Determination of alkaloids in Sinomenium acutum by field‐amplified sample stacking in capillary electrophoresis with chemiluminescene detection

A simple and rapid capillary electrophoresis (CE) with an acidic potassium permanganate chemiluminescence (CL) detection method was developed to determine three alkaloids (curine, sinomenine and magnoflorine) simultaneously. A laboratory‐built CE–CL detection interface was used. The field‐amplified sample stacking technique was applied to the online concentration of alkaloids. Experimental conditions for CE separation and CL detection were investigated in detail to acquire optimum conditions. Under optimal conditions, the three alkaloids were baseline separated within 6 min, and the detection limits (S/N = 3) ranged from 0.03 µg/mL to 0.49 µg/mL. This method was successfully applied to determine the above three alkaloids in Sinomenium acutum, and the result of the determination of sinomenine was in good agreement with those given by high‐performance liquid chromatography and CE methods. In addition, a possible CL reaction mechanism of sinomenine–KMnO₄–H₂SO₄ was proposed. Copyright © 2013 John Wiley & Sons, Ltd.     

多维液相色谱分离技术在复杂蛋白质组学样品鉴定中的应用

目的：随着蛋白组学技术的发展,液相色谱-串联质谱的联用技术（液质联用）逐渐成为蛋白组学的主流技术。方法：通过结合各种不同原理的色谱分离类型,多维液相色谱分离技术能够极大的提高分离系统的峰容量,达到有效分离复杂程度很高的蛋白质组学样品的目的。结果：最广泛使用的多维液相色谱分离系统是离子交换色谱（IEX）和反相色谱（RP）的二维结合,近年来又发展出了分离能力更强的三维液相色谱分离系统,并且已经在蛋白质组学研究中得到了应用。结论：本文综述了多种多维液相色谱分离方法,在这些方法中,不同的分离原理的色谱类型被用于肽段或蛋白混合物的预分离中,有效促进了样品的充分分离,极大地提高了复杂样品的蛋白组学鉴定能力。     

Mass spectrometry in plant proteomic analysis

Abstract

The current revolution in proteomics has been generated by the combination of very sensitive mass spectrometers coupled to microcapillary liquid chromatography, specific proteolysis of protein mixtures and software that is capable of searching vast numbers of mass measurements against predicted peptides from sequenced genomes. The challenges of post‐genomic plant biology include characterization of protein function, post‐translational modifications and composition of protein complexes as well as deciphering protein complements in intracellular compartments – proteomes of cell organelles. In this review we summarize the current mass spectrometry methods currently being used in plant proteomics and discuss the various tagging strategies that are being used for purification and proteomic analysis of plant protein complexes.

Abbreviations: BCCD, biotin carboxyl carrier protein domain; CBP, calmodulin‐binding protein; CID, collision‐induced dissociation; ESI, electrospray ionization; EST, expressed sequence tag; FT‐ICR, Fourier transform ion cyclotron resonance; GFP, green fluorescent protein; GST, glutathione S‐transferase; HA, haemagglutinin; HILEP, hydroponic isotope labelling of entire plants; His, histidine; HPB, HA–PreScission–Biotin; HPLC, high‐performance liquid chromatography; ICAT, isotope‐coded affinity tags; ICPL, isotope‐coded protein label; iTRAQ, isobaric tag for relative and absolute quantification; LC, liquid chromatography; MALDI, matrix‐assisted laser desorption ionization; MBP, maltose‐binding protein; MS, mass spectrometry; SDS‐PAGE, sodium dodecyl sulphate‐polyacrylamide gel electrophoresis; SILAC, stable isotope labelling with amino acids in cell culture; SILIP, stable isotope labelling in planta; Strep, streptavidin; TAP, tandem affinity purification; TBP, TATA‐box‐binding protein; TOF, time‐of‐flight; UPLC, ultraperformance liquid chromatography     

Fitting distributions to microbial contamination data collected with an unequal probability sampling design

Aims

The fitting of statistical distributions to microbial sampling data is a common application in quantitative microbiology and risk assessment applications. An underlying assumption of most fitting techniques is that data are collected with simple random sampling, which is often times not the case. This study develops a weighted maximum likelihood estimation framework that is appropriate for microbiological samples that are collected with unequal probabilities of selection.

Methods and Results

A weighted maximum likelihood estimation framework is proposed for microbiological samples that are collected with unequal probabilities of selection. Two examples, based on the collection of food samples during processing, are provided to demonstrate the method and highlight the magnitude of biases in the maximum likelihood estimator when data are inappropriately treated as a simple random sample.

Conclusions

Failure to properly weight samples to account for how data are collected can introduce substantial biases into inferences drawn from the data.

Significance and Impact of the Study

The proposed methodology will reduce or eliminate an important source of bias in inferences drawn from the analysis of microbial data. This will also make comparisons between studies and the combination of results from different studies more reliable, which is important for risk assessment applications.     

Inference of population genetic parameters from an irregular time series of seasonal influenza virus sequences

Basic summary statistics that quantify the population genetic structure of influenza virus are important for understanding and inferring the evolutionary and epidemiological processes. However, the sampling dates of global virus sequences in the last several decades are scattered nonuniformly throughout the calendar. Such temporal structure of samples and the small effective size of viral population hampers the use of conventional methods to calculate summary statistics. Here, we define statistics that overcome this problem by correcting for the sampling-time difference in quantifying a pairwise sequence difference. A simple linear regression method jointly estimates the mutation rate and the level of sequence polymorphism, thus providing an estimate of the effective population size. It also leads to the definition of Wright’s F_ST for arbitrary time-series data. Furthermore, as an alternative to Tajima’s D statistic or the site-frequency spectrum, a mismatch distribution corrected for sampling-time differences can be obtained and compared between actual and simulated data. Application of these methods to seasonal influenza A/H3N2 viruses sampled between 1980 and 2017 and sequences simulated under the model of recurrent positive selection with metapopulation dynamics allowed us to estimate the synonymous mutation rate and find parameter values for selection and demographic structure that fit the observation. We found that the mutation rates of HA and PB1 segments before 2007 were particularly high and that including recurrent positive selection in our model was essential for the genealogical structure of the HA segment. Methods developed here can be generally applied to population genetic inferences using serially sampled genetic data.     

Effect of charge on protein preferred orientation at the air–water interface in cryo-electron microscopy

The air–water interface (AWI) tends to adsorb proteins and frequently causes preferred orientation problems in cryo-electron microscopy (cryo-EM). Here, we examined cryo-EM data from protein samples frozen with different detergents and found that both anionic and cationic detergents promoted binding of proteins to the AWI. By contrast, some of the nonionic and zwitterionic detergents tended to prevent proteins from attaching to the AWI. The protein orientation distributions with different anionic detergents were similar and resembled that obtained without detergent. By contrast, cationic detergents gave distinct orientation distributions. Our results indicate that proteins adsorb to charged interface and the negative charge of the AWI plays an important role in adsorbing proteins in the conventional cryo-EM sample preparation. According to these findings, a new method was developed by adding anionic detergent at a concentration between 0.002% and 0.005%. Using this method, the protein particles exhibited a more evenly distributed orientations and still adsorbed to the AWI enabling them embedding in a thin layer of ice with high concentration, which will benefit the cryo-EM structural determination.     

生命条形码新秀：DNA微型条形码技术

近些年来,DNA条形码技术为便捷的物种鉴定提供了很大的帮助,但随着该技术的发展,也出现了一系列的问题。微型条形码技术是作为DNA条形码技术的补充而出现的一项新兴技术,具体是指通过通用引物扩增出比细胞色素c氧化酶I号基因全序列更短的一段序列,并通过该序列进行物种鉴定、分类等研究工作。作为一项新兴技术,其优点包括,适用于部分降解的DNA样品的目的基因扩增,能够很好地解决环境混合样品多样性的调查等。但是,该技术所选DNA片段非常短,因此标记序列包含的遗传信息有限,在鉴定的精确度方面和COI全条形码存在一定的差距。本文在总结前人研究的基础上,简要概述了微型条形码技术的优缺点,并对其未来在害虫分子识别方面的应用做了初步探讨。     

14. Lake Sedmo Rilsko (Bulgaria): Lateglacial vegetation history

The length of the pollen deposition period covered by an individual moss sample is a matter of discussion. Here we evaluate (1) how many years of pollen deposition are contained in individual moss samples, (2) which factors (i.e. moss type, geographical location and thickness of sample) affect the pollen content, and (3) whether the time span of the pollen deposited in the moss is related to the pollen type. The pollen deposition period covered by 20 individual moss samples adjacent to pollen traps was estimated using the accumulation method. The investigated moss samples usually contain pollen from a period of two to five years. The length of the time period covered by the moss depends on the thickness of the moss cushion and, therefore, we recommend estimating the time period over which the moss has been growing by the increment method. Compared to pollen traps, mosses tend to accumulate more Poaceae and bisaccate grains (especially Picea) but less Cyperaceae pollen. Betula and pollen tetrads tend to be equally represented in mosses and traps. This study demonstrates that moss samples may contain sufficient pollen to be a reliable modern analogue for Quaternary peat and sediment samples but cannot be used to calculate pollen accumulation rates.