78 research outputs found

    Investigating iPSC derived macrophages as a model to study Mtb infection compared to alveolar macrophages, monocyte derived macrophages and THP-1 macrophages

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    Mycobacterium tuberculosis (Mtb) er fortsatt et omfattende folkehelseproblem for en stor del av verdens utviklingsland, og forårsaker mer enn 1,5 millioner dødsfall årlig. Imidlertid forblir mange aspekter av interaksjonene i vertspatogenet flyktige og vanskelige å forstå. Dette er delvis på grunn av patogenets relasjon til den alveolære makrofagen, som gir en tidlig replikativ nisje. Dette legger til rette for immununnvikelse og etablering av den la-tente sykdommen som antas å påvirke en fjerdedel av dagens verdensbefolkning. De unike egenskapene til den alveolære makrofagen og miljøet den er spesifikk for, hemmer vår forståelse av de tidlige interaksjonene ettersom in vitro-modeller av dette miljøet er vanskelige å simulere. Nyere fremskritt innen stamcellebaserte teknologier gir imidlertid en rekke nye celletyper for forskningsformål som, i teorien, kan imitere enhver celles-kjebne, inkludert den flyktige alveolære makrofagen. iPSC-avledede makrofager (iMAC) har nylig blitt brukt til tuberkuloserelatert forskning, men deres Mtb-induserte immunre-spons og potensielle rolle som en modellcellelinje for alveolære makrofager har ikke blitt evaluert. Derfor har denne oppgaven sammenlignet iMAC-er med alveolære makrofager, monocyttavledede makrofager og den etablerte TB- modellcellelinjen, THP1-makrofager, for å analysere deres egnethet som et verktøy for tuberkuloseforskning. For å gi en bred oversikt over de Mtb-induserte immunresponsene, ble mRNA-sekvensering utført for å sammenligne genuttrykket til ubehandlede og Mtb-behandlede celler. mRNA-sekvensering er et effektivt verktøy for en innledende granskning og gir data om en rekke biologiske prosesser. Dette er nyttig når man prøver å etablere oversikt over en celles immunre-spons. Dataene som er analysert i denne oppgaven viser at Mtb-induserte endringer i genuttryk-ket til iMAC-er er svært sammenlignbare med AM-er og MDM-er i aspekter som inflam-matorisk respons, reseptoruttrykk og antigenpresentasjonsprosesser. Flere viktige for-skjeller er også observert, inkludert en mye sterkere type 1 interferonrespons og i ut-trykket av proteiner som kan påvirke celleskjebnen til T-celler som samhandler med iMAC-er. Selv om MDM-er viser et nærmere forhold til AM-er, har iMAC-er fordeler som homogenitet, reproduserbarhet og enkel manipulering, tidligere bare funnet i andre se-kundære cellelinjer som THP1. Videre viser denne oppgaven at iMAC-er er bedre egnet for AM- (og MDM)-emulering enn THP1-celler, som, selv om de er en veletablert celletype for tuberkuloseforskning, viser seg som en avviker sammenlignet med de andre cellene. Selv om det kan trekkes en begrenset mengde spesifikke konklusjoner fra mRNA-uttrykksdata, tjener observasjonene som er gjort i denne oppgaven som en guide for forskere i å bestemme de spesifikke anvendelsene av iMAC-er. Videre fremhever datae-ne egenskaper som kan påvirke observasjoner i fremtidige iMAC-baserte eksperimenter. Forhåpentligvis kan denne oppgaven bidra til ytterligere forbedringer rettet mot å gjøre iMAC-er til en nøyaktig modellcellelinje, en sårt tiltrengt ressurs innen tuberkuloseforsk-ning

    Dynamics of Dual Specificity Phosphatases and Their Interplay with Protein Kinases in Immune Signaling

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    Dual specificity phosphatases (DUSPs) have a well-known role as regulators of the immune response through the modulation of mitogen-activated protein kinases (MAPKs). Yet the precise interplay between the various members of the DUSP family with protein kinases is not well understood. Recent multi-omics studies characterizing the transcriptomes and proteomes of immune cells have provided snapshots of molecular mechanisms underlying innate immune response in unprecedented detail. In this study, we focus on deciphering the interplay between members of the DUSP family with protein kinases in immune cells using publicly available omics datasets. Our analysis resulted in the identification of potential DUSP-mediated hub proteins including MAPK7, MAPK8, AURKA, and IGF1R. Furthermore, we analyzed the association of DUSP expression with TLR4 signaling and identified VEGF, FGFR, and SCF-KIT pathway modules to be regulated by the activation of TLR4 signaling. Finally, we identified several important kinases including LRRK2, MAPK8, and cyclin-dependent kinases as potential DUSP-mediated hubs in TLR4 signaling. The findings from this study have the potential to aid in the understanding of DUSP signaling in the context of innate immunity. Further, this will promote the development of therapeutic modalities for disorders with aberrant DUSP signaling

    The Role of Omics Approaches to Characterize Molecular Mechanisms of Rare Ovarian Cancers: Recent Advances and Future Perspectives

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    Rare ovarian cancers are ovarian cancers with an annual incidence of less than 6 cases per 100,000 women. They generally have a poor prognosis due to being delayed diagnosis and treatment. Exploration of molecular mechanisms in these cancers has been challenging due to their rarity and research efforts being fragmented across the world. Omics approaches can provide detailed molecular snapshots of the underlying mechanisms of these cancers. Omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, can identify potential candidate biomarkers for diagnosis, prognosis, and screening of rare gynecological cancers and can aid in identifying therapeutic targets. The integration of multiple omics techniques using approaches such as proteogenomics can provide a detailed understanding of the molecular mechanisms of carcinogenesis and cancer progression. Further, omics approaches can provide clues towards developing immunotherapies, cancer recurrence, and drug resistance in tumors; and form a platform for personalized medicine. The current review focuses on the application of omics approaches and integrative biology to gain a better understanding of rare ovarian cancers

    MultiOMICs landscape of SARS-CoV-2-induced host responses in human lung epithelial cells

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    COVID-19 pandemic continues to remain a global health concern due to the emergence of newer variants. Several multiOmics studies have produced extensive evidence on host-pathogen interactions and potential therapeutic targets. Nonetheless, an increased understanding of host signaling networks regulated by post-translational modifications and their ensuing effect on the cellular dynamics is critical to expanding the current knowledge on SARS-CoV-2 infections. Through an unbiased transcriptomics, proteomics, acetylomics, phosphoproteomics, and exometabolome analysis of a lung-derived human cell line, we show that SARS-CoV-2 Norway/Trondheim-S15 strain induces time-dependent alterations in the induction of type I IFN response, activation of DNA damage response, dysregulated Hippo signaling, among others. We identified interplay of phosphorylation and acetylation dynamics on host proteins and its effect on the altered release of metabolites, especially organic acids and ketone bodies. Together, our findings serve as a resource of potential targets that can aid in designing novel host-directed therapeutic strategies

    Serum autoantibody profiling of oral squamous cell carcinoma patients reveals NUBP2 as a potential diagnostic marker

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    IntroductionOral Squamous Cell Carcinoma (OSCC), a common malignancy of the head and neck region, is frequently diagnosed at advanced stages, necessitating the development of efficient diagnostic methods. Profiling autoantibodies generated against tumor-associated antigens have lately demonstrated a promising role in diagnosis, predicting disease course, and response to therapeutics and relapse.MethodsIn the current study, we, for the first time, aimed to identify and evaluate the diagnostic value of autoantibodies in serum samples of patients with OSCC using autoantibody profiling by an immunome protein array. The utility of anti-NUBP2 antibody and tissue positivity in OSCC was further evaluated.Results and discussionWe identified a total of 53 autoantibodies with significant differential levels between OSCC and control groups, including 25 that were increased in OSCC and 28 that were decreased. These included autoantibodies against Thymidine kinase 1 (TK1), nucleotide-binding protein 2 (NUBP2), and protein pyrroline-5-carboxylate reductase 1 (PYCR1), among others. Immunohistochemical validation indicated positive staining of NUBP2 in a large majority of cases (72%). Further, analysis of OSCC data available in TCGA revealed higher NUBP2 expression correlated with better disease-free patient survival. In conclusion, the differential serum autoantibodies identified in the current study, including those for NUBP2, could be used as potential biomarkers for early diagnosis or as screening biomarkers for OSCC pending investigation in a larger cohort

    Proteogenomics Analysis Reveals Novel Micropeptides in Primary Human Immune Cells

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    Short open reading frames (sORFs) encoding functional peptides have emerged as important mediators of biological processes. Recent studies indicate that sORFs of long non-coding RNAs (lncRNAs) can encode functional micropeptides regulating immunity and inflammation. However, large-scale identification of potential micropeptide-encoding sequences is a significant challenge. We present a data analysis pipeline that uses immune cell-derived mass spectrometry-based proteomic data reanalyzed using a rigorous proteogenomics-based workflow. Our analysis resulted in the identification of 2815 putative lncRNA-encoded micropeptides across three human immune cell types. Stringent score cut-off and manual verification confidently identified 185 high-confidence putative micropeptide-coding events, of which a majority have not been reported previously. Functional validation revealed the expression and localization of lnc-MKKS in both nucleus and cytoplasmic compartments. Our pilot analysis serves as a resource for future studies focusing on the role of micropeptides in immune cell response
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