Membrane glycoproteomics of fetal lung fibroblasts using LC/MS

Some aberrant N‐glycosylations are being used as tumor markers, and glycoproteomics is expected to provide novel diagnosis markers and targets of drug developments. However, one has trouble in mass spectrometric glycoproteomics of membrane fraction because of lower intensity of glycopeptides in the existence of surfactants. Previously, we developed a glycopeptide enrichment method by acetone precipitation, and it was successfully applied to human serum glycoproteomics. In this study, we confirmed that this method is useful to remove the surfactants and applicable to membrane glycoproteomics. The glycoproteomic approach to the human fetal lung fibroblasts membrane fraction resulted in the identification of over 272 glycoforms on 63 sites of the 44 glycoproteins. According to the existing databases, the structural features on 41 sites are previously unreported. The most frequently occurring forms at N‐glycosylation site were high‐mannose type containing nine mannose residues (M9) and monosialo‐fucosylated biantennary oligosaccharides. Several unexpected N‐glycans, such as fucosylated complex‐type and fucosylated high‐mannose and/or fucosylated pauci‐mannose types were found in ER and lysosome proteins. Our method provides new insights into transport, biosynthesis, and degradation of glycoproteins.     

Mannan-binding protein blocks the activation of metalloproteases meprin alpha and beta

Mannan-binding protein (MBP) is a C-type serum lectin that is known to be a host defense factor involved in innate immunity, and recognizes mannose, fucose, and N-acetylglucosamine residues. Although some exogenous MBP ligands have been reported, little is known about its endogenous ligands. In the present study, we found that endogenous MBP ligands are highly expressed in the brush border epithelial cells of kidney-proximal tubules by immunohistochemistry, and both meprin alpha and beta (meprins), as novel endogenous MBP ligands, have been identified through affinity chromatography and mass spectrometry. Meprins are membrane-bound and secreted zinc metalloproteases extensively glycosylated and highly expressed in kidney and small intestinal epithelial cells, leukocytes, and certain cancer cells. Meprins are capable of cleaving growth factors, extracellular matrix proteins, and biologically active peptides. Deglycosylation experiments indicated that the MBP ligands on meprins are high mannose- or complex-type N-glycans. The interaction of MBP with meprins resulted in significant decreases in the proteolytic activity and matrix-degrading ability of meprins. Our results suggest that core N-linked oligosaccharides on meprins are associated with the optimal enzymatic activity and that MBP is an important regulator for modulation of the localized meprin proteolytic activity via N-glycan binding. Because meprins are known to be some of the major matrix-degrading metalloproteases in the kidney and intestine, MBP, which functions as a natural and effective inhibitor of meprins, may contribute, as a potential therapeutic target, to tumor progression by facilitating the migration, intravasation, and metastasis of carcinoma cells, and to acute renal failure and inflammatory bowel diseases.     

Analysis of oligomeric stability of insulin analogs using hydrogen/deuterium exchange mass spectrometry

Insulin analog products for subcutaneous injection are prepared as solutions in which insulin analog molecules exist in several oligomeric states. Oligomeric stability can affect their onset and duration of action and has been exploited in designing them. To investigate the oligomeric stability of insulin analog products having different pharmacokinetics, we performed hydrogen/deuterium exchange mass spectrometry (HDX/MS), which is a rapid method to analyze dynamic aspects of protein structures. Two rapid-acting analogs (lispro and glulisine) incorporated deuteriums more and faster than recombinant human insulin, whereas a long-acting analog (glargine) and two intermediate-acting preparations (protamine-containing formulations) incorporated them less and more slowly. Kinetic analysis revealed that the number of slowly exchanged hydrogens (D(s)) (k<0.01 min(-1)) accounted for the difference in HDX reactivity among analogs. Furthermore, we found correlations between HDX kinetics and pharmacokinetics reported previously. Their maximum serum concentration (C(max)) was linearly correlated with D(s) (r=0.88) and the number of maximum exchangeable hydrogens (D(∞)) (r=0.89). The maximum drug concentration time (t(max)) was also correlated with reciprocals of D(s) and D(∞) (r=0.86 and r=0.96, respectively). Here we demonstrate the ability of HDX/MS to evaluate oligomeric stability of insulin analog products.     

Stem kernels for RNA sequence analyses

Several computational methods based on stochastic context-free grammars have been developed for modeling and analyzing functional RNA sequences. These grammatical methods have succeeded in modeling typical secondary structures of RNA, and are used for structural alignment of RNA sequences. However, such stochastic models cannot sufficiently discriminate member sequences of an RNA family from nonmembers and hence detect noncoding RNA regions from genome sequences. A novel kernel function, stem kernel, for the discrimination and detection of functional RNA sequences using support vector machines (SVMs) is proposed. The stem kernel is a natural extension of the string kernel, specifically the all-subsequences kernel, and is tailored to measure the similarity of two RNA sequences from the viewpoint of secondary structures. The stem kernel examines all possible common base pairs and stem structures of arbitrary lengths, including pseudoknots between two RNA sequences, and calculates the inner product of common stem structure counts. An efficient algorithm is developed to calculate the stem kernels based on dynamic programming. The stem kernels are then applied to discriminate members of an RNA family from nonmembers using SVMs. The study indicates that the discrimination ability of the stem kernel is strong compared with conventional methods. Furthermore, the potential application of the stem kernel is demonstrated by the detection of remotely homologous RNA families in terms of secondary structures. This is because the string kernel is proven to work for the remote homology detection of protein sequences. These experimental results have convinced us to apply the stem kernel in order to find novel RNA families from genome sequences.     

Determination of non-protein-bound iron in human synovial fluid by high-performance liquid chromatography with electrochemical detection

Non-protein-bound iron in human synovial fluid was determined using high-performance liquid chromatography with electrochemical detection. The procedure was based on the separation of the iron—diethylenetriaminepentaacetic acid (DPTA) complex formed directly on a chromatographic column containing an anion-exchange resin followed by electrochemical detection. The method enabled more than 0.1 μM Fe(III) to be determined with an injection volume of 10 μl. A mixture of synovial fluid, 20 μM DTPA and acetate buffer was incubated in the presence and absence of superoxide (O⁻₂) generated by a xanthine—xanthine oxidase system and was ultrafiltered through a 30 000 molecular mass cut-off filter. No iron was detected in the ultrafiltrate at physiological pH. However, the presence of iron was observed in the ultrafiltrate at low pH, and O⁻₂ and decreased pH, iron may be released into the synovial fluid.     

革兰氏阴性细菌β-桶状结构外膜蛋白体外折叠的研究进展

除了细胞质膜,革兰氏阴性细菌细胞还有一层组成细胞壁的外膜(Outer Membrane)。膜蛋白是外膜的主要组成成分之一,绝大多数外膜蛋白是由反向平行的β-折叠(β-Strands)通过相邻的氢键结合形成的β-桶状结构蛋白(β-Barrel Proteins)。这些蛋白既可作为通道蛋白、转运蛋白、酶、受体、毒力因子,也可作为结构蛋白发挥稳定外膜的重要作用,它们是否正确折叠并整合到外膜对革兰氏阴性细菌的生存至关重要。大多数外膜蛋白易于重组表达和体外重折叠(in vitro refolding),并且折叠状态可通过多种方法测定,因此β-桶状结构外膜蛋白被当着模式蛋白来研究各类生物和非生物因子对膜蛋白折叠的影响,是膜蛋白研究的一大热点。本文将从β-桶状结构外膜蛋白体外折叠的研究方法和影响折叠的因素角度对近年相关研究进展进行综合述评,最后总结了外膜蛋白体外折叠模式,并结合作者的相关研究结果和观点对该领域的研究前景进行了展望。     

Genetic Mechanisms in Apc-Mediated Mammary Tumorigenesis

Many components of Wnt/β-catenin signaling pathway also play critical roles in mammary tumor development, yet the role of the tumor suppressor gene APC (adenomatous polyposis coli) in breast oncongenesis is unclear. To better understand the role of Apc in mammary tumorigenesis, we introduced conditional Apc mutations specifically into two different mammary epithelial populations using K14-cre and WAP-cre transgenic mice that express Cre-recombinase in mammary progenitor cells and lactating luminal cells, respectively. Only the K14-cre–mediated Apc heterozygosity developed mammary adenocarcinomas demonstrating histological heterogeneity, suggesting the multilineage progenitor cell origin of these tumors. These tumors harbored truncation mutation in a defined region in the remaining wild-type allele of Apc that would retain some down-regulating activity of β-catenin signaling. Activating mutations at codons 12 and 61 of either H-Ras or K-Ras were also found in a subset of these tumors. Expression profiles of acinar-type mammary tumors from K14-cre; Apc^CKO/+ mice showed luminal epithelial gene expression pattern, and clustering analysis demonstrated more correlation to MMTV-neu model than to MMTV-Wnt1. In contrast, neither WAP-cre–induced Apc heterozygous nor homozygous mutations resulted in predisposition to mammary tumorigenesis, although WAP-cre–mediated Apc deficiency resulted in severe squamous metaplasia of mammary glands. Collectively, our results suggest that not only the epithelial origin but also a certain Apc mutations are selected to achieve a specific level of β-catenin signaling optimal for mammary tumor development and explain partially the colon- but not mammary-specific tumor development in patients that carry germline mutations in APC.     

Charge Transfer Modulated Activity of Carbon‐Based Electrocatalysts

Electrocatalysis is the most important electrode reactions for many energy storage and conversion devices, which are considered a key part of the resolution of the energy crisis. Toward this end, design of efficient electrocatalysts is of critical significance. While extensive research has been extended to develop excellent electrocatalysts, the fundamental understanding of the relationship between the electronic and structural properties of electrocatalysts and the catalytic activity must remain a priority. In this review, the activity modulation of electrocatalysts by charge transfer effects, including intramolecular and intermolecular charge transfer, is systematically introduced. With suitable charge transfer modification, such as heteroatom doping, defect engineering, molecule functionalization, and heterojunctions, the electrocatalytic activity of carbon‐based electrocatalysts can be significantly boosted. The manipulation of the electronic structure of carbon‐based materials by charge transfer may serve as a fundamental mechanism for performance enhancement. After establishing an understanding of the relationship between catalytic activity and charge transfer, the opportunities and challenges for the design of electrocatalyst with charge transfer effects are discussed.