New Proteomic Signatures to Distinguish Between Zika and Dengue Infections.
New Proteomic Signatures to Distinguish Between Zika and Dengue Infections.
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DOI：
10.1016/j.mcpro.2021.100052
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Vogel C
中科院分区：
文献类型：
--
作者：
Allgoewer K;Maity S;Zhao A;Lashua L;Ramgopal M;Balkaran BN;Liu L;Purushwani S;Arévalo MT;Ross TM;Choi H;Ghedin E;Vogel C
区分寨卡病毒和登革热病毒感染对于准确治疗至关重要，但我们仍然缺乏对它们对宿主影响的详细了解。为了确定这两种感染的新蛋白质特征，我们使用下一代蛋白质组学分析了来自62名寨卡和登革热患者的122份血清样本。我们对bbb500个蛋白进行了定量分析，鉴定出13个蛋白表达有显著差异（调整p值< 0.05）。这些蛋白质通常在感染和伤口愈合中起作用，其中一些还与怀孕和大脑功能有关。我们成功地验证了碳酸酐酶2在原始和独立样本集中的表达差异。其中三种差异表达蛋白，即纤维蛋白原α、血小板因子4变异1和促血小板基础蛋白，预测寨卡病毒感染的真阳性率为70%，假阳性率为6%。此外，我们发现个体内蛋白质特征的时间变化可以消除诊断的歧义，并作为过去感染的指标。总之，我们证明血清蛋白质组学可以提供新的资源，用于区分不同的病毒感染。寨卡病毒和登革热病毒感染的独特蛋白质特征作为过去感染的指标的蛋白质特征的时间变化机器学习解释混杂因素区分蚊媒寨卡病毒和登革热黄病毒感染对正确治疗具有重要的临床意义，但仍然具有挑战性。我们使用质谱法量化了62例患者血清样本中277种蛋白质的表达水平，为社区提供了资源。我们确定了13种蛋白在密切相关的感染类型之间具有显著的表达差异。大多数蛋白质与怀孕和大脑功能有关。我们还确定了在时间差异方面标记模棱两可感染的表达特征。
Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika and dengue patients. We quantified >500 proteins and identified 13 proteins that were significantly differentially expressed (adjusted p-value < 0.05). These proteins typically function in infection and wound healing, with several also linked to pregnancy and brain function. We successfully validated expression differences with Carbonic Anhydrase 2 in both the original and an independent sample set. Three of the differentially expressed proteins, i.e., Fibrinogen Alpha, Platelet Factor 4 Variant 1, and Pro-Platelet Basic Protein, predicted Zika virus infection at a ∼70% true-positive and 6% false-positive rate. Further, we showed that intraindividual temporal changes in protein signatures can disambiguate diagnoses and serve as indicators for past infections. Taken together, we demonstrate that serum proteomics can provide new resources that serve to distinguish between different viral infections. Analysis of human serum samples with extreme protein abundance ranges Unique protein signatures for Zika and dengue virus infection Temporal changes in protein signatures as indicators for past infections Machine learning to account for confounding factors Differentiation between the mosquito-borne Zika and dengue Flavivirus infections is clinically important for correct treatment, but remains challenging. We used mass spectrometry to quantify expression levels for 277 proteins measured in serum samples from 62 patients, providing a resource to the community. We identified 13 proteins with significant differential expression between the closely related types of infections. Most of the proteins link to pregnancy and brain function. We also identified expression signatures that mark ambiguous infections with respect to temporal differences.
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影响因子：
3.7
作者：
Nascimento EJ;Silva AM;Cordeiro MT;Brito CA;Gil LH;Braga-Neto U;Marques ET
通讯作者：
Marques ET
影响因子：
3.7
作者：
Li W;Zhu S;Li J;Huang Y;Zhou R;Fan X;Yang H;Gong X;Eissa NT;Jahnen-Dechent W;Wang P;Tracey KJ;Sama AE;Wang H
通讯作者：
Wang H
影响因子：
7
作者：
Bruderer, Roland;Muntel, Jan;Reiter, Lukas
通讯作者：
Reiter, Lukas
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
14.9
作者：
Ng YC;Chung WC;Kang HR;Cho HJ;Park EB;Kang SJ;Song MJ
通讯作者：
Song MJ