On the evolutionary trail of MagRs.

Magnetic sense, or termed magnetoreception, has evolved in a broad range of taxa within the animal kingdom to facilitate orientation and navigation. MagRs, highly conserved A-type iron-sulfur proteins, are widely distributed across all phyla and play essential roles in both magnetoreception and iron-sulfur cluster biogenesis. However, the evolutionary origins and functional diversification of MagRs from their prokaryotic ancestor remain unclear. In this study, MagR sequences from 131 species, ranging from bacteria to humans, were selected for analysis, with 23 representative sequences covering species from prokaryotes to Mollusca, Arthropoda, Osteichthyes, Reptilia, Aves, and mammals chosen for protein expression and purification. Biochemical studies revealed a gradual increase in total iron content in MagRs during evolution. Three types of MagRs were identified, each with distinct iron and/or iron-sulfur cluster binding capacity and protein stability, indicating continuous expansion of the functional roles of MagRs during speciation and evolution. This evolutionary biochemical study provides valuable insights into how evolution shapes the physical and chemical properties of biological molecules such as MagRs and how these properties influence the evolutionary trajectories of MagRs.

Evolution of olfactory receptor superfamily in bats based on high throughput molecular modelling.

The origin of flight and laryngeal echolocation in bats is likely to have been accompanied by evolutionary changes in other aspects of their sensory biology. Of all sensory modalities in bats, olfaction is perhaps the least well understood. Olfactory receptors (ORs) function in recognizing odour molecules, with crucial roles in evaluating food, as well as in processing social information. Here we compare OR repertoire sizes across taxa and apply a new pipeline that integrates comparative genome data with protein structure modelling and then we employ molecular docking techniques with small molecules to analyse OR functionality based on binding energies. Our results suggest a sharp contraction in odorant recognition of the functional OR repertoire during the origin of bats, consistent with a reduced dependence on olfaction. We also compared bat lineages with contrasting different ecological characteristics and found evidence of differences in OR gene expansion and contraction, and in the composition of ORs with different tuning breadths. The strongest binding energies of ORs in non-echolocating fruit-eating bats were seen to correspond to ester odorants, although we did not detect a quantitative advantage of functional OR repertoires in these bats compared with echolocating insectivorous species. Overall, our findings based on molecular modelling and computational docking suggest that bats have undergone olfactory evolution linked to dietary adaptation. Our results from extant and ancestral bats help to lay the groundwork for targeted experimental functional tests in the future.

Structural, static, and dynamic functional MRI predictors for conversion from mild cognitive impairment to Alzheimer's disease: Inter-cohort validation of Shanghai Memory Study and ADNI.

Mild cognitive impairment (MCI) is a critical prodromal stage of Alzheimer's disease (AD), and the mechanism underlying the conversion is not fully explored. Construction and inter-cohort validation of imaging biomarkers for predicting MCI conversion is of great challenge at present, due to lack of longitudinal cohorts and poor reproducibility of various study-specific imaging indices. We proposed a novel framework for inter-cohort MCI conversion prediction, involving comparison of structural, static, and dynamic functional brain features from structural magnetic resonance imaging (sMRI) and resting-state functional MRI (fMRI) between MCI converters (MCI_C) and non-converters (MCI_NC), and support vector machine for construction of prediction models. A total of 218 MCI patients with 3-year follow-up outcome were selected from two independent cohorts: Shanghai Memory Study cohort for internal cross-validation, and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort for external validation. In comparison with MCI_NC, MCI_C were mainly characterized by atrophy, regional hyperactivity and inter-network hypo-connectivity, and dynamic alterations characterized by regional and connectional instability, involving medial temporal lobe (MTL), posterior parietal cortex (PPC), and occipital cortex. All imaging-based prediction models achieved an area under the curve (AUC) > 0.7 in both cohorts, with the multi-modality MRI models as the best with excellent performances of AUC > 0.85. Notably, the combination of static and dynamic fMRI resulted in overall better performance as relative to static or dynamic fMRI solely, supporting the contribution of dynamic features. This inter-cohort validation study provides a new insight into the mechanisms of MCI conversion involving brain dynamics, and paves a way for clinical use of structural and functional MRI biomarkers in future.

How genomic insights into the evolutionary history of clouded leopards inform their conservation.

Clouded leopards (Neofelis spp.), a morphologically and ecologically distinct lineage of big cats, are severely threatened by habitat loss and fragmentation, targeted hunting, and other human activities. The long-held poor understanding of their genetics and evolution has undermined the effectiveness of conservation actions. Here, we report a comprehensive investigation of the whole genomes, population genetics, and adaptive evolution of Neofelis. Our results indicate the genus Neofelis arose during the Pleistocene, coinciding with glacial-induced climate changes to the distributions of savannas and rainforests, and signatures of natural selection associated with genes functioning in tooth, pigmentation, and tail development, associated with clouded leopards' unique adaptations. Our study highlights high-altitude adaptation as the main factor driving nontaxonomic population differentiation in Neofelis nebulosa. Population declines and inbreeding have led to reduced genetic diversity and the accumulation of deleterious variation that likely affect reproduction of clouded leopards, highlighting the urgent need for effective conservation efforts.

Phylogenomic analyses provide insights into primate evolution.

Comparative analysis of primate genomes within a phylogenetic context is essential for understanding the evolution of human genetic architecture and primate diversity. We present such a study of 50 primate species spanning 38 genera and 14 families, including 27 genomes first reported here, with many from previously less well represented groups, the New World monkeys and the Strepsirrhini. Our analyses reveal heterogeneous rates of genomic rearrangement and gene evolution across primate lineages. Thousands of genes under positive selection in different lineages play roles in the nervous, skeletal, and digestive systems and may have contributed to primate innovations and adaptations. Our study reveals that many key genomic innovations occurred in the Simiiformes ancestral node and may have had an impact on the adaptive radiation of the Simiiformes and human evolution.

iORbase: A database for the prediction of the structures and functions of insect olfactory receptors.

Insect olfactory receptors (iORs) with atypical 7-transmembrane domains, unlike Chordata olfactory receptors, are not in the GPCR protein family. iORs selectively bind to volatile ligands in the environment and affect essential insect behaviors. In this study, we constructed a new platform (iORbase, https://www.iorbase.com) for the structural and functional analysis of iORs based on a combined algorithm for gene annotation and protein structure prediction. Moreover, it provides the option to calculate the binding affinities and binding residues between iORs and pheromone molecules by virtual screening of docking. Furthermore, iORbase supports the automatic structural and functional prediction of user-submitted iORs or pheromones. iORbase contains the well-analyzed results of approximately 6 000 iORs and their 3D protein structures identified from 59 insect species and 2 077 insect pheromones from the literature, as well as approximately 12 million pairs of simulated interactions between functional iORs and pheromones. We also built 4 online modules, iORPDB, iInteraction, iModelTM, and iOdorTool to easily retrieve and visualize the 3D structures and interactions. iORbase can help greatly improve the experimental efficiency and success rate, identify new insecticide targets, or develop electronic nose technology. This study will shed light on the olfactory recognition mechanism and evolutionary characteristics from the perspectives of omics and macroevolution.

Associations of [18F]-APN-1607 Tau PET Binding in the Brain of Alzheimer's Disease Patients With Cognition and Glucose Metabolism.

Molecular imaging of tauopathies is complicated by the differing specificities and off-target binding properties of available radioligands for positron emission tomography (PET). [18F]-APN-1607 ([18F]-PM-PBB3) is a newly developed PET tracer with promising properties for tau imaging. We aimed to characterize the cerebral binding of [18F]-APN-1607 in Alzheimer's disease (AD) patients compared to normal control (NC) subjects. Therefore, we obtained static late frame PET recordings with [18F]-APN-1607 and [18F]-FDG in patients with a clinical diagnosis of AD group, along with an age-matched NC group ([18F]-APN-1607 only). Using statistical parametric mapping (SPM) and volume of interest (VOI) analyses of the reference region normalized standardized uptake value ratio maps, we then tested for group differences and relationships between both PET biomarkers, as well as their associations with clinical general cognition. In the AD group, [18F]-APN-1607 binding was elevated in widespread cortical regions (P < 0.001 for VOI analysis, familywise error-corrected P < 0.01 for SPM analysis). The regional uptake in AD patients correlated negatively with Mini-Mental State Examination score (frontal lobe: R = -0.632, P = 0.004; temporal lobe: R = -0.593, P = 0.008; parietal lobe: R = -0.552, P = 0.014; insula: R = -0.650, P = 0.003; cingulum: R = -0.665, P = 0.002) except occipital lobe (R = -0.417, P = 0.076). The hypometabolism to [18F]-FDG PET in AD patients also showed negative correlations with regional [18F]-APN-1607 binding in some signature areas of AD (temporal lobe: R = -0.530, P = 0.020; parietal lobe: R = -0.637, P = 0.003; occipital lobe: R = -0.567, P = 0.011). In conclusion, our results suggested that [18F]-APN-1607 PET sensitively detected tau deposition in AD and that individual tauopathy correlated with impaired cerebral glucose metabolism and cognitive function.

The Evolution History of Fe-S Cluster A-Type Assembly Protein Reveals Multiple Gene Duplication Events and Essential Protein Motifs.

Iron-sulfur (Fe-S) clusters play important roles in electron transfer, metabolic and biosynthetic reactions, and the regulation of gene expression. Understanding the biogenesis of Fe-S clusters is therefore relevant to many fields. In the complex process of Fe-S protein formation, the A-type assembly protein (ATAP) family, which consists of several subfamilies, plays an essential role in Fe-S cluster formation and transfer and is highly conserved across the tree of life. However, the taxonomic distribution, motif compositions, and the evolutionary history of the ATAP subfamilies are not well understood. To address these problems, our study investigated the taxonomic distribution of 321 species from a broad cross-section of taxa. Then, we identified common and specific motifs in multiple ATAP subfamilies to explain the functional conservation and nonredundancy of the ATAPs, and a novel, essential motif was found in Eumetazoa IscA1, which has a newly found magnetic function. Finally, we used phylogenetic analytical methods to reconstruct the evolution history of this family. Our results show that two types of ErpA proteins (nonproteobacteria-type ErpA1 and proteobacteria-type ErpA2) exist in bacteria. The ATAP family, consisting of seven subfamilies, can be further classified into two types of ATAPs. Type-I ATAPs include IscA, SufA, HesB, ErpA1, and IscA1, with an ErpA1-like gene as their last common ancestor, whereas type-II ATAPs consist of ErpA2 and IscA2, duplicated from an ErpA2-like gene. During the mitochondrial endosymbiosis, IscA became IscA1 in eukaryotes and ErpA2 became IscA2 in eukaryotes, respectively.

Decreased Retinal Vascular Density in Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI): An Optical Coherence Tomography Angiography (OCTA) Study.

BACKGROUND: To explore the retinal vascular density changes in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients using optical coherence tomography angiography (OCTA). METHODS: We recruit 62 AD patients, 47 MCI patients, and 49 cognitively healthy controls (HC) in this study. All participants in the study received a comprehensive ophthalmological and neurological evaluation, including global cognitive screening, as well as the Mini-Mental State Examination (MMSE), and completed the following eye examinations: visual acuity (VA), intraocular pressure (IOP), examination with slit-lamp, fundus photography (Version 1.5.0.0, NIDEK CO, LTD) and Optical coherence tomography imaging (software ReVue version 2017.1.0.155, Optovue Inc., Fremont, CA, United States). The visual rating scales for atrophy and white matter lesion in MRI was evaluated for all the patients with AD and MCI. RESULTS: In the AD patient group, the superficial vascular density in the superior, inferior and whole retina was 44.64 ± 3.34, 44.65 ± 3.55, and 44.66 ± 3.36, respectively. These values were 44.24 ± 3.15, 43.72 ± 3.16, and 44 ± 3.07, respectively, in the MCI patient group. After multivariate analysis of the generalized linear model, adjustments for the confounding factors of sex, age, hypertension, diabetes and the quality index of OCTA image, the superficial vascular density in the AD and MCI patient groups was significantly lower than that in the HC group (P < 0.05): 46.94 ± 2.04, 46.67 ± 2.26, and 46.82 ± 2.08, respectively. No difference in the area of the FAZ among the three groups was observed (AD group: 0.34 ± 0.11 mm2; MCI group: 0.36 ± 0.12 mm2; control group: 0.33 ± 0.12 mm2, p > 0.05). The ganglion cell complex (GCC) thickness, inner parafovea thickness, and peripapillary retinal nerve fiber layer (p-RNFL) thickness were associated with the superficial vascular density. We found no significant correlation between the global cognition (MMSE scores) or between the Fazekas score and retinal OCT angiogram flow density. CONCLUSION: The superficial vascular density in the AD and MCI patient groups was significantly lower than that in the HC group. Our findings suggest the retinal microvascular dysfunction occurred in MCI and AD.

Comparison of the roles of estrogens and androgens in breast cancer and prostate cancer.

Breast cancer (BC) and prostate cancer (PC) are the second most common malignant tumors in women and men in western countries, respectively. The risks of death are 14% for BC and 9% for PC. Abnormal estrogen and androgen levels are related to carcinogenesis of the breast and prostate. Estradiol stimulates cancer development in BC. The effect of estrogen on PC is concentration-dependent, and estrogen can regulate androgen production, further affecting PC. Estrogen can also increase the risk of androgen-induced PC. Androgen has dual effects on BC via different metabolic pathways, and the role of the androgen receptor (AR) in BC also depends on cell subtype and downstream target genes. Androgen and AR can stimulate both primary PC and castration-resistant PC. Understanding the mechanisms of the effects of estrogen and androgen on BC and PC may help us to improve curative BC and PC treatment strategies.

Predicting combinative drug pairs via multiple classifier system with positive samples only.

BACKGROUND AND OBJECTIVE: Due to the synergistic effects of drugs, drug combination is one of the effective approaches for treating complex diseases. However, the identification of drug combinations by dose-response methods is still costly. It is promising to develop supervised learning-based approaches to predict potential drug combinations on a large scale. Nevertheless, these approaches have the inadequate utilization of heterogeneous features, which causes the loss of information useful to classification. Moreover, they have an intrinsic bias, because they assume unknown drug pairs as non-combinations, of which some could be real drug combinations in practice. METHODS: To address above issues, this work first designs a two-layer multiple classifier system (TLMCS) to effectively integrate heterogeneous features involving anatomical therapeutic chemical codes of drugs, drug-drug interactions, drug-target interactions, gene ontology of drug targets, and side effects. To avoid the bias caused by labelling unknown samples as negative, it then utilizes the one-class support vector machines, (which requires no negative instance and only labels approved drug combinations as positive instances), as the member classifiers in TLMCS. Last, both a 10-fold cross validation (10-CV) and a novel prediction are performed to validate the performance of TLMCS. RESULTS: The comparison with three state-of-the-art approaches under 10-CV exhibits the superiority of TLMCS, which achieves the area under the receiver operating characteristic curve = 0.824 and the area under the precision-recall curve = 0.372. Moreover, the experiment under the novel prediction demonstrates its ability, where 9 out of the top-20 predicted combinative drug pairs are validated by checking the published literature. Furthermore, for each of the newly-validated drug combinations, this work analyses the combining mode of the member drugs and investigates their relationship in terms of drug targeting pathways. CONCLUSIONS: The proposed TLMCS provides an effective framework to integrate those heterogeneous features and is trained by only positive samples such that the bias of taking unknown drug pairs as negative samples can be avoided. Furthermore, its results in the novel prediction reveal five types of drug combinations and three types of drug relationships in terms of pathways.

Effects of large gradient high magnetic field (LG-HMF) on the long-term culture of aquatic organisms: Planarians example.

Large gradient high magnetic field (LG-HMF) is a powerful tool to study the effects of altered gravity on organisms. In our study, a platform for the long-term culture of aquatic organisms was designed based on a special superconducting magnet with an LG-HMF, which can provide three apparent gravity levels (µ g, 1 g, and 2 g), along with a control condition on the ground. Planarians, Dugesia japonica, were head-amputated and cultured for 5 days in a platform for head reconstruction. After planarian head regeneration, all samples were taken out from the superconducting magnet for a behavioral test under geomagnetic field and normal gravity conditions. To analyze differences among the four groups, four aspects of the planarians were considered, including head regeneration rate, phototaxis response, locomotor velocity, and righting behavior. Data showed that there was no significant difference in the planarian head regeneration rate under simulated altered gravity. According to statistical analysis of the behavioral test, all of the groups had normal functioning of the phototaxis response, while the planarians that underwent head reconstruction under the microgravity environment had significantly slower locomotor velocity and spent more time in righting behavior. Furthermore, histological staining and immunohistochemistry results helped us reveal that the locomotor system of planarians was affected by the simulated microgravity environment. We further demonstrated that the circular muscle of the planarians was weakened (hematoxylin and eosin staining), and the epithelial cilia of the planarians were reduced (anti-acetylated tubulin staining) under the simulated microgravity environment. Bioelectromagnetics. 2018;39:428-440. © 2018 Wiley Periodicals, Inc.

Ligand-binding characterization of simulated ß-adrenergic-like octopamine receptor in Schistocerca gregaria via progressive structure simulation.

It is important to design insecticides having both low drug resistance and less undesirable toxicity for desert locust control. Specific GPCRs of Schistocerca gregaria, especially ß-adrenergic-like octopamine receptor (SgOctßR), can be considered as its potential effective insecticide targets. However, either the unavailability of SgOctßR's structure or the inadequate capability of its sequence lead the development of insecticide for Schistocerca gregaria meets its plateau. To relax this difficulty, this paper develops a promising progressive structure simulation from SgOctßR's sequence, to its predicted structure of SgOctßR in vacuum, to its conformation as well as its complex with endogenous ligand octopamine in a solvent-membrane system. The combined approach of multiple sequence alignment, static structural characterization, and dynamic process of conformational change during binding octopamine reveal three important aspects. The first one is the characterization of SgOctßR's active pocket, including the attending secondary structure elements, its hydrophobic residues and nonpolar surface. The second one is the interaction with octopamine, especially the involved hydrogen bonds and an aromatic stacking of pi-pi interactions. The third one is the potential binding sites, including six highly conserved residues and one highly variable residue for locust insecticide design. This work is definitely helpful for the further structure-based drug design for efficient and eco-friendly insecticides, as well as site-directed mutagenesis biochemical research of SgOctßR.

Characterization and analysis of a de novo transcriptome from the pygmy grasshopper Tetrix japonica.

The pygmy grasshopper Tetrix japonica is a common insect distributed throughout the world, and it has the potential for use in studies of body colour polymorphism, genomics and the biology of Tetrigoidea (Insecta: Orthoptera). However, limited biological information is available for this insect. Here, we conducted a de novo transcriptome study of adult and larval T. japonica to provide a better understanding of its gene expression and develop genomic resources for future work. We sequenced and explored the characteristics of the de novo transcriptome of T. japonica using Illumina HiSeq 2000 platform. A total of 107 608 206 paired-end clean reads were assembled into 61 141 unigenes using the trinity software; the mean unigene size was 771 bp, and the N50 length was 1238 bp. A total of 29 225 unigenes were functionally annotated to the NCBI nonredundant protein sequences (Nr), NCBI nonredundant nucleotide sequences (Nt), a manually annotated and reviewed protein sequence database (Swiss-Prot), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. A large number of putative genes that are potentially involved in pigment pathways, juvenile hormone (JH) metabolism and signalling pathways were identified in the T. japonica transcriptome. Additionally, 165 769 and 156 796 putative single nucleotide polymorphisms occurred in the adult and larvae transcriptomes, respectively, and a total of 3162 simple sequence repeats were detected in this assembly. This comprehensive transcriptomic data for T. japonica will provide a usable resource for gene predictions, signalling pathway investigations and molecular marker development for this species and other pygmy grasshoppers.

Measurement of contact angles in a simulated microgravity environment generated by a large gradient magnetic field.

The contact angle is an important parameter that is essential for studying interfacial phenomena. The contact angle can be measured using commercially available instruments. However, these well-developed instruments may not function or may be unsuitable for use in some special environments. A simulated microgravity generated by a large gradient magnetic field is such an environment in which the current measurement instruments cannot be installed. To measure the contact angle in this environment, new tools must be designed and manufactured to be compatible with the size and physical environment. In this study, we report the development and construction of a new setup that was specifically designed for use in a strong magnetic field to measure the contact angle between a levitated droplet and a solid surface. The application of the setup in a large gradient magnetic field was tested, and the contact angles were readily measured.

Predicting existing targets for new drugs base on strategies for missing interactions.

BACKGROUND: There has been paid more and more attention to supervised classification models in the area of predicting drug-target interactions (DTIs). However, in terms of classification, unavoidable missing DTIs in data would cause three issues which have not yet been addressed appropriately by former approaches. Directly labeled as negatives (non-DTIs), missing DTIs increase the confusion of positives (DTIs) and negatives, aggravate the imbalance between few positives and many negatives, and are usually discriminated as highly-scored false positives, which influence the existing measures sharply. RESULTS: Under the framework of local classification model (LCM), this work focuses on the scenario of predicting how possibly a new drug interacts with known targets. To address the first two issues, two strategies, Spy and Super-target, are introduced accordingly and further integrated to form a two-layer LCM. In the bottom layer, Spy-based local classifiers for protein targets are built by positives, as well as reliable negatives identified among unlabeled drug-target pairs. In the top layer, regular local classifiers specific to super-targets are built with more positives generated by grouping similar targets and their interactions. Furthermore, to handle the third issue, an additional performance measure, Coverage, is presented for assessing DTI prediction. The experiments based on benchmark datasets are finally performed under five-fold cross validation of drugs to evaluate this approach. The main findings are concluded as follows. (1) Both two individual strategies and their combination are effective to missing DTIs, and the combination wins the best. (2) Having the advantages of less confusing decision boundary at the bottom layer and less biased decision boundary at the top layer, our two-layer LCM outperforms two former approaches. (3) Coverage is more robust to missing interactions than other measures and is able to evaluate how far one needs to go down the list of targets to cover all the proper targets of a drug. CONCLUSIONS: Proposing two strategies and one performance measure, this work has addressed the issues derived from missing interactions, which cause confusing and biased decision boundaries in classifiers, as well as the inappropriate measure of predicting performance, in the scenario of predicting interactions between new drugs and known targets.

A Systematic Analysis of the Structures of Heterologously Expressed Proteins and Those from Their Native Hosts in the RCSB PDB Archive.

Recombinant expression of proteins has become an indispensable tool in modern day research. The large yields of recombinantly expressed proteins accelerate the structural and functional characterization of proteins. Nevertheless, there are literature reported that the recombinant proteins show some differences in structure and function as compared with the native ones. Now there have been more than 100,000 structures (from both recombinant and native sources) publicly available in the Protein Data Bank (PDB) archive, which makes it possible to investigate if there exist any proteins in the RCSB PDB archive that have identical sequence but have some difference in structures. In this paper, we present the results of a systematic comparative study of the 3D structures of identical naturally purified versus recombinantly expressed proteins. The structural data and sequence information of the proteins were mined from the RCSB PDB archive. The combinatorial extension (CE), FATCAT-flexible and TM-Align methods were employed to align the protein structures. The root-mean-square distance (RMSD), TM-score, P-value, Z-score, secondary structural elements and hydrogen bonds were used to assess the structure similarity. A thorough analysis of the PDB archive generated five-hundred-seventeen pairs of native and recombinant proteins that have identical sequence. There were no pairs of proteins that had the same sequence and significantly different structural fold, which support the hypothesis that expression in a heterologous host usually could fold correctly into their native forms.

De Novo Assembly and Characterization of the Transcriptome of Grasshopper Shirakiacris shirakii.

BACKGROUND: The grasshopper Shirakiacris shirakii is an important agricultural pest and feeds mainly on gramineous plants, thereby causing economic damage to a wide range of crops. However, genomic information on this species is extremely limited thus far, and transcriptome data relevant to insecticide resistance and pest control are also not available. METHODS: The transcriptome of S. shirakii was sequenced using the Illumina HiSeq platform, and we de novo assembled the transcriptome. RESULTS: Its sequencing produced a total of 105,408,878 clean reads, and the de novo assembly revealed 74,657 unigenes with an average length of 680 bp and N50 of 1057 bp. A total of 28,173 unigenes were annotated for the NCBI non-redundant protein sequences (Nr), NCBI non-redundant nucleotide sequences (Nt), a manually-annotated and reviewed protein sequence database (Swiss-Prot), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Based on the Nr annotation results, we manually identified 79 unigenes encoding cytochrome P450 monooxygenases (P450s), 36 unigenes encoding carboxylesterases (CarEs) and 36 unigenes encoding glutathione S-transferases (GSTs) in S. shirakii. Core RNAi components relevant to miroRNA, siRNA and piRNA pathways, including Pasha, Loquacious, Argonaute-1, Argonaute-2, Argonaute-3, Zucchini, Aubergine, enhanced RNAi-1 and Piwi, were expressed in S. shirakii. We also identified five unigenes that were homologous to the Sid-1 gene. In addition, the analysis of differential gene expressions revealed that a total of 19,764 unigenes were up-regulated and 4185 unigenes were down-regulated in larvae. In total, we predicted 7504 simple sequence repeats (SSRs) from 74,657 unigenes. CONCLUSIONS: The comprehensive de novo transcriptomic data of S. shirakii will offer a series of valuable molecular resources for better studying insecticide resistance, RNAi and molecular marker discovery in the transcriptome.

[Progresses in predicting the crystallizability of proteins].

Determination of protein 3-dimensional structure offers very important information in biology researches, especially for understanding protein functions and redundant drug design. The X-ray crystallography is still the main technique for protein structure determination. Obtaining protein crystals is an essential procedure after protein purification in this technique. However, there is only 42% of soluble purified proteins yield crystals by statistics. Experimental verification of protein crystallizability is relatively expensive and time-consuming. Thus it is desired to predict the protein crystallizability by a computational method before starting the experiment. In this paper, combined with our own efforts, some successful in silico methods to predict the protein crystallizability are reviewed.

A quality comparison of protein crystals grown under containerless conditions generated by diamagnetic levitation, silicone oil and agarose gel.

High-quality crystals are key to obtaining accurate three-dimensional structures of proteins using X-ray diffraction techniques. However, obtaining such protein crystals is often a challenge. Several containerless crystallization techniques have been reported to have the ability to improve crystal quality, but it is unknown which is the most favourable way to grow high-quality protein crystals. In this paper, a quality comparison of protein crystals which were grown under three containerless conditions provided by diamagnetic levitation, silicone oil and agarose gel was conducted. A control experiment on a vessel wall was also simultaneously carried out. Seven different proteins were crystallized under the four conditions, and the crystal quality was assessed in terms of the resolution limit, the mosaicity and the Rmerge. It was found that the crystals grown under the three containerless conditions demonstrated better morphology than those of the control. X-ray diffraction data indicated that the quality of the crystals grown under the three containerless conditions was better than that of the control. Of the three containerless crystallization techniques, the diamagnetic levitation technique exhibited the best performance in enhancing crystal quality. This paper is to our knowledge the first report of improvement of crystal quality using a diamagnetic levitation technique. Crystals obtained from agarose gel demonstrated the second best improvement in crystal quality. The study indicated that the diamagnetic levitation technique is indeed a favourable method for growing high-quality protein crystals, and its utilization is thus potentially useful in practical efforts to obtain well diffracting protein crystals.