寡齿新银鱼同工酶及其与幼态持续的关系

采用聚丙烯酰胺垂直板状连续电泳方法,对幼态持续(neoteny)的寡齿新银鱼(Neosalanx oligodontis Chen)13种同工酶的18个位点进行研究,并进行乳酸脱氢酶热变性实验。结果表明ADH、GOT、α-GPDH、LDH、MDH、ME、POX和SOD表现出一定的幼态持续的特征,其中LDH由A、B两个位点编码,C位点不表达,是因为个体发育早期C基因尚未表达时发生幼态持续的结果。ES和IDH无幼态持续特征。α-AMY、FUM和CAT因数据不足,未进行分析。寡齿新银鱼同工酶基因表达中幼态特征的表现为研究鱼类幼态持续的产生机制和遗传基础提供线索。     

Develope Monoclonal Antibody against Foot-and-mouth Disease Virus A Type

In order to develop an anti-FMDV A Type monoclonal antibody (mAb),BABL/c mice were immunized with FMDV A type.Monoclonal antibodies (mAbs) 7B11 and 8H4 against Foot-and-mouth disease virus (FMDV) serotype A were produced by fusing SP2/0 myeloma cells with splenocyte from the mouse immunized with A/AV88.The microneutralization titer of the mAbs 7B11 and 8H4 were 1024 and 512,respectively.Both mAbs contain kappa light chains,the mAbs were IgG1.In order to define the mAbs binding epitopes,the reactivity of the...     

Temporal and spatial variability of chlorophyll <Emphasis Type="Italic">a</Emphasis> concentration in Lake Taihu using MODIS time-series data

In order to predict the distribution of chlorophyll a synoptically in Lake Taihu from 2006 to 2008, a common empirical algorithm was developed to relate time series chlorophyll a concentrations in the lake to reflectance derived as a function of band 2 MODIS data (r ² = 0.907, n = 145) using time series from 2005. The empirical model was further validated with chlorophyll a data from a 2008 to 2009 dataset, with RMSE < 7.48 μg l⁻¹ and r ² = 0.978. The seasonal and inter-annual variability of the surface chlorophyll a concentration from 2006 to 2008 was then examined using Empirical Orthogonal Function (EOF) analysis. The results revealed that the first four modes were significant, explaining 54.0% of the total chlorophyll a variance, and indicated that during the summer, algal blooms always occur in the northern bays, Meiliang Bay and Gonghu Bay, while they occur along the southwestern lakeshore during early summer, fall, and even early winter. The inter-annual variance analysis showed that the duration of algal blooms was from April to December of 2007, which was different from the bloom periods in 2006 and 2008. The results of EOF analysis show its potential for long-term integrated lake monitoring, not only in Lake Taihu but also in other large lakes threatened by accelerating eutrophication.     

Adaptation or preadaptation: why are keelback snakes (<Emphasis Type="Italic">Tropidonophis mairii</Emphasis>) less vulnerable to invasive cane toads (<Emphasis Type="Italic">Bufo marinus</Emphasis>) than are other Australian snakes?

Biological invasions can expose native predators to novel prey which may be less nutritious or detrimental to predators. The introduction and subsequent spread of cane toads (Bufo marinus) through Australia has killed many anuran-eating snakes unable to survive the toad’s toxins. However, one native species, the keelback snake (Tropidonophis mairii), is relatively resistant to toad toxins and remains common in toad-infested areas. Is the keelback’s ability to coexist with toads a function of its ancestral Asian origins, or a consequence of rapid adaptation since cane toads arrived in Australia? And does the snake’s feeding preference for frogs rather than toads reflect an innate or learned behaviour? We compared keelback populations long sympatric with toads with a population that has encountered toads only recently. Unlike toad-vulnerable snake species, sympatry with toads has not affected keelback toxin tolerances or feeding responses: T. mairii from toad-sympatric and toad-naïve populations show a similar sensitivity to toad toxin, and a similar innate preference for frogs rather than toads. Feeding responses of neonatal keelbacks demonstrate that learning plays little or no role in the snake’s aversion to toads. Thus, behavioural aversion to B. marinus as prey, and physiological tolerance to toad toxins are pre-existing innate characteristics of Australian keelbacks rather than adaptations to the cane toad’s invasion of Australia. Such traits were most likely inherited from ancestral keelbacks that adapted to the presence of bufonids in Asia. Our results suggest that the impact of invasive species on native taxa may be strongly influenced by the biogeographic histories of the species involved.     

Minimal antizyme peptide fully functioning in the binding and inhibition of ornithine decarboxylase and antizyme inhibitor

Antizyme (AZ) is a protein with 228 amino acid residues that regulates ornithine decarboxylase (ODC) by binding to ODC and dissociating its homodimer, thus inhibiting its enzyme activity. Antizyme inhibitor (AZI) is homologous to ODC, but has a higher affinity than ODC for AZ. In this study, we quantified the biomolecular interactions between AZ and ODC as well as AZ and AZI to identify functional AZ peptides that could bind to ODC and AZI and inhibit their function as efficiently as the full-length AZ protein. For these AZ peptides, the inhibitory ability of AZ_95-228 was similar to that of AZ_WT. Furthermore, AZ_95-176 displayed an inhibition (IC(50): 0.20 μM) similar to that of AZ-95-228 (IC(50): 0.16 μM), even though a large segment spanning residues 177-228 was deleted. However, further deletion of AZ_95-176 from either the N-terminus or the C-terminus decreased its ability to inhibit ODC. The AZ_100-176 and AZ_95-169 peptides displayed a noteworthy decrease in ability to inhibit ODC, with IC(50) values of 0.43 and 0.37 μM, respectively. The AZ_95-228, AZ_100-228 and AZ_95-176 peptides had IC(50) values comparable to that of AZ_WT and formed AZ-ODC complexes with K(d,AZ-ODC) values of 1.5, 5.3 and 5.6 μM, respectively. Importantly, our data also indicate that AZI can rescue AZ peptide-inhibited ODC enzyme activity and that it can bind to AZ peptides with a higher affinity than ODC. Together, these data suggest that these truncated AZ proteins retain their AZI-binding ability. Thus, we suggest that AZ_95-176 is the minimal AZ peptide that is fully functioning in the binding of ODC and AZI and inhibition of their function.     

Burkholderia multivorans acts as an antagonist against the growth of Burkholderia pseudomallei in soil

In this study, it was demonstrated, by using agar diffusion tests and a Transwell system, that Burkholderia multivorans NKI379 has an antagonistic effect against the growth of B. pseudomallei. Bacterial representatives were isolated from agricultural crop soil and mixed to construct a partial bacterial community structure that was based on the results of reproducible patterns following PCR-denaturing gradient gel electrophoresis analysis of total soil chromosomes. The antagonistic effect of B. multivorans on B. pseudomallei was observed in this imitate community. In a field study of agricultural crop soil, the presence of B. pseudomallei was inversely related to the presence of the antagonistic strains B. multivorans or B. cenocepacia. B. multivorans NKI379 can survive in a broader range of pH, temperatures and salt concentrations than B. pseudomallei, suggesting that B. multivorans can adapt to extreme environmental changes and therefore predominates over B. pseudomallei in natural environments.     

一种简易的家兔离体心脏灌流方法

生理实验中的经典实验,蛙心灌流给研究药物对心脏的影响提供了很好的实验平台,但是蛙心的结构毕竟区别于哺乳动物的心脏,研究结果不能说明药物对哺乳动物心脏的影响。然而哺乳动物是恒温动物,体外存活条件苛刻,设备复杂,非一般教学实验室能够实现。介绍了一种在常规生理教学实验室可以实现的简易的哺乳动物心脏离体灌流的方法。     

The natural compound n-butylidenephthalide derived from Angelica sinensis inhibits malignant brain tumor growth in vitro and in vivo

The naturally-occurring compound, n-butylidenephthalide (BP), which is isolated from the chloroform extract of Angelica sinensis (AS-C), has been investigated with respect to the treatment of angina. In this study, we have examined the anti-tumor effects of n-butylidenephthalide on glioblastoma multiforme (GBM) brain tumors both in vitro and in vivo. In vitro, GBM cells were treated with BP, and the effects of proliferation, cell cycle and apoptosis were determined. In vivo, DBTRG-05MG, the human GBM tumor, and RG2, the rat GBM tumor, were injected subcutaneously or intracerebrally with BP. The effects on tumor growth were determined by tumor volumes, magnetic resonance imaging and survival rate. Here, we report on the potency of BP in suppressing growth of malignant brain tumor cells without simultaneous fibroblast cytotocixity. BP up-regulated the expression of Cyclin Kinase Inhibitor (CKI), including p21 and p27, to decrease phosphorylation of Rb proteins, and down-regulated the cell-cycle regulators, resulting in cell arrest at the G(0)/G(1) phase for DBTRG-05MG and RG2 cells, respectively. The apoptosis-associated proteins were dramatically increased and activated by BP in DBTRG-05MG cells and RG2 cells, but RG2 cells did not express p53 protein. In vitro results showed that BP triggered both p53-dependent and independent pathways for apoptosis. In vivo, BP not only suppressed growth of subcutaneous rat and human brain tumors but also, reduced the volume of GBM tumors in situ, significantly prolonging survival rate. These in vitro and in vivo anti-cancer effects indicate that BP could serve as a new anti-brain tumor drug.     

Effects of Familial Mutations on the Monomer Structure of Aβ42

Amyloid beta (Aβ) peptide plays an important role in Alzheimer’s disease. A number of mutations in the Aβ sequence lead to familial Alzheimer’s disease, congophilic amyloid angiopathy, or hereditary cerebral hemorrhage with amyloid. Using molecular dynamics simulations of ∼200 μs for each system, we characterize and contrast the consequences of four pathogenic mutations (Italian, Dutch, Arctic, and Iowa) for the structural ensemble of the Aβ monomer. The four familial mutations are found to have distinct consequences for the monomer structure.Amyloid beta (Aβ) peptides have long been thought to play a central role in Alzheimer’s disease (AD). Usually 40 or 42 residues in length, Aβ peptides are proteolytic products of the Aβ precursor protein and they aggregate to form the fibrillar plaques in AD patients’ brains. Besides fibrillar plaques, Aβ oligomers are also neurotoxic. The significance and nature of Aβ oligomerization has recently become a focus of intensive research studies and debates (1,2). Notably, numerous pathogenic mutations have been identified in the Aβ precursor protein sequence and in the enzymes involved in Aβ processing (3). These mutations generally lead to early onset of AD or cerebral amyloid angiopathy. Understanding how the pathogenic mutations alter Aβ oligomerization/aggregation is essential to our understanding of the disease mechanism.Four of these pathogenic mutations (Italian E22K, Dutch E22Q, Arctic E22G, and Iowa D23N) cluster in the region of E22 and D23 in the Aβ sequence (distal from proteolytic cleavage sites) and they have higher neurotoxicity compared to wild-type (WT) Aβ (4). These mutations are thought to modify the physicochemistry of the peptide. For example, kinetic studies (4) show that the E22K and E22Q mutations lead to faster peptide aggregation, whereas the E22G and D23N mutations result in slightly slower aggregation than WT Aβ₄₂ (although the E22G mutation shows increased protofibril formation (5)). Recent solid-state NMR studies also suggest that rather than the in-register β-sheet conformation adopted by WT Aβ, the Iowa D23N mutant forms amyloid fibrils with antiparallel β-sheet structure (6).To understand how the mutations modify the peptide oligomerization/aggregation it is critical to characterize the starting point of the process, the monomers. Unfortunately, investigating the early phase of the oligomerization process experimentally is a challenging task due to the high aggregation propensity of Aβ and its intrinsic disorder. Therefore, a number of computational approaches have been adopted to investigate the consequences of mutations for the monomer structure (7–16). However, due to the high computational demands of explicit-solvent molecular dynamics (MD) simulations to simulate full-length Aβ peptides, most of these computational studies are either on Aβ fragments (to decrease the system size) using explicit-solvent simulations (8–12) or on full-length Aβ using implicit-solvent simulations (which are less computationally demanding and enable longer simulation times, but lack explicit water molecules in the simulations to fully describe water-peptide interactions) (13–15). In a very recent report, explicit-solvent simulations were used to study the effects of the E22Q mutation on full-length Aβ; however, rather limited data (<10 μs) were collected (16). Thus, characterizing full-length Aβ monomers remains quite a daunting task even with simulations.To characterize the effects of mutations on full-length Aβ monomer using explicit-solvent MD simulations, we employed distributed computing (17) to simulate the WT Aβ₄₂, Aβ₄₂-E22K, Aβ₄₂-E22Q, Aβ₄₂-E22G, and Aβ₄₂-D23N monomers. MD simulations of >200 μs were performed for each system and AMBER ff99sb (18) and the tip3p water model (19) were used for force field parameters. Peptide configurations in the MD trajectories were clustered with the root mean-square deviation metric to identify representative conformations (i.e., states) and transitions between these states were counted. Markov state model analysis was then performed where the master equations were solved and the equilibrium population of each state deduced (20). Details of the MD simulation procedures and Markov state model analysis can be found in the Supporting Material.Each of the five Aβ monomer systems exhibits great structural diversity and can only be characterized in an ensemble fashion (rather than described by a handful of representative configurations). This is in accord with the notion that full-length Aβ peptides are intrinsically disordered (21,22). Using the Dictionary of Secondary Structure of Proteins program (23) to assign secondary structure, it is clear that the five Aβ monomer systems are found overall not well structured, although small β-hairpins and α-helices are observed. In Fig. 1 we plot the residue-dependent extended β propensity and α-helix propensity, in the top and bottom panels, respectively, for each Aβ monomer system. Although we are reasonably confident of the convergence behavior of the α-helix propensity, we note that the convergence of the extended β-propensity might be more challenging and demand a much longer sampling time than the current aggregate simulation time of ∼200 μs (24).Open in a separate windowFigure 1Ensemble-averaged %population of β-strand (top) and α-helix (bottom) propensity for all five monomer systems. The sequence of the WT Aβ₄₂ is given on the x axis.We observe in Fig. 1 that all five Aβ monomer systems share a rather similar residue-dependent tendency to form an extended β-structure, although minor differences are present. On the other hand, these pathogenic mutations alter the α-helix propensity quite significantly. The E22K and E22Q mutations increase the α-helix propensity in the region of residues 20–23. All four mutations (E22K, E22Q, E22G, and D23N) decrease the α-helix propensity in the region of residues 33–36.Notably, we find that in all five systems only short stretches of α-helices are formed. That is, when a residue is involved in α-helix formation, it participates in forming mostly short helical segments (consisting of only four helical residues). To provide more insight into the changes of α-helix propensity due to the mutations, in Fig. S1 we plot the tendency of forming short α-helices along the sequence for all five systems. Each data point in Fig. S1 represents the propensity to form an α-helix of four residues in length, ending at the specific residue. For example, in the structural ensemble adopted by the WT peptide, ∼5.5% of the conformations have a short α-helix of size four, involving residues 15–18. We see from Fig. S1 that the E22K and E22Q mutations induce the formation of two short helices in residues 19–22 and 20–23. The higher α-helix propensity in this region for the E22K mutant compared to the WT was previously attributed to the elimination of the electrostatic repulsion between E22 and D23 in the WT by the mutation and the longer aliphatic chain of K22 in the mutant compared to E22 in the WT (9,22). This is consistent with the observation that the E22Q mutation also induces helix formation in this region (by eliminating the electrostatic repulsion between E22 and D23 in the WT) but to a lesser extent, possibly due to the shorter aliphatic chain of Q22 compared to K22.In the E22G mutant, although the mutation eliminates the electrostatic repulsion between E22 and D23 in the WT peptide, glycine is known to be a helix breaker (25), leading to diminished α-helix propensity in the region around residue G22 seen in Fig. S1.In the D23N mutant, although the mutation eliminates the electrostatic repulsion between E22 and D23 in the WT peptide, it does not induce (or rather even slightly decreases) helix formation around residue 23. This may be due to the short aliphatic chain of N23 but it is possible that the mutation induces some nonlocal effects on the peptide structure, disfavoring helix formation in this region.It is worth noting that all four mutations (E22K, E22Q, E22G, and D23N) virtually eliminate the α-helix propensity in the region of residues 33–36. This region is rather far away from the mutation sites in sequence but its α-helix propensity is nonetheless affected. The origin of such a nonlocal effect is less straightforward to explain and further analysis will aid untangling this behavior. Nonetheless, the diminished α-helix propensity in the region of residues 33–36 appears to be a consistent feature across all four mutants.The four mutations studied here (E22K, E22Q, E22G, and D23N) have been thought to modify the physicochemistry of the peptide and alter the oligomerization/aggregation process, leading to higher neurotoxicity. In predicting intrinsic aggregation propensities using peptide sequences, all four mutants are suggested to be more aggregation prone (26). On the other hand, kinetic studies show that only the E22K and E22Q mutants aggregate more quickly, whereas the E22G and D23N mutations result in slightly slower aggregation than WT Aβ₄₂ (4). Our simulation results suggest these pathogenic mutations have complicated effects on the monomer structure—all four mutations decrease helix propensity in residues 33–36, whereas only the E22K and E22Q mutations increase helix propensity in residues 20–23. It is interesting to note that α-helix propensity is generally thought to anticorrelate with aggregation propensity; however, recent studies have suggested an important role of α-helical intermediates in amyloid oligomerization (27–29). Our studies suggest that it would be of great value to investigate how the distinct patterns of α-helix propensity in these five systems may propagate to give rise to different oligomerization kinetics or even mechanisms. The pathogenic mutations studied here have complex effects on the oligomerization of the peptide. The characterization of the monomer structural ensembles reported here should aid understanding of such an important and complicated process.