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  • Resultat 11-20 av 252
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11.
  • Altay, Özlem, et al. (författare)
  • Current Status of COVID-19 Therapies and Drug Repositioning Applications
  • 2020
  • Ingår i: Iscience. - : Elsevier BV. - 2589-0042. ; 23:7
  • Tidskriftsartikel (refereegranskat)abstract
    • The rapid and global spread of a new human coronavirus (SARS-CoV-2) has produced an immediate urgency to discover promising targets for the treatment of COVID-19. Drug repositioning is an attractive approach that can facilitate the drug discovery process by repurposing existing pharmaceuticals to treat illnesses other than their primary indications. Here, we review current information concerning the global health issue of COVID-19 including promising approved drugs and ongoing clinical trials for prospective treatment options. In addition, we describe computational approaches to be used in drug repurposing and highlight examples of in silico studies of drug development efforts against SARS-CoV-2.
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12.
  • Altay, Özlem, et al. (författare)
  • Revealing the Metabolic Alterations during Biofilm Development of Burkholderia cenocepacia Based on Genome-Scale Metabolic Modeling
  • 2021
  • Ingår i: Metabolites. - : MDPI AG. - 2218-1989 .- 2218-1989. ; 11:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Burkholderia cenocepacia is among the important pathogens isolated from cystic fibrosis (CF) patients. It has attracted considerable attention because of its capacity to evade host immune defenses during chronic infection. Advances in systems biology methodologies have led to the emergence of methods that integrate experimental transcriptomics data and genome-scale metabolic models (GEMs). Here, we integrated transcriptomics data of bacterial cells grown on exponential and biofilm conditions into a manually curated GEM of B. cenocepacia. We observed substantial differences in pathway response to different growth conditions and alternative pathway susceptibility to extracellular nutrient availability. For instance, we found that blockage of the reactions was vital through the lipid biosynthesis pathways in the exponential phase and the absence of microenvironmental lysine and tryptophan are essential for survival. During biofilm development, bacteria mostly had conserved lipid metabolism but altered pathway activities associated with several amino acids and pentose phosphate pathways. Furthermore, conversion of serine to pyruvate and 2,5-dioxopentanoate synthesis are also identified as potential targets for metabolic remodeling during biofilm development. Altogether, our integrative systems biology analysis revealed the interactions between the bacteria and its microenvironment and enabled the discovery of antimicrobial targets for biofilm-related diseases.
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13.
  • Altay, Özlem, et al. (författare)
  • Systems biology perspective for studying the gut microbiota in human physiology and liver diseases
  • 2019
  • Ingår i: EBioMedicine. - : Elsevier BV. - 2352-3964. ; 49:November, s. 363-373
  • Forskningsöversikt (refereegranskat)abstract
    • The advancement in high-throughput sequencing technologies and systems biology approaches have revolutionized our understanding of biological systems and opened a new path to investigate unacknowledged biological phenomena. In parallel, the field of human microbiome research has greatly evolved and the relative contribution of the gut microbiome to health and disease have been systematically explored. This review provides an overview of the network-based and translational systems biology-based studies focusing on the function and composition of gut microbiota. We also discussed the association between the gut microbiome and the overall human physiology, as well as hepatic diseases and other metabolic disorders.
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14.
  • Alvez, Maria Bueno, et al. (författare)
  • Next generation pan-cancer blood proteome profiling using proximity extension assay
  • 2023
  • Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
  • Tidskriftsartikel (refereegranskat)abstract
    • A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.
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15.
  • Ambikan, Anoop T., et al. (författare)
  • Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity
  • 2022
  • Ingår i: Cell systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 13:8, s. 665-681
  • Tidskriftsartikel (refereegranskat)abstract
    • The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolo-mics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a sub-stantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and person-alized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as a-ketoglutarate, succi-nate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.
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16.
  • Ambikan, Anoop T., et al. (författare)
  • Systems-level temporal immune-metabolic profile in Crimean-Congo hemorrhagic fever virus infection
  • 2023
  • Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 120:37
  • Tidskriftsartikel (refereegranskat)abstract
    • Crimean-Congo hemorrhagic fever (CCHF) caused by CCHF virus (CCHFV) is one of the epidemic-prone diseases prioritized by the World Health Organisation as public health emergency with an urgent need for accelerated research. The trajectory of host response against CCHFV is multifarious and remains unknown. Here, we reported the temporal spectrum of pathogenesis following the CCHFV infection using genome-wide blood transcriptomics analysis followed by advanced systems biology analysis, temporal immune-pathogenic alterations, and context-specific progressive and postinfection genome-scale metabolic models (GSMM) on samples collected during the acute (T0), early convalescent (T1), and convalescent-phase (T2). The interplay between the retinoic acid-inducible gene-I-like/nucleotide-binding oligomerization domain-like receptor and tumor necrosis factor signaling governed the trajectory of antiviral immune responses. The rearrangement of intracellular metabolic fluxes toward the amino acid metabolism and metabolic shift toward oxidative phosphorylation and fatty acid oxidation during acute CCHFV infection determine the pathogenicity. The upregulation of the tricarboxylic acid cycle during CCHFV infection, compared to the noninfected healthy control and between the severity groups, indicated an increased energy demand and cellular stress. The upregulation of glycolysis and pyruvate metabolism potentiated energy generation through alternative pathways associated with the severity of the infection. The downregulation of metabolic processes at the convalescent phase identified by blood cell transcriptomics and single-cell type proteomics of five immune cells (CD4+ and CD8+ T cells, CD14+ monocytes, B cells, and NK cells) potentially leads to metabolic rewiring through the recovery due to hyperactivity during the acute phase leading to post-viral fatigue syndrome.
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17.
  • Andersson, Linda, 1973, et al. (författare)
  • Glucosylceramide synthase deficiency in the heart compromises β1-adrenergic receptor trafficking
  • 2021
  • Ingår i: European Heart Journal. - : Oxford University Press. - 0195-668X .- 1522-9645. ; 42:43, s. 4481-4492
  • Tidskriftsartikel (refereegranskat)abstract
    • AIMS: Cardiac injury and remodelling are associated with the rearrangement of cardiac lipids. Glycosphingolipids are membrane lipids that are important for cellular structure and function, and cardiac dysfunction is a characteristic of rare monogenic diseases with defects in glycosphingolipid synthesis and turnover. However, it is not known how cardiac glycosphingolipids regulate cellular processes in the heart. The aim of this study is to determine the role of cardiac glycosphingolipids in heart function.METHODS AND RESULTS: Using human myocardial biopsies, we showed that the glycosphingolipids glucosylceramide and lactosylceramide are present at very low levels in non-ischaemic human heart with normal function and are elevated during remodelling. Similar results were observed in mouse models of cardiac remodelling. We also generated mice with cardiomyocyte-specific deficiency in Ugcg, the gene encoding glucosylceramide synthase (hUgcg-/- mice). In 9- to 10-week-old hUgcg-/- mice, contractile capacity in response to dobutamine stress was reduced. Older hUgcg-/- mice developed severe heart failure and left ventricular dilatation even under baseline conditions and died prematurely. Using RNA-seq and cell culture models, we showed defective endolysosomal retrograde trafficking and autophagy in Ugcg-deficient cardiomyocytes. We also showed that responsiveness to β-adrenergic stimulation was reduced in cardiomyocytes from hUgcg-/- mice and that Ugcg knockdown suppressed the internalization and trafficking of β1-adrenergic receptors.CONCLUSIONS: Our findings suggest that cardiac glycosphingolipids are required to maintain β-adrenergic signalling and contractile capacity in cardiomyocytes and to preserve normal heart function.
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18.
  • Arif, Muhammad, et al. (författare)
  • INetModels 2.0: An interactive visualization and database of multi-omics data
  • 2021
  • Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 49:W1, s. W271-W276
  • Tidskriftsartikel (refereegranskat)abstract
    • It is essential to reveal the associations between various omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics, plasma metabolomics, as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and disease research. iNetModels can be accessed freely at https://inetmodels.com without any limitation.
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19.
  • Arif, Muhammad, et al. (författare)
  • Integrative transcriptomic analysis of tissue-specific metabolic crosstalk after myocardial infarction
  • 2021
  • Ingår i: Elife. - : eLife Sciences Publications, Ltd. - 2050-084X. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • Myocardial infarction (MI) promotes a range of systemic effects, many of which are unknown. Here, we investigated the alterations associated with MI progression in heart and other metabolically active tissues (liver, skeletal muscle, and adipose) in a mouse model of MI (induced by ligating the left ascending coronary artery) and sham-operated mice. We performed a genomewide transcriptomic analysis on tissue samples obtained 6- and 24 hr post MI or sham operation. By generating tissue-specific biological networks, we observed: (1) dysregulation in multiple biological processes (including immune system, mitochondrial dysfunction, fatty-acid beta-oxidation, and RNA and protein processing) across multiple tissues post MI and (2) tissue-specific dysregulation in biological processes in liver and heart post MI. Finally, we validated our findings in two independent MI cohorts. Overall, our integrative analysis highlighted both common and specific biological responses to MI across a range of metabolically active tissues.
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20.
  • Arif, Muhammad (författare)
  • Systems and Network-based Approaches to Complex Metabolic Diseases
  • 2021
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The future of healthcare is personalized medicine, in which disease treatments are tailored based on the individual characteristics of each patient. To reach that objective, we need to obtain a better understanding of diseases. The main facilitator of personalized medicine is systems and data-driven biology, which makes omics data a top commodity in this era. Coupled with computational and biological expertise, omics data can be a useful asset for obtaining mechanistic insights into the biological conundrum, particularly in disease-related contexts. This thesis describes systems biology approaches and their applications in disease-specific contexts. Systems biology assists us in systematically and comprehensively understanding complex biological systems as a whole interconnected system.The first part of the thesis describes the generation of more than 100 biological networks based on personalized data originated from several different omics, usually referred to as multiomics data, including clinical data and metabolomics, proteomics, and metagenomics data collected from the same individuals. Moreover, we present a web-based multiomics biological network database and visualization platform called iNetModels.In the second part of the thesis, we describe systems biology frameworks and their applications to the study of various biological questions in disease contexts using single- and multiomics data. First, we present our findings on the integrative view of metabolic activities from multiple tissues after myocardial infarction using transcriptomics data from the heart and other metabolically active tissues. Second, we used transcriptomics data to describe the mechanistic effect of lifelong training on skeletal muscle in both men and women and the role of short-term training in reversing damage from metabolic-related diseases. Third, we deciphered the molecular mechanism of nonalcoholic fatty liver disease (NAFLD) based on clinical data, plasma metabolomics, plasma inflammatory proteomics, and oral and gut metagenomics data. Finally, we elucidated the mechanism of action of CMA supplementation, a potential treatment for NAFLD, based on proteomics and metabolomics data.In summary, this thesis presents a novel platform for biological network analysis and proven systems biology frameworks to provide mechanistic and systematic understandings of specific diseases using single- and multiomics data.
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