Vegetation and Soil Development in Compost‐Amended Iron Oxide Precipitates at a 50‐Year‐Old Acid Mine Drainage Barrens

Acid mine drainage (AMD) barrens result from destruction of vegetation within AMD flow paths. When exposed to air, soluble iron in AMD undergoes oxidation and hydrolysis to form ferric iron (oxyhydr)oxides which accumulate on soil surfaces. A restoration experiment was conducted at a 50‐year‐old AMD barrens created by discharge from an abandoned underground coal mine. The objective was to determine whether vegetation could be established by altering rather than removing surface layers of acidic precipitates at a site representative of other mining‐degraded areas. Three zones in the barrens were identified based on moisture content, pH (2.7–3.3), and thickness of precipitates (0–35 cm). Our hypothesis was that application of the same reclamation method to all zones would fail to sustain >70% vegetative cover in each zone after four growing seasons. The method consisted of applying 11 t/ha lime and 27 or 54 t/ha compost before rototilling (top 15 cm) and mulching with oat straw containing viable seeds for a nurse crop. Lime‐only plots were included for comparison, and all amended plots were sown with a mine reclamation seed mix. Oats, sown species, and indigenous species dominated cover in the first, second, and fourth growing seasons, respectively. In the fourth year following reclamation, compost‐amended plots had >70% cover and improved soil properties in all three zones, providing evidence to reject our hypothesis. Vegetative restoration of AMD barrens did not require removal of highly acidic precipitates, since they could be transformed at low‐cost into a medium that supports indigenous plants.     

Electrocardiogram data mining based on frame classification by dynamic time warping matching

This paper presents an electrocardiogram (ECG) data mining scheme based on the ECG frame classification realised by a dynamic time warping (DTW) matching technique, which has been used successfully in speech recognition. We use the DTW to classify ECG frames because ECG and speech signals have similar non-stationary characteristics. The DTW mapping function is obtained by searching the frame from its end to start. A threshold is setup for DTW matching residual either to classify an ECG frame or to add a new class. Classification and establishment of a template set are carried out simultaneously. A frame is classified into a category with a minimal residual and satisfying a threshold requirement. A classification residual of 1.33% is achieved by the DTW for a 10-min ECG recording.     

Risk Assessment of the Abandoned Jukjeon Metal Mine in South Korea Following the Korean Guidelines

Toxic metal contamination in the vicinity of Korean abandoned metal mines has been reported. A risk assessment for these metals was performed for the inhabitants in the area of the abandoned Jukjeon metal mine. Soil, groundwater, and crop samples were collected around the mine. After pretreatment of these samples, metal concentrations were measured and then a risk assessment was performed using the Korean soil-contamination risk assessment guidelines. Phytoaccumulation of metals in crops was observed in soybeans (As and Zn), red peppers (Zn), sweet potatoes (As and Zn), and cabbage (Cu), which had higher metal concentrations than soils in the area. The metal intake rate was highest for inhalation of soil. Cancer risk was highest from ingestion of As-contaminated crops. The sum of carcinogenic risks was 6.29 × 10^–3. The non-carcinogenic risk was highest for ingestion of As-contaminated crops (8.17). Most of the risks were attributable to As, Pb, and Hg contamination, therefore these three metals must be considered as the principal metals toxic to human health in the sampled area. In particular, the inhalation of metal-contaminated soil should be considered for risk assessment along with ingestion of water and crops in abandoned mine areas.     

Identification and characterization of candidates involved in production of OMEGAs in microalgae: a gene mining and phylogenomic approach

Abstract

Optimizing the production of the high-value renewables such as OMEGAs through pathway engineering requires an in-depth understanding of the structure–function relationship of genes involved in the OMEGA biosynthetic pathways. In this preliminary study, our rationale is to identify and characterize the ～221 putative genes involved in production of OMEGAs using bioinformatic analysis from the Streptophyte (plants), Chlorophyte (green algae), Rhodophyta (red algae), and Bacillariophyta (diatoms) lineages based on their phylogenomic profiling, conserved motif/domain organization and physico-chemical properties. The MEME suite predicted 12 distinct protein domains, which are conserved among these putative genes. The phylogenomic analysis of the putative candidate genes [such as FAD2 (delta-12 desaturase); ECR (enoyl-CoA reductase); FAD2 (delta-12 desaturase); ACOT (acyl CoA thioesterase); ECH (enoyl-CoA hydratase); and ACAT (acetyl-CoA acyltransferase)] with similar domains and motif patterns were remarkably well conserved. Furthermore, the subcellular network prediction of OMEGA biosynthetic pathway genes revealed a unique interaction between the light-dependent chlorophyll biosynthesis and glycerol-3-phosphate dehydrogenase, which predicts a major cross-talk between the key essential pathways. Such bioinformatic analysis will provide insights in finding the key regulatory genes to optimize the productivity of OMEGAs in microalgal cell factories.     

Open access to tree genomes: the path to a better forest

An open-access culture and a well-developed comparative-genomics infrastructure must be developed in forest trees to derive the full potential of genome sequencing in this diverse group of plants that are the dominant species in much of the earth''s terrestrial ecosystems.     

PTM MarkerFinder,a software tool to detect and validate spectra from peptides carrying post‐translational modifications

Mass spectrometry (MS) analysis of peptides carrying post‐translational modifications is challenging due to the instability of some modifications during MS analysis. However, glycopeptides as well as acetylated, methylated and other modified peptides release specific fragment ions during CID (collision‐induced dissociation) and HCD (higher energy collisional dissociation) fragmentation. These fragment ions can be used to validate the presence of the PTM on the peptide. Here, we present PTM MarkerFinder, a software tool that takes advantage of such marker ions. PTM MarkerFinder screens the MS/MS spectra in the output of a database search (i.e., Mascot) for marker ions specific for selected PTMs. Moreover, it reports and annotates the HCD and the corresponding electron transfer dissociation (ETD) spectrum (when present), and summarizes information on the type, number, and ratios of marker ions found in the data set. In the present work, a sample containing enriched N‐acetylhexosamine (HexNAc) glycopeptides from yeast has been analyzed by liquid chromatography‐mass spectrometry on an LTQ Orbitrap Velos using both HCD and ETD fragmentation techniques. The identification result (Mascot .dat file) was submitted as input to PTM MarkerFinder and screened for HexNAc oxonium ions. The software output has been used for high‐throughput validation of the identification results.     

Evaluation of structural features in fungal cytochromes P450 predicted to rule catalytic diversification

Fungi belong to the large kingdom of lower eukaryotic organisms encompassing yeasts along with filamentous and dimorphic members. Microbial P450 enzymes have contributed to exploration of and adaptation to diverse ecological niches such as conversion of lipophilic compounds to more hydrophilic derivatives or degradation of a vast array of environmental toxicants. To better understand diversification of the catalytic behavior of fungal P450s, detailed insight into the molecular machinery steering oxidative attack on the distinctly structured endogenous and xenobiotic substrates is of preeminent interest. Based on a general, CYP102A1-related template the bulk of predicted substrate/inhibitor-binding determinants were shown to cluster near the distal heme face within the six known substrate recognition sites (SRSs) made up by the α-helical B′/F/G/I tetrad, the B′–C interhelical loop and strands of the β6-sheet, population density being highest in the structurally flexible SRS-1 and SRS-4 domains, showing a low degree of conservation. Reactivity toward ligands favorably coincides with the lipophilicity/hydrophilicity profile and bulkiness of critical amino acids acting as selective filters. Some decisive elements may also serve in maintenance of catalytic competence via their action as gatekeepers directing substrate access/positioning or stabilizers of the heme environment enabling dioxygen activation. Non-SRS residues seem to control spin state equilibria and attract redox partners by electrostatic forces. Of note, the inhibitory potency of azole-type fungicides is likely to arise from perturbation of the complex interplay of the mechanistic principles addressed above. Knowledge-supported exploitation of the topological data will be helpful in the manufacture of commodity/specialty chemicals as well as therapeutic agents. Also, engineered fungal P450s may be used to improve pollutant-specific bioremediation of contaminated soils.     

乳腺肿瘤组织标本库与数据库的建立及信息化管理

目的:随着基础和临床研究的深入开展,拥有完整基因信息的组织标本成为了肿瘤研究工作的基础.建立电子信息化管理的乳腺肿瘤组织标本库和数据库,为临床和科研收集、保存和管理标本资源.方法:标准化收集手术切除的乳腺肿瘤组织、正常腺体组织,以及患者血液标本,预处理后保存于-80℃冰箱中.每3个月从标本库中随机抽取5例标本,提取标本的总RNA,琼脂糖凝胶电泳验证总RNA质量;运用免疫组织化学法(Immunohistochemistry,IHC)检测标本中人表皮生长因子-2(Human epidermal growth factor receptor,HER-2 or c-erbB-2)和Ki67的表达,并与术后免疫组化结果进行比较.同时利用Epidata软件管理乳腺肿瘤组织标本库.结果:收集恶性肿瘤507例,良性肿瘤212例,血液标本9347份,并建立了一套高效的信息化管理系统.总RNA电泳结果显示28 S和18S亚基条带清晰明亮,5S条带很弱,表明标本中的RNA质量较高,无降解.免疫组化结果显示标本中的HER-2和Ki67的表达与术后免疫组化结果情况吻合,存储的标本质量良好.结论:建立的实验标本收集、储存流程是有效可行的,收集的标本质量是可靠的,管理方法是高效实用的,为乳腺肿瘤基础和临床研究提供质量可靠的标本来源,可为乳腺肿瘤研究提供良好的服务平台.     

Microsatellite markers uncover cryptic species of Odontotermes (Termitoidae: Termitidae) from Peninsular Malaysia

Termites from the genus Odontotermes are known to contain numerous species complexes that are difficult to tell apart morphologically or with mitochondrial DNA sequences. We developed markers for one such cryptic species complex, that is, Odontotermes srinakarinensis sp. nov. from Maxwell Hill Forest Reserve (Perak, Malaysia), and characterised them using a sample of 41 termite workers from three voucher samples from the same area. We then genotyped 150 termite individuals from 23 voucher samples/colonies of this species complex from several sites in Peninsular Malaysia. We analysed their population by constructing dendograms from the proportion of shared-alleles between individuals and genetic distances between colonies; additionally, we examined the Bayesian clustering pattern of their genotype data. All methods of analysis indicated that there were two distinct clusters within our data set. After the morphologies of specimens from each cluster were reexamined, we were able to separate the two species morphologically and found that a single diagnostic character found on the mandibles of its soldiers could be used to separate the two species quite accurately. The additional species in the clade was identified as Odontotermes denticulatus after it was matched to type specimens at the NHM London and Cambridge Museum of Zoology.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.