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Vaccines of enhanced range of protection could help to control newly emerging infectious diseases while providing greater resilience to any subsequent variants. Such “universal vaccines” are an idealized, but unrealized, goal that may benefit from unbiased, high-throughput approaches that define antibody cross-reactivity to enable rational selection of cross-protective epitopes. The priority of this investigation is to establish a pipeline for the identification and preliminary characterization of epitopes with enhanced cross-reactivity. A peptide immunoarray representing the proteomes of SARS-CoV, SARS-CoV-II, and MERS-CoV was applied to characterize spike glycoprotein-specific antibody populations within convalescence serum of SARS-CoV-II infected ferrets. Through two alternate bioinformatic approaches, twenty candidate epitopes were identified and translated into vaccines. Epitopes inducing antibodies with cross-reactivity across naturally occurring versions of spike glycoprotein, including SARS-CoV-II Delta and Omicron variants, as well as antigenically distant SARS-CoV and MERS-CoV, were identified. Working from the assumption that cross-reactivity is prerequisite for cross-protection, this highlights the opportunity and mechanisms by which immunoarrays, coupled with in vitro screening assays, can enable rational selection of epitopes with enhanced potential for cross-protection.

There is a growing appreciation within the livestock industry and throughout society that animal stress is an important issue that must be addressed. With implications for animal health, well-being, and productivity, minimizing animal stress through improved animal management procedures and/or selective breeding is becoming a priority. Effective management of stress, however, depends on the ability to identify and quantify the effects of various stressors and determine if individual or combined stressors have distinct biological effects. Furthermore, it is critical to determine the duration of stress-induced biological effects if we are to understand how stress alters animal production and disease susceptibility. Common stress models used to evaluate both psychological and physical stressors in cattle are reviewed. We identify some of the major gaps in our knowledge regarding responses to specific stressors and propose more integrated methodologies and approaches to measuring these responses. These approaches are based on an increased knowledge of both the metabolic and immune effects of stress. Finally, we speculate on how these findings may impact animal agriculture, as well as the potential application of large animal models to understanding human stress.

Prion diseases are a novel class of infectious disease based in the misfolding of the cellular prion protein (PrP C ) into a pathological, self-propagating isoform (PrP Sc ). These fatal, untreatable neurodegenerative disorders affect a variety of species causing scrapie in sheep and goats, bovine spongiform encephalopathy (BSE) in cattle, chronic wasting disease (CWD) in cervids, and Creutzfeldt-Jacob disease (CJD) in humans. Of the animal prion diseases, CWD is currently regarded as the most significant threat due its ongoing geographical spread, environmental persistence, uptake into plants, unpredictable evolution, and emerging evidence of zoonotic potential. The extensive efforts to manage CWD have been largely ineffective, highlighting the need for new disease management tools, including vaccines. Development of an effective CWD vaccine is challenged by the unique biology of these diseases, including the necessity, and associated dangers, of overcoming immune tolerance, as well the logistical challenges of vaccinating wild animals. Despite these obstacles, there has been encouraging progress towards the identification of safe, protective antigens as well as effective strategies of formulation and delivery that would enable oral delivery to wild cervids. In this review we highlight recent strategies for antigen selection and optimization, as well as considerations of various platforms for oral delivery, that will enable researchers to accelerate the rate at which candidate CWD vaccines are developed and evaluated.

Kinase-mediated protein phosphorylation is a central mechanism for regulation of cellular responses and phenotypes. While considerable information is available regarding the evolutionary relationships within the kinase family, as well as the evolutionary conservation of phosphorylation sites, each aspect of this partnership is typically considered in isolation, despite their clear functional relationship. Here, to offer a more holistic perspective on the evolution of protein phosphorylation, the conservation of protein phosphorylation sites is considered in the context of the conservation of the corresponding modifying kinases. Specifically, conservation of defined kinase-phosphorylation site pairings (KPSPs), as well as of each of the component parts (the kinase and the phosphorylation site), were examined across a range of species. As expected, greater evolutionary distance between species was generally associated with lower probability of KPSP conservation, and only a small fraction of KPSPs were maintained across all species, with the vast majority of KPSP losses due to the absence of the phosphorylation site. This supports a model in which a relatively stable kinome promotes the emergence of functional substrates from an evolutionarily malleable phosphoproteome.

Background Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K) to enable researchers to make more informed decisions in selecting cell lines for specific studies. Information about these cell lines was obtained from a wide variety of sources. In addition, new information about cellular pathways that are activated within each cell line was generated. Methods We determined key protein expression data using immunoblot analyses. In addition, two analyses on serum-starved cells were carried out to identify cellular proteins and pathways that are activated in these cells. These analyses were performed using a commercial PathScan array and a novel and more extensive phosphopeptide-based kinome analysis that queries 1290 phosphorylation events in major signaling pathways. Data about this panel of breast cancer cell lines was also accessed from several online sources, compiled and summarized for the following areas: molecular classification, mRNA expression, mutational status of key proteins and other possible cancer-associated mutations, and the tumorigenic and metastatic capacity in mouse xenograft models of breast cancer. Results The cell lines that were characterized included 10 estrogen receptor (ER)-positive, 12 human epidermal growth factor receptor 2 (HER2)-amplified and 18 triple negative breast cancer cell lines, in addition to 4 non-tumorigenic breast cell lines. Within each subtype, there was significant genetic heterogeneity that could impact both the selection of model cell lines and the interpretation of the results obtained. To capture the net activation of key signaling pathways as a result of these mutational combinations, profiled pathway activation status was examined. This provided further clarity for which cell lines were particularly deregulated in common or unique ways. Conclusions These two new kinase or “Kin-OMIC” analyses add another dimension of important data about these frequently used breast cancer cell lines. This will assist researchers in selecting the most appropriate cell lines to use for breast cancer studies and provide context for the interpretation of the emerging results.

Peptide microarrays consisting of defined phosphorylation target sites are an effective approach for high throughput analysis of cellular kinase (kinome) activity. Kinome peptide arrays are highly customizable and do not require species-specific reagents to measure kinase activity, making them amenable for kinome analysis in any species. Our group developed software, Platform for Integrated, Intelligent Kinome Analysis (PIIKA), to enable more effective extraction of meaningful biological information from kinome peptide array data. A subsequent version, PIIKA2, unveiled new statistical tools and data visualization options. Here we introduce PIIKA 2.5 to provide two essential quality control metrics and a new background correction technique to increase the accuracy and consistency of kinome results. The first metric alerts users to improper spot size and informs them of the need to perform manual resizing to enhance the quality of the raw intensity data. The second metric uses inter-array comparisons to identify outlier arrays that sometimes emerge as a consequence of technical issues. In addition, a new background correction method, background scaling, can sharply reduce spatial biases within a single array in comparison to background subtraction alone. Collectively, the modifications of PIIKA 2.5 enable identification and correction of technical issues inherent to the technology and better facilitate the extraction of meaningful biological information. We show that these metrics demonstrably enhance kinome analysis by identifying low quality data and reducing batch effects, and ultimately improve clustering of treatment groups and enhance reproducibility. The web-based and stand-alone versions of PIIKA 2.5 are freely accessible at via http://saphire.usask.ca .

Congenital virus infections, for example cytomegalovirus and rubella virus infections, commonly affect the central nervous and hematological systems in fetuses and offspring. However, interactions between emerging congenital Zika virus and hematological system-bone marrow and blood-in fetuses and offspring are mainly unknown. Our overall goal was to determine whether silent in utero Zika virus infection can cause functional and molecular footprints in the bone marrow and blood of fetuses and offspring. We specifically focused on silent fetal infection because delayed health complications in initially asymptomatic offspring were previously demonstrated in animal and human studies. Using a well-established porcine model for Zika virus infection and a set of cellular and molecular experimental tools, we showed that silent in utero infection causes multi-organ inflammation in fetuses and local inflammation in the fetal bone marrow. In utero infection also caused footprints in the offspring bone marrow and PBMCs. These findings should be considered in a broader clinical context because of growing concerns about health sequelae in cohorts of children affected with congenital Zika virus infection in the Americas. Understanding virus-induced molecular mechanisms of immune activation and inflammation in fetuses may provide targets for early in utero interventions. Also, identifying early biomarkers of in utero-acquired immunopathology in offspring may help to alleviate long-term sequelae.

Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

Protein kinase-mediated phosphorylation is among the most important post-translational modifications. However, few phosphorylation sites have been experimentally identified for most species, making it difficult to determine the degree to which phosphorylation sites are conserved. The goal of this study was to use computational methods to characterize the conservation of human phosphorylation sites in a wide variety of eukaryotes. Using experimentally-determined human sites as input, homologous phosphorylation sites were predicted in all 432 eukaryotes for which complete proteomes were available. For each pair of species, we calculated phosphorylation site conservation as the number of phosphorylation sites found in both species divided by the number found in at least one of the two species. A clustering of the species based on this conservation measure was concordant with phylogenies based on traditional genomic measures. For a subset of the 432 species, phosphorylation site conservation was compared to conservation of both protein kinases and proteins in general. Protein kinases exhibited the highest degree of conservation, while general proteins were less conserved and phosphorylation sites were least conserved. Although preliminary, these data tentatively suggest that variation in phosphorylation sites may play a larger role in explaining phenotypic differences among organisms than differences in the complements of protein kinases or general proteins.

Within human health research, the remarkable utility of kinase inhibitors as therapeutics has motivated efforts to understand biology at the level of global cellular kinase activity (the kinome). In contrast, the diminished potential for using kinase inhibitors in food animals has dampened efforts to translate this research approach to livestock species. This, in our opinion, was a lost opportunity for livestock researchers given the unique potential of kinome analysis to offer insight into complex biology. To remedy this situation, our lab developed user-friendly, cost-effective approaches for kinome analysis that can be readily incorporated into most research programs but with a specific priority to enable the technology to livestock researchers. These contributions include the development of custom software programs for the creation of species-specific kinome arrays as well as comprehensive deconvolution and analysis of kinome array data. Presented in this review are examples of the application of kinome analysis to highlight the utility of the technology to further our understanding of two key complex biological events of priority to the livestock industry: host immune responses to infectious diseases and animal stress responses. These advances and examples of application aim to provide both mechanisms and motivation for researchers, particularly livestock researchers, to incorporate kinome analysis into their research programs.