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Infections are one of the most significant healthcare and economic burdens across the world as underscored by the recent coronavirus pandemic. Moreover, with the increasing incidence of antimicrobial resistance, there is an urgent need to better understand host-pathogen interactions to design effective treatment strategies. The complement system is a key arsenal of the host defense response to pathogens and bridges both innate and adaptive immunity. However, in the contest between pathogens and host defense mechanisms, the host is not always victorious. Pathogens have evolved several approaches, including co-opting the host complement regulators to evade complement-mediated killing. Furthermore, deficiencies in the complement proteins, both genetic and therapeutic, can lead to an inefficient complement-mediated pathogen eradication, rendering the host more susceptible to certain infections. On the other hand, overwhelming infection can provoke fulminant complement activation with uncontrolled inflammation and potentially fatal tissue and organ damage. This review presents an overview of critical aspects of the complement-pathogen interactions during infection and discusses perspectives on designing therapies to mitigate complement dysfunction and limit tissue injury.
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Advanced age is associated with an increased susceptibility to Coronavirus Disease (COVID)-19 and more severe outcomes, although the underlying mechanisms are understudied. The lung endothelium is located next to infected epithelial cells and bystander inflammation may contribute to thromboinflammation and COVID-19-associated coagulopathy. Here, we investigated age-associated SARS-CoV-2 pathogenesis and endothelial inflammatory responses using humanized K18-hACE2 mice. Survival was reduced to 20% in aged mice (85-112 weeks) versus 50% in young mice (12-15 weeks) at 10 days post infection (dpi). Bulk RNA-sequencing of endothelial cells from mock and infected mice at 2dpi of both age groups (aged: 72-85 weeks; young: 15 weeks) showed substantially lower significant differentially regulated genes in infected aged mice than in young mice (712 versus 2294 genes). Viral recognition and anti-viral pathways such as RIG-I-like receptor signaling, NOD-like receptor signaling and interferon signaling were regulated in response to SARS-CoV-2. Young mice showed several fold higher interferon responses (Ifitm3, Ifit1, Isg15, Stat1) and interferon-induced chemokines (Cxcl10 and Cxcl11) than aged mice. Endothelial cells from infected young mice displayed elevated expression of chemokines (Cxcl9, Ccl2) and leukocyte adhesion markers (Icam1) underscoring that inflammation of lung endothelium during infection could facilitate leukocyte adhesion and thromboinflammation. TREM1 and acute phase response signaling were particularly prominent in endothelial cells from infected young mice. Immunohistochemistry was unable to detect viral protein in pulmonary endothelium. In conclusion, our data demonstrate that the early host response of the endothelium to SARS-CoV-2 infection declines with aging, which could be a potential contributor to disease severity.
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Envejecimiento , COVID-19 , Células Endoteliales , Pulmón , SARS-CoV-2 , Animales , COVID-19/inmunología , COVID-19/patología , SARS-CoV-2/fisiología , Células Endoteliales/metabolismo , Células Endoteliales/virología , Células Endoteliales/inmunología , Ratones , Pulmón/inmunología , Pulmón/virología , Pulmón/patología , Humanos , Envejecimiento/inmunología , Modelos Animales de Enfermedad , Inflamación/inmunología , Enzima Convertidora de Angiotensina 2/metabolismo , Enzima Convertidora de Angiotensina 2/genética , Ratones TransgénicosRESUMEN
To understand functional duality of the complement system in host defense and lung injury, a more comprehensive view of its localized production in the lung, and the impact of age on complement production are essential. Here, we explored the expression of complement genes through computational analysis of preexisting single cell RNA sequencing data from lung transcriptomes of healthy young (3 months) and old C57BL/6 mice (24 months), and humans. We characterized the distribution of 48 complement genes. Across 28 distinct immune and non-immune cell types in mice, mesothelial cells expressed the greatest number of complement genes (e.g., C1ra, C2, C3), and regulators (e.g., Serping1, Cfh). C5 was abundant in type II alveolar epithelial cells and C1q in interstitial lung macrophages. There were only moderate differences in gene expression between young and old mice. Among 57 human lung cell types, mesothelial cells showed abundant complement expression. A few differences in gene expression (e.g., FCN1, CFI, C6, C7) were also evident between mice and human lung cells. Our findings present a novel perspective on the expression patterns of complement genes in normal lungs. These findings highlight the potential functions of complement in tissue-specific homeostasis and immunity and may foster a mechanistic understanding of its role in lung health and disease.
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Proteínas del Sistema Complemento , Pulmón , Animales , Proteínas del Sistema Complemento/genética , Proteínas del Sistema Complemento/metabolismo , Epitelio/metabolismo , Humanos , Ratones , Ratones Endogámicos C57BLRESUMEN
Several reports document the role of tumor necrosis factor alpha (TNF-α) and lipid metabolism in the context of acute inflammation as a causative factor in obesity-associated insulin resistance and as one of the causative parameter of type 2 diabetes mellitus (T2DM). Our aim was to investigate the association between -308G/A and -238G/A polymorphisms located in the promoter region of the TNF-α gene in T2DM in the Indian population with bioinformatics analysis of TNF-α protein networking with an aim to find new target sites for the treatment of T2DM. Demographics of 100 diabetes patients and 100 healthy volunteers were collected in a structured proforma and 3 ml blood samples were obtained from the study group, after approval of Institutional Ethics Committee of the hospital (IEC). The information on clinical parameters was obtained from medical records. Genomic DNA was extracted; PCR-RFLP was performed using TNF-α primers specific to detect the presence of SNPs. Various bioinformatics tools such as STRING software were used to determine its network with other associated genes. The PCR-RFLP studies showed that among the -238G/A types the GG genotype was 87%, GA genotype was 12% and AA genotype was 1%. Almost a similar pattern of results was obtained with TNF-α -308G/A polymorphism. The results obtained were evaluated statistically to determine the significance. By constructing TNF-α protein interaction network we could analyze ontology and hubness of the network to identify the networking of this gene which may influence the functioning of other genes in promoting T2DM. We could identify new targets in T2DM which may function in association with TNF-α. Through hub analysis of TNF-α protein network we have identified three novel proteins RIPK1, BIRC2 and BIRC3 which may contribute to TNF-mediated T2DM pathogenesis. In conclusion, our study indicated that some of the genotypes of TNF-α -308G/A, -238G/A were not significantly associated to type 2 diabetes mellitus, but TNF-α -308G/A polymorphism was reported to be a potent risk factor for diabetes in higher age (>45) groups. Also, the novel hub proteins may serve as new targets against TNF-α T2DM pathogenesis.
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There is a need to identify novel targets in Acute Lymphoblastic Leukemia (ALL), a hematopoietic cancer affecting children, to improve our understanding of disease biology and that can be used for developing new therapeutics. Hence, the aim of our study was to find new genes as targets using in silico studies; for this we retrieved the top 10% overexpressed genes from Oncomine public domain microarray expression database; 530 overexpressed genes were short-listed from Oncomine database. Then, using prioritization tools such as ENDEAVOUR, DIR and TOPPGene online tools, we found fifty-four genes common to the three prioritization tools which formed our candidate leukemogenic genes for this study. As per the protocol we selected thirty training genes from PubMed. The prioritized and training genes were then used to construct STRING functional association network, which was further analyzed using cytoHubba hub analysis tool to investigate new genes which could form drug targets in leukemia. Analysis of the STRING protein network built from these prioritized and training genes led to identification of two hub genes, SMAD2 and CDK9, which were not implicated in leukemogenesis earlier. Filtering out from several hundred genes in the network we also found MEN1, HDAC1 and LCK genes, which re-emphasized the important role of these genes in leukemogenesis. This is the first report on these five additional signature genes in leukemogenesis. We propose these as new targets for developing novel therapeutics and also as biomarkers in leukemogenesis, which could be important for prognosis and diagnosis.
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MDR1, a protein commonly involved in drug transport, has been linked to multi drug resistance and disease progression in cancers such as non-small cell lung cancer. Hence, targeting this protein is essential for improving drug design and preventing adverse drug-drug interactions. The aim of the study was to examine chemotherapeutic drug binding to MDR1 and the interactions therein. We have used Schrödinger suite 2014, to perform homology modelling of human MDR1 based on Mouse MDR1, followed by Induced Fit Docking with Paclitaxel, Docetaxel, Gemcitabine, Carboplatin and Cisplatin drugs. Finally, we evaluated drug binding affinities using Prime/MMGBSA and using these scores we compared the affinities of combination therapies against MDR1. Analysis of the docking results showed Paclitaxel>Docetaxel>Gemcitabine>Carboplatin>Cisplatin as the order of binding affinities, with Paclitaxel having the best docking score. The combination drug binding affinity analysis showed Paclitaxel+Gemcitabine to have the best docking score and hence, efficacy. Through our investigation we have identified the residues Gln 195 and Gln 946 to be more frequently involved in drug binding interactions with MDR1. Our results suggest that, Paclitaxel or combination of Paclitaxel+Gemcitabine could serve as a suitable therapy against MDR1 in NSCLC patients. Thus, our study provides new insight into the possible repurposing of chemotherapeutic drugs in targeting elevated MDR1 levels in NSCLC patients, thereby ensuring better overall outcome. Further our study highlights the use of in silico methodologies in understanding drug binding to protein targets and its relevance to advancing lung cancer therapy.
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Antineoplásicos/química , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Neoplasias Pulmonares/tratamiento farmacológico , Simulación del Acoplamiento Molecular , Homología Estructural de Proteína , Subfamilia B de Transportador de Casetes de Unión a ATP/química , Secuencia de Aminoácidos , Animales , Antineoplásicos/uso terapéutico , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Sitios de Unión , Carboplatino/química , Carboplatino/uso terapéutico , Cisplatino/química , Cisplatino/uso terapéutico , Desoxicitidina/análogos & derivados , Desoxicitidina/química , Desoxicitidina/uso terapéutico , Docetaxel , Humanos , Ratones , Datos de Secuencia Molecular , Paclitaxel/química , Paclitaxel/uso terapéutico , Alineación de Secuencia , Taxoides/química , Taxoides/uso terapéutico , Termodinámica , GemcitabinaRESUMEN
Alterations in cell cycle regulating proteins are a key characteristic in neoplastic proliferation of lymphoblast cells in patients with Acute Lymphoblastic Leukemia (ALL). The aim of our study was to investigate whether the routinely administered ALL chemotherapeutic agents would be able to bind and inhibit the key deregulated cell cycle proteins such as--Cyclins E1, D1, D3, A1 and Cyclin Dependent Kinases (CDK) 2 and 6. We used Schrödinger Glide docking protocol to dock the chemotherapeutic drugs such as Doxorubicin and Daunorubicin and others which are not very common including Clofarabine, Nelarabine and Flavopiridol, to the crystal structures of these proteins. We observed that the drugs were able to bind and interact with cyclins E1 and A1 and CDKs 2 and 6 while their docking to cyclins D1 and D3 were not successful. This binding proved favorable to interact with the G1/S cell cycle phase proteins that were examined in this study and may lead to the interruption of the growth of leukemic cells. Our observations therefore suggest that these drugs could be explored for use as inhibitors for these cell cycle proteins. Further, we have also highlighted residues which could be important in the designing of pharmacophores against these cell cycle proteins. This is the first report in understanding the mechanism of action of the drugs targeting these cell cycle proteins in leukemia through the visualization of drug-target binding and molecular docking using computational methods.
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Antineoplásicos/química , Simulación del Acoplamiento Molecular , Leucemia-Linfoma Linfoblástico de Células Precursoras/tratamiento farmacológico , Arabinonucleósidos/química , Carcinogénesis , Dominio Catalítico , Puntos de Control del Ciclo Celular/efectos de los fármacos , Proteínas de Ciclo Celular/química , Curcumina/química , Daunorrubicina/química , Doxorrubicina/química , Humanos , Enlace de Hidrógeno , Terapia Molecular DirigidaRESUMEN
Notch signaling plays a critical role in cell fate determination and maintenance of progenitors in many developmental systems. Notch receptors have been shown to be expressed on hematopoietic progenitor cells as well as to various degrees in peripheral blood T and B lymphocytes, monocytes, and neutrophils. Our aim was to understand the protein interaction network, using Notch1 protein name as query in STRING database and we generated a model to assess the significance of Notch1 associated proteins in Acute Lymphoblastic Leukemia (ALL). We further analyzed the expression levels of the genes encoding hub proteins, using Oncomine database, to determine their significance in leukemogenesis. Of the forty two hub genes, we observed that sixteen genes were underexpressed and eleven genes were overexpressed in T-cell Acute Lymphoblastic samples in comparison to their expression levels in normal cells. Of these, we found three novel genes which have not been reported earlier- KAT2B, PSEN1 (underexpressed) and CDH2 (overexpressed).These three identified genes may provide new insights into the abnormal hematopoietic process observed in Leukemia as these genes are involved in Notch signaling and cell adhesion processes. It is evident that experimental validation of the protein interactors in leukemic cells could help in the identification of new diagnostic markers for leukemia.