Comparative Genomics Platform and Phylogenetic Analysis of Fungal Laccases and Multi-Copper Oxidases

Abstract Laccases (EC 1.10.3.2), a group of multi-copper oxidases (MCOs), play multiple biological functions and widely exist in many species. Fungal laccases have been extensively studied for their industrial applications, however, there was no database specially focused on fungal laccases. To provide a comparative genomics platform for fungal laccases, we have developed a comparative genomics platform for laccases and MCOs (http://laccase.riceblast.snu.ac.kr/). Based on protein domain profiles of characterized sequences, 3,571 laccases were predicted from 690 genomes including 253 fungi. The number of putative laccases and their properties exhibited dynamic distribution across the taxonomy. A total of 505 laccases from 68 genomes were selected and subjected to phylogenetic analysis. As a result, four clades comprised of nine subclades were phylogenetically grouped by their putative functions and analyzed at the sequence level. Our work would provide a workbench for putative laccases mainly focused on the fungal kingdom as well as a new perspective in the identification and classification of putative laccases and MCOs.Peer reviewe

sTarPicker: A Method for Efficient Prediction of Bacterial sRNA Targets Based on a Two-Step Model for Hybridization

Bacterial sRNAs are a class of small regulatory RNAs involved in regulation of expression of a variety of genes. Most sRNAs act in trans via base-pairing with target mRNAs, leading to repression or activation of translation or mRNA degradation. To date, more than 1,000 sRNAs have been identified. However, direct targets have been identified for only approximately 50 of these sRNAs. Computational predictions can provide candidates for target validation, thereby increasing the speed of sRNA target identification. Although several methods have been developed, target prediction for bacterial sRNAs remains challenging.Here, we propose a novel method for sRNA target prediction, termed sTarPicker, which was based on a two-step model for hybridization between an sRNA and an mRNA target. This method first selects stable duplexes after screening all possible duplexes between the sRNA and the potential mRNA target. Next, hybridization between the sRNA and the target is extended to span the entire binding site. Finally, quantitative predictions are produced with an ensemble classifier generated using machine-learning methods. In calculations to determine the hybridization energies of seed regions and binding regions, both thermodynamic stability and site accessibility of the sRNAs and targets were considered. Comparisons with the existing methods showed that sTarPicker performed best in both performance of target prediction and accuracy of the predicted binding sites.sTarPicker can predict bacterial sRNA targets with higher efficiency and determine the exact locations of the interactions with a higher accuracy than competing programs. sTarPicker is available at http://ccb.bmi.ac.cn/starpicker/

Karst collapse risk zonation and evaluation in Wuhan, China based on analytic hierarchy process, logistic regression, and insar angular distortion approaches

The current study presents a detailed assessment of risk zones related to karst collapse in Wuhan by analytical hierarchy process (AHP) and logistic regression (LR) models. The results showed that the LR model was more accurate with an area under the receiver operating characteristic (ROC) curve of 0.911 compared to 0.812 derived from the AHP model. Both models performed well in identifying high-risk zones with only a 3% discrepancy in area. However, for the medium-and low-risk classes, although the spatial distribution of risk zoning results were similar between two approaches, the spatial extent of the risk areas varied between final models. The reliability of both methods were reduced significantly by excluding the InSAR-based ground subsidence map from the analysis, with the karst collapse presence falling into the high-risk zone being reduced by approximately 14%, and karst collapse absence falling into the karst area being increased by approximately 6.5% on the training samples. To evaluate the practicality of using only results from ground subsidence maps for the risk zonation, the results of AHP and LR are compared with a weighted angular distortion (WAD) method for karst risk zoning in Wuhan. We find that the areas with relatively large subsidence horizontal gradient values within the karst belts are generally spatially consistent with high-risk class areas identified by the AHP-and LR-based approaches. However, the WAD-based approach cannot be used alone as an ideal karst collapse risk assessment model as it does not include geological and natural factors into the risk zonation. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Toward Sustainability:Using Big Data to Explore Decisive Supply Chain Risk Factors Under Uncertainty

Rapid market changes aimed at sustainability have led to supply chain risks and uncertainties in the Taiwanese light-emitting diode industry. These risks and uncertainties can be captured by social media, quantitative and qualitative data (referred to herein as big data), but the industry has been unable to manage this information boom to respond to customer needs. These various types of data have their own characteristics that affect decision making about developing firm capabilities. This study aggregates the various data to undertake an extensive investigation of supply chain risks and uncertainties. Specifically, this study proposes using the fuzzy and grey Delphi methods to identify a set of reliable attributes and, based on these attributes, transforming big data to a manageable scale to consider their impacts. Subsequently, both the fuzzy and grey Decision Making Trial and Evaluation Laboratories applied to determine the causal relationships for supply chain risks and uncertainties. The results reveal that capacity and operations have greater influence than other supply chain attributes and that risks stemming from triggering events are difficult to diagnose and control. The implications, conclusions and findings are addressed

Genome-wide DNA methylation and transcriptomic profiles in the lifestyle strategies and asexual development of the forest fungal pathogen Heterobasidion parviporum

Heterobasidion parviporum is the most devastating fungal pathogen of conifer forests in Northern Europe. The fungus has dual life strategies, necrotrophy on living trees and saprotrophy on dead woods. DNA cytosine methylation is an important epigenetic modification in eukaryotic organisms. Our presumption is that the lifestyle transition and asexual development in H. parviporum could be driven by epigenetic effects. Involvements of DNA methylation in the regulation of aforementioned processes have never been studied thus far. RNA-seq identified lists of highly induced genes enriched in carbohydrate-active enzymes during necrotrophic interaction with host trees and saprotrophic sawdust growth. It also highlighted signaling- and transcription factor-related genes potentially associated with the transition of saprotrophic to necrotrophic lifestyle and groups of primary cellular activities throughout asexual development. Whole-genome bisulfite sequencing revealed that DNA methylation displayed pronounced preference in CpG dinucleotide context across the genome and mostly targeted transposable element (TE)-rich regions. TE methylation level demonstrated a strong negative correlation with TE expression, reinforcing the protective function of DNA methylation in fungal genome stability. Small groups of genes putatively subject to methylation transcriptional regulation in response to saprotrophic and necrotrophic growth in comparison with free-living mycelia were also explored. Our study reported on the first methylome map of a forest pathogen. Analysis of transcriptome and methylome variations associated with asexual development and different lifestyle strategies provided further understanding of basic biological processes in H. parviporum. More importantly, our work raised additional potential roles of DNA methylation in fungi apart from controlling the proliferation of TEs.Peer reviewe

Viral Infection Induces Expression of Novel Phased MicroRNAs from Conserved Cellular MicroRNA Precursors

RNA silencing, mediated by small RNAs including microRNAs (miRNAs) and small interfering RNAs (siRNAs), is a potent antiviral or antibacterial mechanism, besides regulating normal cellular gene expression critical for development and physiology. To gain insights into host small RNA metabolism under infections by different viruses, we used Solexa/Illumina deep sequencing to characterize the small RNA profiles of rice plants infected by two distinct viruses, Rice dwarf virus (RDV, dsRNA virus) and Rice stripe virus (RSV, a negative sense and ambisense RNA virus), respectively, as compared with those from non-infected plants. Our analyses showed that RSV infection enhanced the accumulation of some rice miRNA*s, but not their corresponding miRNAs, as well as accumulation of phased siRNAs from a particular precursor. Furthermore, RSV infection also induced the expression of novel miRNAs in a phased pattern from several conserved miRNA precursors. In comparison, no such changes in host small RNA expression was observed in RDV-infected rice plants. Significantly RSV infection elevated the expression levels of selective OsDCLs and OsAGOs, whereas RDV infection only affected the expression of certain OsRDRs. Our results provide a comparative analysis, via deep sequencing, of changes in the small RNA profiles and in the genes of RNA silencing machinery induced by different viruses in a natural and economically important crop host plant. They uncover new mechanisms and complexity of virus-host interactions that may have important implications for further studies on the evolution of cellular small RNA biogenesis that impact pathogen infection, pathogenesis, as well as organismal development

The effect of acupuncture at the Taiyang acupoint on visual function and EEG microstates in myopia

ObjectiveAcupuncture has certain effects to improve myopia visual function, but its neural mechanism is unclear. In this study, we acupunctured at the right Taiyang acupoint of myopic patients to analyze the effects of acupuncture on visual function and electroencephalographic activity and to investigate the correlation between improvements in visual function and changes in the brain.MethodsIn this study, a total of 18 myopic patients were recruited. The contrast sensitivity (CS) of the subjects was examined before and after acupuncture, and electroencephalography (EEG) data of the entire acupuncture process were recorded.ResultsThe study found that compared with before acupuncture, the CS of both eyes in myopic patients at each spatial frequency was increased after acupuncture; compared with the resting state, the contribution of microstate C was decreased during the post-acupuncture state, and the transition probability between microstate A and microstate C was reduced; in addition, the contribution of microstate C was negatively correlated with CS at both 12 and 18 cpd.ConclusionThe contrast sensitivity of myopic patients was improved after acupuncture at the Taiyang acupoint (20 min), which may be related to microstate C

Clinical Implementation of a 6D Treatment Chair for Fixed Ion Beam Lines

PurposeTo verify the practicality and safety of a treatment chair with six degrees of freedom (6DTC) through demonstrating the efficacy of the workflow in clinical settings and analyzing the obtained technical data, including intra-fraction patient movement during the use of the 6DTC.Materials and MethodsA clinical study was designed and conducted to test the clinical treatment workflow and the safety of the 6DTC. Based on the demonstrated dosimetric advantages, fifteen patients with head and neck tumors were selected and treated with the 6DTC. The positional error at the first beam position (PE-B1) and the second beam position (PE-B2) were analyzed and compared with the results from daily quality assurance (QA) procedures of the 6DTC and imaging system performed each day before clinical treatment. The intra-fraction patient movement was derived from the total patient alignment positional error and the QA data based on a Gaussian distribution formulism.ResultsThe QA results showed sub-millimeter mechanical accuracy of the 6DTC over the course of the clinical study. For 150 patient treatment fractions, the mean deviations between PE-B1 and PE-B2 were 0.13mm (SD 0.88mm), 0.25mm (SD 1.17mm), -0.57mm (SD 0.85mm), 0.02° (SD 0.35°), 0.00° (SD 0.37°), and -0.02° (SD 0.37°) in the x, y, z (translational), and u, v, w (rotational) directions, respectively. The calculated intra-fraction patient movement was -0.08mm (SD 0.56mm), 0.71mm (SD 1.12mm), -0.52mm (SD 0.84mm), 0.10° (SD 0.32°), 0.09° (SD 0.36°), and -0.04° (SD 0.36°) in the x, y, z, u, v, w directions, respectively.ConclusionsThe performance stability of the 6DTC was satisfactory. The position accuracy and intra-fraction patient movement in an upright posture with the 6DTC were verified and found adequate for clinical implementation