PSMD: An extensive database for pan‐species microsatellite investigation and marker development

Microsatellites are widely distributed throughout nearly all genomes which have been extensively exploited as powerful genetic markers for diverse applications due to their high polymorphisms. Their length variations are involved in gene regulation and implicated in numerous genetic diseases even in cancers. Although much effort has been devoted in microsatellite database construction, the existing microsatellite databases still had some drawbacks, such as limited number of species, unfriendly export format, missing marker development, lack of compound microsatellites and absence of gene annotation, which seriously restricted researchers to perform downstream analysis. In order to overcome the above limitations, we developed PSMD (Pan‐Species Microsatellite Database, http://big.cdu.edu.cn/psmd/ ) as a web‐based database to facilitate researchers to easily identify microsatellites, exploit reliable molecular markers and compare microsatellite distribution pattern on genome‐wide scale. In current release, PSMD comprises 678,106,741 perfect microsatellites and 43,848,943 compound microsatellites from 18,408 organisms, which covered almost all species with available genomic data. In addition to interactive browse interface, PSMD also offers a flexible filter function for users to quickly gain desired microsatellites from large data sets. PSMD allows users to export GFF3 formatted file and CSV formatted statistical file for downstream analysis. We also implemented an online tool for analysing occurrence of microsatellites with user‐defined parameters. Furthermore, Primer3 was embedded to help users to design high‐quality primers with customizable settings. To our knowledge, PSMD is the most extensive resource which is likely to be adopted by scientists engaged in biological, medical, environmental and agricultural research.     

Evolutionary history and climate conditions constrain the flower colours of woody plants in China

进化历史和气候条件共同影响中国木本植物花色的分布 本研究以中国木本植物为研究对象,主要探讨两个问题：(1)不同生活型物种花色组成的差异;(2)生物地理区、进化年龄和气候条件对不同花色地理分布格局的影响。研究使用7673种木本植物的物种分布数据和花色信息(分为白色、红色、黄色、黄绿色、绿色和蓝紫色),并结合属级系统进化树来比较不同生活型(包括灌木、乔木和藤本)物种花色组成的差异,分析不同生物地理区、进化年龄和现代气候对花色地理格局的影响。研究结果表明,与乔木和藤本植物相比,灌木具有更高比例 的由花青素着色的红色花和蓝紫色花物种。中国木本植物的花色地理格局受到区域效应和现代气候(尤其是降水和UVB辐射)的共同影响。倾向于蜂媒传粉的黄色花和蓝紫色花物种和由花青素着色、耐环境胁迫的红色花和蓝紫色花物种比例在中国西北部地区更高。绿色花物种的进化起源更早,但进化时间对花色地理格局的解释力很弱。这些结果说明中国木本植物花色的地理格局受到进化历史和现代环境的共同影响。     

Climate–ecosystem modelling made easy: The Land Sites Platform

Dynamic Global Vegetation Models (DGVMs) provide a state-of-the-art process-based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single-site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version-controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site-level simulations. We provide input data for 20 established geo-ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.     

Ribosomal protein L22-like1 promotes prostate cancer progression by activating PI3K/Akt/mTOR signalling pathway

Prostate cancer (PCa) is one of the most common malignancies in men. Ribosomal protein L22-like1 (RPL22L1), a component of the ribosomal 60 S subunit, is associated with cancer progression, but the role and potential mechanism of RPL22L1 in PCa remain unclear. The aim of this study was to investigate the role of RPL22L1 in PCa progression and the mechanisms involved. Bioinformatics and immunohistochemistry analysis showed that the expression of RPL22L1 was significantly higher in PCa tissues than in normal prostate tissues. The cell function analysis revealed that RPL22L1 significantly promoted the proliferation, migration and invasion of PCa cells. The data of xenograft tumour assay suggested that the low expression of RPL22L1 inhibited the growth and invasion of PCa cells in vivo. Mechanistically, the results of Western blot proved that RPL22L1 activated PI3K/Akt/mTOR pathway in PCa cells. Additionally, LY294002, an inhibitor of PI3K/Akt pathway, was used to block this pathway. The results showed that LY294002 remarkably abrogated the oncogenic effect of RPL22L1 on PCa cell proliferation and invasion. Taken together, our study demonstrated that RPL22L1 is a key gene in PCa progression and promotes PCa cell proliferation and invasion via PI3K/Akt/mTOR pathway, thus potentially providing a new target for PCa therapy.     

A biofilm model to understand the onset of sulfate reduction in denitrifying membrane biofilm reactors

This work presents a multispecies biofilm model that describes the co‐existence of nitrate‐ and sulfate‐reducing bacteria in the H₂‐based membrane biofilm reactor (MBfR). The new model adapts the framework of a biofilm model for simultaneous nitrate and perchlorate removal by considering the unique metabolic and physiological characteristics of autotrophic sulfate‐reducing bacteria that use H₂ as their electron donor. To evaluate the model, the simulated effluent H₂, UAP (substrate‐utilization‐associated products), and BAP (biomass‐associated products) concentrations are compared to experimental results, and the simulated biomass distributions are compared to real‐time quantitative polymerase chain reaction (qPCR) data in the experiments for parameter optimization. Model outputs and experimental results match for all major trends and explain when sulfate reduction does or does not occur in parallel with denitrification. The onset of sulfate reduction occurs only when the nitrate concentration at the fiber's outer surface is low enough so that the growth rate of the denitrifying bacteria is equal to that of the sulfate‐reducing bacteria. An example shows how to use the model to design an MBfR that achieves satisfactory nitrate reduction, but suppresses sulfate reduction. Biotechnol. Bioeng. 2013; 110: 763–772. © 2012 Wiley Periodicals, Inc.     

Altered patterns of fractionation and exon deletions in Brassica rapa support a two-step model of paleohexaploidy

The genome sequence of the paleohexaploid Brassica rapa shows that fractionation is biased among the three subgenomes and that the least fractionated subgenome has approximately twice as many orthologs as its close (and relatively unduplicated) relative Arabidopsis than had either of the other two subgenomes. One evolutionary scenario is that the two subgenomes with heavy gene losses (I and II) were in the same nucleus for a longer period of time than the third subgenome (III) with the fewest gene losses. This "two-step" hypothesis is essentially the same as that proposed previously for the eudicot paleohexaploidy; however, the more recent nature of the B. rapa paleohexaploidy makes this model more testable. We found that subgenome II suffered recent small deletions within exons more frequently than subgenome I, as would be expected if the genes in subgenome I had already been near maximally fractionated before subgenome III was introduced. We observed that some sequences, before these deletions, were flanked by short direct repeats, a unique signature of intrachromosomal illegitimate recombination. We also found, through simulations, that short--single or two-gene--deletions appear to dominate the fractionation patterns in B. rapa. We conclude that the observed patterns of the triplicated regions in the Brassica genome are best explained by a two-step fractionation model. The triplication and subsequent mode of fractionation could influence the potential to generate morphological diversity--a hallmark of the Brassica genus.     

Continuous microalgae cultivation in a photobioreactor

New biomass sources for alternative fuels has become a subject of increasing importance as the nation strives to resolve the economic and strategic impacts of limited fossil fuel resources on our national security, environment, and global climate. Algae are among the most promising non‐food‐crop‐based biomass feedstocks. However, there are currently no commercially viable microalgae‐based production systems for biofuel production that have been developed, as limitations include less‐than optimal oil content, growth rates, and cultivation techniques. While batch studies are critical for determining basic growth phases and characteristics of the algal species, steady‐state studies are necessary to better understand and measure the specific growth parameters. This study evaluated the effects of dilution rate on microalgal biomass productivity, lipid content, and fatty acid profile under steady‐state conditions with continuous illumination and carbon dioxide supplemention for two types of algae. Continuous cultures were conducted for more that 3 months. Our results show that the productivity of Chlorella minutissima varied from 39 to 137 mg/L/day (dry mass) when the dilution rate varied from 0.08 to 0.64 day^?1. The biomass productivity of C. minutissima reached a maximum value (137 mg/L/day) at a dilution rate of 0.33 day^?1, while the productivity of Dunaliella tertiolecta varied from 46 to 91 mg/L/day at a dilution rate of 0.17 to 0.74 day^?1. The biomass productivity of D. tertiolecta reached a maximum value of 91 mg/L/day at a dilution rate of 0.42 day^?1. Moreover, the lipid content had no significant change with various dilution rates. Biotechnol. Bioeng. 2012; 109: 2468–2474. © 2012 Wiley Periodicals, Inc.     

Analysis of Antarctic proteobacteria by PCR fingerprinting and screening for antimicrobial secondary metabolites

Fifty-seven proteobacterium species were successfully isolated from soils of Barrientos Island of the Antarctic using 11 different isolation media. Analysis of 16S rDNA sequencing of these isolates showed that they belonged to eight different genera, namely Bradyrhizobium, Sphingomonas, Methylobacterium, Caulobacter, Paracoccus, Ralstonia, Rhizobium, and Staphylococcus. All isolates were studied for capability of producing antimicrobial and antifungal secondary metabolites using high-throughput screening models. Approximately 23 (13/57) and 2% (1/57) of isolates inhibited growth of Candida albicans ATCC 10231(T) and Staphylococcus aureus ATCC 51650(T), respectively. These results indicated that proteobacterium species isolates from Antarctic could serve as potential source of useful bioactive metabolites. Enterobacterial repetitive intergenic consensus (ERIC)-PCR fingerprinting produced nine clusters and 13 single isolates, with a high D value of 0.9248. RAPD fingerprinting produced six clusters and 13 single isolates, with a relatively low D value of 0.7776. ERIC-PCR analysis proved to have better discrimination capability than RAPD analysis and generated better clustering for all proteobacterium species isolates. We conclude that ERIC-PCR is a robust, reliable and rapid molecular typing method for discriminating different genera of proteobacteria.