mSpecs: a software tool for the administration and editing of mass spectral libraries in the field of metabolomics

<p>Abstract</p> <p>Background</p> <p>Metabolome analysis with GC/MS has meanwhile been established as one of the "omics" techniques. Compound identification is done by comparison of the MS data with compound libraries. Mass spectral libraries in the field of metabolomics ought to connect the relevant mass traces of the metabolites to other relevant data, e.g. formulas, chemical structures, identification numbers to other databases etc. Since existing solutions are either commercial and therefore only available for certain instruments or not capable of storing such information, there is need to provide a software tool for the management of such data.</p> <p>Results</p> <p>Here we present mSpecs, an open source software tool to manage mass spectral data in the field of metabolomics. It provides editing of mass spectra and virtually any associated information, automatic calculation of formulas and masses and is extensible by scripts. The graphical user interface is capable of common techniques such as copy/paste, undo/redo and drag and drop. It owns import and export filters for the major public file formats in order to provide compatibility to commercial instruments.</p> <p>Conclusion</p> <p>mSpecs is a versatile tool for the management and editing of mass spectral libraries in the field of metabolomics. Beyond that it provides capabilities for the automatic management of libraries though its scripting functionality. mSpecs can be used on all major platforms and is licensed under the GNU General Public License and available at <url>http://mspecs.tu-bs.de</url>.</p

KID - an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information of enzymes

<p>Abstract</p> <p>Background</p> <p>The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger projects aiming at the analysis, modelling and simulation of biological networks as well as large scale comparison of cellular properties. It is therefore essential that biological knowledge is easily accessible. However, most information is contained in the written literature in an unstructured way, so that methods for the systematic extraction of knowledge directly from the primary literature have to be deployed.</p> <p>Description</p> <p>Here we present a text mining algorithm for the extraction of kinetic information such as K_M, K_i, k_catetc. as well as associated information such as enzyme names, EC numbers, ligands, organisms, localisations, pH and temperatures. Using this rule- and dictionary-based approach, it was possible to extract 514,394 kinetic parameters of 13 categories (K_M, K_i, k_cat, k_cat/K_M, V_max, IC₅₀, S_0.5, K_d, K_a, t_1/2, pI, n_H, specific activity, V_max/K_M) from about 17 million PubMed abstracts and combine them with other data in the abstract.</p> <p>A manual verification of approx. 1,000 randomly chosen results yielded a recall between 51% and 84% and a precision ranging from 55% to 96%, depending of the category searched.</p> <p>The results were stored in a database and are available as "KID the KInetic Database" via the internet.</p> <p>Conclusions</p> <p>The presented algorithm delivers a considerable amount of information and therefore may aid to accelerate the research and the automated analysis required for today's systems biology approaches. The database obtained by analysing PubMed abstracts may be a valuable help in the field of chemical and biological kinetics. It is completely based upon text mining and therefore complements manually curated databases.</p> <p>The database is available at <url>http://kid.tu-bs.de</url>. The source code of the algorithm is provided under the GNU General Public Licence and available on request from the author.</p

Introduction. Trust and Narratives of Crisis and Catastrophe

Introduction to the Special Issue by the Guest Editors

Entwicklung einer Textminingmethode zur automatisierten Extraktion von kinetischen Informationen aus der Literatur

Die Menge an verfügbaren biologischen Informationen ist über die letzten Jahre stetig angestiegen. Es ist daher essentiell, dass das enthaltene Wissen leicht zugänglich gemacht wird, wie z.B. in Datenbänken. Zum Erstellen solcher Datenbänke können Methoden zur automatischen Extraktion dieser Informationen verwendet werden. Eine pragmatische Methode zur Extraktion kinetischer Informationen aus ca. 17 Millionen Abstracts der PubMed unter Verwendung von Lexika wurde entwickelt. Es wurden Informationen zu KM, Ki, kcat, kcat/KM, Vmax, IC50, S0.5, Kd, Ka, t1/2, pI, Enzymnamen, EC Nummern, Liganden, Organismen, Lokalisationen, pH-Wert und Temperatur extrahiert. 509.153 kinetische Informationen konnten extrahiert werden, mit einer Precision von 55% bis zu 96% und einem Recall von 51% bis zu 84%. Die erhaltenen Informationen sind in der Datenbank "KID the KInetic Database" im Internet zugänglich

Inhibitors of dihydroorotate dehydrogenase cooperate with molnupiravir and N4-hydroxycytidine to suppress SARS-CoV-2 replication

Funding Information: We thank Thorsten Wolff, Daniel Bourquain, Jessica Schulz, and Christian Mache from the Robert-Koch Institute and Martin Beer from the Friedrich Loeffler Institute (FLI) for providing isolates of SARS-CoV-2 variants. We thank Anna Kraft and Gabriele Czerwinski (both FLI) for support in the preparation of samples for pathology, and Catherine Hambly (University of Aberdeen) for help with daily energy expenditure measurements. We would like to thank Cathrin Bierwirth (University Medical Center Göttingen), Isabell Schulz, Anne-Kathrin Donner, and Frank-Thorben Peters for excellent technician assistance and Jasmin Fertey and Alexandra Rockstroh for providing the virus stocks for the mice experiment (Fraunhofer Institute IZI Leipzig). We acknowledge support by the Open Access Publication Funds of the Göttingen University. KMS was a member of the Göttingen Graduate School GGNB during this work. This work was funded by the COVID-19 Forschungsnetzwerk Niedersachsen (COFONI) to MD, by the Federal Ministry of Education and Research Germany ( Bundesministerium für Bildung und Forschung; BMBF ; OrganSARS , 01KI2058 ) to SP and TM, and by a grant of the Max Planck Foundation to DG. Declaration of interests AS, HK, EP, and DV are employees of Immunic AG and own shares and/or stock-options of the parent company of Immunic AG, Immunic Inc. Some of the Immunic AG employees also hold patents for the Immunic compounds described in this manuscript (WO2012/001,148, WO03006425). KMS, AD, and MD are employees of University Medical Center Göttingen, which has signed a License Agreement with Immunic AG covering the combination of DHODH inhibitors and nucleoside analogs to treat viral infections, including COVID-19 (inventors: MD, KMS, and AD). The other authors declare no conflict of interest.Peer reviewedPublisher PD

In-depth analysis of T cell immunity and antibody responses in heterologous prime-boost-boost vaccine regimens against SARS-CoV-2 and Omicron variant.

With the emergence of novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Variants of Concern (VOCs), vaccination studies that elucidate the efficiency and effectiveness of a vaccination campaign are critical to assess the durability and the protective immunity provided by vaccines. SARS-CoV-2 vaccines have been found to induce robust humoral and cell-mediated immunity in individuals vaccinated with homologous vaccination regimens. Recent studies also suggest improved immune response against SARS-CoV-2 when heterologous vaccination strategies are employed. Yet, few data exist on the extent to which heterologous prime-boost-boost vaccinations with two different vaccine platforms have an impact on the T cell-mediated immune responses with a special emphasis on the currently dominantly circulating Omicron strain. In this study, we collected serum and peripheral blood mononuclear cells (PBMCs) from 57 study participants of median 35-year old's working in the health care field, who have received different vaccination regimens. Neutralization assays revealed robust but decreased neutralization of Omicron VOC, including BA.1 and BA.4/5, compared to WT SARS-CoV-2 in all vaccine groups and increased WT SARS-CoV-2 binding and neutralizing antibodies titers in homologous mRNA prime-boost-boost study participants. By investigating cytokine production, we found that homologous and heterologous prime-boost-boost-vaccination induces a robust cytokine response of CD4+ and CD8+ T cells. Collectively, our results indicate robust humoral and T cell mediated immunity against Omicron in homologous and heterologous prime-boost-boost vaccinated study participants, which might serve as a guide for policy decisions

A 32 kb Critical Region Excluding Y402H in CFH Mediates Risk for Age-Related Macular Degeneration

Complement factor H shows very strong association with Age-related Macular Degeneration (AMD), and recent data suggest that multiple causal variants are associated with disease. To refine the location of the disease associated variants, we characterized in detail the structural variation at CFH and its paralogs, including two copy number polymorphisms (CNP), CNP147 and CNP148, and several rare deletions and duplications. Examination of 34 AMD-enriched extended families (N = 293) and AMD cases (White N = 4210 Indian = 134; Malay = 140) and controls (White N = 3229; Indian = 117; Malay = 2390) demonstrated that deletion CNP148 was protective against AMD, independent of SNPs at CFH. Regression analysis of seven common haplotypes showed three haplotypes, H1, H6 and H7, as conferring risk for AMD development. Being the most common haplotype H1 confers the greatest risk by increasing the odds of AMD by 2.75-fold (95% CI = [2.51, 3.01]; p = 8.31×10−109); Caucasian (H6) and Indian-specific (H7) recombinant haplotypes increase the odds of AMD by 1.85-fold (p = 3.52×10−9) and by 15.57-fold (P = 0.007), respectively. We identified a 32-kb region downstream of Y402H (rs1061170), shared by all three risk haplotypes, suggesting that this region may be critical for AMD development. Further analysis showed that two SNPs within the 32 kb block, rs1329428 and rs203687, optimally explain disease association. rs1329428 resides in 20 kb unique sequence block, but rs203687 resides in a 12 kb block that is 89% similar to a noncoding region contained in ΔCNP148. We conclude that causal variation in this region potentially encompasses both regulatory effects at single markers and copy number

TMPRSS2-mediated SARS-CoV-2 uptake boosts innate immune activation, enhances cytopathology, and drives convergent virus evolution.

The accessory protease transmembrane protease serine 2 (TMPRSS2) enhances severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake into ACE2-expressing cells, although how increased entry impacts downstream viral and host processes remains unclear. To investigate this in more detail, we performed infection assays in engineered cells promoting ACE2-mediated entry with and without TMPRSS2 coexpression. Electron microscopy and inhibitor experiments indicated TMPRSS2-mediated cell entry was associated with increased virion internalization into endosomes, and partially dependent upon clathrin-mediated endocytosis. TMPRSS2 increased panvariant uptake efficiency and enhanced early rates of virus replication, transcription, and secretion, with variant-specific profiles observed. On the host side, transcriptional profiling confirmed the magnitude of infection-induced antiviral and proinflammatory responses were linked to uptake efficiency, with TMPRSS2-assisted entry boosting early antiviral responses. In addition, TMPRSS2-enhanced infections increased rates of cytopathology, apoptosis, and necrosis and modulated virus secretion kinetics in a variant-specific manner. On the virus side, convergent signatures of cell-uptake-dependent innate immune induction were recorded in viral genomes, manifesting as switches in dominant coupled Nsp3 residues whose frequencies were correlated to the magnitude of the cellular response to infection. Experimentally, we demonstrated that selected Nsp3 mutations conferred enhanced interferon antagonism. More broadly, we show that TMPRSS2 orthologues from evolutionarily diverse mammals facilitate panvariant enhancement of cell uptake. In summary, our study uncovers previously unreported associations, linking cell entry efficiency to innate immune activation kinetics, cell death rates, virus secretion dynamics, and convergent selection of viral mutations. These data expand our understanding of TMPRSS2's role in the SARS-CoV-2 life cycle and confirm its broader significance in zoonotic reservoirs and animal models