The microbiological safety of avian eggs is a major concern for the poultry industry and for consumers due to the potential for severe impacts on public health. Innate immune defense is formed by proteins with antimicrobial and immune-modulatory activities and ensures the protection of the chick embryo against pathogens. The objective of this project was to identify the chicken eggshell membrane (ESM) proteins that play a role in these innate immune defense mechanisms. We hypothesized that ESM Ovocalyxin-36 (OCX-36) is a pattern recognition protein, and characterized purified ESM OCX-36. OCX-36 has antimicrobial activity against S. aureus and binds E. coli lipopolysaccharide (LPS) and S. aureus lipoteichoic acid (LTA). We additionally investigated the OCX-36 nonsynonymous single nucleotide polymorphisms (SNPs) at cDNA position 211. The corresponding isoforms (proline-71 or serine-71) were purified from eggs collected from genotyped homozygous hens. A significant difference between Pro-71 and Ser-71 OCX-36s for S. aureus LTA binding activity was observed. From these experiments, we confirmed the hypothesis that OCX-36 is a pattern recognition molecule. We also found that OCX-36 has anti-endotoxin properties and is a macrophage immunostimulator to produce NO and TNF-α. Digested OCX-36 down-regulated the expression of genes involved in LPS signaling and inflammatory responses. Moreover, OCX-36-derived peptides inhibited the production of LPS-induced pro-inflammatory mediators associated with endotoxemia in vivo. Quantitative proteomics analysis of ESMs was performed to evaluate changes in ESM protein abundance during chick embryonic development. Bioinformatics analysis revealed enrichment of proteins associated with antimicrobial and immune protection, vascularization, calcium mobilization and lipid transport, which are vital for chick embryonic development. In unfertilized eggs, protease inhibitors and antimicrobial proteins were enriched. In summary, the ESMs are enriched in proteins with antimicrobial, antioxidant and immune-modulatory properties, which aid in the development of the chick embryo and protect the embryo and unfertilized egg against pathogen invasion.

The discovery of drug targets is a vital component in the development of therapeutic treatments, as it is only through the modulation of a target’s activity that a drug can alleviate symptoms or cure. Accurate identification of drug targets is therefore an important part of any development program, and has an outsized impact on the program’s success due to its position as the first step in the pipeline. This makes the stringent selection of potential targets all the more vital when attempting to control the increasing cost and time needed to successfully complete a development program, and in order to increase the throughput of the entire drug discovery pipeline. In this work, a computational approach was taken to the investigation of protein drug targets. First, a new heuristic, Leaf, for the approximation of a maximum independent set was developed, and evaluated in terms of its ability to remove redundancy from protein datasets, the goal being to generate the largest possible non-redundant dataset. The ability of Leaf to remove redundancy was compared to that of pre-existing heuristics and an optimal algorithm, Cliquer. Not only did Leaf find unbiased non-redundant sets that were around 10% larger than the commonly used PISCES algorithm, it found ones that were no more than one protein smaller than the maximum possible found by Cliquer. Following this, the human proteome was mined to discover properties of proteins that may be important in determining their suitability for pharmaceutical modulation. Data was gathered concerning each protein’s sequence, post-translational modifications, secondary structure, germline variants, expression profile and target status. The data was then analysed to determine features for which the target and non-target proteins had significantly different values. This analysis was repeated for subsets of the proteome consisting of all GPCRs, ion channels, kinases and proteases, as well as for a subset consisting of all proteins that are implicated in cancer. Next, machine learning was used to quantify the proteins in each dataset in terms of their potential to serve as a drug target. For each dataset, this was accomplished by first inducing a random forest that could distinguish between its targets and non-targets, and then using the random forest to quantify the drug target likeness of the non-targets. The properties that can best differentiate targets from non-targets were primarily found to be those that are directly related to a protein’s sequence (e.g. secondary structure). Germline variants, expression levels and interactions between proteins had minimal discriminative power. Overall, the best indicators of drug target likeness were found to be the proteins’ hydrophobicities, in vivo half-lives, propensity for being membrane bound and the fraction of non-polar amino acids in their sequences. In terms of predicting potential targets, datasets of proteases, ion channels and cancer proteins were able to induce random forests that were highly capable of distinguishing between targets and non-targets. The non-target proteins predicted to be targets by these random forests comprise the set of the most suitable potential future drug targets, and are therefore likely to produce the best results if used as the basis for building a drug development programme.

Background Breast cancer is the most commonly diagnosed cancer in women worldwide. The identification of breast cancer molecular biomarkers would provide a more accurate assessment of individual disease risks and prognosis. Exosomes, small extracellular vesicles, have been shown to contribute to various aspects of cancer development and progression. Within the last decade, the content of exosomes has been increasingly explored as a new source of potential biomarker molecules for early disease detection. Methods Exosomal proteomes of MDA-MB-231, a metastatic breast cancer cell line, and MCF-10A, a non-cancerous epithelial breast cell line, were compared. Proteomic analysis was conducted using nano-liquid chromatography coupled to tandem mass spectrometry. The expression of proteins in MDA-MB-231cells was analyzed using label-free protein quantification methods. For the selection of potential biomarkers, the following criteria were used: (i) proteins must be unique to MDA-MB-231 cells when compared to MCF-10A cells, ii) localized on the membrane, (iii) abundant in breast cancer and (iii) are reported to increase in expression as the disease progresses. The presence of selected proteins on exosomes was verified using flow cytometry methods. Results In total, 1,107 exosomal proteins were identified in both cell lines, 726 of which were unique to the MDA-MB-231 breast cancer cell line. The biomarker selection process identified three exosomal proteins (glucose transporter 1, glypican 1, and “disintegrin and metalloproteinase domain-containing protein 10”) as potential breast cancer biomarkers. The presence of these three proteins was validated using flow cytometry methods. The proteomics dataset was also rich in other interesting breast cancer proteins, such as 16 metastasis-associated proteins and two kinases. Conclusion We demonstrate that breast cancer exosomes are a rich source of protein biomarkers that may be beneficial for diagnosis and prognosis.

Les cancers du poumon sont généralement classés en deux groupes principaux: le cancer du poumon à petites cellules et le cancer du poumon non à petites cellules (NSCLC), qui représentent environ 83% de tous les cas de cancer du poumon avec un taux de survie global de 21%. Les thérapies conventionnelles dans le NSCLC, y compris la radiothérapie et la chimiothérapie à base de platine, manquent de spécificité et provoquent souvent de graves effets secondaires car elles affectent les cellules saines. Pour résoudre ce problème, des thérapies ciblées ont été utilisées avec succès en raison de leur spécificité pour les cellules cancéreuses. Des thérapies ciblées contre les mutations du récepteur du facteur de croissance épidermique (EGFR) et les réarrangements anaplasiques de la lymphome kinase (ALK) se sont révélées efficaces dans le CBNPC. Cependant, la réponse thérapeutique peut être limitée en raison de la résistance aux médicaments. C'est le cas des patients développant des tumeurs avec une mutation KRAS activatrice qui conduit à une activité constitutive de la signalisation RAS indépendante des signaux amont. Pour cette raison, une meilleure compréhension de la progression tumorale et de la résistance est nécessaire pour améliorer les traitements contre le cancer. À ce jour, les approches ciblant le KRAS oncogène ont échoué. Compte tenu de l'importance de la reprogrammation métabolique dans plusieurs cancers, y compris le cancer du poumon et le rôle régulateur de la signalisation KRAS. Nous avons exploré la reprogrammation métabolique des cellules NSCLC contrôlées par KRAS pour trouver des vulnérabilités dans le métabolisme modifié qui peuvent être exploitées comme cibles thérapeutiques.Pour cela, nous avons caractérisé le protéome de lignées cellulaires NSCLC (A549 et NCI-H460) hébergeant des mutations activatrices de l'oncogène KRAS avec un accent particulier sur les enzymes métaboliques. Nous avons trouvé non seulement une expression régulatrice des enzymes glycolytiques, fréquente dans le cancer dans le cadre de l'effet Warburg, mais aussi une régulation positive remarquable de la voie des pentoses phosphates (PPP) dans les branches oxydatives et non oxydatives. Sur la base de cette étude, nous avons évalué la faisabilité de l'utilisation de l'enzyme PPP (glucose 6-phosphate déshydrogénase (G6PD) et 6-phosphogluconate déshydrogénase (6PGD) et transcétolase (TKT)) comme cibles pour améliorer ou développer de nouvelles thérapies.Récemment, l'acétylation de la protéine lysine (KDAC) est apparue comme un mécanisme de coordination du métabolisme et des preuves croissantes ont montré que la régulation de l'acétylation des enzymes métaboliques joue un rôle majeur dans le cancer. Par conséquent, les inhibiteurs de la lysine désacétylases (KDACI) ont attiré l'attention non seulement comme des stratégies prometteuses pour l'intervention thérapeutique, mais aussi comme un outil pour étudier le rôle de l'acétylation de la lysine dans la reprogrammation métabolique NSCLC. En outre, la reprogrammation métabolique dépend également fortement du microenvironnement tumoral tel que le niveau d'oxygène. Par conséquent, nous avons également analysé l'inhibition de KDAC dans des conditions normoxiques et hypoxiques afin de mieux comprendre les stratégies adaptatives sous de telles perturbations. Nos résultats ont montré que les KDACI induisent une prolifération cellulaire faible, une différenciation, un arrêt du cycle cellulaire et une apoptose accompagnés d'une modification du phénotype métabolique de la tumeur favorisée par l'hypoxie. Ensemble, ces résultats nous permettent de mieux comprendre comment les KDACI contrôlent les voies métaboliques sous hypoxie dans le NSCLC. / Lung cancers are broadly classified into two main groups: small cell lung cancer and non-small cell lung cancer (NSCLC), which accounts for approximately 83% of all lung cancer cases with an overall 5-year survival rate of 21%. Conventional therapies in NSCLC including radiotherapy and platinum-based chemotherapy lack specificity and often cause severe side effects as they affect healthy cells. To address this problem, targeted therapies have been successfully used due to their specificity for cancer cells. Targeted therapies against epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements have been shown to be effective in NSCLC. However, therapeutic response may be limited due to drug resistance. This is the case of patients whose tumors harbor activating KRAS mutation that leads to constitutive activity of RAS signaling independent of upstream signals. For this reason, a better comprehension of tumor progression and resistance is needed to improve cancer treatments. To date, approaches targeting oncogenic KRAS have been unsuccessful. Given the importance of metabolic reprogramming in multiple cancers including lung cancer and the regulatory role of KRAS signaling. We explored the metabolic reprogramming of KRAS-driven NSCLC cells to find vulnerabilities in the altered metabolism that can be exploited as therapeutic targets.For this, we characterized the proteome of NSCLC cell lines (A549 and NCI-H460) harboring activating mutations of the oncogene KRAS with particular focus on metabolic enzymes. We found not only up-regulation expression of glycolytic enzymes, which is frequently found in cancer as part of the “Warburg effect”, but also a remarkable up-regulation of the pentose phosphate pathway (PPP) in both oxidative and non-oxidative branches. Based on this study, we evaluated the feasibility of use PPP enzyme (glucose 6-phosphate dehydrogenase (G6PD) and 6-phosphogluconate dehydrogenase (6PGD) and transketolase (TKT)) as targets for improve or develop of new therapies.Recently, protein lysine acetylation (KDAC) has emerged as a metabolism-coordinating mechanism and mounting evidence has shown that acetylation regulation of metabolic enzymes plays a major role in cancer. Consequently, lysine deacetylases inhibitors (KDACIs) have drawn attention not only as promising strategies for therapeutic intervention but also as tool for studying the role of lysine acetylation in NSCLC metabolic reprogramming. Furthermore, metabolic reprogramming also depends strongly on the tumor microenvironment such as oxygen level. Therefore, we also analyzed the inhibition of KDAC under normoxic and hypoxic conditions in order to better understand the adaptive strategies under such perturbations. Our results showed that KDACIs induce low cell proliferation, differentiation, cell cycle arrest and apoptosis accompanied by a change in the tumor metabolic phenotype enhanced under hypoxia. Together, these results allow us to better understand how KDACIs control metabolic pathways under hypoxia in NSCLC.

Lysosomes represent the central degradative compartment of eukaryote cells. Harboring a variety of acid hydrolases at acidic pH, this organelle is designed for the degradation and recycling of material for cellular homeostasis and sustenance. Studies on mammalian lysosomes have been extensive and revealed a long list of lysosomal proteins. While the function of most of these remains elusive, it is not surprising that a large subset have been found to be hydrolases. However, little is known about the biogenesis and function of this organelle in parasitic protists, and even less about its role in secretion. This work aimed to shed light on the (phago-)lysosomal proteome of the human parasite Trichomonas vaginalis, its protein targeting, and involvement in hydrolase secretion. Our studies revealed a lysosomal proteome of 462 proteins in 21 functional classes. Hydrolases represented the largest functional class and included proteases, lipases, phosphatases, and glycosidases. The identification of a large set of proteins involved in vesicular trafficking and cytoskeleton rearrangement indicates a dynamic phagolysosomal compartment. Our research, as well as the research of others, have identified several hydrolases also in the secretome, including the cysteine protease TvCP2. However, previously the mode...

The Musculus complexus (pipping muscle) plays a primary role in the hatching of the chick from the eggshell at the end of its embryonic life. Various metabolic and cellular changes have been associated with the pipping muscle during development. These studies profiled the pipping muscle at the molecular level by identifying proteins which are associated with the developmental changes. In the first phase of the study, protein expression profile of the Day 13 chicken embryo pipping muscle was obtained using DDF with nano HPLC mass spectrometric analyzer. Identified proteins were categorized based on Gene Ontology. In the second phase, pipping muscle lymph was profiled from Day 20 chicken embryo using PCT with LTQ-Orbitrap mass spectrometric analyzer. The identification of constituent proteins of the piping muscle provides a better understanding of the complex cellular processes and functionality of the pipping muscle with potential benefits for improving hatchability in the poultry industry.

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Nitrate is the most common ionic form of nitrogen in aquatic ecosystems. Although nitrate is known to affect ecosystems at high levels through eutrophication, hypoxia and loss of biodiversity, it is considered to be physiologically inert to the individual aquatic organism. To test the physiological effects of nitrate on aquatic life, we exposed gill tissue of the Pacific oyster, Crassostrea gigas, to nitrate and characterized changes in protein expression, using a gel-based proteomics approach. Of the 642 protein spots detected, we found that 24 proteins (15 identified) changed expression in response to a 6-hour exposure to nitrate concentrations ranging from 0-73 mg/L, values that characterize highly contaminated surface and ground waters. Proteins changing expression included the oxidative stress proteins thioredoxin and cavortin (a member of the superoxide dismutase family) as well as proteins that are involved in G-protein signaling (Rho-GDI, ADP-ribosylation factor, G-protein ß-subunit), protein homeostasis (heat shock protein 70, prohibitin, calreticulin, and proteasome &#;-type 4 subunit), glycolysis (enolase), transport of hydrophobic molecules (lipocalin) and cytoskeletal arrangements (intermediate filaments and a gelsolin-like adseverin). The most parsimonious explanation for these changes in protein expression assumes that C. gigas reduces nitrate to nitrite and nitric oxide, which reacts with superoxide anions to form the very reactive peroxynitrite. We propose that part of the cellular response to reactive nitrogen species,phagocytic hemocytes inhibit the production of reactive oxygen species, potentially compromising the immune response of oysters to invading pathogens.

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No description available.