148 research outputs found

    Insect Cells for High-Yield Production of SARS-CoV-2 Spike Protein: Building a Virosome-Based COVID-19 Vaccine Candidate.

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    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) homotrimeric spike (S) protein is responsible for mediating host cell entry by binding to the angiotensin-converting enzyme 2 (ACE2) receptor, thus being a key viral antigen to target in a coronavirus disease 19 (COVID-19) vaccine. Despite the availability of COVID-19 vaccines, low vaccine coverage as well as unvaccinated and immune compromised subjects are contributing to the emergence of SARS-CoV-2 variants of concern. Therefore, continued development of novel and/or updated vaccines is essential for protecting against such new variants. In this study, we developed a scalable bioprocess using the insect cells-baculovirus expression vector system (IC-BEVS) to produce high-quality S protein, stabilized in its pre-fusion conformation, for inclusion in a virosome-based COVID-19 vaccine candidate. By exploring different bioprocess engineering strategies (i.e., signal peptides, baculovirus transfer vectors, cell lines, infection strategies and formulation buffers), we were able to obtain ~4 mg/L of purified S protein, which, to the best of our knowledge, is the highest value achieved to date using insect cells. In addition, the insect cell-derived S protein exhibited glycan processing similar to mammalian cells and mid-term stability upon storage (up to 90 days at -80 and 4 °C or after 5 freeze-thaw cycles). Noteworthy, antigenicity of S protein, either as single antigen or displayed on the surface of virosomes, was confirmed by ELISA, with binding of ACE2 receptor, pan-SARS antibody CR3022 and neutralizing antibodies to the various epitope clusters on the S protein. Binding capacity was also maintained on virosomes-S stored at 4 °C for 1 month. This work demonstrates the potential of using IC-BEVS to produce the highly glycosylated and complex S protein, without compromising its integrity and antigenicity, to be included in a virosome-based COVID-19 vaccine candidate

    Longer lifespan in male mice treated with a weakly estrogenic agonist, an antioxidant, an α-glucosidase inhibitor or a Nrf2-inducer

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    The National Institute on Aging Interventions Testing Program (ITP) evaluates agents hypothesized to increase healthy lifespan in genetically heterogeneous mice. Each compound is tested in parallel at three sites, and all results are published. We report the effects of lifelong treatment of mice with four agents not previously tested: Protandim, fish oil, ursodeoxycholic acid (UDCA) and metformin – the latter with and without rapamycin, and two drugs previously examined: 17-α-estradiol and nordihydroguaiaretic acid (NDGA), at doses greater and less than used previously. 17-α-estradiol at a threefold higher dose robustly extended both median and maximal lifespan, but still only in males. The male-specific extension of median lifespan by NDGA was replicated at the original dose, and using doses threefold lower and higher. The effects of NDGA were dose dependent and male specific but without an effect on maximal lifespan. Protandim, a mixture of botanical extracts that activate Nrf2, extended median lifespan in males only. Metformin alone, at a dose of 0.1% in the diet, did not significantly extend lifespan. Metformin (0.1%) combined with rapamycin (14 ppm) robustly extended lifespan, suggestive of an added benefit, based on historical comparison with earlier studies of rapamycin given alone. The α-glucosidase inhibitor, acarbose, at a concentration previously tested (1000 ppm), significantly increased median longevity in males and 90th percentile lifespan in both sexes, even when treatment was started at 16 months. Neither fish oil nor UDCA extended lifespan. These results underscore the reproducibility of ITP longevity studies and illustrate the importance of identifying optimal doses in lifespan studies

    The Two Caenorhabditis elegans UDP-Glucose:Glycoprotein Glucosyltransferase Homologues Have Distinct Biological Functions

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    The UDP-Glc:glycoprotein glucosyltransferase (UGGT) is the sensor of glycoprotein conformations in the glycoprotein folding quality control as it exclusively glucosylates glycoproteins not displaying their native conformations. Monoglucosylated glycoproteins thus formed may interact with the lectin-chaperones calnexin (CNX) and calreticulin (CRT). This interaction prevents premature exit of folding intermediates to the Golgi and enhances folding efficiency. Bioinformatic analysis showed that in C. elegans there are two open reading frames (F48E3.3 and F26H9.8 to be referred as uggt-1 and uggt-2, respectively) coding for UGGT homologues. Expression of both genes in Schizosaccharomyces pombe mutants devoid of UGGT activity showed that uggt-1 codes for an active UGGT protein (CeUGGT-1). On the other hand, uggt-2 coded for a protein (CeUGGT-2) apparently not displaying a canonical UGGT activity. This protein was essential for viability, although cnx/crt null worms were viable. We constructed transgenic worms carrying the uggt-1 promoter linked to the green fluorescent protein (GFP) coding sequence and found that CeUGGT-1 is expressed in cells of the nervous system. uggt-1 is upregulated under ER stress through the ire-1 arm of the unfolded protein response (UPR). Real-time PCR analysis showed that both uggt-1 and uggt-2 genes are expressed during the entire C. elegans life cycle. RNAi-mediated depletion of CeUGGT-1 but not of CeUGGT-2 resulted in a reduced lifespan and that of CeUGGT-1 and CeUGGT-2 in a developmental delay. We found that both CeUGGT1 and CeUGGT2 play a protective role under ER stress conditions, since 10 µg/ml tunicamycin arrested development at the L2/L3 stage of both uggt-1(RNAi) and uggt-2(RNAi) but not of control worms. Furthermore, we found that the role of CeUGGT-2 but not CeUGGT-1 is significant in relieving low ER stress levels in the absence of the ire-1 unfolding protein response signaling pathway. Our results indicate that both C. elegans UGGT homologues have distinct biological functions

    The economics of debt clearing mechanisms

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    We examine the evolution of decentralized clearinghouse mechanisms from the 13th to the 18th century; in particular, we explore the clearing of non- or limitedtradable debts like bills of exchange. We construct a theoretical model of these clearinghouse mechanisms, similar to the models in the theoretical matching literature, and show that specific decentralized multilateral clearing algorithms known as rescontre, skontrieren or virement des parties used by merchants were efficient in specific historical contexts. We can explain both the evolutionary self-organizing emergence of late medieval and early modern fairs, and its robustness during the 17th and 18th century

    IRE1α–XBP1 controls T cell function in ovarian cancer by regulating mitochondrial activity

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    Tumours evade immune control by creating hostile microenvironments that perturb T cell metabolism and effector function 1?4 . However, it remains unclear how intra-tumoral T cells integrate and interpret metabolic stress signals. Here we report that ovarian cancer?an aggressive malignancy that is refractory to standard treatments and current immunotherapies 5?8 ?induces endoplasmic reticulum stress and activates the IRE1α?XBP1 arm of the unfolded protein response 9,10 in T cells to control their mitochondrial respiration and anti-tumour function. In T cells isolated from specimens collected from patients with ovarian cancer, upregulation of XBP1 was associated with decreased infiltration of T cells into tumours and with reduced IFNG mRNA expression. Malignant ascites fluid obtained from patients with ovarian cancer inhibited glucose uptake and caused N-linked protein glycosylation defects in T cells, which triggered IRE1α?XBP1 activation that suppressed mitochondrial activity and IFNγ production. Mechanistically, induction of XBP1 regulated the abundance of glutamine carriers and thus limited the influx of glutamine that is necessary to sustain mitochondrial respiration in T cells under glucose-deprived conditions. Restoring N-linked protein glycosylation, abrogating IRE1α?XBP1 activation or enforcing expression of glutamine transporters enhanced mitochondrial respiration in human T cells exposed to ovarian cancer ascites. XBP1-deficient T cells in the metastatic ovarian cancer milieu exhibited global transcriptional reprogramming and improved effector capacity. Accordingly, mice that bear ovarian cancer and lack XBP1 selectively in T cells demonstrate superior anti-tumour immunity, delayed malignant progression and increased overall survival. Controlling endoplasmic reticulum stress or targeting IRE1α?XBP1 signalling may help to restore the metabolic fitness and anti-tumour capacity of T cells in cancer hosts.Fil: Song, Minkyung. Weill Cornell Medicine; Estados UnidosFil: Sandoval, Tito A.. Weill Cornell Medicine; Estados UnidosFil: Chae, Chang-Suk. Weill Cornell Medicine; Estados UnidosFil: Chopra, Sahil. Weill Cornell Medicine; Estados UnidosFil: Tan, Chen. Weill Cornell Medicine; Estados UnidosFil: Rutkowski, Melanie R.. University of Virginia; Estados UnidosFil: Raundhal, Mahesh. Dana Farber Cancer Institute; Estados Unidos. Harvard Medical School; Estados UnidosFil: Chaurio, Ricardo A.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Payne, Kyle K.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Konrad, Csaba. Weill Cornell Medicine; Estados UnidosFil: Bettigole, Sarah E.. Quentis Therapeutics Inc.; Estados UnidosFil: Shin, Hee Rae. Quentis Therapeutics Inc.; Estados UnidosFil: Crowley, Michael J. P.. Weill Cornell Graduate School of Medical Sciences; Estados UnidosFil: Cerliani, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Kossenkov, Andrew V.. The Wistar Institute; Estados UnidosFil: Motorykin, Ievgen. Weill Cornell Medicine,; Estados UnidosFil: Zhang, Sheng. Weill Cornell Medicine,; Estados UnidosFil: Manfredi, Giovanni. Weill Cornell Medicine,; Estados UnidosFil: Zamarin, Dmitriy. Memorial Sloan Kettering Cancer Center; Estados UnidosFil: Holcomb, Kevin. Weill Cornell Medicine,; Estados UnidosFil: Rodriguez, Paulo C.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Rabinovich, Gabriel Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Conejo Garcia, Jose R.. H. Lee Moffitt Cancer Center & Research Institute; Estados UnidosFil: Glimcher, Laurie H.. Dana Farber Cancer Institute; Estados Unidos. Harvard Medical School; Estados UnidosFil: Cubillos-Ruiz, Juan R.. Weill Graduate School Of Medical Sciences; Estados Unidos. Weill Graduate School Of Medical Sciences; Estados Unido

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

    Get PDF
    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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