内参基因加标法定量土壤微生物目标基因绝对拷贝数

【目的】通过荧光定量PCR技术对土壤微生物目标基因进行绝对定量,其定量结果的准确性容易受到DNA提取得率以及腐殖酸抑制性的影响。【方法】采用内参基因加标法,利用构建的突变质粒DNA,对供试水稻土壤样品中的微生物16S r RNA目标基因的绝对拷贝数进行荧光定量PCR检测,用来表征该样品中细菌群落总体丰度。在定量前通过双向引物扩增方法验证突变质粒中的内参基因对供试土壤的特异性。【结果】不同水稻土壤样品的DNA提取量在样品间差异较大。通过内参基因加标法对DNA提取量进行校正,显著提高了16S r RNA基因绝对定量的精确度。不同水稻土壤样品间的变异系数为17.8,与未加标处理相比降低了66.7%。在此基础上,进一步通过内参基因加标法对土壤有机质和含水率均呈现典型空间特征差异的6处亚热带湿地土壤样品中的16S r RNA基因进行绝对定量。16S r RNA基因绝对拷贝数与土壤微生物生物量碳具有显著的线性相关性(R2=0.694,P0.001),表明内参校正后的16S r RNA基因绝对拷贝数可以准确反映单位质量土壤中微生物的丰度。【结论】内参基因加标法可以对DNA提取得率以及腐殖酸对PCR扩增的抑制性进行校正,从而提高绝对定量的准确性。基于内参基因加标法的目标基因绝对定量PCR检测,可作为土壤微生物生物量测量,以及微生物功能基因绝对丰度定量的一种核酸检测方法。     

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC–MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC–MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC–MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.     

The current state of the art of quantitative phosphoproteomics and its applications to diabetes research

Protein phosphorylation is a fundamental regulatory mechanism in many cellular processes and aberrant perturbation of phosphorylation has been implicated in various human diseases. Kinases and their cognate inhibitors have been considered as hotspots for drug development. Therefore, the emerging tools, which enable a system-wide quantitative profiling of phosphoproteome, would offer a powerful impetus in unveiling novel signaling pathways, drug targets and/or biomarkers for diseases of interest. This review highlights recent advances in phosphoproteomics, the current state of the art of the technologies and the challenges and future perspectives of this research area. Finally, some exemplary applications of phosphoproteomics in diabetes research are underscored.     

数字聚合酶链反应及其在感染性疾病中的应用

数字聚合酶链反应(polymerase chain reaction,PCR)采用与定量PCR相同的荧光化学原理和不同的数学原理来实现对靶标核酸序列的绝对定量,其摒弃了对外部参照的依赖,同时具有更高的数据精密度,提高了重复性和再现性。数字PCR的应用涵盖生命科学众多领域,特别是在医学检验领域,其对疾病相关核酸分子标记的准确分析,为疾病的早期诊断、进展监测、疗效评估提供了动态量化指标。数字PCR的出现将推动基于核酸扩增技术的分子生物学检测迈入精准定量阶段。本文就数字PCR尤其是微滴式数字PCR在感染性疾病中的应用进展及前沿进行综述。     

Plasma Proteome Signature of Sepsis: a Functionally Connected Protein Network

Sepsis is an extreme host response to infection that leads to loss of organ function and cardiovascular integrity. Mortality from sepsis is on the rise. Despite more than three decades of research and clinical trials, specific diagnostic and therapeutic strategies for sepsis are still absent. The use of LFQ‐ and TMT‐based quantitative proteomics is reported here to study the plasma proteome in five mouse models of sepsis. A knowledge‐based interpretation of the data reveals a protein network with extensive connectivity through documented functional or physical interactions. The individual proteins in the network all have a documented role in sepsis and are known to be extracellular. The changes in protein abundance observed in the mouse models of sepsis have for the most part the same directionality (increased or decreased abundance) as reported in the literature for human sepsis. This network has been named the Plasma Proteome Signature of Sepsis (PPSS). The PPSS is a quantifiable molecular readout that can supplant the current symptom‐based approach used to diagnose sepsis. This type of molecular interpretation of sepsis, its progression, and its response to therapeutic intervention are an important step in advancing our understanding of sepsis, and for discovering and evaluating new therapeutic strategies.     

ComplexBrowser: A Tool for Identification and Quantification of Protein Complexes in Large-scale Proteomics Datasets

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Highlights

• •Automated analysis of protein complexes in proteomic experiments.
• •Quantitative measurement of the coordinated changes in protein complex components.
• •Interactive visualizations for exploratory analysis of proteomic results.

     

Immunomic Identification of Malaria Antigens Associated With Protection in Mice

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Highlights

• •Production of sera with different levels of protection against rodent Plasmodium.
• •Generation of immunomic and proteomic data sets enriched in protective antigens.
• •Prediction of the most likely protective antigens using a weighted scoring system.

     

Spatiotemporal Changes of the Phagosomal Proteome in Dendritic Cells in Response to LPS Stimulation*

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Highlights

• •Characterization of the phagosomal proteome comparing resting and LPS-treated BMDCs.
• •Label-free quantification determined 2843 phagosomal proteins.
• •Reduced recruitment of hydrolases and V-ATPase to phagosomes of LPS-treated cells.
• •Increased recruitment of antigen cross-presentation molecules to these phagosomes.