temperatures during embryonic development irreversibly determines sex. Higher temperatures produce mainly female turtles and lower temperatures produce mainly male turtles. Incubation temperature can have long term effects on the immunity, migratory ability, and ultimately longevity of hatchlings. We perform RNA-seq differential expression analysis to investigate tissue- and temperature-specific gene expression within brain (n = 7) and gonadal (n = 4) tissue of male and female loggerhead hatchlings. Results: We assemble tissue- and temperature-specific transcriptomes and identify differentially expressed genes relevant to sexual development and life history traits of broad adaptive interest to turtles and other amniotic species. We summarize interactions among differentially expressed genes by producing network visualizations, and highlight shared biological pathways related to migration, immunity, and longevity reported in the avian and reptile literature. Conclusions: The measurement of tissue- and temperature-specific global gene expression of an endangered, flagship species such as the loggerhead sea turtle (Caretta caretta) reveals the genomic basis for potential resiliency and is crucial to future management and conservation strategies with attention to changing climates. Brain and gonadal tissue collected from experimentally reared loggerhead male and female hatchlings comprise an exceedingly rare dataset that permits the identification of genes enriched in functions related to sexual development, immunity, longevity, and migratory behavior and will serve as a large, new genomic resource for the investigation of genotype-phenotype relationships in amniotes.

Influenza A virus NS1 induces degradation of sphingosine 1-phosphate lyase to obstruct the host innate immune response.

The type I interferon (IFN)-mediated innate immune response is one of the central obstacles influenza A virus (IAV) must overcome in order to successfully replicate within the host. We have previously shown that sphingosine 1-phosphate (S1P) lyase (SPL) enhances IKKϵ-mediated type I IFN responses. Here, we demonstrate that the nonstructural protein 1 (NS1) of IAV counteracts the SPL-mediated antiviral response by inducing degradation of SPL. SPL was ubiquitinated and downregulated upon IAV infection or NS1 expression, whereas NS1-deficient IAV failed to elicit SPL ubiquitination or downregulation. Transiently overexpressed SPL increased phosphorylation of IKKϵ, resulting in enhanced expression of type I IFNs. However, this induction was markedly inhibited by IAV NS1. Collectively, this study reveals a novel strategy employed by IAV to subvert the type I IFN response, providing new insights into the interplay between IAV and host innate immunity.

Characterization of 1H NMR spectroscopic data and the generation of synthetic validation sets.

MOTIVATION: Common contemporary practice within the nuclear magnetic resonance (NMR) metabolomics community is to evaluate and validate novel algorithms on empirical data or simplified simulated data. Empirical data captures the complex characteristics of experimental data, but the optimal or most correct analysis is unknown a priori; therefore, researchers are forced to rely on indirect performance metrics, which are of limited value. In order to achieve fair and complete analysis of competing techniques more exacting metrics are required. Thus, metabolomics researchers often evaluate their algorithms on simplified simulated data with a known answer. Unfortunately, the conclusions obtained on simulated data are only of value if the data sets are complex enough for results to generalize to true experimental data. Ideally, synthetic data should be indistinguishable from empirical data, yet retain a known best analysis. RESULTS: We have developed a technique for creating realistic synthetic metabolomics validation sets based on NMR spectroscopic data. The validation sets are developed by characterizing the salient distributions in sets of empirical spectroscopic data. Using this technique, several validation sets are constructed with a variety of characteristics present in 'real' data. A case study is then presented to compare the relative accuracy of several alignment algorithms using the increased precision afforded by these synthetic data sets. AVAILABILITY: These data sets are available for download at http://birg.cs.wright.edu/nmr_synthetic_data_sets.

Transcriptomic analysis of polyketide synthases in a highly ciguatoxic dinoflagellate, Gambierdiscus polynesiensis and low toxicity Gambierdiscus pacificus, from French Polynesia.

Marine dinoflagellates produce a diversity of polyketide toxins that are accumulated in marine food webs and are responsible for a variety of seafood poisonings. Reef-associated dinoflagellates of the genus Gambierdiscus produce toxins responsible for ciguatera poisoning (CP), which causes over 50,000 cases of illness annually worldwide. The biosynthetic machinery for dinoflagellate polyketides remains poorly understood. Recent transcriptomic and genomic sequencing projects have revealed the presence of Type I modular polyketide synthases in dinoflagellates, as well as a plethora of single domain transcripts with Type I sequence homology. The current transcriptome analysis compares polyketide synthase (PKS) gene transcripts expressed in two species of Gambierdiscus from French Polynesia: a highly toxic ciguatoxin producer, G. polynesiensis, versus a non-ciguatoxic species G. pacificus, each assembled from approximately 180 million Illumina 125 nt reads using Trinity, and compares their PKS content with previously published data from other Gambierdiscus species and more distantly related dinoflagellates. Both modular and single-domain PKS transcripts were present. Single domain ß-ketoacyl synthase (KS) transcripts were highly amplified in both species (98 in G. polynesiensis, 99 in G. pacificus), with smaller numbers of standalone acyl transferase (AT), ketoacyl reductase (KR), dehydratase (DH), enoyl reductase (ER), and thioesterase (TE) domains. G. polynesiensis expressed both a larger number of multidomain PKSs, and larger numbers of modules per transcript, than the non-ciguatoxic G. pacificus. The largest PKS transcript in G. polynesiensis encoded a 10,516 aa, 7 module protein, predicted to synthesize part of the polyether backbone. Transcripts and gene models representing portions of this PKS are present in other species, suggesting that its function may be performed in those species by multiple interacting proteins. This study contributes to the building consensus that dinoflagellates utilize a combination of Type I modular and single domain PKS proteins, in an as yet undefined manner, to synthesize polyketides.

Sea Turtle Population Genomic Discovery: Global and Locus-Specific Signatures of Polymorphism, Selection, and Adaptive Potential.

In the era of genomics, single-nucleotide polymorphisms (SNPs) have become a preferred molecular marker to study signatures of selection and population structure and to enable improved population monitoring and conservation of vulnerable populations. We apply a SNP calling pipeline to assess population differentiation, visualize linkage disequilibrium, and identify loci with sex-specific genotypes of 45 loggerhead sea turtles (Caretta caretta) sampled from the southeastern coast of the United States, including 42 individuals experimentally confirmed for gonadal sex. By performing reference-based SNP calling in independent runs of Stacks, 3,901-6,998 SNPs and up to 30 potentially sex-specific genotypes were identified. Up to 68 pairs of loci were found to be in complete linkage disequilibrium, potentially indicating regions of natural selection and adaptive evolution. This study provides a valuable SNP diagnostic workflow and a large body of new biomarkers for guiding targeted studies of sea turtle genome evolution and for managing legally protected nonmodel iconic species that have high economic and ecological importance but limited genomic resources.

Standardized Method for Aerosol Challenge of Rodents with Yersinia pestis for Modeling Primary Pneumonic Plague.

Primary pneumonic plague occurs when Yersinia pestis is inhaled into the lower respiratory tract where it invades the alveoli and grows. Rapid bacterial growth eventually elicits a neutrophilic inflammatory response that is ineffective and damaging, leading to accelerated progression of disease. In the laboratory, modeling of primary pneumonic plague can be accomplished by instillation of bacterial culture in the nares of anesthetized mice and rats. Although primary pneumonic plague can develop from this method, variability in dosing and side effects of anesthesia can complicate data interpretation. In contrast, aerosol challenge models allow for well-controlled studies of pneumonic plague with minimal experimental bias and unwanted side effects. For these reasons, antibiotic testing and the licensing of new treatments depend on efficacy data generated from aerosol delivery of Y. pestis in order to more accurately model transmission and the early stages of human pneumonic plague. In order to meet this need, we have extensively characterized pneumonic plague in mice and rats challenged by nose-only exposure to Yersinia pestis. With this approach, simultaneous challenge of large cohorts of animals, gently restrained and not anesthetized, assures safe, well-controlled, unbiased, and uniform infection. In this chapter, we present a standardized method for reproducible aerosol delivery of wild-type Y. pestis to rodents for experimental models of primary pneumonic plague.

Research and Development of High-performance Explosives.

Developmental testing of high explosives for military applications involves small-scale formulation, safety testing, and finally detonation performance tests to verify theoretical calculations. small-scale For newly developed formulations, the process begins with small-scale mixes, thermal testing, and impact and friction sensitivity. Only then do subsequent larger scale formulations proceed to detonation testing, which will be covered in this paper. Recent advances in characterization techniques have led to unparalleled precision in the characterization of early-time evolution of detonations. The new technique of photo-Doppler velocimetry (PDV) for the measurement of detonation pressure and velocity will be shared and compared with traditional fiber-optic detonation velocity and plate-dent calculation of detonation pressure. In particular, the role of aluminum in explosive formulations will be discussed. Recent developments led to the development of explosive formulations that result in reaction of aluminum very early in the detonation product expansion. This enhanced reaction leads to changes in the detonation velocity and pressure due to reaction of the aluminum with oxygen in the expanding gas products.

FLI1 expression is correlated with breast cancer cellular growth, migration, and invasion and altered gene expression.

ETS factors have been shown to be dysregulated in breast cancer. ETS factors control the expression of genes involved in many biological processes, such as cellular proliferation, differentiation, and apoptosis. FLI1 is an ETS protein aberrantly expressed in retrovirus-induced hematological tumors, but limited attention has been directed towards elucidating the role of FLI1 in epithelial-derived cancers. Using data mining, we show that loss of FLI1 expression is associated with shorter survival and more aggressive phenotypes of breast cancer. Gain and loss of function cellular studies indicate the inhibitory effect of FLI1 expression on cellular growth, migration, and invasion. Using Fli1 mutant mice and both a transgenic murine breast cancer model and an orthotopic injection of syngeneic tumor cells indicates that reduced Fli1 contributes to accelerated tumor growth. Global expression analysis and RNA-Seq data from an invasive human breast cancer cell line with over expression of either FLI1 and another ETS gene, PDEF, shows changes in several cellular pathways associated with cancer, such as the cytokine-cytokine receptor interaction and PI3K-Akt signaling pathways. This study demonstrates a novel role for FLI1 in epithelial cells. In addition, these results reveal that FLI1 down-regulation in breast cancer may promote tumor progression.

Remote monitoring of the progression of primary pneumonic plague in Brown Norway rats in high-capacity, high-containment housing.

Development of new vaccines, diagnostics, and therapeutics for biodefense or other relatively rare infectious diseases is hindered by the lack of naturally occurring human disease on which to conduct clinical trials of efficacy. To overcome this experimental gap, the U.S. Food and Drug Administration established the Animal Rule, in which efficacy testing in two well-characterized animal models that closely resemble human disease may be accepted in lieu of large-scale clinical trials for diseases with limited natural human incidence. In this report, we evaluated the Brown Norway rat as a model for pneumonic plague and describe the natural history of clinical disease following inhalation exposure to Yersinia pestis. In high-capacity, high-containment housing, we monitored temperature, activity, heart rate, and rhythm by capturing electronic impulses transmitted from abdominal telemeter implants. Using this system, we show that reduced activity and development of fever are sensitive indications of disease progression. Furthermore, we identified heart arrhythmias as contributing factors to the rapid progression to lethality following the fever response. Together, these data validate the Brown Norway rat as an experimental model for human pneumonic plague and provide new insight that may ultimately lead to novel approaches in postexposure treatment of this devastating infection.

Host stress and immune responses during aerosol challenge of Brown Norway rats with Yersinia pestis.

Inhalation exposure models are becoming the preferred method for the comparative study of respiratory infectious diseases due to their resemblance to the natural route of infection. To enable precise delivery of pathogen to the lower respiratory tract in a manner that imposes minimal biosafety risk, nose-only exposure systems have been developed. Early inhalation exposure technology for infectious disease research grew out of technology used in asthma research where predominantly the Collison nebulizer is used to generate an aerosol by beating a liquid sample against glass. Although infectious aerosol droplets of 1-5 µm in size can be generated, the Collison often causes loss of viability. In this work, we evaluate a gentler method for aerosolization of living cells and describe the use of the Sparging Liquid Aerosol Generator (SLAG) in a rat pneumonic plague model. The SLAG creates aerosols by continuous dripping of liquid sample on a porous metal disc. We show the generation of 0.5-1 µm Yersinia pestis aerosol particles using the SLAG with spray factors typically ranging from 10(-7) to 10(-8) with no detectable loss of bacterial viability. Delivery of these infectious particles via nose-only exposure led to the rapid development of lethal pneumonic plague. Further, we evaluated the effect of restraint-stress imposed by the nose-only exposure chamber on early inflammatory responses and bacterial deposition. Elevated serum corticosterone which peaked at 2 h post-procedure indicated the animals experienced stress as a result of restraint in the nose-only chamber. However, we observed no correlation between elevated corticosterone and the amount of bacterial deposition or inflammation in the lungs. Together these data demonstrate the utility of the SLAG and the nose-only chamber for aerosol challenge of rodents by Y. pestis.

Novel genetic tools for diaminopimelic acid selection in virulence studies of Yersinia pestis.

Molecular studies of bacterial virulence are enhanced by expression of recombinant DNA during infection to allow complementation of mutants and expression of reporter proteins in vivo. For highly pathogenic bacteria, such as Yersinia pestis, these studies are currently limited because deliberate introduction of antibiotic resistance is restricted to those few which are not human treatment options. In this work, we report the development of alternatives to antibiotics as tools for host-pathogen research during Yersinia pestis infections focusing on the diaminopimelic acid (DAP) pathway, a requirement for cell wall synthesis in eubacteria. We generated a mutation in the dapA-nlpB(dapX) operon of Yersinia pestis KIM D27 and CO92 which eliminated the expression of both genes. The resulting strains were auxotrophic for diaminopimelic acid and this phenotype was complemented in trans by expressing dapA in single and multi-copy. In vivo, we found that plasmids derived from the p15a replicon were cured without selection, while selection for DAP enhanced stability without detectable loss of any of the three resident virulence plasmids. The dapAX mutation rendered Y. pestis avirulent in mouse models of bubonic and septicemic plague which could be complemented when dapAX was inserted in single or multi-copy, restoring development of disease that was indistinguishable from the wild type parent strain. We further identified a high level, constitutive promoter in Y. pestis that could be used to drive expression of fluorescent reporters in dapAX strains that had minimal impact to virulence in mouse models while enabling sensitive detection of bacteria during infection. Thus, diaminopimelic acid selection for single or multi-copy genetic systems in Yersinia pestis offers an improved alternative to antibiotics for in vivo studies that causes minimal disruption to virulence.