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1
Gintjee, Thomas J., Monica A. Donnelley, and George R. Thompson. "Aspiring Antifungals: Review of Current Antifungal Pipeline Developments." Journal of Fungi 6, no. 1 (February 25, 2020): 28. http://dx.doi.org/10.3390/jof6010028.
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Invasive fungal infections are associated with significant morbidity and mortality, and their management is restricted to a variety of agents from five established classes of antifungal medication. In practice, existing antifungal agents are often constrained by dose-limiting toxicities, drug interactions, and the routes of administration. An increasing prevalence of invasive fungal infections along with rising rates of resistance and the practical limitations of existing agents has created a demand for the development of new antifungals, particularly those with novel mechanisms of action. This article reviews antifungal agents currently in various stages of clinical development. New additions to existing antifungal classes will be discussed, including SUBA-itraconazole, a highly bioavailable azole, and amphotericin B cochleate, an oral amphotericin formulation, as well as rezafungin, a long-acting echinocandin capable of once-weekly administration. Additionally, novel first-in-class agents such as ibrexafungerp, an oral glucan synthase inhibitor with activity against various resistant fungal isolates, and olorofim, a pyrimidine synthesis inhibitor with a broad spectrum of activity and oral formulation, will be reviewed. Various other innovative antifungal agents and classes, including MGCD290, tetrazoles, and fosmanogepix, will also be examined.
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Blin, Kai, Simon Shaw, Katharina Steinke, Rasmus Villebro, Nadine Ziemert, Sang Yup Lee, Marnix H. Medema, and Tilmann Weber. "antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline." Nucleic Acids Research 47, W1 (April 29, 2019): W81—W87. http://dx.doi.org/10.1093/nar/gkz310.
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Abstract Secondary metabolites produced by bacteria and fungi are an important source of antimicrobials and other bioactive compounds. In recent years, genome mining has seen broad applications in identifying and characterizing new compounds as well as in metabolic engineering. Since 2011, the ‘antibiotics and secondary metabolite analysis shell—antiSMASH’ (https://antismash.secondarymetabolites.org) has assisted researchers in this, both as a web server and a standalone tool. It has established itself as the most widely used tool for identifying and analysing biosynthetic gene clusters (BGCs) in bacterial and fungal genome sequences. Here, we present an entirely redesigned and extended version 5 of antiSMASH. antiSMASH 5 adds detection rules for clusters encoding the biosynthesis of acyl-amino acids, β-lactones, fungal RiPPs, RaS-RiPPs, polybrominated diphenyl ethers, C-nucleosides, PPY-like ketones and lipolanthines. For type II polyketide synthase-encoding gene clusters, antiSMASH 5 now offers more detailed predictions. The HTML output visualization has been redesigned to improve the navigation and visual representation of annotations. We have again improved the runtime of analysis steps, making it possible to deliver comprehensive annotations for bacterial genomes within a few minutes. A new output file in the standard JavaScript object notation (JSON) format is aimed at downstream tools that process antiSMASH results programmatically.
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Van Daele, Ruth, Isabel Spriet, Joost Wauters, Johan Maertens, Toine Mercier, Sam Van Hecke, and Roger Brüggemann. "Antifungal drugs: What brings the future?" Medical Mycology 57, Supplement_3 (June 1, 2019): S328—S343. http://dx.doi.org/10.1093/mmy/myz012.
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AbstractThe high burden and growing prevalence of invasive fungal infections (IFIs), the toxicity and interactions associated with current antifungal drugs, as well as the increasing resistance, ask for the development of new antifungal drugs, preferably with a novel mode of action. Also, the availability of oral or once-weekly alternatives would enable ambulatory treatment resulting in an improved patient's comfort and therapy adherence. However, only one new azole and two new posaconazole-formulations were marketed over the last decade. This review focuses on the antifungal drugs in the pipeline undergoing clinical evaluation. First, the newest azole, isavuconazole, with its improved safety profile and reduction in DDIs, will be discussed. Moreover, there are two glucan synthase inhibitors (GSIs) in the antifungal pipeline: rezafungin (CD101), a long-acting echinocandin with an improved stability that enables once weekly administration, and SCY-078, an orally available GSI with efficacy against azole- and echinocandin resistant isolates. A new oral formulation of amphotericin B will also be presented. Moreover, the first representative of a new antifungal class, the orotomides, with a broad spectrum and no cross-resistance with current antifungal classes, will be discussed. Finally, an overview of other antifungals that are still in earlier clinical development phases, is provided.
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Gastaldelli, Amalia, Norbert Stefan, and Hans-Ulrich Häring. "Liver-targeting drugs and their effect on blood glucose and hepatic lipids." Diabetologia 64, no. 7 (April 20, 2021): 1461–79. http://dx.doi.org/10.1007/s00125-021-05442-2.
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AbstractThe global epidemic of non-alcoholic fatty liver disease (NAFLD) and steatohepatitis (NASH) and the high prevalence among individuals with type 2 diabetes has attracted the attention of clinicians specialising in liver disorders. Many drugs are in the pipeline for the treatment of NAFLD/NASH, and several glucose-lowering drugs are now being tested specifically for the treatment of liver disease. Among these are nuclear hormone receptor agonists (e.g. peroxisome proliferator-activated receptor agonists, farnesoid X receptor agonists and liver X receptor agonists), fibroblast growth factor-19 and -21, single, dual or triple incretins, sodium–glucose cotransporter inhibitors, drugs that modulate lipid or other metabolic pathways (e.g. inhibitors of fatty acid synthase, diacylglycerol acyltransferase-1, acetyl-CoA carboxylase and 11β-hydroxysteroid dehydrogenase type-1) or drugs that target the mitochondrial pyruvate carrier. We have reviewed the metabolic effects of these drugs in relation to improvement of diabetic hyperglycaemia and fatty liver disease, as well as peripheral metabolism and insulin resistance. Graphical abstract
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Joppe, Mirko, Edoardo D'Imprima, Nina Salustros, Karthik S. Paithankar, Janet Vonck, Martin Grininger, and Werner Kühlbrandt. "The resolution revolution in cryoEM requires high-quality sample preparation: a rapid pipeline to a high-resolution map of yeast fatty acid synthase." IUCrJ 7, no. 2 (January 25, 2020): 220–27. http://dx.doi.org/10.1107/s2052252519017366.
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Single-particle electron cryo-microscopy (cryoEM) has undergone a `resolution revolution' that makes it possible to characterize megadalton (MDa) complexes at atomic resolution without crystals. To fully exploit the new opportunities in molecular microscopy, new procedures for the cloning, expression and purification of macromolecular complexes need to be explored. Macromolecular assemblies are often unstable, and invasive construct design or inadequate purification conditions and sample-preparation methods can result in disassembly or denaturation. The structure of the 2.6 MDa yeast fatty acid synthase (FAS) has been studied by electron microscopy since the 1960s. Here, a new, streamlined protocol for the rapid production of purified yeast FAS for structure determination by high-resolution cryoEM is reported. Together with a companion protocol for preparing cryoEM specimens on a hydrophilized graphene layer, the new protocol yielded a 3.1 Å resolution map of yeast FAS from 15 000 automatically picked particles within a day. The high map quality enabled a complete atomic model of an intact fungal FAS to be built.
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Leber, Christopher A., C. Benjamin Naman, Lena Keller, Jehad Almaliti, Eduardo J. E. Caro-Diaz, Evgenia Glukhov, Valsamma Joseph, et al. "Applying a Chemogeographic Strategy for Natural Product Discovery from the Marine Cyanobacterium Moorena bouillonii." Marine Drugs 18, no. 10 (October 14, 2020): 515. http://dx.doi.org/10.3390/md18100515.
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The tropical marine cyanobacterium Moorena bouillonii occupies a large geographic range across the Indian and Western Tropical Pacific Oceans and is a prolific producer of structurally unique and biologically active natural products. An ensemble of computational approaches, including the creation of the ORCA (Objective Relational Comparative Analysis) pipeline for flexible MS1 feature detection and multivariate analyses, were used to analyze various M. bouillonii samples. The observed chemogeographic patterns suggested the production of regionally specific natural products by M. bouillonii. Analyzing the drivers of these chemogeographic patterns allowed for the identification, targeted isolation, and structure elucidation of a regionally specific natural product, doscadenamide A (1). Analyses of MS2 fragmentation patterns further revealed this natural product to be part of an extensive family of herein annotated, proposed natural structural analogs (doscadenamides B–J, 2–10); the ensemble of structures reflect a combinatorial biosynthesis using nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) components. Compound 1 displayed synergistic in vitro cancer cell cytotoxicity when administered with lipopolysaccharide (LPS). These discoveries illustrate the utility in leveraging chemogeographic patterns for prioritizing natural product discovery efforts.
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Freudenberg, Robert A., Luisa Wittemeier, Alexander Einhaus, Thomas Baier, and Olaf Kruse. "The Spermidine Synthase Gene SPD1: A Novel Auxotrophic Marker for Chlamydomonas reinhardtii Designed by Enhanced CRISPR/Cas9 Gene Editing." Cells 11, no. 5 (February 28, 2022): 837. http://dx.doi.org/10.3390/cells11050837.
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Biotechnological application of the green microalga Chlamydomonas reinhardtii hinges on the availability of selectable markers for effective expression of multiple transgenes. However, biological safety concerns limit the establishment of new antibiotic resistance genes and until today, only a few auxotrophic markers exist for C. reinhardtii. The recent improvements in gene editing via CRISPR/Cas allow directed exploration of new endogenous selectable markers. Since editing frequencies remain comparably low, a Cas9-sgRNA ribonucleoprotein (RNP) delivery protocol was strategically optimized by applying nitrogen starvation to the pre-culture, which improved successful gene edits from 10% to 66% after pre-selection. Probing the essential polyamine biosynthesis pathway, the spermidine synthase gene (SPD1) is shown to be a potent selectable marker with versatile biotechnological applicability. Very low levels of spermidine (0.75 mg/L) were required to maintain normal mixotrophic and phototrophic growth in newly designed spermidine auxotrophic strains. Complementation of these strains with a synthetic SPD1 gene was achieved when the mature protein was expressed in the cytosol or targeted to the chloroplast. This work highlights the potential of new selectable markers for biotechnology as well as basic research and proposes an effective pipeline for the identification of new auxotrophies in C. reinhardtii.
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Rehman, Abdur, Sajjad Ahmad, Farah Shahid, Aqel Albutti, Ameen S. S. Alwashmi, Mohammad Abdullah Aljasir, Naif Alhumeed, Muhammad Qasim, Usman Ali Ashfaq, and Muhammad Tahir ul Qamar. "Integrated Core Proteomics, Subtractive Proteomics, and Immunoinformatics Investigation to Unveil a Potential Multi-Epitope Vaccine against Schistosomiasis." Vaccines 9, no. 6 (June 16, 2021): 658. http://dx.doi.org/10.3390/vaccines9060658.
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Schistosomiasis is a parasitic infection that causes considerable morbidity and mortality in the world. Infections of parasitic blood flukes, known as schistosomes, cause the disease. No vaccine is available yet and thus there is a need to design an effective vaccine against schistosomiasis. Schistosoma japonicum, Schistosoma mansoni, and Schistosoma haematobium are the main pathogenic species that infect humans. In this research, core proteomics was combined with a subtractive proteomics pipeline to identify suitable antigenic proteins for the construction of a multi-epitope vaccine (MEV) against human-infecting Schistosoma species. The pipeline revealed two antigenic proteins—calcium binding and mycosubtilin synthase subunit C—as promising vaccine targets. T and B cell epitopes from the targeted proteins were predicted using multiple bioinformatics and immunoinformatics databases. Seven cytotoxic T cell lymphocytes (CTL), three helper T cell lymphocytes (HTL), and four linear B cell lymphocytes (LBL) epitopes were fused with a suitable adjuvant and linkers to design a 217 amino-acid-long MEV. The vaccine was coupled with a TLR-4 agonist (RS-09; Sequence: APPHALS) adjuvant to enhance the immune responses. The designed MEV was stable, highly antigenic, and non-allergenic to human use. Molecular docking, molecular dynamics (MD) simulations, and molecular mechanics/generalized Born surface area (MMGBSA) analysis were performed to study the binding affinity and molecular interactions of the MEV with human immune receptors (TLR2 and TLR4) and MHC molecules (MHC I and MHC II). The MEV expression capability was tested in an Escherichia coli (strain-K12) plasmid vector pET-28a(+). Findings of these computer assays proved the MEV as highly promising in establishing protective immunity against the pathogens; nevertheless, additional validation by in vivo and in vitro experiments is required to discuss its real immune-protective efficacy.
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Randhawa, Gurinder Jit, Ruchi Sharma, and Monika Singh. "Qualitative and Event-Specific Real-Time PCR Detection Methods for Bt Brinjal Event EE-1." Journal of AOAC INTERNATIONAL 95, no. 6 (November 1, 2012): 1733–39. http://dx.doi.org/10.5740/jaoacint.11-478.
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Abstract Bt brinjal event EE-1 with cry1Ac gene, expressing insecticidal protein against fruit and shoot borer, is the first genetically modified food crop in the pipeline for commercialization in India. Qualitative polymerase chain reaction (PCR) along with event-specific conventional as well as real-time PCR methods to characterize the event EE-1 is reported. A multiplex (pentaplex) PCR system simultaneously amplifying cry1Ac transgene, Cauliflower Mosaic Virus (CaMV) 35S promoter, nopaline synthase (nos) terminator, aminoglycoside adenyltransferase (aadA) marker gene, and a taxon-specific β-fructosidase gene in event EE-1 has been developed. Furthermore, construct-specific PCR, targeting the approximate 1.8 kb region of inserted gene construct comprising the region of CaMV 35S promoter and cry1Ac gene has also been developed. The LOD of developed EE-1 specific conventional PCR assay is 0.01%. The method performance of the reported real-time PCR assay was consistent with the acceptance criteria of Codex Alimentarius Commission ALINORM 10/33/23, with the LOD and LOQ values of 0.05%. The developed detection methods would not only facilitate effective regulatory compliance for identification of genetic traits, risk assessment, management, and postrelease monitoring, but also address consumer concerns and resolution of legal disputes.
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Juhás, Martin, Andrea Bachtíková, Daria Elżbieta Nawrot, Paulína Hatoková, Vinod Sukanth Kumar Pallabothula, Adéla Diepoltová, Ondřej Janďourek, et al. "Improving Antimicrobial Activity and Physico-Chemical Properties by Isosteric Replacement of 2-Aminothiazole with 2-Aminooxazole." Pharmaceuticals 15, no. 5 (May 6, 2022): 580. http://dx.doi.org/10.3390/ph15050580.
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Antimicrobial drug resistance is currently one of the most critical health issues. Pathogens resistant to last-resort antibiotics are increasing, and very few effective antibacterial agents have been introduced in recent years. The promising drug candidates are often discontinued in the primary stages of the drug discovery pipeline due to their unspecific reactivity (PAINS), toxicity, insufficient stability, or low water solubility. In this work, we investigated a series of substituted N-oxazolyl- and N-thiazolylcarboxamides of various pyridinecarboxylic acids. Final compounds were tested against several microbial species. In general, oxazole-containing compounds showed high activity against mycobacteria, especially Mycobacterium tuberculosis (best MICH37Ra = 3.13 µg/mL), including the multidrug-resistant strains. Promising activities against various bacterial and fungal strains were also observed. None of the compounds was significantly cytotoxic against the HepG2 cell line. Experimental measurement of lipophilicity parameter log k’w and water solubility (log S) confirmed significantly (typically two orders in logarithmic scale) increased hydrophilicity/water solubility of oxazole derivatives in comparison with their thiazole isosteres. Mycobacterial β-ketoacyl-acyl carrier protein synthase III (FabH) was suggested as a probable target by molecular docking and molecular dynamics simulations.
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Kulyashov, Mikhail, Sergey E. Peltek, and Ilya R. Akberdin. "A Genome-Scale Metabolic Model of 2,3-Butanediol Production by Thermophilic Bacteria Geobacillus icigianus." Microorganisms 8, no. 7 (July 4, 2020): 1002. http://dx.doi.org/10.3390/microorganisms8071002.
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The thermophilic strain of the genus Geobacillus, Geobacillus icigianus is a promising bacterial chassis for a wide range of biotechnological applications. In this study, we explored the metabolic potential of Geobacillus icigianus for the production of 2,3-butanediol (2,3-BTD), one of the cost-effective commodity chemicals. Here we present a genome-scale metabolic model iMK1321 for Geobacillus icigianus constructed using an auto-generating pipeline with consequent thorough manual curation. The model contains 1321 genes and includes 1676 reactions and 1589 metabolites, representing the most-complete and publicly available model of the genus Geobacillus. The developed model provides new insights into thermophilic bacterial metabolism and highlights new strategies for biotechnological applications of the strain. Our analysis suggests that Geobacillus icigianus has a potential for 2,3-butanediol production from a variety of utilized carbon sources, including glycerine, a common byproduct of biofuel production. We identified a set of solutions for enhancing 2,3-BTD production, including cultivation under anaerobic or microaerophilic conditions and decreasing the TCA flux to succinate via reducing citrate synthase activity. Both in silico predicted metabolic alternatives have been previously experimentally verified for closely related strains including the genus Bacillus.
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Canu, Nicolas, Carine Tellier, Morgan Babin, Robert Thai, Inès Ajel, Jérôme Seguin, Olivier Cinquin, et al. "Flexizyme-aminoacylated shortened tRNAs demonstrate that only the aminoacylated acceptor arms of the two tRNA substrates are required for cyclodipeptide synthase activity." Nucleic Acids Research 48, no. 20 (October 23, 2020): 11615–25. http://dx.doi.org/10.1093/nar/gkaa903.
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Abstract Cyclodipeptide synthases (CDPSs) use two aminoacyl-tRNAs (AA-tRNAs) to catalyse cyclodipeptide formation in a ping-pong mechanism. Despite intense studies of these enzymes in past years, the tRNA regions of the two substrates required for CDPS activity are poorly documented, mainly because of two limitations. First, previously studied CDPSs use two identical AA-tRNAs to produce homocyclodipeptides, thus preventing the discriminative study of the binding of the two substrates. Second, the range of tRNA analogues that can be aminoacylated by aminoacyl-tRNA synthetases is limited. To overcome the limitations, we studied a new model CDPS that uses two different AA-tRNAs to produce an heterocyclodipeptide. We also developed a production pipeline for the production of purified shortened AA-tRNA analogues (AA-minitRNAs). This method combines the use of flexizymes to aminoacylate a diversity of minitRNAs and their subsequent purifications by anion-exchange chromatography. Finally, we were able to show that aminoacylated molecules mimicking the entire acceptor arms of tRNAs were as effective a substrate as entire AA-tRNAs, thereby demonstrating that the acceptor arms of the two substrates are the only parts of the tRNAs required for CDPS activity. The method developed in this study should greatly facilitate future investigations of the specificity of CDPSs and of other AA-tRNAs-utilizing enzymes.
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Bustad, Helene J., Juha P. Kallio, Marta Vorland, Valeria Fiorentino, Sverre Sandberg, Caroline Schmitt, Aasne K. Aarsand, and Aurora Martinez. "Acute Intermittent Porphyria: An Overview of Therapy Developments and Future Perspectives Focusing on Stabilisation of HMBS and Proteostasis Regulators." International Journal of Molecular Sciences 22, no. 2 (January 12, 2021): 675. http://dx.doi.org/10.3390/ijms22020675.
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Acute intermittent porphyria (AIP) is an autosomal dominant inherited disease with low clinical penetrance, caused by mutations in the hydroxymethylbilane synthase (HMBS) gene, which encodes the third enzyme in the haem biosynthesis pathway. In susceptible HMBS mutation carriers, triggering factors such as hormonal changes and commonly used drugs induce an overproduction and accumulation of toxic haem precursors in the liver. Clinically, this presents as acute attacks characterised by severe abdominal pain and a wide array of neurological and psychiatric symptoms, and, in the long-term setting, the development of primary liver cancer, hypertension and kidney failure. Treatment options are few, and therapies preventing the development of symptomatic disease and long-term complications are non-existent. Here, we provide an overview of the disorder and treatments already in use in clinical practice, in addition to other therapies under development or in the pipeline. We also introduce the pathomechanistic effects of HMBS mutations, and present and discuss emerging therapeutic options based on HMBS stabilisation and the regulation of proteostasis. These are novel mechanistic therapeutic approaches with the potential of prophylactic correction of the disease by totally or partially recovering the enzyme functionality. The present scenario appears promising for upcoming patient-tailored interventions in AIP.
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Casiano, Ashlie Santaliz, Zeynep Madak-Erdogan, Dhruv Meta, Jonna Frasor, Garth Rauscher, and Kent Hoskins. "Abstract C020: Identification of metabolic and molecular mechanisms contributing to ER+ cancer disparities using a machine-learning pipeline." Cancer Epidemiology, Biomarkers & Prevention 32, no. 1_Supplement (January 1, 2023): C020. http://dx.doi.org/10.1158/1538-7755.disp22-c020.
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Abstract Background: African American (AA) women are less likely to develop breast cancer but when they do, their mortality rates are 40% higher compared to Non-Hispanic White (NHW) women. This disparity is particularly striking among ER+ breast cancer cases. The purpose of this study is to examine whether there are racial differences in metabolic and molecular pathways typically activated in patients with ER+ positive breast cancer. Methods: We collected plasma from AA and NHW cases and controls to conduct an untargeted metabolomics analysis using gas chromatography-mass spectrometry (GC-MS) to identify metabolites that are possibly altered in the different race groups. Statistical methods combined with multiple feature selection and prediction models were employed to identify race-specific altered metabolic signatures. This was followed by the identification of altered metabolic pathways with a focus on AA patients with breast cancer. The clinical significance of the findings was further examined in the PanCancer Atlas breast cancer data set. Results: We identified differential metabolic signatures between NHW and AA patients. In AA patients, we observed disturbed amino acid metabolism, while fatty acid metabolism was significant in NHW patients. By mapping these metabolites to genes, this study identified significant relations with regulators of metabolism such as methionine adenosyltransferase 1A (MAT1A), DNA Methyltransferases, Histone methyltransferases for AA individuals, and Fatty acid Synthase (FASN) and Monoacylglycerol lipase (MGL) for NHW individuals. Specific histone methyltransferase NELFE was overexpressed and associated with poor survival exclusively in AA individuals. Conclusion: We employ a comprehensive and novel approach that integrates multiple machine learning methods, and statistical methods, coupled with human functional pathway analyses. This metabolic profile of serum samples might be used to assess risk progression in AA individuals with ER+ breast cancer. To our knowledge, this is a novel finding that describes metabolic alterations in AA breast cancer and emphasizes a potential biological basis for breast cancer health disparities. Citation Format: Ashlie Santaliz Casiano, Zeynep Madak-Erdogan, Dhruv Meta, Jonna Frasor, Garth Rauscher, Kent Hoskins. Identification of metabolic and molecular mechanisms contributing to ER+ cancer disparities using a machine-learning pipeline [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C020.
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Wiegels, Tim, Joana Pereira, Ioan Vancea, Ciaran Carolan, Daria Beshnova, Philipp Heuser, and Victor Lamzin. "ARP/wARP for crystallographic model building and drug discovery." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C325. http://dx.doi.org/10.1107/s2053273314096740.
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The ARP/wARP software project combines automated model building and refinement into an unified approach for macromolecular crystal structure determination. The project is based on two decades of extensive research and development in the areas of macromolecular X-ray crystallography, informatics, data mining and statistical pattern recognition. ARP/wARP collects a vast amount of computationally efficient methods and provides easy-to-use pipelines for building models of proteins, nucleotides, ligands, as well as their complexes. All methods are intuitively accessible from the ArpNavigator [1], which grants direct visualisation and real-time interaction with model building results. Structures determined using ARP/wARP include histones, hsp70, viral proteases, an insect antifreeze protein, transferases, deadenylases, synthases, kinases, photolyases and the spliceosome. The novel release of ARP/wARP, version 7.4, comes with notable innovations for determining structures at medium-to-low resolution such as exploitation of non-crystallographic symmetry, improved protocols for model update and estimation of validity of built models. Joint releases with the CCP4 suite improve software development and integration, and make the installation and updates fast and convenient for the user. A novel procedure for the automatic identification of ligands in electron density maps is introduced. It is based on the sparse parameterisation of density clusters and the matching of the pseudo-atomic grids thus created to conformationally variant ligands using mathematical descriptors of molecular shape, size and topology. The integration of the ViCi web-server for in-silico ligand-based drug design and updated stereo-chemical restraints for ligand fitting make ARP/wARP an asset for crystallographic drug discovery pipelines.
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Zeng, Nanfang, Cong Wang, Siyu Liu, Qi Miao, Lei Zhou, Xinna Ge, Jun Han, Xin Guo, and Hanchun Yang. "Transcriptome Analysis Reveals Dynamic Gene Expression Profiles in Porcine Alveolar Macrophages in Response to the Chinese Highly Pathogenic Porcine Reproductive and Respiratory Syndrome Virus." BioMed Research International 2018 (2018): 1–23. http://dx.doi.org/10.1155/2018/1538127.
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Porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most economically important swine pathogens and causes reproductive failure in sows and respiratory disease in growing pigs. PRRSV mainly infects porcine alveolar macrophages (PAMs), leading to the subversion of innate and adaptive immunity of pigs. The transcriptome analysis of gene expression profiles in PRRSV-infected PAMs is essential for understanding the pathogenesis of PRRSV. Here we performed next-generation RNA sequencing and a comprehensive bioinformatics analysis to characterize the dynamic transcriptome landscapes in PAMs following PRRSV infection. Totally 38222 annotated mRNAs, 12987 annotated long noncoding RNAs (lncRNAs), and 17624 novel lncRNAs in PRRSV-infected PAMs were identified through a transcripts computational identification pipeline. The differentially expressed mRNAs and lncRNAs during PRRSV infection were characterized. Several differentially expressed transcripts were validated using qRT-PCR. Analyses on dynamic overrepresented GO terms and KEGG pathways in PRRSV-infected PAMs at different time points were performed. Meanwhile the genes involved in IFN-related signaling pathways, proinflammatory cytokines and chemokines, phagocytosis, and antigen presentation and processing were significantly downregulated, indicating the aberrant function of PAMs during PRRSV infection. Moreover, the differentially and highly expressed lncRNA XR_297549.1 was predicted to both cis-regulate and trans-regulate its neighboring gene, prostaglandin-endoperoxide synthase 2 (PTGS2), indicating its role in inflammatory response. Our findings reveal the transcriptome profiles and differentially expressed mRNAs and lncRNAs in PRRSV-infected PAMsin vitro, providing valuable information for further exploration of PRRSV pathogenesis.
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Salcius, Michael, Andras J. Bauer, Qin Hao, Shu Li, Antonin Tutter, Jacob Raphael, Wolfgang Jahnke, et al. "SEC-TID." Journal of Biomolecular Screening 19, no. 6 (February 19, 2014): 917–27. http://dx.doi.org/10.1177/1087057114522691.
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Bioactive small molecules are an invaluable source of therapeutics and chemical probes for exploring biological pathways. Yet, significant hurdles in drug discovery often come from lacking a comprehensive view of the target(s) for both early tool molecules and even late-stage drugs. To address this challenge, a method is provided that allows for assessing the interactions of small molecules with thousands of targets without any need to modify the small molecule of interest or attach any component to a surface. We describe size-exclusion chromatography for target identification (SEC-TID), a method for accurately and reproducibly detecting ligand-macromolecular interactions for small molecules targeting nucleic acid and several protein classes. We report the use of SEC-TID, with a library consisting of approximately 1000 purified proteins derived from the protein databank (PDB), to identify the efficacy targets tankyrase 1 and 2 for the Wnt inhibitor XAV939. In addition, we report novel interactions for the tumor-vascular disrupting agent vadimezan/ASA404 (interacting with farnesyl pyrophosphate synthase) and the diuretic mefruside (interacting with carbonic anhydrase XIII). We believe this method can dramatically enhance our understanding of the mechanism of action and potential liabilities for small molecules in drug discovery pipelines through comprehensive profiling of candidate druggable targets.
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Atencio, Librada A., Cristopher A. Boya P., Christian Martin H., Luis C. Mejía, Pieter C. Dorrestein, and Marcelino Gutiérrez. "Genome Mining, Microbial Interactions, and Molecular Networking Reveals New Dibromoalterochromides from Strains of Pseudoalteromonas of Coiba National Park-Panama." Marine Drugs 18, no. 9 (September 3, 2020): 456. http://dx.doi.org/10.3390/md18090456.
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The marine bacterial genus Pseudoalteromonas is known for their ability to produce antimicrobial compounds. The metabolite-producing capacity of Pseudoalteromonas has been associated with strain pigmentation; however, the genomic basis of their antimicrobial capacity remains to be explained. In this study, we sequenced the whole genome of six Pseudoalteromonas strains (three pigmented and three non-pigmented), with the purpose of identifying biosynthetic gene clusters (BGCs) associated to compounds we detected via microbial interactions along through MS-based molecular networking. The genomes were assembled and annotated using the SPAdes and RAST pipelines and mined for the identification of gene clusters involved in secondary metabolism using the antiSMASH database. Nineteen BGCs were detected for each non-pigmented strain, while more than thirty BGCs were found for two of the pigmented strains. Among these, the groups of genes of nonribosomal peptide synthetases (NRPS) that code for bromoalterochromides stand out the most. Our results show that all strains possess BGCs for the production of secondary metabolites, and a considerable number of distinct polyketide synthases (PKS) and NRPS clusters are present in pigmented strains. Furthermore, the molecular networking analyses revealed two new molecules produced during microbial interactions: the dibromoalterochromides D/D’ (11–12).
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He, Yi, Keren Fu, Peng Cheng, and Jianwei Zhang. "Facial Expression Recognition with Geometric Scattering on 3D Point Clouds." Sensors 22, no. 21 (October 29, 2022): 8293. http://dx.doi.org/10.3390/s22218293.
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As one of the pioneering data representations, the point cloud has shown its straightforward capacity to depict fine geometry in many applications, including computer graphics, molecular structurology, modern sensing signal processing, and more. However, unlike computer graphs obtained with auxiliary regularization techniques or from syntheses, raw sensor/scanner (metric) data often contain natural random noise caused by multiple extrinsic factors, especially in the case of high-speed imaging scenarios. On the other hand, grid-like imaging techniques (e.g., RGB images or video frames) tend to entangle interesting aspects with environmental variations such as pose/illuminations with Euclidean sampling/processing pipelines. As one such typical problem, 3D Facial Expression Recognition (3D FER) has been developed into a new stage, with remaining difficulties involving the implementation of efficient feature abstraction methods for high dimensional observations and of stabilizing methods to obtain adequate robustness in cases of random exterior variations. In this paper, a localized and smoothed overlapping kernel is proposed to extract discriminative inherent geometric features. By association between the induced deformation stability and certain types of exterior perturbations through manifold scattering transform, we provide a novel framework that directly consumes point cloud coordinates for FER while requiring no predefined meshes or other features/signals. As a result, our compact framework achieves 78.33% accuracy on the Bosphorus dataset for expression recognition challenge and 77.55% on 3D-BUFE.
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Tsivileva, Olga M., Oleg V. Koftin, and Nina V. Evseeva. "Coumarins as Fungal Metabolites with Potential Medicinal Properties." Antibiotics 11, no. 9 (August 26, 2022): 1156. http://dx.doi.org/10.3390/antibiotics11091156.
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Coumarins are a structurally varied set of 2H-chromen-2-one compounds categorized also as members of the benzopyrone group of secondary metabolites. Coumarin derivatives attract interest owing to their wide practical application and the unique reactivity of fused benzene and pyrone ring systems in molecular structure. Coumarins have their own specific fingerprints as antiviral, antimicrobial, antioxidant, anti-inflammatory, antiadipogenic, cytotoxic, apoptosis, antitumor, antitubercular, and cytotoxicity agents. Natural products have played an essential role in filling the pharmaceutical pipeline for thousands of years. Biological effects of natural coumarins have laid the basis of low-toxic and highly effective drugs. Presently, more than 1300 coumarins have been identified in plants, bacteria, and fungi. Fungi as cultivated microbes have provided many of the nature-inspired syntheses of chemically diverse drugs. Endophytic fungi bioactivities attract interest, with applications in fields as diverse as cancer and neuronal injury or degeneration, microbial and parasitic infections, and others. Fungal mycelia produce several classes of bioactive molecules, including a wide group of coumarins. Of promise are further studies of conditions and products of the natural and synthetic coumarins’ biotransformation by the fungal cultures, aimed at solving the urgent problem of searching for materials for biomedical engineering. The present review evaluates the fungal coumarins, their structure-related peculiarities, and their future therapeutic potential. Special emphasis has been placed on the coumarins successfully bioprospected from fungi, whereas an industry demand for the same coumarins earlier found in plants has faced hurdles. Considerable attention has also been paid to some aspects of the molecular mechanisms underlying the coumarins’ biological activity. The compounds are selected and grouped according to their cytotoxic, anticancer, antibacterial, antifungal, and miscellaneous effects.
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Ukkola, Anna M., Gab Abramowitz, and Martin G. De Kauwe. "A flux tower dataset tailored for land model evaluation." Earth System Science Data 14, no. 2 (February 3, 2022): 449–61. http://dx.doi.org/10.5194/essd-14-449-2022.
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Abstract. Eddy covariance flux towers measure the exchange of water, energy, and carbon fluxes between the land and atmosphere. They have become invaluable for theory development and evaluating land models. However, flux tower data as measured (even after site post-processing) are not directly suitable for land surface modelling due to data gaps in model forcing variables, inappropriate gap-filling, formatting, and varying data quality. Here we present a quality-control and data-formatting pipeline for tower data from FLUXNET2015, La Thuile, and OzFlux syntheses and the resultant 170-site globally distributed flux tower dataset specifically designed for use in land modelling. The dataset underpins the second phase of the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER), an international model intercomparison project encompassing >20 land surface and biosphere models. The dataset is provided in the Assistance for Land-surface Modelling Activities (ALMA) NetCDF format and is CF-NetCDF compliant. For forcing land surface models, the dataset provides fully gap-filled meteorological data that have had periods of low data quality removed. Additional constraints required for land models, such as reference measurement heights, vegetation types, and satellite-based monthly leaf area index estimates, are also included. For model evaluation, the dataset provides estimates of key water, carbon, and energy variables, with the latent and sensible heat fluxes additionally corrected for energy balance closure. The dataset provides a total of 1040 site years covering the period 1992–2018, with individual sites spanning from 1 to 21 years. The dataset is available at http://doi.org/10.25914/5fdb0902607e1 (Ukkola et al., 2021).
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Zeb, Samia, Amjad Ali, Sardar Muhammad Gulfam, and Habib Bokhari. "Preliminary Work Towards Finding Proteins as Potential Vaccine Candidates for Vibrio cholerae Pakistani Isolates through Reverse Vaccinology." Medicina 55, no. 5 (May 23, 2019): 195. http://dx.doi.org/10.3390/medicina55050195.
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Background and Objective: Vibrio cholerae continues to emerge as a dangerous pathogen because of increasing resistance to a number of antibiotics. This paper provides a solution to emerging antibiotic resistance by introducing novel proteins as vaccine candidates against cholera. Materials and Methods: Vibrio cholerae genome versatility is a hurdle for developing a vaccine to combat diarrhoeal infection, so its core gene information was used to determine a potential vaccine candidate. Whole genome sequence data of more than 100 Vibrio cholerae strains were used simultaneously to get core genome information. The VacSol pipeline based on reverse vaccinology was selected to address the problem of safe, cheap, temperature-stable, and effective vaccine candidates which can be used for vaccine development against Vibrio cholerae. VacSol screens vaccine candidates using integrated, well-known, and robust algorithms/tools for proteome analysis. The proteomes of the pathogens were initially screened to predict homology using BLASTp. Proteomes that are non-homologous to humans are then subjected to a predictor for localization. Helicer predicts transmembrane helices for the protein. Proteins failing to comply with the set parameters were filtered at each step, and finally, 11 proteins were filtered as vaccine candidates. Results: This selected group of vaccine candidates consists of proteins from almost all structural parts of Vibrio cholerae. Their blast results show that this filtered group includes flagellin A protein, a protein from the Zn transporter system, a lipocarrier outer membrane protein, a peptidoglycan-associated protein, a DNA-binding protein, a chemotaxis protein, a tRNA Pseuriudine synthase A, and two selected proteins, which were beta lactamases. The last two uncharacterized proteins possess 100% similarity to V. albensis and Enterobacter, respectively. Tertiary structure and active site determination show a large number of pockets on each protein. Conclusions: The most interesting finding of this study is that 10 proteins out of 11 filtered proteins are introduced as novel potential vaccine candidates. These novel vaccine candidates can result in the development of cost-effective and broad-spectrum vaccines which can be used in countries where cholera is a major contributor to diarrheal disease.
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Liang, Steven H., and Neil Vasdev. "Total Radiosynthesis: Thinking Outside ‘the Box'." Australian Journal of Chemistry 68, no. 9 (2015): 1319. http://dx.doi.org/10.1071/ch15406.
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The logic of total synthesis transformed a stagnant state of chemistry when there was a paucity of methods and reagents to synthesize pharmaceuticals. Molecular imaging by positron emission tomography (PET) is now experiencing a renaissance in the way radiopharmaceuticals are synthesized; however, a paradigm shift is desperately needed in the radiotracer discovery pipeline to accelerate drug development. As with most drugs, most radiotracers also fail, therefore expeditious evaluation of tracers in preclinical models before optimization or derivatization of the lead molecules is necessary. Furthermore the exact position of the 11C and 18F radionuclide in tracers is often critical for metabolic considerations, and flexible methodologies to introduce radionuclides are needed. A challenge in PET radiochemistry is the limited choice of labelled building blocks available with carbon-11 (11C; half-life ~20 min) and fluorine-18 (18F; half-life ~2 h). In fact, most drugs cannot be labelled with 11C or 18F owing to a lack of efficient and diverse radiosynthetic methods. Routine radiopharmaceutical production generally relies on the incorporation of the isotope at the last or penultimate step of synthesis. Such reactions are conducted within the constraints of an automated synthesis unit (‘box’), which has further stifled the exploration of multistep reactions with short-lived radionuclides. Radiopharmaceutical synthesis can be transformed by considering logic of total synthesis to develop novel approaches for 11C- and 18F-radiolabelling complex molecules via retrosynthetic analysis and multistep reactions. As a result of such exploration, new methods, reagents, and radiopharmaceuticals for in vivo imaging studies are discovered and are critical to work towards our ultimate, albeit impossible goal – a concept we term as total radiosynthesis – to radiolabel virtually any molecule. In this account, we show how multistep radiochemical reactions have impacted our radiochemistry program, with prominent examples from others, focusing on impact towards human imaging studies. As the goal of total synthesis is to be concise, we strive to simplify the syntheses of radiopharmaceuticals. New clinically useful strategies, including [11C]CO2 fixation, which has enabled library radiosynthesis, as well as radiofluorination of non-activated arenes via iodonium ylides are highlighted. We also showcase state-of-the-art automation technologies, including microfluidic flow chemistry for radiopharmaceutical production.
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Vincent, Lena, Stephanie Colón-Santos, H. James Cleaves, David A. Baum, and Sarah E. Maurer. "The Prebiotic Kitchen: A Guide to Composing Prebiotic Soup Recipes to Test Origins of Life Hypotheses." Life 11, no. 11 (November 11, 2021): 1221. http://dx.doi.org/10.3390/life11111221.
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“Prebiotic soup” often features in discussions of origins of life research, both as a theoretical concept when discussing abiological pathways to modern biochemical building blocks and, more recently, as a feedstock in prebiotic chemistry experiments focused on discovering emergent, systems-level processes such as polymerization, encapsulation, and evolution. However, until now, little systematic analysis has gone into the design of well-justified prebiotic mixtures, which are needed to facilitate experimental replicability and comparison among researchers. This paper explores principles that should be considered in choosing chemical mixtures for prebiotic chemistry experiments by reviewing the natural environmental conditions that might have created such mixtures and then suggests reasonable guidelines for designing recipes. We discuss both “assembled” mixtures, which are made by mixing reagent grade chemicals, and “synthesized” mixtures, which are generated directly from diversity-generating primary prebiotic syntheses. We discuss different practical concerns including how to navigate the tremendous uncertainty in the chemistry of the early Earth and how to balance the desire for using prebiotically realistic mixtures with experimental tractability and replicability. Examples of two assembled mixtures, one based on materials likely delivered by carbonaceous meteorites and one based on spark discharge synthesis, are presented to illustrate these challenges. We explore alternative procedures for making synthesized mixtures using recursive chemical reaction systems whose outputs attempt to mimic atmospheric and geochemical synthesis. Other experimental conditions such as pH and ionic strength are also considered. We argue that developing a handful of standardized prebiotic recipes may facilitate coordination among researchers and enable the identification of the most promising mechanisms by which complex prebiotic mixtures were “tamed” during the origin of life to give rise to key living processes such as self-propagation, information processing, and adaptive evolution. We end by advocating for the development of a public prebiotic chemistry database containing experimental methods (including soup recipes), results, and analytical pipelines for analyzing complex prebiotic mixtures.
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Shen, Z., A. Mannion, M. T. Whary, S. Muthupalani, A. Sheh, Y. Feng, G. Gong, et al. "Helicobacter saguini, a Novel Helicobacter Isolated from Cotton-Top Tamarins with Ulcerative Colitis, Has Proinflammatory Properties and Induces Typhlocolitis and Dysplasia in Gnotobiotic IL-10−/−Mice." Infection and Immunity 84, no. 8 (May 31, 2016): 2307–16. http://dx.doi.org/10.1128/iai.00235-16.
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A urease-negative, fusiform, novel bacterium namedHelicobacter saguiniwas isolated from the intestines and feces of cotton-top tamarins (CTTs) with chronic colitis.Helicobactersp. was detected in 69% of feces or intestinal samples from 116 CTTs. The draft genome sequence, obtained by Illumina MiSeq sequencing, forH. saguiniisolate MIT 97-6194-5, consisting of ∼2.9 Mb with a G+C content of 35% and 2,704 genes, was annotated using the NCBI Prokaryotic Genomes Automatic Annotation Pipeline.H. saguinicontains homologous genes of known virulence factors found in other enterohepatic helicobacter species (EHS) andH. pylori. These include flagellin, γ-glutamyl transpeptidase (ggt), collagenase, the secreted serine proteasehtrA, and components of a type VI secretion system, but the genome does not harbor genes for cytolethal distending toxin (cdt).H. saguiniMIT 97-6194-5 induced significant levels of interleukin-8 (IL-8) in HT-29 cell culture supernatants by 4 h, which increased through 24 h. mRNAs for the proinflammatory cytokines IL-1β, tumor necrosis factor alpha (TNF-α), IL-10, and IL-6 and the chemokine CXCL1 were upregulated in cocultured HT-29 cells at 4 h compared to levels in control cells. At 3 months postinfection, allH. saguini-monoassociated gnotobiotic C57BL/129 IL-10−/−mice were colonized and had seroconverted toH. saguiniantigen with a significant Th1-associated increase in IgG2c (P< 0.0001).H. saguiniinduced a significant typhlocolitis, associated epithelial defects, mucosa-associated lymphoid tissue (MALT) hyperplasia, and dysplasia. Inflammatory cytokines IL-22, IL-17a, IL-1β, gamma interferon (IFN-γ), and TNF-α, as well as inducible nitric oxide synthase (iNOS) were significantly upregulated in the cecal tissues of infected mice. The expression of the DNA damage response molecule γ-H2AX was significantly higher in the ceca ofH. saguini-infected gnotobiotic mice than in the controls. This model using a nonhuman primateHelicobactersp. can be used to study the pathogenic potential of EHS isolated from primates with naturally occurring inflammatory bowel disease (IBD) and colon cancer.
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Raspor, Eva, Peter K. Hahn, Tom Lancaster, David E. J. Linden, Florian Freudenberg, Andreas Reif, and Robert A. Bittner. "S177. IMPACT OF NOS1AP AND ITS INTERACTION PARTNERS AT THE GLUTAMATERGIC SYNAPSE ON WORKING MEMORY NETWORKS - AN FMRI IMAGING GENETICS STUDY." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S105. http://dx.doi.org/10.1093/schbul/sbaa031.243.
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Abstract Background N-methyl-D-aspartate receptor (NMDAR) hypofunction is an important pathophysiological mechanism in schizophrenia. At the postsynapse the NMDAR interacts with the post-synaptic density (PSD). Neuronal nitric oxide synthase 1 (NOS1) binds to the PSD scaffolding proteins PSD-93 and PSD-95, enabling NMDAR-mediated release of nitric oxide via NOS1. NOS1AP (adaptor of NOS1) is capable of disrupting the interactions between NOS1, PSD-93, and PSD95. Therefore, NOS1AP is closely involved in both glutamatergic and nitrinergic neurotransmission. NOS1AP has been implicated as a risk gene for schizophrenia and cognitive dysfunction. Its increased expression has been observed in dorsolateral prefrontal post-mortem brain tissue of patients with schizophrenia, and NOS1AP SNPs have been associated with established schizophrenia endophenotypes. These findings suggest that the influence of NOS1AP variants should be observable in neural systems implicated in schizophrenia. In the present study, we investigate the impact of NOS1AP and its interaction partners at the glutamatergic synapse on the cortical working memory (WM) networks using fMRI and a gene set analysis approach. Methods 97 right-handed individuals with no personal or family history of psychiatric disorders underwent fMRI in a 3T Siemens Trio scanner during the performance of a visuospatial change detection WM task. Data analysis in Brain Voyager QX 2.8 included standard data preprocessing. Additionally, a multiscale curvature driven cortex based alignment procedure was used to minimize macro-anatomical variability between subjects. Subsequently, data were analyzed using a random-effects multi-subject general linear model. We investigated 19 regions of interest (ROIs) within the core fronto-parietal WM network. We studied all phases of our WM paradigm (encoding, maintenance, retrieval), which were modeled by a total of 5 regressors (encoding, delays 1–3, retrieval). Genetic data was quality controlled and imputed using the RICOPILI pipeline. Gene-set analyses of the 19 ROIs were performed using MAGMA. Two gene sets were selected: 1) NOS1AP/NOS1; 2) NOS1AP/glutamatergic synapse. We applied a Bonferroni correction for the total of 19 ROIs and 5 regressors (95 tests) to both analyses. Results Both gene set analyses revealed multiple associations between brain activation in core fronto-parietal WM areas. For the NOS1/NOS1AP set, most associations were observed during the late maintenance phase (Delay 3) of our WM paradigm. One association was significant Bonferroni correction: a cluster in the left intraparietal sulcus during the late maintenance phase (Delay 3; β=2.2459, SD=0.0239, SE=0.6451, p=0,00025). For NOS1AP / glutamatergic synapse interaction partners, two associations were significant after Bonferroni correction: a cluster in the right IPS during the early maintenance phase (Delay 1; β=0.8525, SD=0.0257, SE=0.2127, p=0.0000308) and a cluster in a different part of the right IPS during the late maintenance phase (Delay 3; β=0.7186, SD=0.0216, SE=0.2119, p=0,000348). Discussion In our gene set analyses we observed multiple associations between brain activation during WM and NOS1AP and its interaction partners, which were most pronounced during the late maintenance phase of our WM task in bilateral areas within the IPS. Both the more constrained NOS1AP / NOS1 gene set and the NOS1AP / glutamatergic synapse gene set showed similar association patterns. Our results implicate the NOS1AP interactome and the glutamatergic system in information processing and brain function in a cognitive domain strongly impaired in schizophrenia. They also indicate that altered activation of parietal WM areas during the maintenance phase is most strongly affected.
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Gilchrist, Cameron L. M., and Yit-Heng Chooi. "Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases." Fungal Biology and Biotechnology 8, no. 1 (November 11, 2021). http://dx.doi.org/10.1186/s40694-021-00120-9.
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Abstract Background Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome. Results Here we report synthaser, a Python package leveraging the NCBI’s conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. Synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. Synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application (http://gamcil.github.io/synthaser). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network. Conclusions Synthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. It is freely available under a MIT license from PyPI (https://pypi.org/project/synthaser) and GitHub (https://github.com/gamcil/synthaser).
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Leferink, Nicole G. H., Mark S. Dunstan, Katherine A. Hollywood, Neil Swainston, Andrew Currin, Adrian J. Jervis, Eriko Takano, and Nigel S. Scrutton. "An automated pipeline for the screening of diverse monoterpene synthase libraries." Scientific Reports 9, no. 1 (August 15, 2019). http://dx.doi.org/10.1038/s41598-019-48452-2.
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Croser, Janine, Dili Mao, Nicole Dron, Simon Michelmore, Larn McMurray, Christopher Preston, Dylan Bruce, et al. "Evidence for the Application of Emerging Technologies to Accelerate Crop Improvement – A Collaborative Pipeline to Introgress Herbicide Tolerance Into Chickpea." Frontiers in Plant Science 12 (December 3, 2021). http://dx.doi.org/10.3389/fpls.2021.779122.
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Accelerating genetic gain in crop improvement is required to ensure improved yield and yield stability under increasingly challenging climatic conditions. This case study demonstrates the effective confluence of innovative breeding technologies within a collaborative breeding framework to develop and rapidly introgress imidazolinone Group 2 herbicide tolerance into an adapted Australian chickpea genetic background. A well-adapted, high-yielding desi cultivar PBA HatTrick was treated with ethyl methanesulfonate to generate mutations in the ACETOHYDROXYACID SYNTHASE 1 (CaAHAS1) gene. After 2 years of field screening with imidazolinone herbicide across >20 ha and controlled environment progeny screening, two selections were identified which exhibited putative herbicide tolerance. Both selections contained the same single amino acid substitution, from alanine to valine at position 205 (A205V) in the AHAS1 protein, and KASP™ markers were developed to discriminate between tolerant and intolerant genotypes. A pipeline combining conventional crossing and F2 production with accelerated single seed descent from F2:4 and marker-assisted selection at F2 rapidly introgressed the herbicide tolerance trait from one of the mutant selections, D15PAHI002, into PBA Seamer, a desi cultivar adapted to Australian cropping areas. Field evaluation of the derivatives of the D15PAHI002 × PBA Seamer cross was analyzed using a factor analytic mixed model statistical approach designed to accommodate low seed numbers resulting from accelerated single seed descent. To further accelerate trait introgression, field evaluation trials were undertaken concurrent with crop safety testing trials. In 2020, 4 years after the initial cross, an advanced line selection CBA2061, bearing acetohydroxyacid synthase (AHAS) inhibitor tolerance and agronomic and disease resistance traits comparable to parent PBA Seamer, was entered into Australian National Variety Trials as a precursor to cultivar registration. The combination of cross-institutional collaboration and the application of novel pre-breeding platforms and statistical technologies facilitated a 3-year saving compared to a traditional breeding approach. This breeding pipeline can be used as a model to accelerate genetic gain in other self-pollinating species, particularly food legumes.
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Zheng, Yao, Wei Wu, Gengdong Hu, Liping Qiu, and Jiazhang Chen. "Transcriptome Analysis of Juvenile Tilapia (Oreochromis niloticus) Blood, Fed With Different Concentrations of Resveratrol." Frontiers in Physiology 11 (December 9, 2020). http://dx.doi.org/10.3389/fphys.2020.600730.
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Oreochromis niloticus (genetically improved farmed tilapia, GIFT) often bites the root of Polygonum cuspidatum when it is used as a floating bed, and resveratrol (RES) is mainly accumulated in the root of P. cuspidatum. Blood acts as a pipeline for the fish immune system. Generating blood transcriptomic resources is crucial for understanding molecular mechanisms underlying blood immune responses. In this study, we determined the effects of RES administration on blood transcriptomic response in GIFT. With increasing RES concentration, 133 (0.025 vs. 0.05 g/kg RES), 155 (0.025 vs. 0.1 g/kg RES), and 123 (0.05 vs. 0.1 g/kg RES) genes were detected as significant differentially expressed genes (DEGs). Three and ninety-five shared significant DEGs were found to be enriched among the three (except 0.1 g/kg RES) and four groups (0, 0.025, 0.05, and 0.1 g/kg RES), respectively. To determine the relationship between mitochondrial regulation and RES supplementation, the results of RNA-Seq were analyzed and nine mitochondria-related genes (ATP synthase or mitochondrial-function-related genes) were verified. The results revealed the same expression pattern: cytochrome c isoform X2 (cox2), katanin p60 ATPase-containing subunit A1 isoform X1 (katna1), plasma membrane calcium-transporting ATPase 1-like (atp2b1) and GTP-binding protein A-like (gtpbpal) showed the highest expression in the 0.1 g/kg RES group, while NADH dehydrogenase [ubiquinone] iron-sulfur protein 2 mitochondrial (nad7), ATP synthase subunit beta, mitochondrial (atpb), ATP synthase subunit alpha, mitochondrial-like (atpal), ATP synthase subunit alpha, mitochondrial (atpa) and ATP-dependent Clp protease proteolytic subunit, mitochondrial (clpp) revealed a dose-dependent expression following RES supplementation. Blood Ca2+-ATPase activity, and malondialdehyde, glutathione, and ATP content were significantly increased in the 0.05 (except Ca2+-ATPase activity), 0.1 g/kg RES group when compared with the controls. Eighty-nine shared DGEs were mainly enriched in antigen processing and presentation, cell adhesion molecules and phagosome pathways, based on the comparison between previous reported hepatic and the present blood transcriptome. Our study demonstrated that RES supplementation might improve the resistance to metabolism dysfunction via mitochondrial energy synthesis and/or the respiratory chain (e.g., ATPase).
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Singh, Baljinder. "Bedaquiline in drug-resistant tuberculosis: A mini-review." Current Molecular Pharmacology 15 (April 21, 2022). http://dx.doi.org/10.2174/1874467215666220421130707.
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Abstract: Mycobacterium tuberculosis causes a contagious pulmonary disease with a high mortality rate in developing countries. However, the recommendation of DOTS (approved by WHO) was effective in treating tuberculosis, but nowadays resistance from the first line (MDR-TB) and the second line (XDR-TB) drugs is highly common. Whereas, the resistance is a result of factors like poor patient constancy due to the long duration of therapy and co-infection with HIV. The approval of bedaquiline under an accelerated program for the treatment of MDR-TB had revealed its effectiveness in clinical trials as a therapeutic novel molecule. BDQ selectively inhibits the ATP synthase of bacterium and reduces ATP production. Additionally, the poor pharmacokinetic properties had raised provocations in the MDR therapy, but the use of targeted drug delivery can solve the hurdles. While the preclinical and clinical studies included in this review are strongly suggesting the usefulness of BDQ in MDR-TB and XDR-TB, the repurposing of different drug classes in resistant TB is opening new opportunities to manage the disease conditions. In this review, we have summarized the examples of pipeline drugs and repurposed molecules with preclinical formulation developments.
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Arabaciyan, Sevan, Michael Saint-Antoine, Cathy Maugis-Rabusseau, Jean-Marie François, Abhyudai Singh, Jean-Luc Parrou, and Jean-Pascal Capp. "Insights on the Control of Yeast Single-Cell Growth Variability by Members of the Trehalose Phosphate Synthase (TPS) Complex." Frontiers in Cell and Developmental Biology 9 (January 28, 2021). http://dx.doi.org/10.3389/fcell.2021.607628.
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Single-cell variability of growth is a biological phenomenon that has attracted growing interest in recent years. Important progress has been made in the knowledge of the origin of cell-to-cell heterogeneity of growth, especially in microbial cells. To better understand the origins of such heterogeneity at the single-cell level, we developed a new methodological pipeline that coupled cytometry-based cell sorting with automatized microscopy and image analysis to score the growth rate of thousands of single cells. This allowed investigating the influence of the initial amount of proteins of interest on the subsequent growth of the microcolony. As a preliminary step to validate this experimental setup, we referred to previous findings in yeast where the expression level of Tsl1, a member of the Trehalose Phosphate Synthase (TPS) complex, negatively correlated with cell division rate. We unfortunately could not find any influence of the initial TSL1 expression level on the growth rate of the microcolonies. We also analyzed the effect of the natural variations of trehalose-6-phosphate synthase (TPS1) expression on cell-to-cell growth heterogeneity, but we did not find any correlation. However, due to the already known altered growth of the tps1Δ mutants, we tested this strain at the single-cell level on a permissive carbon source. This mutant showed an outstanding lack of reproducibility of growth rate distributions as compared to the wild-type strain, with variable proportions of non-growing cells between cultivations and more heterogeneous microcolonies in terms of individual growth rates. Interestingly, this variable behavior at the single-cell level was reminiscent to the high variability that is also stochastically suffered at the population level when cultivating this tps1Δ strain, even when using controlled bioreactors.
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Füzi, Barbara, Rahuman S. Malik-Sheriff, Emma J. Manners, Henning Hermjakob, and Gerhard F. Ecker. "KNIME workflow for retrieving causal drug and protein interactions, building networks, and performing topological enrichment analysis demonstrated by a DILI case study." Journal of Cheminformatics 14, no. 1 (June 13, 2022). http://dx.doi.org/10.1186/s13321-022-00615-6.
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AbstractAs an alternative to one drug-one target approaches, systems biology methods can provide a deeper insight into the holistic effects of drugs. Network-based approaches are tools of systems biology, that can represent valuable methods for visualizing and analysing drug-protein and protein–protein interactions. In this study, a KNIME workflow is presented which connects drugs to causal target proteins and target proteins to their causal protein interactors. With the collected data, networks can be constructed for visualizing and interpreting the connections. The last part of the workflow provides a topological enrichment test for identifying relevant pathways and processes connected to the submitted data. The workflow is based on openly available databases and their web services. As a case study, compounds of DILIRank were analysed. DILIRank is the benchmark dataset for Drug-Induced Liver Injury by the FDA, where compounds are categorized by their likeliness of causing DILI. The study includes the drugs that are most likely to cause DILI (“mostDILI”) and the ones that are not likely to cause DILI (“noDILI”). After selecting the compounds of interest, down- and upregulated proteins connected to the mostDILI group were identified; furthermore, a liver-specific subset of those was created. The downregulated sub-list had considerably more entries, therefore, network and causal interactome were constructed and topological pathway enrichment analysis was performed with this list. The workflow identified proteins such as Prostaglandin G7H synthase 1 and UDP-glucuronosyltransferase 1A9 as key participants in the potential toxic events disclosing the possible mode of action. The topological network analysis resulted in pathways such as recycling of bile acids and salts and glucuronidation, indicating their involvement in DILI. The KNIME pipeline was built to support target and network-based approaches to analyse any sets of drug data and identify their target proteins, mode of actions and processes they are involved in. The fragments of the pipeline can be used separately or can be combined as required.
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Fisher, Kelsey E., Steven P. Bradbury, and Brad S. Coates. "Prediction of mitochondrial genome-wide variation through sequencing of mitochondrion-enriched extracts." Scientific Reports 10, no. 1 (November 5, 2020). http://dx.doi.org/10.1038/s41598-020-76088-0.
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Abstract Although mitochondrial DNA (mtDNA) haplotype variation is often applied for estimating population dynamics and phylogenetic relationships, economical and generalized methods for entire mtDNA genome enrichment prior to high-throughput sequencing are not readily available. This study demonstrates the utility of differential centrifugation to enrich for mitochondrion within cell extracts prior to DNA extraction, short-read sequencing, and assembly using exemplars from eight maternal lineages of the insect species, Ostrinia nubilalis. Compared to controls, enriched extracts showed a significant mean increase of 48.2- and 86.1-fold in mtDNA based on quantitative PCR, and proportion of subsequent short sequence reads that aligned to the O. nubilalis reference mitochondrial genome, respectively. Compared to the reference genome, our de novo assembled O. nubilalis mitochondrial genomes contained 82 intraspecific substitution and insertion/deletion mutations, and provided evidence for correction of mis-annotated 28 C-terminal residues within the NADH dehydrogenase subunit 4. Comparison to a more recent O. nubilalis mtDNA assembly from unenriched short-read data analogously showed 77 variant sites. Twenty-eight variant positions, and a triplet ATT codon (Ile) insertion within ATP synthase subunit 8, were unique within our assemblies. This study provides a generalizable pipeline for whole mitochondrial genome sequence acquisition adaptable to applications across a range of taxa.
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Agrawal, Priyesh, and Debasisa Mohanty. "A machine learning-based method for prediction of macrocyclization patterns of polyketides and non-ribosomal peptides." Bioinformatics, November 22, 2020. http://dx.doi.org/10.1093/bioinformatics/btaa851.
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Abstract Motivation Even though genome mining tools have successfully identified large numbers of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) biosynthetic gene clusters (BGCs) in bacterial genomes, currently no tool can predict the chemical structure of the secondary metabolites biosynthesized by these BGCs. Lack of algorithms for predicting complex macrocyclization patterns of linear PK/NRP biosynthetic intermediates has been the major bottleneck in deciphering the final bioactive chemical structures of PKs/NRPs by genome mining. Results Using a large dataset of known chemical structures of macrocyclized PKs/NRPs, we have developed a machine learning (ML) algorithm for distinguishing the correct macrocyclization pattern of PKs/NRPs from the library of all theoretically possible cyclization patterns. Benchmarking of this ML classifier on completely independent datasets has revealed ROC–AUC and PR–AUC values of 0.82 and 0.81, respectively. This cyclization prediction algorithm has been used to develop SBSPKSv3, a genome mining tool for completely automated prediction of macrocyclized structures of NRPs/PKs. SBSPKSv3 has been extensively benchmarked on a dataset of over 100 BGCs with known PKs/NRPs products. Availability and implementation The macrocyclization prediction pipeline and all the datasets used in this study are freely available at http://www.nii.ac.in/sbspks3.html. Supplementary information Supplementary data are available at Bioinformatics online.
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Pearson, Adam, Dominik Haenni, Jamal Bouitbir, Matthew Hunt, Brendan A. I. Payne, Ashwin Sachdeva, Rachel K. Y. Hung, et al. "Integration of high-throughput imaging and multi-parametric metabolic profiling reveals a mitochondrial mechanism of tenofovir toxicity." Function, December 24, 2022. http://dx.doi.org/10.1093/function/zqac065.
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Abstract Nephrotoxicity is a major cause of kidney disease and failure in drug development, but understanding of cellular mechanisms is limited, highlighting the need for better experimental models and methodological approaches. Most nephrotoxins damage the proximal tubule (PT), causing functional impairment of solute reabsorption and systemic metabolic complications. The anti-viral drug Tenofovir disoproxil fumarate (TDF) is an archetypal nephrotoxin, inducing mitochondrial abnormalities and urinary solute wasting, for reasons that were previously unclear. Here, we developed an automated, high-throughput imaging pipeline to screen the effects of TDF on solute transport and mitochondrial morphology in human-derived RPTEC/TERT1 cells, and leveraged this to generate realistic models of functional toxicity. By applying multiparametric metabolic profiling—including oxygen consumption measurements, metabolomics and transcriptomics—we elucidated a highly robust molecular fingerprint of TDF exposure. Crucially, we identified that the active metabolite inhibits complex V (ATP synthase), and that TDF treatment causes rapid, dose dependent loss of complex V activity and expression. Moreover, we found evidence of complex V suppression in kidney biopsies from humans with TDF toxicity. Thus, we demonstrate an effective and convenient experimental approach to screen for disease relevant functional defects in kidney cells in vitro, and reveal a new paradigm for understanding the pathogenesis of a substantial cause of nephrotoxicity.
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Zaidi, Syed Shujaat Ali, Masood Ur Rehman Kayani, Xuegong Zhang, Younan Ouyang, and Imran Haider Shamsi. "Prediction and analysis of metagenomic operons via MetaRon: a pipeline for prediction of Metagenome and whole-genome opeRons." BMC Genomics 22, no. 1 (January 19, 2021). http://dx.doi.org/10.1186/s12864-020-07357-5.
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Abstract Background Efficient regulation of bacterial genes in response to the environmental stimulus results in unique gene clusters known as operons. Lack of complete operonic reference and functional information makes the prediction of metagenomic operons a challenging task; thus, opening new perspectives on the interpretation of the host-microbe interactions. Results In this work, we identified whole-genome and metagenomic operons via MetaRon (Metagenome and whole-genome opeRon prediction pipeline). MetaRon identifies operons without any experimental or functional information. MetaRon was implemented on datasets with different levels of complexity and information. Starting from its application on whole-genome to simulated mixture of three whole-genomes (E. coli MG1655, Mycobacterium tuberculosis H37Rv and Bacillus subtilis str. 16), E. coli c20 draft genome extracted from chicken gut and finally on 145 whole-metagenome data samples from human gut. MetaRon consistently achieved high operon prediction sensitivity, specificity and accuracy across E. coli whole-genome (97.8, 94.1 and 92.4%), simulated genome (93.7, 75.5 and 88.1%) and E. coli c20 (87, 91 and 88%,), respectively. Finally, we identified 1,232,407 unique operons from 145 paired-end human gut metagenome samples. We also report strong association of type 2 diabetes with Maltose phosphorylase (K00691), 3-deoxy-D-glycero-D-galacto-nononate 9-phosphate synthase (K21279) and an uncharacterized protein (K07101). Conclusion With MetaRon, we were able to remove two notable limitations of existing whole-genome operon prediction methods: (1) generalizability (ability to predict operons in unrelated bacterial genomes), and (2) whole-genome and metagenomic data management. We also demonstrate the use of operons as a subset to represent the trends of secondary metabolites in whole-metagenome data and the role of secondary metabolites in the occurrence of disease condition. Using operonic data from metagenome to study secondary metabolic trends will significantly reduce the data volume to more precise data. Furthermore, the identification of metabolic pathways associated with the occurrence of type 2 diabetes (T2D) also presents another dimension of analyzing the human gut metagenome. Presumably, this study is the first organized effort to predict metagenomic operons and perform a detailed analysis in association with a disease, in this case type 2 diabetes. The application of MetaRon to metagenomic data at diverse scale will be beneficial to understand the gene regulation and therapeutic metagenomics.
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Van Harsselaar, Jessica K., Joelle Claußen, Jens Lübeck, Norbert Wörlein, Norman Uhlmann, Uwe Sonnewald, and Stefan Gerth. "X-Ray CT Phenotyping Reveals Bi-Phasic Growth Phases of Potato Tubers Exposed to Combined Abiotic Stress." Frontiers in Plant Science 12 (March 30, 2021). http://dx.doi.org/10.3389/fpls.2021.613108.
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As a consequence of climate change, heat waves in combination with extended drought periods will be an increasing threat to crop yield. Therefore, breeding stress tolerant crop plants is an urgent need. Breeding for stress tolerance has benefited from large scale phenotyping, enabling non-invasive, continuous monitoring of plant growth. In case of potato, this is compromised by the fact that tubers grow belowground, making phenotyping of tuber development a challenging task. To determine the growth dynamics of tubers before, during and after stress treatment is nearly impossible with traditional destructive harvesting approaches. In contrast, X-ray Computed Tomography (CT) offers the opportunity to access belowground growth processes. In this study, potato tuber development from initiation until harvest was monitored by CT analysis for five different genotypes under stress conditions. Tuber growth was monitored three times per week via CT analysis. Stress treatment was started when all plants exhibited detectable tubers. Combined heat and drought stress was applied by increasing growth temperature for 2 weeks and simultaneously decreasing daily water supply. CT analysis revealed that tuber growth is inhibited under stress within a week and can resume after the stress has been terminated. After cessation of stress, tubers started growing again and were only slightly and insignificantly smaller than control tubers at the end of the experimental period. These growth characteristics were accompanied by corresponding changes in gene expression and activity of enzymes relevant for starch metabolism which is the driving force for tuber growth. Gene expression and activity of Sucrose Synthase (SuSy) reaffirmed the detrimental impact of the stress on starch biosynthesis. Perception of the stress treatment by the tubers was confirmed by gene expression analysis of potential stress marker genes whose applicability for potato tubers is further discussed. We established a semi-automatic imaging pipeline to analyze potato tuber delevopment in a medium thoughput (5 min per pot). The imaging pipeline presented here can be scaled up to be used in high-throughput phenotyping systems. However, the combination with automated data processing is the key to generate objective data accelerating breeding efforts to improve abiotic stress tolerance of potato genotypes.
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Iyer, Kali, Kaddy Camara, Martin Daniel-Ivad, Nicole Revie, Jennifer Lou, Sheena Li, Richard Trilles, et al. "Exploiting diverse chemical collections to uncover novel antifungals." Access Microbiology 3, no. 12 (December 17, 2021). http://dx.doi.org/10.1099/acmi.cc2021.po0006.
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The rise in drug resistance amongst pathogenic fungi, paired with the limited arsenal of antifungals available is an imminent threat to our medical system. To address this, we screened two distinct compound libraries to identify novel strategies to expand the antifungal armamentarium. The first collection wasthe RIKEN Natural Product Depository (NPDepo), which was screened for antifungal activity against four major human fungal pathogens: Candida albicans, Candida glabrata, Candida auris, and Cryptococcus neoformans. Through a prioritization pipeline, one compound, NPD6433, emerged as having broad-spectrum antifungal activity and minimal mammalian cytotoxicity. Chemical-genetic and biochemical assays demonstrated that NPD6433 inhibits the essential fungal enzyme fatty acid synthase 1 (Fas1). Treatment with NPD6433 inhibited various virulence traits in C. neoformans and C. auris, and rescued mammalian cell growth in a co-culture model with C. auris. The second compound library screened was adiversity-oriented collectionfrom Boston University. This chemical screen was focused on identifying novel molecules that enhance the activity of the widely deployed antifungal, fluconazole, against C. auris. Through this endeavour, we discovered a potent compound that enhanced fluconazole efficacy against C. auris through increasing azole intracellular accumulation. This activity was dependent on expression of the multidrug transporter geneCDR1, suggesting that this compound targets efflux mechanisms. Furthermore, this molecule significantly reduced fungal burden alone and in combination with fluconazole in a murine model of C. auris disseminated infection. Overall, this work identifies novel compounds with bioactivity against fungal pathogens, revealing important biology, and paving the way for the critical development of therapeutic strategies.
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Wu, Yu-Ching, Chia-I. Chen, Peng-Ying Chen, Chun-Hung Kuo, Yi-Hsuan Hung, Kang-Yung Peng, Vin-Cent Wu, Jyy-Jih Tsai-Wu, and Chia-Lang Hsu. "GRAde: a long-read sequencing approach to efficiently identifying the CYP11B1/CYP11B2 chimeric form in patients with glucocorticoid-remediable aldosteronism." BMC Bioinformatics 22, S10 (May 2021). http://dx.doi.org/10.1186/s12859-022-04561-w.
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Abstract Background Glucocorticoid-remediable aldosteronism (GRA) is a form of heritable hypertension caused by a chimeric fusion resulting from unequal crossing over between 11β‐hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2), which are two genes with similar sequences. Different crossover patterns of the CYP11B1 and CYP11B2 chimeric genes may be associated with a variety of clinical presentations. It is therefore necessary to develop an efficient approach for identifying the differences between the hybrid genes of a patient with GRA. Results We developed a long-read analysis pipeline named GRAde (GRA deciphering), which utilizes the nonidentical bases in the CYP11B1 and CYP11B2 genomic sequences to identify and visualize the chimeric form. We sequenced the polymerase chain reaction (PCR) products of the CYP11B1/CYP11B2 chimeric gene from 36 patients with GRA using the Nanopore MinION device and analyzed the sequences using GRAde. Crossover events were identified for 30 out of the 36 samples. The crossover sites appeared in the region exhibiting high sequence similarity between CYP11B1 and CYP11B2, and 53.3% of the cases were identified as having a gene conversion in intron 2. More importantly, there were six cases for whom the PCR products indicated a chimeric gene, but the GRAde results revealed no crossover pattern. The crossover regions were further verified by Sanger sequencing analysis. Conclusions PCR-based target enrichment followed by long-read sequencing is an efficient and precise approach to dissecting complex genomic regions, such as those involved in GRA mutations, which could be directly applied to clinical diagnosis. The scripts of GRAde are available at https://github.com/hsu-binfo/GRAde.
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Eggertsen, Taylor, and Jeffrey J. Saucerman. "Abstract P433: A Pharmacological Model Predicts Drug Activity In Cardiomyocyte Hypertrophy." Circulation Research 129, Suppl_1 (September 3, 2021). http://dx.doi.org/10.1161/res.129.suppl_1.p433.
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Introduction: Cardiomyocyte (CM) hypertrophy is predictive of heart failure, however there are no clinical therapies that target its intracellular pathways. Hypertrophy is a complex process involving numerous neurohormonal and cytokine inputs, resulting in context-dependent responses that determine CM growth. In the face of this complexity, it is critical that computational models are developed. Accurate predictions of drug activity in CM hypertrophy will require a pharmacological model that is developed with and validated against experimental data. Hypothesis: We test the hypothesis that our in silico pharmacological model accurately predicts drugs that inhibit cardiac hypertrophy as well as the context-dependent mechanisms by which they work. Methods: Here we employ a previously published computational model of cardiac hypertrophy signaling. This model utilizes logic-based ordinary differential equations to simulate a network of 106 nodes. Using the DrugBank database, we constructed a pipeline for simulating FDA-approved drugs within this hypertrophy network under multiple environmental contexts. The predicted outcomes of the model were then compared to measured phenotypes from experimental findings in literature. Results: Predicted outcomes of our model were successfully validated against 29 out of 36 distinct experiments described in literature. These simulations identify the optimal drug types that inhibit hypertrophy for each of 17 different stimuli. Sensitivity analyses performed by simulating knockdowns in our model reveals context-dependent mechanisms predicted for 51 drug types. These predictions confirmed, for example, the role of celecoxib in inhibiting CM hypertrophy induced by isoproterenol. Mechanistic analysis suggests celecoxib prevents protein kinase B (Akt) inhibition of glycogen synthase kinase 3 beta (GSK3β), consistent with literature. Conclusions: Our pharmacological model accurately predicts FDA-approved drugs that show in vitro inhibition of CM hypertrophy.
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Xing, Kai, Xitong Zhao, Hong Ao, Shaokang Chen, Ting Yang, Zhen Tan, Yuan Wang, et al. "Transcriptome analysis of miRNA and mRNA in the livers of pigs with highly diverged backfat thickness." Scientific Reports 9, no. 1 (November 14, 2019). http://dx.doi.org/10.1038/s41598-019-53377-x.
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AbstractFat deposition is very important in pig production, and its mechanism is not clearly understood. MicroRNAs (miRNAs) play critical roles in fat deposition and energy metabolism. In the current study, we investigated the mRNA and miRNA transcriptome in the livers of Landrace pigs with extreme backfat thickness to explore miRNA-mRNA regulatory networks related to lipid deposition and metabolism. A comparative analysis of liver mRNA and miRNA transcriptomes from pigs (four pigs per group) with extreme backfat thickness was performed. We identified differentially expressed genes from RNA-seq data using a Cufflinks pipeline. Seventy-one differentially expressed genes (DEGs), including twenty-eight well annotated on the porcine reference genome genes, were found. The upregulation genes in pigs with higher backfat thickness were mainly involved in fatty acid synthesis, and included fatty acid synthase (FASN), glucokinase (GCK), phosphoglycerate dehydrogenase (PHGDH), and apolipoprotein A4 (APOA4). Cytochrome P450, family 2, subfamily J, polypeptide 34 (CYP2J34) was lower expressed in pigs with high backfat thickness, and is involved in the oxidation of arachidonic acid. Moreover, 13 differentially expressed miRNAs were identified. Seven miRNAs were associated with fatty acid synthesis, lipid metabolism, and adipogenic differentiation. Based on comprehensive analysis of the transcriptome of both mRNAs and miRNAs, an important regulatory network, in which six DEGs could be regulated by differentially expressed miRNAs, was established for fat deposition. The negative correlate in the regulatory network including, miR-545-5p and GRAMD3, miR-338 and FASN, and miR-127, miR-146b, miR-34c, miR-144 and THBS1 indicate that direct suppressive regulation may be involved in lipid deposition and energy metabolism. Based on liver mRNA and miRNA transcriptomes from pigs with extreme backfat thickness, we identified 28 differentially expressed genes and 13 differentially expressed miRNAs, and established an important miRNA-mRNA regulatory network. This study provides new insights into the molecular mechanisms that determine fat deposition in pigs.
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Kawas, Mohammad Iyas, Ahmad Shamulzai, Carol Kittel, Brian Curry, Jeongchul Kim, Kyle Fargen, Christopher Whitlow, and Stacey Quintero Wolfe. "Abstract 023: Quantification Of White Matter Lesion Volume From Clinical T1 Weighted Magnetic Resonance Images To Predict Functional Outcomes Post-thrombectomy." Hypertension 79, Suppl_1 (September 2022). http://dx.doi.org/10.1161/hyp.79.suppl_1.023.
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Background: Endovascular treatment (EVT) has immense benefits for patients with large vessel occlusion (LVO). However, many patients do not achieve functional independence despite successful EVT. This may be due to concurrent cerebral small vessel disease (CSVD) mitigating recovery. CSVD manifests as white matter hypointensities on T1-weighted (T1w) MRI and is usually qualitatively assessed from clinical-quality MRI, which does not allow for objective quantification. Objectives: Implement a processing pipeline to quantify white matter hypointensity volume (WMHV) from clinical images and examine WMHV's influence on functional outcomes post successful EVT. Methods: We performed a retrospective analysis of the Atrium Wake Forest Stroke Thrombectomy and Aneurysm Registry (n=602) collected between 2015 - 2021. We selected patients with LVO who underwent successful EVT, defined as a Thrombolysis in Cerebral Infarction score of 2B or better. Clinical T1w images were transformed into high-resolution images using the convolutional neural network SynthSR. Then, FreeSurfer was used to quantify baseline WMHV from the side of the brain contralateral to the stroke to minimize stroke interference. To correct for head size, WMHV was adjusted to the estimated total intracranial volume and then log-transformed to address skewness. Results: The analysis included 213 patients (mean age 67.5 ± 14.6, 49.3% (105 of 213) female) who had MRI of sufficient quality for assessment and 90-day mRS. Baseline WMHV was significantly predictive of 90-day mRS in an ordinal regression model adjusted for baseline mRS (p<0.001). After adjusting for confounders and comorbidities, WMHV remained an independent predictor of 90-day mRS (p<0.001). Conclusions: Increased volume of white matter hypointensities correlates with poorer functional outcomes after mechanical thrombectomy and may attenuate EVT benefit. Furthermore, advances in neural networks enable the quantification of cerebral small vessel disease from clinical T1w MRI. Such approaches expand the utility of clinical imaging for research purposes.
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Sá-Pessoa, Joana, Kornelia Przybyszewska, Filipe Nuno Vasconcelos, Amy Dumigan, Christian G. Frank, Laura Hobley, and Jose A. Bengoechea. "Klebsiella pneumoniae Reduces SUMOylation To Limit Host Defense Responses." mBio 11, no. 5 (September 29, 2020). http://dx.doi.org/10.1128/mbio.01733-20.
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ABSTRACT Klebsiella pneumoniae is an important cause of multidrug-resistant infections worldwide. Understanding the virulence mechanisms of K. pneumoniae is a priority and timely to design new therapeutics. Here, we demonstrate that K. pneumoniae limits the SUMOylation of host proteins in epithelial cells and macrophages (mouse and human) to subvert cell innate immunity. Mechanistically, in lung epithelial cells, Klebsiella increases the levels of the deSUMOylase SENP2 in the cytosol by affecting its K48 ubiquitylation and its subsequent degradation by the ubiquitin proteasome. This is dependent on Klebsiella preventing the NEDDylation of the Cullin-1 subunit of the ubiquitin ligase complex E3-SCF-βTrCP by exploiting the CSN5 deNEDDylase. Klebsiella induces the expression of CSN5 in an epidermal growth factor receptor (EGFR)-phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT)-extracellular signal-regulated kinase (ERK)-glycogen synthase kinase 3 beta (GSK3β) signaling pathway-dependent manner. In macrophages, Toll-like receptor 4 (TLR4)-TRAM-TRIF-induced type I interferon (IFN) via IFN receptor 1 (IFNAR1)-controlled signaling mediates Klebsiella-triggered decrease in the levels of SUMOylation via let-7 microRNAs (miRNAs). Our results revealed the crucial role played by Klebsiella polysaccharides, the capsule, and the lipopolysaccharide (LPS) O-polysaccharide, to decrease the levels of SUMO-conjugated proteins in epithelial cells and macrophages. A Klebsiella-induced decrease in SUMOylation promotes infection by limiting the activation of inflammatory responses and increasing intracellular survival in macrophages. IMPORTANCE Klebsiella pneumoniae has been singled out as an urgent threat to human health due to the increasing isolation of strains resistant to “last-line” antimicrobials, narrowing the treatment options against Klebsiella infections. Unfortunately, at present, we cannot identify candidate compounds in late-stage development for treatment of multidrug-resistant Klebsiella infections; this pathogen is exemplary of the mismatch between unmet medical needs and the current antimicrobial research and development pipeline. Furthermore, there is still limited evidence on K. pneumoniae pathogenesis at the molecular and cellular levels in the context of the interactions between bacterial pathogens and their hosts. In this research, we have uncovered a sophisticated strategy employed by Klebsiella to subvert the activation of immune defenses by controlling the modification of proteins. Our research may open opportunities to develop new therapeutics based on counteracting this Klebsiella-controlled immune evasion strategy.
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Eddens, Taylor, Waleed Elsegeiny, David Ricks, Meagan Goodwin, William T. Horne, Mingquan Zheng, and Jay K. Kolls. "Transcriptomic and Proteomic Approaches to Finding Novel Diagnostic and Immunogenic Candidates in Pneumocystis." mSphere 4, no. 5 (September 4, 2019). http://dx.doi.org/10.1128/msphere.00488-19.
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ABSTRACT Pneumocystis pneumonia is the most common serious opportunistic infection in patients with HIV/AIDS. Furthermore, Pneumocystis pneumonia is a feared complication of the immunosuppressive drug regimens used to treat autoimmunity, malignancy, and posttransplantation rejection. With an increasing at-risk population, there is a strong need for novel approaches to discover diagnostic and vaccine targets. There are multiple challenges to finding these targets, however. First, Pneumocystis has a largely unannotated genome. To address this, we evaluated each protein encoded within the Pneumocystis genome by comparisons to proteins encoded within the genomes of other fungi using NCBI BLAST. Second, Pneumocystis relies on a multiphasic life cycle, as both the transmissible form (the ascus) and the replicative form (the trophozoite [troph]) reside within the alveolar space of the host. To that end, we purified asci and trophs from Pneumocystis murina and utilized transcriptomics to identify differentially regulated genes. Two such genes, Arp9 and Sp, are differentially regulated in the ascus and the troph, respectively, and can be utilized to characterize the state of the Pneumocystis life cycle in vivo. Gsc1, encoding a β-1,3-glucan synthase with a large extracellular domain previously identified using surface proteomics, was more highly expressed on the ascus form of Pneumocystis. GSC-1 ectodomain immunization generated a strong antibody response that demonstrated the ability to recognize the surface of the Pneumocystis asci. GSC-1 ectodomain immunization was also capable of reducing ascus burden following primary challenge with Pneumocystis murina. Finally, mice immunized with the GSC-1 ectodomain had limited fungal burden following natural transmission of Pneumocystis using a cohousing model. IMPORTANCE The current report enhances our understanding of Pneumocystis biology in a number of ways. First, the current study provided a preliminary annotation of the Pneumocystis murina genome, addressing a long-standing issue in the field. Second, this study validated two novel transcripts enriched in the two predominant life forms of Pneumocystis. These findings allow better characterization of the Pneumocystis life cycle in vivo and could be valuable diagnostic tools. Furthermore, this study outlined a novel pipeline of -omics techniques capable of revealing novel antigens (e.g., GSC-1) for the development of vaccines against Pneumocystis.
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Liu, Lei, Yulin Wang, You Che, Yiqiang Chen, Yu Xia, Ruibang Luo, Suk Hang Cheng, Chunmiao Zheng, and Tong Zhang. "High-quality bacterial genomes of a partial-nitritation/anammox system by an iterative hybrid assembly method." Microbiome 8, no. 1 (November 6, 2020). http://dx.doi.org/10.1186/s40168-020-00937-3.
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Abstract Background Genome-centric approaches are widely used to investigate microbial compositions, dynamics, ecology, and interactions within various environmental systems. Hundreds or even thousands of genomes could be retrieved in a single study contributed by the cost-effective short-read sequencing and developed assembly/binning pipelines. However, conventional binning methods usually yield highly fragmented draft genomes that limit our ability to comprehensively understand these microbial communities. Thus, to leverage advantage of both the long and short reads to retrieve more complete genomes from environmental samples is a must-do task to move this direction forward. Results Here, we used an iterative hybrid assembly (IHA) approach to reconstruct 49 metagenome-assembled genomes (MAGs), including 27 high-quality (HQ) and high-contiguity (HC) genomes with contig number ≤ 5, eight of which were circular finished genomes from a partial-nitritation anammox (PNA) reactor. These 49 recovered MAGs (43 MAGs encoding full-length rRNA, average N50 of 2.2 Mbp), represented the majority (92.3%) of the bacterial community. Moreover, the workflow retrieved HQ and HC MAGs even with an extremely low coverage (relative abundance < 0.1%). Among them, 34 MAGs could not be assigned to the genus level, indicating the novelty of the genomes retrieved using the IHA method proposed in this study. Comparative analysis of HQ MAG pairs reconstructed using two methods, i.e., hybrid and short reads only, revealed that identical genes in the MAG pairs represented 87.5% and 95.5% of the total gene inventory of hybrid and short reads only assembled MAGs, respectively. In addition, the first finished anammox genome of the genus Ca. Brocadia reconstructed revealed that there were two identical hydrazine synthase (hzs) genes, providing the exact gene copy number of this crucial phylomarker of anammox at the genome level. Conclusions Our results showcased the high-quality and high-contiguity genome retrieval performance and demonstrated the feasibility of complete genome reconstruction using the IHA workflow from the enrichment system. These (near-) complete genomes provided a high resolution of the microbial community, which might help to understand the bacterial repertoire of anammox-associated systems. Combined with other validation experiments, the workflow can enable a detailed view of the anammox or other similar enrichment systems.
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Jones, Briony, Tim Goodall, Paul B. L. George, Hyun S. Gweon, Jeremy Puissant, Daniel S. Read, Bridget A. Emmett, David A. Robinson, Davey L. Jones, and Robert I. Griffiths. "Beyond Taxonomic Identification: Integration of Ecological Responses to a Soil Bacterial 16S rRNA Gene Database." Frontiers in Microbiology 12 (July 19, 2021). http://dx.doi.org/10.3389/fmicb.2021.682886.
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High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalizing syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterize taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth CS) to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from survey metadata. Specifically, we modeled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on both the shape of landscape scale pH-abundance responses, and pH optima (pH at which OTU abundance is maximal). We identify that most of the soil OTUs examined exhibited a non-flat relationship with soil pH. Further, the pH optima could not be generalized by broad taxonomy, highlighting the need for tools and databases synthesizing ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER/), and flat files are made available for use in bioinformatic pipelines. The further development of advanced informatics infrastructures incorporating modeled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.