Morphology and Phylogeny of the Soil Ciliate Metopus yantaiensis n. sp. (Ciliophora,Metopida), with Identification of the Intracellular Bacteria

The morphology and infraciliature of a new ciliate, Metopus yantaiensis n. sp., discovered in coastal soil of northern China, were investigated. It is distinguished from its congeners by a combination of the following features: nuclear apparatus situated in the preoral dome; 18–21 somatic ciliary rows, of which three extend onto the preoral dome (dome kineties); three to five distinctly elongated caudal cilia, and 21–29 adoral polykinetids. The 18S rRNA genes of this new species and two congeners, Metopus contortus and Metopus hasei, were sequenced and phylogenetically analyzed. The new species is more closely related to M. hasei and the clevelandellids than to other congeners; both the genus Metopus and the order Metopida are not monophyletic. In addition, the digestion‐resistant bacteria in the cytoplasm of M. yantaiensis were identified, using a 16S rRNA gene clone library, sequencing, and fluorescence in situ hybridization. The detected intracellular bacteria are affiliated with Sphingomonadales, Rhizobiales, Rickettsiales (Alphaproteobacteria), Pseudomonas (Gammaproteobacteria), Rhodocyclales (Betaproteobacteria), Clostridiales (Firmicutes), and Flavobacteriales (Bacteroidetes).     

Comparative metabolomics reveals the mechanism of avermectin production enhancement by <Emphasis Type="Italic">S</Emphasis>-adenosylmethionine

It was found that S-adenosylmethionine (SAM) could effectively improve avermectin titer with 30–60 μg/mL addition to FH medium. To clearly elucidate the mechanism of SAM on intracellular metabolites of Streptomyces avermitilis, a GC–MS-based comparative metabolomics approach was carried out. First, 230 intracellular metabolites were identified and 14 of them remarkably influenced avermectin biosynthesis were discriminative biomarkers between non-SAM groups and SAM-treated groups by principal components analysis (PCA) and partial least squares (PLS). Based on further key metabolic pathway analyses, these biomarkers, such as glucose, oxaloacetic acid, fatty acids (in soybean oil), threonine, valine, and leucine, were identified as potentially beneficial precursors and added in medium. Compared with single-precursor feeding, the combined feeding of the precursors and SAM markedly increased the avermectin titer. The co-feeding approach not only directly verified our hypothesis on the mechanism of SAM by comparative metabolomics, but also provided a novel strategy to increase avermectin production.     

A genetic analysis of the quality of northern-style Chinese steamed bread

Dissecting the genetic basis for the traits of northern-style Chinese steamed bread (NCSB) is of great significance for wheat quality breeding. Quantitative trait loci (QTLs) for the processing quality of NCSB were studied using a recombinant inbred line (RIL) consisting of 173 lines derived from a “Shannong01–35 × Gaocheng9411” cross. Twenty-four putative additive QTLs were detected on chromosomes 1A, 1B, 1D, 3A, 3B, 4A, 4B, 5B, 6B, and 7B. Of these QTLs, QTex1A.1-27, QHei5B.5-488, and QGum4B.4-17 had the highest contribution and accounted for 9.33, 10.9, and 12.0% of the phenotypic variations, respectively. Several co-located QTLs with additive effects were detected on chromosomes 1A, 1D, 4B, and 5B. Two clusters (RFL_CONTIG2160_524-WSNP_CAP12_C2438_1180601 and EX_C101685_705-RAC875_C27536_611) for height, total score, and texture and for chewiness, gumminess, and hardness were detected on chromosomes 1A and 4B, respectively. Two QTLs for chewiness and hardness (QCh1D-4, QHa1D-4) with additive effects were detected; these alleles could be good targets for improving the processing quality of steamed bread from common wheat (Triticum aestivum L.). In addition, QTLs for wheat flour quality and the associated correlations with NCSB were simultaneously analyzed. Negative correlations were detected between chewiness and the wet/dry gluten content (WGC/DGC) or protein content. Two QTLs (QCh4B.4-17 and QPr4B.4-17) and three QTLs (QCh4B.4-13, QWG4B.4-13, and QDG4B.4-13) clustered in the same chromosomal region. The detected QTL clusters should be further investigated during wheat breeding and could be used by breeders to improve wheat quality and especially the processing quality of NCSB.     

Molecular mapping of quantitative trait loci for three kernel-related traits in maize using a double haploid population

Kernel size and kernel weight are important factors possibly involved in the determination of grain yield in maize, so identifying the genetic basis of kernel-related traits provides insights into the breeding of high-yield maize varieties. Kernel length (KL), kernel width (KW) and hundred kernel weight (HKW) were evaluated in three various planting conditions for the 240 field-grown double haploid (DH) lines derived from the single-cross hybrid Xianyu335. Variations in KL, KW and HKW were observed among DH lines, and all three traits showed a broad sense heritability of 76%. A total of 964 single nucleotide polymorphisms (SNPs) from the MaizeSNP3072 chip was utilised to create a high-density genetic map of 1546.4 cM and to identify quantitative trait loci (QTLs). Using composite interval mapping, a total of five, seven and five QTLs have been mapped for KL, KW and HKW, respectively. qkl1-2 and qkl4-1 explained 17.8% and 14.2% of the phenotypic variation in KL, respectively, and the other three QTLs contributed 3.2–4.0%. The phenotypic variation explained (PVE) of seven QTLs responsible for KW ranged from 3.3 to 9.5%. Three QTLs for HKW, qhkw1, qhkw5 and qhkw10 each explained more than 10% of the phenotypic variation, and qhkw4 and qhkw9 accounted for 3.0% and 6.0%, respectively. Due to their detection in multiple planting environments, the loci mapped here appear to be potential targets for the improvement of maize grain yield.     

Simplified Aeroelastic Model for Fluid Structure Interaction between Microcantilever Sensors and Fluid Surroundings

Fluid-structural coupling occurs when microcantilever sensors vibrate in a fluid. Due to the complexity of the mechanical characteristics of microcantilevers and lack of high-precision microscopic mechanical testing instruments, effective methods for studying the fluid-structural coupling of microcantilevers are lacking, especially for non-rectangular microcantilevers. Here, we report fluid-structure interactions (FSI) of the cable-membrane structure via a macroscopic study. The simplified aeroelastic model was introduced into the microscopic field to establish a fluid-structure coupling vibration model for microcantilever sensors. We used the finite element method to solve the coupled FSI system. Based on the simplified aeroelastic model, simulation analysis of the effects of the air environment on the vibration of the commonly used rectangular microcantilever was also performed. The obtained results are consistent with the literature. The proposed model can also be applied to the auxiliary design of rectangular and non-rectangular sensors used in fluid environments.     

Multi-actor multi-criteria sustainability assessment framework for energy and industrial systems in life cycle perspective under uncertainties. Part 1: weighting method

Purpose

Life cycle sustainability assessment is meaningful for the decision-makers/stakeholders to select the most sustainable option among multiple alternatives; however, there are usually various severe uncertainty problems in sustainability-oriented decision-making, i.e., the vagueness and ambiguity that existed in human judgments and the lack of information. This study aims at developing a novel life cycle multi-criteria sustainability assessment method for helping the decision-makers/stakeholders to determine the sustainability level of the industrial and energy systems. In part 1, an improved interval analytic hierarchy process (AHP) which allows multiple decision-makers/stakeholders to participate in the decision-making was developed to determine the weights of the criteria which were used in life cycle sustainability assessment.

Methods

It is usually difficult for the decision-makers/stakeholders to use the numbers from 1 to 9 and their reciprocals for determining the comparison matrix when using the traditional AHP method for weight calculation, because human judgments usually involve various uncertainties. In order to the overcome this weak point of the traditional AHP, an improved AHP, so-called interval AHP, in which, multiple decision-makers/stakeholders are allowed to participate in the decision-making and allowed to use interval numbers instead of crisp numbers to establish the comparison matrix for determining the weights of the criteria for life cycle sustainability assessment, has been developed.

Results and discussion

The proposed method was used to determine the weights of the four aspects for life cycle sustainability assessment including economic, safety, social, and environmental aspects. Five representative stakeholders were invited to participate in the decision-making. After Monte Carlo simulation, the final weights of the four aspects have been determined with the proposed interval AHP.

Conclusions and perspectives

An interval AHP method was developed for determining the weights of the criteria for life cycle sustainability assessment; the decision-makers are allowed to use interval numbers to establish the comparison matrix for weight calculation. The weighting coefficients determined by Monte Carlo method can accurately reflect the preferences and willingness of multi-actor comparing with the traditional AHP method. This paper merely presents a novel method to calculate the weights of the criteria for life cycle sustainability assessment, but the method for determining the sustainability performance has been presented in part 2.