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分析 HIV 转导后早期宿主蛋白的网络。

Analysis of networks of host proteins in the early time points following HIV transduction.

机构信息

Proteomics Core Facility, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem ter 1., Debrecen, 4032, Hungary.

Laboratory of Retroviral Biochemistry, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Egyetem ter 1., Debrecen, 4032, Hungary.

出版信息

BMC Bioinformatics. 2019 Jul 17;20(1):398. doi: 10.1186/s12859-019-2990-3.

Abstract

BACKGROUND

Utilization of quantitative proteomics data on the network level is still a challenge in proteomics data analysis. Currently existing models use sophisticated, sometimes hard to implement analysis techniques. Our aim was to generate a relatively simple strategy for quantitative proteomics data analysis in order to utilize as much of the data generated in a proteomics experiment as possible.

RESULTS

In this study, we applied label-free proteomics, and generated a network model utilizing both qualitative, and quantitative data, in order to examine the early host response to Human Immunodeficiency Virus type 1 (HIV-1). A weighted network model was generated based on the amount of proteins measured by mass spectrometry, and analysis of weighted networks and functional sub-networks revealed upregulation of proteins involved in translation, transcription, and DNA condensation in the early phase of the viral life-cycle.

CONCLUSION

A relatively simple strategy for network analysis was created and applied to examine the effect of HIV-1 on host cellular proteome. We believe that our model may prove beneficial in creating algorithms, allowing for both quantitative and qualitative studies of proteome change in various biological and pathological processes by quantitative mass spectrometry.

摘要

背景

在蛋白质组学数据分析中,利用网络层面的定量蛋白质组学数据仍然是一个挑战。目前现有的模型使用复杂的、有时难以实现的分析技术。我们的目的是生成一种相对简单的定量蛋白质组学数据分析策略,以便尽可能利用蛋白质组学实验中产生的所有数据。

结果

在这项研究中,我们应用无标记蛋白质组学,并生成了一个利用定性和定量数据的网络模型,以研究人类免疫缺陷病毒 1 型(HIV-1)对宿主的早期反应。根据质谱测量的蛋白质数量生成了一个加权网络模型,对加权网络和功能子网络的分析显示,在病毒生命周期的早期,与翻译、转录和 DNA 凝聚相关的蛋白质上调。

结论

创建了一种相对简单的网络分析策略,并应用于研究 HIV-1 对宿主细胞蛋白质组的影响。我们相信,我们的模型可以通过定量质谱法为各种生物学和病理学过程中的蛋白质组变化的定量和定性研究创建算法提供帮助。

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