Publications

576 Publications visible to you, out of a total of 576

Abstract (Expand)

How the network around ROS protects against oxidative stress and Parkinson's disease (PD), and how processes at the minutes timescale cause disease and aging after decades, remains enigmatic. Challenging whether the ROS network is as complex as it seems, we built a fairly comprehensive version thereof which we disentangled into a hierarchy of only five simpler subnetworks each delivering one type of robustness. The comprehensive dynamic model described in vitro data sets from two independent laboratories. Notwithstanding its five-fold robustness, it exhibited a relatively sudden breakdown, after some 80 years of virtually steady performance: it predicted aging. PD-related conditions such as lack of DJ-1 protein or increased alpha-synuclein accelerated the collapse, while antioxidants or caffeine retarded it. Introducing a new concept (aging-time-control coefficient), we found that as many as 25 out of 57 molecular processes controlled aging. We identified new targets for "life-extending interventions": mitochondrial synthesis, KEAP1 degradation, and p62 metabolism.

Authors: A. N Kolodkin, R. P. Sharma, A. M. Colangelo, A. Ignatenko, F. Martorana, D. Jennen, J. J. Briede, N. Brady, M. Barberis, T. D. G. A. Mondeel, M. Papa, V. Kumar, B. Peters, A. Skupin, L. Alberghina, R. Balling, H. V. Westerhoff

Date Published: 26th Oct 2020

Publication Type: Journal

Abstract (Expand)

The use of controlled mixed inocula of Saccharomyces cerevisiae and non-Saccharomyces yeasts is a common practice in winemaking, with Torulaspora delbrueckii, Lachancea thermotolerans and Metschnikowia pulcherrima being the most commonly used non-Saccharomyces species. Although S. cerevisiae is usually the dominant yeast at the end of mixed fermentations, some non-Saccharomyces species are also able to reach the late stages; such species may not grow in culture media, which is a status known as viable but non-culturable (VBNC). Thus, an accurate methodology to properly monitor viable yeast population dynamics during alcoholic fermentation is required to understand microbial interactions and the contribution of each species to the final product. Quantitative PCR (qPCR) has been found to be a good and sensitive method for determining the identity of the cell population, but it cannot distinguish the DNA from living and dead cells, which can overestimate the final population results. To address this shortcoming, viability dyes can be used to avoid the amplification and, therefore, the quantification of DNA from non-viable cells. In this study, we validated the use of PMAxx dye (an optimized version of propidium monoazide (PMA) dye) coupled with qPCR (PMAxx-qPCR), as a tool to monitor the viable population dynamics of the most common yeast species used in wine mixed fermentations (S. cerevisiae, T. delbrueckii, L. thermotolerans and M. pulcherrima), comparing the results with non-dyed qPCR and colony counting on differential medium. Our results showed that the PMAxx-qPCR assay used in this study is a reliable, specific and fast method for quantifying these four yeast species during the alcoholic fermentation process, being able to distinguish between living and dead yeast populations. Moreover, the entry into VBNC status was observed for the first time in L. thermotolerans and S. cerevisiae during alcoholic fermentation. Further studies are needed to unravel which compounds trigger this VBNC state during alcoholic fermentation in these species, which would help to better understand yeast interactions.

Authors: Yurena Navarro, María-Jesús Torija, Albert Mas, Gemma Beltran

Date Published: 1st Oct 2020

Publication Type: Journal

Abstract (Expand)

Aryl hydrocarbon receptor (AHR) activation by tryptophan (Trp) catabolites enhances tumor malignancy and suppresses anti-tumor immunity. The context specificity of AHR target genes has so far impeded systematic investigation of AHR activity and its upstream enzymes across human cancers. A pan-tissue AHR signature, derived by natural language processing, revealed that across 32 tumor entities, interleukin-4-induced-1 (IL4I1) associates more frequently with AHR activity than IDO1 or TDO2, hitherto recognized as the main Trp-catabolic enzymes. IL4I1 activates the AHR through the generation of indole metabolites and kynurenic acid. It associates with reduced survival in glioma patients, promotes cancer cell motility, and suppresses adaptive immunity, thereby enhancing the progression of chronic lymphocytic leukemia (CLL) in mice. Immune checkpoint blockade (ICB) induces IDO1 and IL4I1. As IDO1 inhibitors do not block IL4I1, IL4I1 may explain the failure of clinical studies combining ICB with IDO1 inhibition. Taken together, IL4I1 blockade opens new avenues for cancer therapy.

Authors: Ahmed Sadik, Luis F. Somarribas Patterson, Selcen Öztürk, Soumya R. Mohapatra, Verena Panitz, Philipp F. Secker, Pauline Pfänder, Stefanie Loth, Heba Salem, Mirja Tamara Prentzell, Bianca Berdel, Murat Iskar, Erik Faessler, Friederike Reuter, Isabelle Kirst, Verena Kalter, Kathrin I. Foerster, Evelyn Jäger, Carina Ramallo Guevara, Mansour Sobeh, Thomas Hielscher, Gernot Poschet, Annekathrin Reinhardt, Jessica C. Hassel, Marc Zapatka, Udo Hahn, Andreas von Deimling, Carsten Hopf, Rita Schlichting, Beate I. Escher, Jürgen Burhenne, Walter E. Haefeli, Naveed Ishaque, Alexander Böhme, Sascha Schäuble, Kathrin Thedieck, Saskia Trump, Martina Seiffert, Christiane A. Opitz

Date Published: 1st Sep 2020

Publication Type: Journal

Abstract

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Authors: Sara Sadat Aghamiri, Vidisha Singh, Aurélien Naldi, Tomáš Helikar, Sylvain Soliman, Anna Niarakis

Date Published: 15th Aug 2020

Publication Type: Journal

Abstract (Expand)

Droplet-based microfluidic systems offer a high potential for miniaturization and automation. Therefore, they are becoming an increasingly important tool in analytical chemistry, biosciences, and medicine. Heterogeneous assays commonly utilize magnetic beads as a solid phase. However, the sensitivity of state of the art microfluidic systems is limited by the high bead concentrations required for efficient extraction across the water–oil interface. Furthermore, current systems suffer from a lack of technical solutions for sequential measurements of multiple samples, limiting their throughput and capacity for automation. Taking advantage of the different wetting properties of hydrophilic and hydrophobic areas in the channels, we improve the extraction efficiency of magnetic beads from aqueous nanoliter-sized droplets by 2 orders of magnitude to the low μg/mL range. Furthermore, the introduction of a switchable magnetic trap enables repetitive capture and release of magnetic particles for sequential analysis of multiple samples, enhancing the throughput. In comparison to conventional ELISA-based sandwich immunoassays on microtiter plates, our microfluidic setup offers a 25–50-fold reduction of sample and reagent consumption with up to 50 technical replicates per sample. The enhanced sensitivity and throughput of this system open avenues for the development of automated detection of biomolecules at the nanoliter scale.

Authors: Lukas Metzler, Ulrike Rehbein, Jan-Niklas Schönberg, Thomas Brandstetter, Kathrin Thedieck, Jürgen Rühe

Date Published: 4th Aug 2020

Publication Type: Journal

Abstract (Expand)

Background: The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing segmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the "German Corona Consensus Dataset" (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data. Methods: Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats. Results: A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, anamnesis, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined. Conclusion: GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.

Authors: Julian Sass, Alexander Bartschke, Moritz Lehne, Andrea Essenwanger, Eugenia Rinaldi, Stefanie Rudolph, Kai Uwe Heitmann, Joerg Janne Vehreschild, Christof von Kalle, Sylvia Thun

Date Published: 29th Jul 2020

Publication Type: Journal

Abstract (Expand)

This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.

Authors: Dagmar Waltemath, Martin Golebiewski, Michael L Blinov, Padraig Gleeson, Henning Hermjakob, Michael Hucka, Esther Thea Inau, Sarah M Keating, Matthias König, Olga Krebs, Rahuman S Malik-Sheriff, David Nickerson, Ernst Oberortner, Herbert M Sauro, Falk Schreiber, Lucian Smith, Melanie I Stefan, Ulrike Wittig, Chris J Myers

Date Published: 29th Jun 2020

Publication Type: Journal

Abstract (Expand)

This special issue of the Journal of Integrative Bioinformatics presents papers related to the 10th COMBINE meeting together with the annual update of COMBINE standards in systems and synthetic biology.Not specified

Authors: Falk Schreiber, Björn Sommer, Tobias Czauderna, Martin Golebiewski, Thomas E. Gorochowski, Michael Hucka, Sarah M. Keating, Matthias König, Chris Myers, David Nickerson, Dagmar Waltemath

Date Published: 29th Jun 2020

Publication Type: Journal

Abstract (Expand)

The booming demand for environmentally benign industrial processes relies on the ability to quickly find or engineer a biocatalyst suitable to ideal process conditions. Both metagenomic approaches and directed evolution involve the screening of huge libraries of protein variants, which can only be managed reasonably by flexible platforms for (ultra)high-throughput profiling against the desired criteria. Here, we review the most recent additions toward a growing toolbox of versatile assays using fluorescence, absorbance and mass spectrometry readouts. While conventional solution based high-throughput screening in microtiter plate formats is still important, the implementation of novel screening protocols for microfluidic cell or droplet sorting systems supports technological advances for ultra-high-frequency screening that now can dramatically reduce the timescale of engineering projects. We discuss practical issues of scope, scalability, sensitivity and stereoselectivity for the improvement of biotechnologically relevant enzymes from different classes.

Authors: Yuriy V Sheludko, Wolf-Dieter Fessner

Date Published: 29th Jun 2020

Publication Type: Journal

Abstract

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Authors: Tatjana Walter, Nour Al Medani, Arthur Burgardt, Katarina Cankar, Lenny Ferrer, Anastasia Kerbs, Jin-Ho Lee, Melanie Mindt, Joe Max Risse, Volker F. Wendisch

Date Published: 1st Jun 2020

Publication Type: Journal

Abstract

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Authors: Zichen Wang, Amanda B Zheutlin, Yu-Han Kao, Kristin L Ayers, Susan J Gross, Patricia Kovatch, Sharon Nirenberg, Alexander W Charney, Girish N Nadkarni, Paul F O'Reilly, Allan C Just, Carol R Horowitz, Glenn Martin, Andrea D Branch, Benjamin S Glicksberg, Dennis S Charney, David L Reich, William K Oh, Eric E Schadt, Rong Chen, Li Li

Date Published: 4th May 2020

Publication Type: Misc

Abstract (Expand)

The alcohol content in wine has increased due to external factors in recent decades. In recent reports, some non-Saccharomyces yeast species have been confirmed to reduce ethanol during the alcoholic fermentation process. Thus, an efficient screening of non-Saccharomyces yeasts with low ethanol yield is required due to the broad diversity of these yeasts. In this study, we proposed a rapid method for selecting strains with a low ethanol yield from forty-five non-Saccharomyces yeasts belonging to eighteen species. Single fermentations were carried out for this rapid selection. Then, sequential fermentations in synthetic and natural must were conducted with the selected strains to confirm their capacity to reduce ethanol compared with that of Saccharomyces cerevisiae. The results showed that ten non-Saccharomyces strains were able to reduce the ethanol content, namely, Hanseniaspora uvarum (2), Issatchenkia terricola (1), Metschnikowia pulcherrima (2), Lachancea thermotolerans (1), Saccharomycodes ludwigii (1), Torulaspora delbrueckii (2), and Zygosaccharomyces bailii (1). Compared with S. cerevisiae, the ethanol reduction of the selected strains ranged from 0.29 to 1.39% (v/v). Sequential inoculations of M. pulcherrima (Mp51 and Mp FA) and S. cerevisiae reduced the highest concentration of ethanol by 1.17 to 1.39% (v/v) in synthetic or natural must. Second, sequential fermentations with Z. bailii (Zb43) and T. delbrueckii (Td Pt) performed in natural must yielded ethanol reductions of 1.02 and 0.84% (v/v), respectively.

Authors: Xiaolin Zhu, Yurena Navarro, Albert Mas, María-Jesús Torija, Gemma Beltran

Date Published: 1st May 2020

Publication Type: Journal

Abstract (Expand)

Many cancer cells consume glutamine at high rates; counterintuitively, they simultaneously excrete glutamate, the first intermediate in glutamine metabolism. Glutamine consumption has been linked to replenishment of tricarboxylic acid cycle (TCA) intermediates and synthesis of adenosine triphosphate (ATP), but the reason for glutamate excretion is unclear. Here, we dynamically profile the uptake and excretion fluxes of a liver cancer cell line (HepG2) and use genome-scale metabolic modeling for in-depth analysis. We find that up to 30% of the glutamine is metabolized in the cytosol, primarily for nucleotide synthesis, producing cytosolic glutamate. We hypothesize that excreting glutamate helps the cell to increase the nucleotide synthesis rate to sustain growth. Indeed, we show experimentally that partial inhibition of glutamate excretion reduces cell growth. Our integrative approach thus links glutamine addiction to glutamate excretion in cancer and points toward potential drug targets.

Authors: Avlant Nilsson, Jurgen R. Haanstra, Martin Engqvist, Albert Gerding, Barbara M. Bakker, Ursula Klingmüller, Bas Teusink, Jens Nielsen

Date Published: 27th Apr 2020

Publication Type: Journal

Abstract (Expand)

The Simulation Foundry (SF) is a modular workflow for the automated creation of molecular modeling (MM) data. MM allows for the reliable prediction of the microscopic and macroscopic properties of multicomponent systems from first principles. The SF makes MM repeatable, replicable, and findable, accessible, interoperable, and reusable (F.A.I.R.). The SF uses a standardized data structure and file naming convention, allowing for replication on different supercomputers and re-entrancy. We focus on keeping the SF simple by basing it on scripting languages that are widely used by the MM community (bash, Python) and making it reusable and re-editable. The SF was developed to assist expert users in performing parameter studies of multicomponent systems by high throughput molecular dynamics simulations. The usability of the SF is demonstrated by simulations of thermophysical properties of binary mixtures. A standardized data exchange format enables the integration of simulated data with data from experiments. The SF also provides a complete documentation of how the results were obtained, thus assigning provenance. Increasing computational power facilitates the intensification of the simulation process and requires automation and modularity. The SF provides a community platform on which to integrate new methods and create data that is reproducible and transparent (https://fairdomhub.org/studies/639/snapshots/1, https://fairdomhub.org/studies/639/snapshots/2).

Authors: Gudrun Gygli, Juergen Pleiss

Date Published: 27th Apr 2020

Publication Type: Journal

Abstract (Expand)

Background and aims: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has recently spread worldwide and been declared a pandemic. We aim to describe here the various clinical presentations of this disease by examining eleven cases. Methods: Electronic medical records of 11 patients with COVID-19 were collected and demographics, clinical manifestations, outcomes, key laboratory results, and radiological images are discussed. Results: The clinical course of the eleven cases demonstrated the complexity of the COVID-19 profile with different clinical presentations. Clinical manifestations range from asymptomatic cases to patients with mild and severe symptoms, with or without pneumonia. Laboratory detection of the viral nucleic acid can yield false-negative results, and serological testing of virus specific IgG and IgM antibodies should be used as an alternative for diagnosis. Patients with common allergic diseases did not develop distinct symptoms and severe courses. Cases with a pre-existing condition of chronic obstructive pulmonary disease or complicated with a secondary bacterial pneumonia were more severe. Conclusion: All different clinical characteristics of COVID-19 should be taken into consideration to identify patients that need to be in strict quarantine for the efficient containment of the pandemic.

Authors: Xiang Dong, Yi-yuan Cao, Xiao-xia Lu, Jin-jin Zhang, Hui Du, You-qin Yan, Cezmi A. Akdis, Ya-dong Gao

Date Published: 6th Apr 2020

Publication Type: Journal

Abstract

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Authors: Michael Getz, Yafei Wang, Gary An, Maansi Asthana, Andrew Becker, Chase Cockrell, Nicholson Collier, Morgan Craig, Courtney L. Davis, James R. Faeder, Ashlee N. Ford Versypt, Tarunendu Mapder, Juliano F. Gianlupi, James A. Glazier, Sara Hamis, Randy Heiland, Thomas Hillen, Dennis Hou, Mohammad Aminul Islam, Adrianne L. Jenner, Furkan Kurtoglu, Caroline I. Larkin, Bing Liu, Fiona Macfarlane, Pablo Maygrundter, Penelope A Morel, Aarthi Narayanan, Jonathan Ozik, Elsje Pienaar, Padmini Rangamani, Ali Sinan Saglam, Jason Edward Shoemaker, Amber M. Smith, Jordan J.A. Weaver, Paul Macklin

Date Published: 5th Apr 2020

Publication Type: Journal

Abstract (Expand)

In 2019, a new coronavirus (2019-nCoV) infecting Humans has emerged in Wuhan, China. Its genome has been sequenced and the genomic information promptly released. Despite a high similarity with the genome sequence of SARS-CoV and SARS-like CoVs, we identified a peculiar furin-like cleavage site in the Spike protein of the 2019-nCoV, lacking in the other SARS-like CoVs. In this article, we discuss the possible functional consequences of this cleavage site in the viral cycle, pathogenicity and its potential implication in the development of antivirals.

Authors: B. Coutard, C. Valle, X. de Lamballerie, B. Canard, N.G. Seidah, E. Decroly

Date Published: 1st Apr 2020

Publication Type: Journal

Abstract

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Authors: Michael Letko, Andrea Marzi, Vincent Munster

Date Published: 1st Apr 2020

Publication Type: Journal

Abstract

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Authors: Justin Stebbing, Anne Phelan, Ivan Griffin, Catherine Tucker, Olly Oechsle, Dan Smith, Peter Richardson

Date Published: 1st Apr 2020

Publication Type: Journal

Abstract

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Authors: Shuai Xia, Meiqin Liu, Chao Wang, Wei Xu, Qiaoshuai Lan, Siliang Feng, Feifei Qi, Linlin Bao, Lanying Du, Shuwen Liu, Chuan Qin, Fei Sun, Zhengli Shi, Yun Zhu, Shibo Jiang, Lu Lu

Date Published: 1st Apr 2020

Publication Type: Journal

Abstract (Expand)

During its first two and a half months, the recently emerged 2019 novel coronavirus, SARS-CoV-2, has already infected over one-hundred thousand people worldwide and has taken more than four thousand lives. However, the swiftly spreading virus also caused an unprecedentedly rapid response from the research community facing the unknown health challenge of potentially enormous proportions. Unfortunately, the experimental research to understand the molecular mechanisms behind the viral infection and to design a vaccine or antivirals is costly and takes months to develop. To expedite the advancement of our knowledge, we leveraged data about the related coronaviruses that is readily available in public databases and integrated these data into a single computational pipeline. As a result, we provide comprehensive structural genomics and interactomics roadmaps of SARS-CoV-2 and use this information to infer the possible functional differences and similarities with the related SARS coronavirus. All data are made publicly available to the research community.

Authors: Suhas Srinivasan, Hongzhu Cui, Ziyang Gao, Ming Liu, Senbao Lu, Winnie Mkandawire, Oleksandr Narykov, Mo Sun, Dmitry Korkin

Date Published: 1st Apr 2020

Publication Type: Journal

Abstract (Expand)

The novel coronavirus pneumonia (COVID-19) is an infectious acute respiratory infection caused by the novel coronavirus. The virus is a positive-strand RNA virus with high homology to bat coronavirus. In this study, conserved domain analysis, homology modeling, and molecular docking were used to compare the biological roles of certain proteins of the novel coronavirus. The results showed the ORF8 and surface glycoprotein could bind to the porphyrin, respectively. At the same time, orf1ab, ORF10, and ORF3a proteins could coordinate attack the heme on the 1-beta chain of hemoglobin to dissociate the iron to form the porphyrin. The attack will cause less and less hemoglobin that can carry oxygen and carbon dioxide. The lung cells have extremely intense poisoning and inflammatory due to the inability to exchange carbon dioxide and oxygen frequently, which eventually results in ground-glass-like lung images. The mechanism also interfered with the normal heme anabolic pathway of the human body, is expected to result in human disease. According to the validation analysis of these finds, chloroquine could prevent orf1ab, ORF3a, and ORF10 to attack the heme to form the porphyrin, and inhibit the binding of ORF8 and surface glycoproteins to porphyrins to a certain extent, effectively relieve the symptoms of respiratory distress. Favipiravir could inhibit the envelope protein and ORF7a protein bind to porphyrin, prevent the virus from entering host cells, and catching free porphyrins. Because the novel coronavirus is dependent on porphyrins, it may originate from an ancient virus. Therefore, this research is of high value to contemporary biological experiments, disease prevention, and clinical treatment.

Authors: Liu Wenzhong, Li Hualan

Date Published: 30th Mar 2020

Publication Type: Journal

Abstract

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Authors: Muthiah Vaduganathan, Orly Vardeny, Thomas Michel, John J.V. McMurray, Marc A. Pfeffer, Scott D. Solomon

Date Published: 30th Mar 2020

Publication Type: Journal

Abstract

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Authors: Guang Chen, Di Wu, Wei Guo, Yong Cao, Da Huang, Hongwu Wang, Tao Wang, Xiaoyun Zhang, Huilong Chen, Haijing Yu, Xiaoping Zhang, Minxia Zhang, Shiji Wu, Jianxin Song, Tao Chen, Meifang Han, Shusheng Li, Xiaoping Luo, Jianping Zhao, Qin Ning

Date Published: 27th Mar 2020

Publication Type: Journal

Abstract (Expand)

The pandemic caused by emerging coronavirus SARS-CoV-2 presents a serious global public health emergency in urgent need of prophylactic and therapeutic interventions. SARS CoV-2 cellular entry depends on binding between the viral Spike protein receptor-binding domain (RBD) and the angiotensin converting enzyme 2 (ACE2) target cell receptor. Here, we report on the isolation and characterization of 206 RBD-specific monoclonal antibodies (mAbs) derived from single B cells of eight SARS-CoV-2 infected individuals. These mAbs come from diverse families of antibody heavy and light chains without apparent enrichment for particular families in the repertoire. In samples from one patient selected for further analyses, we found coexistence of germline and germline divergent clones. Both clone types demonstrated impressive binding and neutralizing activity against pseudovirus and live SARS-CoV-2. However, the antibody neutralizing potency is determined by competition with ACE2 receptor for RBD binding. Surprisingly, none of the SARS CoV 2 antibodies nor the infected plasma cross-reacted with RBDs from either SARS CoV or MERS CoV although substantial plasma cross reactivity to the trimeric Spike proteins from SARS-CoV and MERS-CoV was found. These results suggest that antibody response to RBDs is viral species-specific while that cross-recognition target regions outside the RBD. The specificity and neutralizing characteristics of this plasma cross-reactivity requires further investigation. Nevertheless, the diverse and potent neutralizing antibodies identified here are promising candidates for prophylactic and therapeutic SARS-CoV-2 interventions.

Authors: Bin Ju, Qi Zhang, Xiangyang Ge, Ruoke Wang, Jiazhen Yu, Sisi Shan, Bing Zhou, Shuo Song, Xian Tang, Jinfang Yu, Jiwan Ge, Jun Lan, Jing Yuan, Haiyan Wang, Juanjuan Zhao, Shuye Zhang, Youchun Wang, Xuanling Shi, Lei Liu, Xinquan Wang, Zheng Zhang, Linqi Zhang

Date Published: 25th Mar 2020

Publication Type: Tech report

Abstract (Expand)

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 67 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

Authors: David E. Gordon, Gwendolyn M. Jang, Mehdi Bouhaddou, Jiewei Xu, Kirsten Obernier, Matthew J. O’Meara, Jeffrey Z. Guo, Danielle L. Swaney, Tia A. Tummino, Ruth Hüttenhain, Robyn M. Kaake, Alicia L. Richards, Beril Tutuncuoglu, Helene Foussard, Jyoti Batra, Kelsey Haas, Maya Modak, Minkyu Kim, Paige Haas, Benjamin J. Polacco, Hannes Braberg, Jacqueline M. Fabius, Manon Eckhardt, Margaret Soucheray, Melanie J. Bennett, Merve Cakir, Michael J McGregor, Qiongyu Li, Zun Zar Chi Naing, Yuan Zhou, Shiming Peng, Ilsa T. Kirby, James E. Melnyk, John S. Chorba, Kevin Lou, Shizhong A. Dai, Wenqi Shen, Ying Shi, Ziyang Zhang, Inigo Barrio-Hernandez, Danish Memon, Claudia Hernandez-Armenta, Christopher J.P. Mathy, Tina Perica, Kala B. Pilla, Sai J. Ganesan, Daniel J. Saltzberg, Rakesh Ramachandran, Xi Liu, Sara B. Rosenthal, Lorenzo Calviello, Srivats Venkataramanan, Yizhu Lin, Stephanie A. Wankowicz, Markus Bohn, Raphael Trenker, Janet M. Young, Devin Cavero, Joe Hiatt, Theo Roth, Ujjwal Rathore, Advait Subramanian, Julia Noack, Mathieu Hubert, Ferdinand Roesch, Thomas Vallet, Björn Meyer, Kris M. White, Lisa Miorin, David Agard, Michael Emerman, Davide Ruggero, Adolfo García-Sastre, Natalia Jura, Mark von Zastrow, Jack Taunton, Olivier Schwartz, Marco Vignuzzi, Christophe d’Enfert, Shaeri Mukherjee, Matt Jacobson, Harmit S. Malik, Danica G. Fujimori, Trey Ideker, Charles S. Craik, Stephen Floor, James S. Fraser, John Gross, Andrej Sali, Tanja Kortemme, Pedro Beltrao, Kevan Shokat, Brian K. Shoichet, Nevan J. Krogan

Date Published: 22nd Mar 2020

Publication Type: Unpublished

Abstract (Expand)

The COVID-2019 disease caused by the SARS-CoV-2 virus (aka 2019-nCoV) has raised significant health concerns in China and worldwide. While novel drug discovery and vaccine studies are long, repurposing old drugs against the COVID-2019 epidemic can help identify treatments, with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter Phase 3 or 4 or can be used directly in clinical settings. In this study, we presented a novel network based drug repurposing platform to identify potential drugs for the treatment of COVID-2019. We first analysed the genome sequence of SARS-CoV-2 and identified SARS as the closest disease, based on genome similarity between both causal viruses, followed by MERS and other human coronavirus diseases. Using our AutoSeed pipeline (text mining and database searches), we obtained 34 COVID-2019-related genes. Taking those genes as seeds, we automatically built a molecular network for which our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules and finally suggested 78 drugs to repurpose. Following manual filtering based on clinical knowledge, we re-prioritized 30 potential repurposable drugs against COVID-2019 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide) . We hope that this data can provide critical insights into SARS-CoV-2 biology and help design rapid clinical trials of treatments against COVID-2019.

Authors: Xu Li, Jinchao Yu, Zhiming Zhang, Jing Ren, Alex E. Peluffo, Wen Zhang, Yujie Zhao, Kaijing Yan, Daniel Cohen, Wenjia Wang

Date Published: 18th Mar 2020

Publication Type: Tech report

Abstract

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Authors: Irani Thevarajan, Thi H. O. Nguyen, Marios Koutsakos, Julian Druce, Leon Caly, Carolien E. van de Sandt, Xiaoxiao Jia, Suellen Nicholson, Mike Catton, Benjamin Cowie, Steven Y. C. Tong, Sharon R. Lewin, Katherine Kedzierska

Date Published: 16th Mar 2020

Publication Type: Journal

Abstract (Expand)

The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and replication. SARS-CoV-2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS-CoV-2 infection. Our data provide a rich resource for future investigations of COVID-19 infection and pathogenesis.

Authors: Soeren Lukassen, Robert Lorenz Chua, Timo Trefzer, Nicolas C. Kahn, Marc A. Schneider, Thomas Muley, Hauke Winter, Michael Meister, Carmen Veith, Agnes W. Boots, Bianca P. Hennig, Michael Kreuter, Christian Conrad, Roland Eils

Date Published: 14th Mar 2020

Publication Type: Tech report

Abstract (Expand)

Currently, COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread around the world; nevertheless, so far there exist no specific antiviral drugs for treatment of the disease, which poses great challenge to control and contain the virus. Here, we reported a research finding that SARS-CoV-2 invaded host cells via a novel route of CD147-spike protein (SP). SP bound to CD147, a receptor on the host cells, thereby mediating the viral invasion. Our further research confirmed this finding. First, in vitro antiviral tests indicated Meplazumab, an anti-CD147 humanized antibody, significantly inhibited the viruses from invading host cells, with an EC50 of 24.86 μg/mL and IC50 of 15.16 μg/mL. Second, we validated the interaction between CD147 and SP, with an affinity constant of 1.85×10-7M. Co-Immunoprecipitation and ELISA also confirmed the binding of the two proteins. Finally, the localization of CD147 and SP was observed in SARS-CoV-2 infected Vero E6 cells by immuno-electron microscope. Therefore, the discovery of the new route CD147-SP for SARS-CoV-2 invading host cells provides a critical target for development of specific antiviral drugs.

Authors: Ke Wang, Wei Chen, Yu-Sen Zhou, Jian-Qi Lian, Zheng Zhang, Peng Du, Li Gong, Yang Zhang, Hong-Yong Cui, Jie-Jie Geng, Bin Wang, Xiu-Xuan Sun, Chun-Fu Wang, Xu Yang, Peng Lin, Yong-Qiang Deng, Ding Wei, Xiang-Min Yang, Yu-Meng Zhu, Kui Zhang, Zhao-Hui Zheng, Jin-Lin Miao, Ting Guo, Ying Shi, Jun Zhang, Ling Fu, Qing-Yi Wang, Huijie Bian, Ping Zhu, Zhi-Nan Chen

Date Published: 14th Mar 2020

Publication Type: Tech report

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