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1.
Methods Mol Biol ; 2390: 177-190, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34731469

RESUMO

We describe an approach to early stage drug discovery that explicitly engages with the complexities of human biology. The combined computational and experimental approach is formulated on a conceptual framework in which network biology is used to bridge between individual molecular entities and the cellular phenotype that emerges when those entities interact in a network. Multiple aspects of early stage discovery are addressed including the data-driven elucidation of biological processes implicated in disease, target identification and validation, phenotypic discovery of active molecules and their mechanism of action, and extraction of genetic target support from human population genetics data. Validation is described via summary of a number of discovery projects and details from a project aimed at COVID-19 disease.


Assuntos
Antivirais/uso terapêutico , COVID-19/tratamento farmacológico , Descoberta de Drogas , SARS-CoV-2/efeitos dos fármacos , Biologia de Sistemas , Animais , Antivirais/efeitos adversos , COVID-19/diagnóstico , COVID-19/virologia , Interações Hospedeiro-Patógeno , Humanos , Estrutura Molecular , Terapia de Alvo Molecular , SARS-CoV-2/patogenicidade , Relação Estrutura-Atividade
2.
Bioresour Technol ; 343: 126007, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34634665

RESUMO

Cyanobacteria are oxygenic photoautotrophs whose metabolism contains key biochemical pathways to fix atmospheric CO2 and synthesize various metabolites. The development of bioengineering tools has enabled the manipulation of cyanobacterial chassis to produce various valuable bioproducts photosynthetically. However, effective utilization of cyanobacteria as photosynthetic cell factories needs a detailed understanding of their metabolism and its interaction with other cellular processes. Implementing systems and synthetic biology tools has generated a wealth of information on various metabolic pathways. However, to design effective engineering strategies for further improvement in growth, photosynthetic efficiency, and enhanced production of target biochemicals, in-depth knowledge of their carbon/nitrogen metabolism, pathway fluxe distribution, genetic regulation and integrative analyses are necessary. In this review, we discuss the recent advances in the development of genome-scale metabolic models (GSMMs), omics analyses (metabolomics, transcriptomics, proteomics, fluxomics), and integrative modeling approaches to showcase the current understanding of cyanobacterial metabolism.


Assuntos
Cianobactérias , Biologia de Sistemas , Cianobactérias/genética , Engenharia Metabólica , Metabolômica , Fotossíntese , Biologia Sintética
3.
Sci Rep ; 11(1): 21872, 2021 11 08.
Artigo em Inglês | MEDLINE | ID: mdl-34750486

RESUMO

Severe acute respiratory syndrome (SARS) is a highly contagious viral respiratory illness. This illness is spurred on by a coronavirus known as SARS-associated coronavirus (SARS-CoV). SARS was first detected in Asia in late February 2003. The genome of this virus is very similar to the SARS-CoV-2. Therefore, the study of SARS-CoV disease and the identification of effective drugs to treat this disease can be new clues for the treatment of SARS-Cov-2. This study aimed to discover novel potential drugs for SARS-CoV disease in order to treating SARS-Cov-2 disease based on a novel systems biology approach. To this end, gene co-expression network analysis was applied. First, the gene co-expression network was reconstructed for 1441 genes, and then two gene modules were discovered as significant modules. Next, a list of miRNAs and transcription factors that target gene co-expression modules' genes were gathered from the valid databases, and two sub-networks formed of transcription factors and miRNAs were established. Afterward, the list of the drugs targeting obtained sub-networks' genes was retrieved from the DGIDb database, and two drug-gene and drug-TF interaction networks were reconstructed. Finally, after conducting different network analyses, we proposed five drugs, including FLUOROURACIL, CISPLATIN, SIROLIMUS, CYCLOPHOSPHAMIDE, and METHYLDOPA, as candidate drugs for SARS-CoV-2 coronavirus treatment. Moreover, ten miRNAs including miR-193b, miR-192, miR-215, miR-34a, miR-16, miR-16, miR-92a, miR-30a, miR-7, and miR-26b were found to be significant miRNAs in treating SARS-CoV-2 coronavirus.


Assuntos
COVID-19/tratamento farmacológico , COVID-19/imunologia , COVID-19/virologia , Reposicionamento de Medicamentos , Perfilação da Expressão Gênica , Regulação Viral da Expressão Gênica , SARS-CoV-2 , Biologia Computacional , Redes Reguladoras de Genes , Genes Virais , Técnicas Genéticas , Humanos , MicroRNAs/metabolismo , Análise de Sequência com Séries de Oligonucleotídeos , Biologia de Sistemas , Fatores de Transcrição
4.
Adv Exp Med Biol ; 1336: 1-15, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34628624

RESUMO

Omics sciences have been facing challenges in different fields, especially in life sciences. One of these challenges involves assessing biology into systems interpretation. With the advance of genomics, molecular biology has been projected into the realm of systems biology. In a different direction, systems approaches are making definitive strides toward scientific understanding and biotechnological applications. Separation techniques provided meaningful progress in the omics era, conducting the classical molecular biology to contemporary systems biology. In this introductory chapter, the relevance of these techniques to the development of different omics sciences, within the systems biology context, will be discussed.


Assuntos
Genômica , Biologia de Sistemas , Biologia Molecular
5.
Nat Protoc ; 16(11): 5030-5082, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34635859

RESUMO

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are emerging as a valuable avenue for predicting, understanding and designing microbial communities. Computation of microbial ecosystems in time and space (COMETS) extends dynamic flux balance analysis to generate simulations of multiple microbial species in molecularly complex and spatially structured environments. Here we describe how to best use and apply the most recent version of COMETS, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, evolutionary dynamics and extracellular enzyme activity modules. In addition to a command-line option, COMETS includes user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, as well as comprehensive documentation and tutorials. This protocol provides a detailed guideline for installing, testing and applying COMETS to different scenarios, generating simulations that take from a few minutes to several days to run, with broad applicability to microbial communities across biomes and scales.


Assuntos
Modelos Biológicos , Biologia de Sistemas , Microbiota
6.
BMC Bioinformatics ; 22(1): 424, 2021 Sep 07.
Artigo em Inglês | MEDLINE | ID: mdl-34493207

RESUMO

BACKGROUND: In systems biology, it is important to reconstruct regulatory networks from quantitative molecular profiles. Gaussian graphical models (GGMs) are one of the most popular methods to this end. A GGM consists of nodes (representing the transcripts, metabolites or proteins) inter-connected by edges (reflecting their partial correlations). Learning the edges from quantitative molecular profiles is statistically challenging, as there are usually fewer samples than nodes ('high dimensional problem'). Shrinkage methods address this issue by learning a regularized GGM. However, it remains open to study how the shrinkage affects the final result and its interpretation. RESULTS: We show that the shrinkage biases the partial correlation in a non-linear way. This bias does not only change the magnitudes of the partial correlations but also affects their order. Furthermore, it makes networks obtained from different experiments incomparable and hinders their biological interpretation. We propose a method, referred to as 'un-shrinking' the partial correlation, which corrects for this non-linear bias. Unlike traditional methods, which use a fixed shrinkage value, the new approach provides partial correlations that are closer to the actual (population) values and that are easier to interpret. This is demonstrated on two gene expression datasets from Escherichia coli and Mus musculus. CONCLUSIONS: GGMs are popular undirected graphical models based on partial correlations. The application of GGMs to reconstruct regulatory networks is commonly performed using shrinkage to overcome the 'high-dimensional problem'. Besides it advantages, we have identified that the shrinkage introduces a non-linear bias in the partial correlations. Ignoring this type of effects caused by the shrinkage can obscure the interpretation of the network, and impede the validation of earlier reported results.


Assuntos
Biologia de Sistemas , Animais , Camundongos , Distribuição Normal
7.
BMC Musculoskelet Disord ; 22(1): 789, 2021 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-34521416

RESUMO

BACKGROUND: Ankylosing spondylitis (AS) is an autoimmune rheumatic disease. Few candidate gene associations have been reported for AS and the current understanding of its pathogenesis remains still poor. Thus, the exact mechanism of AS is needed to urgently be disclosed. The purpose of this study was to identify candidate genes involving in AS disease. METHODS AND RESULTS: GSE25101 publicly available microarray and GSE117769 RNA-seq datasets of AS patients were obtained for bioinformatics analyses. Gene set enrichment analysis showed that in the microarray dataset, the ribosome pathway was significantly up-regulated in AS compared with controls. Furthermore, some ribosomal components demonstrated overexpression in patients in the RNA-seq dataset. To confirm the findings, 20 AS patients and 20 matching controls were selected from the Rheumatology Research Center clinic, Shariati Hospital. PBMCs were separated from whole blood and RNA contents were extracted. Following the results of datasets analysis, the expression level of rRNA5.8S pseudogene, rRNA18S pseudogene, RPL23, RPL7, and RPL17 genes were measured through real-time PCR. Our findings showed dysregulation of rRNA5.8S and rRNA18S pseudogenes, and also the RPL17 gene in patients. CONCLUSION: Considering that genes involved in ribosome biogenesis contributed to some AS-associated biological processes as well as diseases that have comorbidities with AS, our results might advance our understanding of the pathological mechanisms of ankylosing spondylitis.


Assuntos
Espondilite Anquilosante , Biologia Computacional , Humanos , Ribossomos/genética , Espondilite Anquilosante/genética , Biologia de Sistemas
8.
BMC Bioinformatics ; 22(1): 442, 2021 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-34535069

RESUMO

BACKGROUND: The desire to understand genomic functions and the behavior of complex gene regulatory networks has recently been a major research focus in systems biology. As a result, a plethora of computational and modeling tools have been proposed to identify and infer interactions among biological entities. Here, we consider the general question of the effect of perturbation on the global dynamical network behavior as well as error propagation in biological networks to incite research pertaining to intervention strategies. RESULTS: This paper introduces a computational framework that combines the formulation of Boolean networks and factor graphs to explore the global dynamical features of biological systems. A message-passing algorithm is proposed for this formalism to evolve network states as messages in the graph. In addition, the mathematical formulation allows us to describe the dynamics and behavior of error propagation in gene regulatory networks by conducting a density evolution (DE) analysis. The model is applied to assess the network state progression and the impact of gene deletion in the budding yeast cell cycle. Simulation results show that our model predictions match published experimental data. Also, our findings reveal that the sample yeast cell-cycle network is not only robust but also consistent with real high-throughput expression data. Finally, our DE analysis serves as a tool to find the optimal values of network parameters for resilience against perturbations, especially in the inference of genetic graphs. CONCLUSION: Our computational framework provides a useful graphical model and analytical tools to study biological networks. It can be a powerful tool to predict the consequences of gene deletions before conducting wet bench experiments because it proves to be a quick route to predicting biologically relevant dynamic properties without tunable kinetic parameters.


Assuntos
Modelos Genéticos , Saccharomyces cerevisiae , Algoritmos , Ciclo Celular/genética , Redes Reguladoras de Genes , Modelos Biológicos , Saccharomyces cerevisiae/genética , Biologia de Sistemas
9.
Elife ; 102021 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-34490844

RESUMO

Bacteria live in environments that are continuously fluctuating and changing. Exploiting any predictability of such fluctuations can lead to an increased fitness. On longer timescales, bacteria can 'learn' the structure of these fluctuations through evolution. However, on shorter timescales, inferring the statistics of the environment and acting upon this information would need to be accomplished by physiological mechanisms. Here, we use a model of metabolism to show that a simple generalization of a common regulatory motif (end-product inhibition) is sufficient both for learning continuous-valued features of the statistical structure of the environment and for translating this information into predictive behavior; moreover, it accomplishes these tasks near-optimally. We discuss plausible genetic circuits that could instantiate the mechanism we describe, including one similar to the architecture of two-component signaling, and argue that the key ingredients required for such predictive behavior are readily accessible to bacteria.


Assuntos
Bactérias , Fenômenos Fisiológicos Bacterianos , Modelos Teóricos , Aprendizagem , Transdução de Sinais , Biologia de Sistemas
10.
Nat Commun ; 12(1): 5357, 2021 09 09.
Artigo em Inglês | MEDLINE | ID: mdl-34504069

RESUMO

Spatial organisation through localisation/compartmentalisation of species is a ubiquitous but poorly understood feature of cellular biomolecular networks. Current technologies in systems and synthetic biology (spatial proteomics, imaging, synthetic compartmentalisation) necessitate a systematic approach to elucidating the interplay of networks and spatial organisation. We develop a systems framework towards this end and focus on the effect of spatial localisation of network components revealing its multiple facets: (i) As a key distinct regulator of network behaviour, and an enabler of new network capabilities (ii) As a potent new regulator of pattern formation and self-organisation (iii) As an often hidden factor impacting inference of temporal networks from data (iv) As an engineering tool for rewiring networks and network/circuit design. These insights, transparently arising from the most basic considerations of networks and spatial organisation, have broad relevance in natural and engineered biology and in related areas such as cell-free systems, systems chemistry and bionanotechnology.


Assuntos
Algoritmos , Modelos Teóricos , Mapas de Interação de Proteínas , Proteômica/métodos , Biologia Sintética/métodos , Biologia de Sistemas/métodos , Animais , Simulação por Computador , Humanos
11.
Int J Mol Sci ; 22(18)2021 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-34576123

RESUMO

Nasu-Hakola Disease (NHD) is a recessively inherited systemic leukodystrophy disorder characterized by a combination of frontotemporal presenile dementia and lytic bone lesions. NHD is known to be genetically related to a structural defect of TREM2 and DAP12, two genes that encode for different subunits of the membrane receptor signaling complex expressed by microglia and osteoclast cells. Because of its rarity, molecular or proteomic studies on this disorder are absent or scarce, only case reports based on neuropsychological and genetic tests being reported. In light of this, the aim of this paper is to provide evidence on the potential of a label-free proteomic platform based on the Multidimensional Protein Identification Technology (MudPIT), combined with in-house software and on-line bioinformatics tools, to characterize the protein expression trends and the most involved pathways in NHD. The application of this approach on the Lymphoblastoid cells from a family composed of individuals affected by NHD, healthy carriers and control subjects allowed for the identification of about 3000 distinct proteins within the three analyzed groups, among which proteins anomalous to each category were identified. Of note, several differentially expressed proteins were associated with neurodegenerative processes. Moreover, the protein networks highlighted some molecular pathways that may be involved in the onset or progression of this rare frontotemporal disorder. Therefore, this fully automated MudPIT platform which allowed, for the first time, the generation of the whole protein profile of Lymphoblastoid cells from Nasu-Hakola subjects, could be a valid approach for the investigation of similar neurodegenerative diseases.


Assuntos
Lipodistrofia/metabolismo , Lipodistrofia/patologia , Linfócitos/metabolismo , Linfócitos/patologia , Osteocondrodisplasias/metabolismo , Osteocondrodisplasias/patologia , Proteômica , Panencefalite Esclerosante Subaguda/metabolismo , Panencefalite Esclerosante Subaguda/patologia , Análise por Conglomerados , Análise Discriminante , Humanos , Glicoproteínas de Membrana/metabolismo , Mapas de Interação de Proteínas , Receptores Imunológicos/metabolismo , Biologia de Sistemas
12.
J Pharm Biomed Anal ; 205: 114357, 2021 Oct 25.
Artigo em Inglês | MEDLINE | ID: mdl-34500237

RESUMO

This study aimed to demonstrate the pharmacological mechanism of total flavonoids extracted from Astragali Radix (AR) on cyclophosphamide (Cy)-induced leucopenia in mice. First, flow cytometry, network pharmacology and plasma metabolomics were integrated to investigate the pharmacological mechanism of total flavonoids, the targets from network pharmacology and metabolites from metabolomics were analyzed by DAVID. Then, the key cytokines were validated to confirm the predicted metabolic pathway results. The results showed that total flavonoids significantly increased body weight, routine blood indices, bone marrow DNA cells, and also markedly caused lymphocyte proliferation by increasing the percentages of CD4+ and CD8+. Using network pharmacology and metabolomics methods, the study identified 13 signal-related pathways regulated by total flavonoids including PI3K-Akt signaling pathway, Jak-STAT signaling pathway, Sphingolipid signaling pathway, and so on. Total flavonoids also reversed changes in serum cytokines IL-2, IL-6, and GM-CSF. Total flavonoids exhibits protective effects against leucopenia probably by modulating immunologic functions, promoting cell proliferation, and regulating related metabolic pathways at the system level.


Assuntos
Medicamentos de Ervas Chinesas , Flavonoides , Animais , Ciclofosfamida/toxicidade , Medicamentos de Ervas Chinesas/farmacologia , Flavonoides/farmacologia , Camundongos , Fosfatidilinositol 3-Quinases , Biologia de Sistemas
13.
Ecotoxicol Environ Saf ; 225: 112793, 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34544019

RESUMO

Understanding the effects of chronic exposure to pollutants over generations is of primary importance for the protection of humans and the environment; however, to date, knowledge on the molecular mechanisms underlying multigenerational adverse effects is scarce. We employed a systems biology approach to analyze effects of chronic exposure to gamma radiation at molecular, tissue and individual levels in the nematode Caenorhabditis elegans. Our data show a decrease of 23% in the number of offspring on the first generation F0 and more than 40% in subsequent generations F1, F2 and F3. To unveil the impact on the germline, an in-depth analysis of reproductive processes involved in gametes formation was performed for all four generations. We measured a decrease in the number of mitotic germ cells accompanied by increased cell-cycle arrest in the distal part of the gonad. Further impact on the germline was manifested by decreased sperm quantity and quality. In order to obtain insight in the molecular mechanisms leading to decreased fecundity, gene expression was investigated via whole genome RNA sequencing. The transcriptomic analysis revealed modulation of transcription factors, as well as genes involved in stress response, unfolded protein response, lipid metabolism and reproduction. Furthermore, a drastic increase in the number of differentially expressed genes involved in defense response was measured in the last two generations, suggesting a cumulative stress effect of ionizing radiation exposure. Transcription factor binding site enrichment analysis and the use of transgenic strain identified daf-16/FOXO as a master regulator of genes differentially expressed in response to radiation. The presented data provide new knowledge with respect to the molecular mechanisms involved in reproductive toxic effects and accumulated stress resulting from multigenerational exposure to ionizing radiation.


Assuntos
Caenorhabditis elegans , Biologia de Sistemas , Animais , Caenorhabditis elegans/genética , Células Germinativas , Humanos , Radiação Ionizante , Análise de Sistemas
14.
Cells ; 10(9)2021 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-34571988

RESUMO

Papaya is a fleshy fruit that undergoes fast ethylene-induced modifications. The fruit becomes edible, but the fast pulp softening is the main factor that limits the post-harvest period. Papaya fast pulp softening occurs due to cell wall disassembling coordinated by ethylene triggering that massively expresses pectinases. In this work, RNA-seq analysis of ethylene-treated and non-treated papayas enabled a wide transcriptome overview that indicated the role of ethylene during ripening at the gene expression level. Several families of transcription factors (AP2/ERF, NAC, and MADS-box) were differentially expressed. ACO, ACS, and SAM-Mtase genes were upregulated, indicating a high rate of ethylene biosynthesis after ethylene treatment. The correlation among gene expression and physiological data demonstrated ethylene treatment can indeed simulate ripening, and regulation of changes in fruit color, aroma, and flavor could be attributed to the coordinated expression of several related genes. Especially about pulp firmness, the identification of 157 expressed genes related to cell wall metabolism demonstrated that pulp softening is accomplished by a coordinated action of several different cell wall-related enzymes. The mechanism is different from other commercially important fruits, such as strawberry, tomato, kiwifruit, and apple. The observed behavior of this new transcriptomic data confirms ethylene triggering is the main event that elicits fast pulp softening in papayas.


Assuntos
Carica/metabolismo , Etilenos/metabolismo , Frutas/metabolismo , Carica/enzimologia , Carica/genética , Parede Celular/metabolismo , Etilenos/farmacologia , Frutas/efeitos dos fármacos , Frutas/enzimologia , Expressão Gênica/genética , Regulação da Expressão Gênica de Plantas/efeitos dos fármacos , Genes de Plantas , Proteínas de Plantas/metabolismo , Biologia de Sistemas/métodos , Fatores de Transcrição/metabolismo , Transcriptoma/efeitos dos fármacos
15.
BMC Med Genomics ; 14(1): 226, 2021 09 17.
Artigo em Inglês | MEDLINE | ID: mdl-34535131

RESUMO

BACKGROUND: Higher mortality of COVID-19 patients with lung disease is a formidable challenge for the health care system. Genetic association between COVID-19 and various lung disorders must be understood to comprehend the molecular basis of comorbidity and accelerate drug development. METHODS: Lungs tissue-specific neighborhood network of human targets of SARS-CoV-2 was constructed. This network was integrated with lung diseases to build a disease-gene and disease-disease association network. Network-based toolset was used to identify the overlapping disease modules and drug targets. The functional protein modules were identified using community detection algorithms and biological processes, and pathway enrichment analysis. RESULTS: In total, 141 lung diseases were linked to a neighborhood network of SARS-CoV-2 targets, and 59 lung diseases were found to be topologically overlapped with the COVID-19 module. Topological overlap with various lung disorders allows repurposing of drugs used for these disorders to hit the closely associated COVID-19 module. Further analysis showed that functional protein-protein interaction modules in the lungs, substantially hijacked by SARS-CoV-2, are connected to several lung disorders. FDA-approved targets in the hijacked protein modules were identified and that can be hit by exiting drugs to rescue these modules from virus possession. CONCLUSION: Lung diseases are clustered with COVID-19 in the same network vicinity, indicating the potential threat for patients with respiratory diseases after SARS-CoV-2 infection. Pathobiological similarities between lung diseases and COVID-19 and clinical evidence suggest that shared molecular features are the probable reason for comorbidity. Network-based drug repurposing approaches can be applied to improve the clinical conditions of COVID-19 patients.


Assuntos
COVID-19/tratamento farmacológico , COVID-19/epidemiologia , Reposicionamento de Medicamentos , Pneumopatias/epidemiologia , Pandemias , SARS-CoV-2 , Algoritmos , Antivirais/uso terapêutico , COVID-19/genética , Comorbidade , Descoberta de Drogas , Reposicionamento de Medicamentos/métodos , Redes Reguladoras de Genes/efeitos dos fármacos , Interações entre Hospedeiro e Microrganismos/efeitos dos fármacos , Interações entre Hospedeiro e Microrganismos/genética , Humanos , Pneumopatias/tratamento farmacológico , Pneumopatias/genética , Mapas de Interação de Proteínas/efeitos dos fármacos , Mapas de Interação de Proteínas/genética , Biologia de Sistemas
16.
PLoS One ; 16(9): e0255736, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34582494

RESUMO

Dalbergia Odorifera (DO) has been widely used for the treatment of cardiovascular and cerebrovascular diseasesinclinical. However, the effective substances and possible mechanisms of DO are still unclear. In this study, network pharmacology and molecular docking were used toelucidate the effective substances and active mechanisms of DO in treating ischemic stroke (IS). 544 DO-related targets from 29 bioactive components and 344 IS-related targets were collected, among them, 71 overlapping common targets were got. Enrichment analysis showed that 12 components were the possible bioactive components in DO, which regulating 9 important signaling pathways in 3 biological processes including 'oxidative stress' (KEGG:04151, KEGG:04068, KEGG:04915), 'inflammatory response'(KEGG:04668, KEGG:04064) and 'vascular endothelial function regulation'(KEGG:04066, KEGG:04370). Among these, 5 bioactive components with degree≥20 among the 12 potential bioactive components were selected to be docked with the top5 core targets using AutodockVina software. According to the results of molecular docking, the binding sites of core target protein AKT1 and MOL002974, MOL002975, and MOL002914 were 9, 8, and 6, respectively, and they contained 2, 1, and 0 threonine residues, respectively. And some binding sites were consistent, which may be the reason for the similarities and differences between the docking results of the 3 core bioactive components. The results of in vitro experiments showed that OGD/R could inhibit cell survival and AKT phosphorylation which were reversed by the 3 core bioactive components. Among them, MOL002974 (butein) had a slightly better effect. Therefore, the protective effect of MOL002974 (butein) against cerebral ischemia was further evaluated in a rat model of middle cerebral artery occlusion (MCAO) by detecting neurological score, cerebral infarction volume and lactate dehydrogenase (LDH) level. The results indicated that MOL002974 (butein) could significantly improve the neurological score of rats, decrease cerebral infarction volume, and inhibit the level of LDH in the cerebral tissue and serum in a dose-dependent manner. In conclusion, network pharmacology and molecular docking predicate the possible effective substances and mechanisms of DO in treating IS. And the results are verified by the in vitro and in vivo experiments. This research reveals the possible effective substances from DO and its active mechanisms for treating IS and provides a new direction for the secondary development of DO for treating IS.


Assuntos
Dalbergia/química , Medicamentos de Ervas Chinesas/farmacologia , Regulação da Expressão Gênica/efeitos dos fármacos , Redes Reguladoras de Genes/efeitos dos fármacos , AVC Isquêmico/tratamento farmacológico , Fármacos Neuroprotetores/farmacologia , Mapas de Interação de Proteínas/efeitos dos fármacos , Animais , Sobrevivência Celular , Infarto Cerebral/tratamento farmacológico , Infarto Cerebral/metabolismo , Infarto Cerebral/patologia , Edaravone/farmacologia , AVC Isquêmico/metabolismo , AVC Isquêmico/patologia , Simulação de Acoplamento Molecular , Células PC12 , Ratos , Ratos Sprague-Dawley , Biologia de Sistemas
17.
BMC Bioinformatics ; 22(Suppl 9): 105, 2021 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-34433410

RESUMO

BACKGROUND: Many systems biology studies leverage the integration of multiple data types (across different data sources) to offer a more comprehensive view of the biological system being studied. While SQL (Structured Query Language) databases are popular in the biomedical domain, NoSQL database technologies have been used as a more relationship-based, flexible and scalable method of data integration. RESULTS: We have created a graph database integrating data from multiple sources. In addition to using a graph-based query language (Cypher) for data retrieval, we have developed a web-based dashboard that allows users to easily browse and plot data without the need to learn Cypher. We have also implemented a visual graph query interface for users to browse graph data. Finally, we have built a prototype to allow the user to query the graph database in natural language. CONCLUSION: We have demonstrated the feasibility and flexibility of using a graph database for storing and querying immunological data with complex biological relationships. Querying a graph database through such relationships has the potential to discover novel relationships among heterogeneous biological data and metadata.


Assuntos
Armazenamento e Recuperação da Informação , Web Semântica , Bases de Dados Factuais , Idioma , Biologia de Sistemas
18.
Gene ; 805: 145908, 2021 Dec 30.
Artigo em Inglês | MEDLINE | ID: mdl-34411649

RESUMO

Transcriptome profiling of Vrindavani and Tharparkar cattle (n = 5 each) revealed that more numbers of genes were dysregulated in Vrindavani than in Tharparkar. A contrast in gene expression was observed with 18.9 % of upregulated genes in Vrindavani downregulated in Tharparkar and 17.8% upregulated genes in Tharparkar downregulated in Vrindavani. Functional annotation of genes differentially expressed in Tharparkar and Vrindavani revealed that the systems biology in Tharparkar is moving towards counteracting the effects due to heat stress. Unlike Vrindavani, Tharparkar is not only endowed with higher expression of the scavengers (UBE2G1, UBE2S, and UBE2H) of misfolded proteins but also with protectors (VCP, Serp1, and CALR) of naïve unfolded proteins. Further, higher expression of the antioxidants in Tharparkar enables it to cope up with higher levels of free radicals generated as a result of heat stress. In this study, we found relevant genes dysregulated in Tharparkar in the direction that can counter heat stress.


Assuntos
Resposta ao Choque Térmico/genética , Resposta ao Choque Térmico/fisiologia , Animais , Bovinos/genética , Expressão Gênica/genética , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica/genética , Índia , Biologia de Sistemas/métodos , Transcriptoma/genética
19.
Sci Rep ; 11(1): 16814, 2021 08 19.
Artigo em Inglês | MEDLINE | ID: mdl-34413339

RESUMO

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has emerged as a pandemic. Paucity of information concerning the virus and therapeutic interventions have made SARS-CoV-2 infection a genuine threat to global public health. Therefore, there is a growing need for understanding the molecular mechanism of SARS-CoV-2 infection at cellular level. To address this, we undertook a systems biology approach by analyzing publicly available RNA-seq datasets of SARS-CoV-2 infection of different cells and compared with other lung pathogenic infections. Our study identified several key genes and pathways uniquely associated with SARS-CoV-2 infection. Genes such as interleukin (IL)-6, CXCL8, CCL20, CXCL1 and CXCL3 were upregulated, which in particular regulate the cytokine storm and IL-17 signaling pathway. Of note, SARS-CoV-2 infection strongly activated IL-17 signaling pathway compared with other respiratory viruses. Additionally, this transcriptomic signature was also analyzed to predict potential drug repurposing and small molecule inhibitors. In conclusion, our comprehensive data analysis identifies key molecular pathways to reveal underlying pathological etiology and potential therapeutic targets in SARS-CoV-2 infection.


Assuntos
COVID-19/imunologia , Interleucina-17/genética , SARS-CoV-2/fisiologia , Biologia de Sistemas/métodos , Antivirais/uso terapêutico , COVID-19/tratamento farmacológico , Quimiocina CCL20/genética , Quimiocina CXCL1/genética , Quimiocinas CXC/genética , Reposicionamento de Medicamentos , Humanos , Interleucina-17/metabolismo , Interleucina-6/genética , Interleucina-8/genética , Especificidade de Órgãos , Transdução de Sinais , Transcriptoma
20.
Microb Pathog ; 158: 105114, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34333072

RESUMO

Understanding the pathogenesis of SARS-CoV-2 is essential for developing effective treatment strategies. Viruses hijack the host metabolism to redirect the resources for their replication and survival. The influence of SARS-CoV-2 on host metabolism is yet to be fully understood. In this study, we analyzed the transcriptomic data obtained from different human respiratory cell lines and patient samples (nasopharyngeal swab, peripheral blood mononuclear cells, lung biopsy, bronchoalveolar lavage fluid) to understand metabolic alterations in response to SARS-CoV-2 infection. We explored the expression pattern of metabolic genes in the comprehensive genome-scale network model of human metabolism, Recon3D, to extract key metabolic genes, pathways, and reporter metabolites under each SARS-CoV-2-infected condition. A SARS-CoV-2 core metabolic interactome was constructed for network-based drug repurposing. Our analysis revealed the host-dependent dysregulation of glycolysis, mitochondrial metabolism, amino acid metabolism, nucleotide metabolism, glutathione metabolism, polyamine synthesis, and lipid metabolism. We observed different pro- and antiviral metabolic changes and generated hypotheses on how the host metabolism can be targeted for reducing viral titers and immunomodulation. These findings warrant further exploration with more samples and in vitro studies to test predictions.


Assuntos
COVID-19 , SARS-CoV-2 , Humanos , Leucócitos Mononucleares , Biologia de Sistemas , Transcriptoma
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