MetaSquare: an integrated metadatabase of 16S rRNA gene amplicon for microbiome taxonomic classification.

MOTIVATION: Taxonomic classification of 16S ribosomal RNA gene amplicon is an efficient and economic approach in microbiome analysis. 16S rRNA sequence databases like SILVA, RDP, EzBioCloud and HOMD used in downstream bioinformatic pipelines have limitations on either the sequence redundancy or the delay on new sequence recruitment. To improve the 16S rRNA gene-based taxonomic classification, we merged these widely used databases and a collection of novel sequences systemically into an integrated resource. RESULTS: MetaSquare version 1.0 is an integrated 16S rRNA sequence database. It is composed of more than 6 million sequences and improves taxonomic classification resolution on both long-read and short-read methods. AVAILABILITY AND IMPLEMENTATION: Accessible at https://hub.docker.com/r/lsbnb/metasquare_db and https://github.com/lsbnb/MetaSquare. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Intelligent De Novo Design of Novel Antimicrobial Peptides against Antibiotic-Resistant Bacteria Strains.

Because of the growing number of clinical antibiotic resistance cases in recent years, novel antimicrobial peptides (AMPs) may be ideal for next-generation antibiotics. This study trained a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) based on known AMPs to generate novel AMP candidates. The quality of the GAN-designed peptides was evaluated in silico, and eight of them, named GAN-pep 1-8, were selected by an AMP Artificial Intelligence (AI) classifier and synthesized for further experiments. Disc diffusion testing and minimum inhibitory concentration (MIC) determinations were used to identify the antibacterial effects of the synthesized GAN-designed peptides. Seven of the eight synthesized GAN-designed peptides displayed antibacterial activity. Additionally, GAN-pep 3 and GAN-pep 8 presented a broad spectrum of antibacterial effects and were effective against antibiotic-resistant bacteria strains, such as methicillin-resistant Staphylococcus aureus and carbapenem-resistant Pseudomonas aeruginosa. GAN-pep 3, the most promising GAN-designed peptide candidate, had low MICs against all the tested bacteria. In brief, our approach shows an efficient way to discover AMPs effective against general and antibiotic-resistant bacteria strains. In addition, such a strategy also allows other novel functional peptides to be quickly designed, identified, and synthesized for validation on the wet bench.

EpiMOLAS: an intuitive web-based framework for genome-wide DNA methylation analysis.

BACKGROUND: DNA methylation is a crucial epigenomic mechanism in various biological processes. Using whole-genome bisulfite sequencing (WGBS) technology, methylated cytosine sites can be revealed at the single nucleotide level. However, the WGBS data analysis process is usually complicated and challenging. RESULTS: To alleviate the associated difficulties, we integrated the WGBS data processing steps and downstream analysis into a two-phase approach. First, we set up the required tools in Galaxy and developed workflows to calculate the methylation level from raw WGBS data and generate a methylation status summary, the mtable. This computation environment is wrapped into the Docker container image DocMethyl, which allows users to rapidly deploy an executable environment without tedious software installation and library dependency problems. Next, the mtable files were uploaded to the web server EpiMOLAS_web to link with the gene annotation databases that enable rapid data retrieval and analyses. CONCLUSION: To our knowledge, the EpiMOLAS framework, consisting of DocMethyl and EpiMOLAS_web, is the first approach to include containerization technology and a web-based system for WGBS data analysis from raw data processing to downstream analysis. EpiMOLAS will help users cope with their WGBS data and also conduct reproducible analyses of publicly available data, thereby gaining insights into the mechanisms underlying complex biological phenomenon. The Galaxy Docker image DocMethyl is available at https://hub.docker.com/r/lsbnb/docmethyl/. EpiMOLAS_web is publicly accessible at http://symbiosis.iis.sinica.edu.tw/epimolas/.

SQUAT: a Sequencing Quality Assessment Tool for data quality assessments of genome assemblies.

BACKGROUND: With the rapid increase in genome sequencing projects for non-model organisms, numerous genome assemblies are currently in progress or available as drafts, but not made available as satisfactory, usable genomes. Data quality assessment of genome assemblies is gaining importance not only for people who perform the assembly/re-assembly processes, but also for those who attempt to use assemblies as maps in downstream analyses. Recent studies of the quality control, quality evaluation/ assessment of genome assemblies have focused on either quality control of reads before assemblies or evaluation of the assemblies with respect to their contiguity and correctness. However, correctness assessment depends on a reference and is not applicable for de novo assembly projects. Hence, development of methods providing both post-assembly and pre-assembly quality assessment reports for examining the quality/correctness of de novo assemblies and the input reads is worth studying. RESULTS: We present SQUAT, an efficient tool for both pre-assembly and post-assembly quality assessment of de novo genome assemblies. The pre-assembly module of SQUAT computes quality statistics of reads and presents the analysis in a well-designed interface to visualize the distribution of high- and poor-quality reads in a portable HTML report. The post-assembly module of SQUAT provides read mapping analytics in an HTML format. We categorized reads into several groups including uniquely mapped reads, multiply mapped, unmapped reads; for uniquely mapped reads, we further categorized them into perfectly matched, with substitutions, containing clips, and the others. We carefully defined the poorly mapped (PM) reads into several groups to prevent the underestimation of unmapped reads; indeed, a high PM% would be a sign of a poor assembly that requires researchers' attention for further examination or improvements before using the assembly. Finally, we evaluate SQUAT with six datasets, including the genome assemblies for eel, worm, mushroom, and three bacteria. The results show that SQUAT reports provide useful information with details for assessing the quality of assemblies and reads. AVAILABILITY: The SQUAT software with links to both its docker image and the on-line manual is freely available at https://github.com/luke831215/SQUAT .

A gene profiling deconvolution approach to estimating immune cell composition from complex tissues.

BACKGROUND: A new emerged cancer treatment utilizes intrinsic immune surveillance mechanism that is silenced by those malicious cells. Hence, studies of tumor infiltrating lymphocyte populations (TILs) are key to the success of advanced treatments. In addition to laboratory methods such as immunohistochemistry and flow cytometry, in silico gene expression deconvolution methods are available for analyses of relative proportions of immune cell types. RESULTS: Herein, we used microarray data from the public domain to profile gene expression pattern of twenty-two immune cell types. Initially, outliers were detected based on the consistency of gene profiling clustering results and the original cell phenotype notation. Subsequently, we filtered out genes that are expressed in non-hematopoietic normal tissues and cancer cells. For every pair of immune cell types, we ran t-tests for each gene, and defined differentially expressed genes (DEGs) from this comparison. Equal numbers of DEGs were then collected as candidate lists and numbers of conditions and minimal values for building signature matrixes were calculated. Finally, we used v -Support Vector Regression to construct a deconvolution model. The performance of our system was finally evaluated using blood biopsies from 20 adults, in which 9 immune cell types were identified using flow cytometry. The present computations performed better than current state-of-the-art deconvolution methods. CONCLUSIONS: Finally, we implemented the proposed method into R and tested extensibility and usability on Windows, MacOS, and Linux operating systems. The method, MySort, is wrapped as the Galaxy platform pluggable tool and usage details are available at https://testtoolshed.g2.bx.psu.edu/view/moneycat/mysort/e3afe097e80a .

TEA: the epigenome platform for Arabidopsis methylome study.

BACKGROUND: Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task. RESULTS: We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits. CONCLUSIONS: TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data. TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw .

Characterization of FN1-FGFR1 and novel FN1-FGF1 fusion genes in a large series of phosphaturic mesenchymal tumors.

Phosphaturic mesenchymal tumors typically cause paraneoplastic osteomalacia, chiefly as a result of FGF23 secretion. In a prior study, we identified FN1-FGFR1 fusion in 9 of 15 phosphaturic mesenchymal tumors. In this study, a total of 66 phosphaturic mesenchymal tumors and 7 tumors resembling phosphaturic mesenchymal tumor but without known phosphaturia were studied. A novel FN1-FGF1 fusion gene was identified in two cases without FN1-FGFR1 fusion by RNA sequencing and cross-validated with direct sequencing and western blot. Fluorescence in situ hybridization analyses revealed FN1-FGFR1 fusion in 16 of 39 (41%) phosphaturic mesenchymal tumors and identified an additional case with FN1-FGF1 fusion. The two fusion genes were mutually exclusive. Combined with previous data, the overall prevalence of FN1-FGFR1 and FN1-FGF1 fusions was 42% (21/50) and 6% (3/50), respectively. FGFR1 immunohistochemistry was positive in 82% (45/55) of phosphaturic mesenchymal tumors regardless of fusion status. By contrast, 121 cases of potential morphologic mimics (belonging to 13 tumor types) rarely expressed FGFR1, the main exceptions being solitary fibrous tumors (positive in 40%), chondroblastomas (40%), and giant cell tumors of bone (38%), suggesting a possible role for FGFR1 immunohistochemistry in the diagnosis of phosphaturic mesenchymal tumor. With the exception of one case reported in our prior study, none of the remaining tumors resembling phosphaturic mesenchymal tumor had either fusion type or expressed significant FGFR1. Our findings provide insight into possible mechanisms underlying the pathogenesis of phosphaturic mesenchymal tumor and imply a central role of the FGF1-FGFR1 signaling pathway. The novel FN1-FGF1 protein is expected to be secreted and serves as a ligand that binds and activates FGFR1 to achieve an autocrine loop. Further study is required to determine the functions of these fusion proteins.

Dual-compartmental transcriptomic + proteomic analysis of a marine endosymbiosis exposed to environmental change.

As significant anthropogenic pressures are putting undue stress on the world's oceans, there has been a concerted effort to understand how marine organisms respond to environmental change. Transcriptomic approaches, in particular, have been readily employed to document the mRNA-level response of a plethora of marine invertebrates exposed to an array of simulated stress scenarios, with the tacit and untested assumption being that the respective proteins show a corresponding trend. To better understand the degree of congruency between mRNA and protein expression in an endosymbiotic marine invertebrate, mRNAs and proteins were sequenced from the same samples of the common, Indo-Pacific coral Seriatopora hystrix exposed to stable or upwelling-simulating conditions for 1 week. Of the 167 proteins downregulated at variable temperature, only two were associated with mRNAs that were also differentially expressed between treatments. Of the 378 differentially expressed genes, none were associated with a differentially expressed protein. Collectively, these results highlight the inherent risk of inferring cellular behaviour based on mRNA expression data alone and challenge the current, mRNA-focused approach taken by most marine and many molecular biologists.

Identification of a novel FN1-FGFR1 genetic fusion as a frequent event in phosphaturic mesenchymal tumour.

Phosphaturic mesenchymal tumours (PMTs) are uncommon soft tissue and bone tumours that typically cause hypophosphataemia and tumour-induced osteomalacia (TIO) through secretion of phosphatonins including fibroblast growth factor 23 (FGF23). PMT has recently been accepted by the World Health Organization as a formal tumour entity. The genetic basis and oncogenic pathways underlying its tumourigenesis remain obscure. In this study, we identified a novel FN1-FGFR1 fusion gene in three out of four PMTs by next-generation RNA sequencing. The fusion transcripts and proteins were subsequently confirmed with RT-PCR and western blotting. Fluorescence in situ hybridization analysis showed six cases with FN1-FGFR1 fusion out of an additional 11 PMTs. Overall, nine out of 15 PMTs (60%) harboured this fusion. The FN1 gene possibly provides its constitutively active promoter and the encoded protein's oligomerization domains to overexpress and facilitate the activation of the FGFR1 kinase domain. Interestingly, unlike the prototypical leukaemia-inducing FGFR1 fusion genes, which are ligand-independent, the FN1-FGFR1 chimeric protein was predicted to preserve its ligand-binding domains, suggesting an advantage of the presence of its ligands (such as FGF23 secreted at high levels by the tumour) in the activation of the chimeric receptor tyrosine kinase, thus effecting an autocrine or a paracrine mechanism of tumourigenesis.

Precise genotyping and recombination detection of Enterovirus.

Enteroviruses (EV) with different genotypes cause diverse infectious diseases in humans and mammals. A correct EV typing result is crucial for effective medical treatment and disease control; however, the emergence of novel viral strains has impaired the performance of available diagnostic tools. Here, we present a web-based tool, named EVIDENCE (EnteroVirus In DEep conception, http://symbiont.iis.sinica.edu.tw/evidence), for EV genotyping and recombination detection. We introduce the idea of using mixed-ranking scores to evaluate the fitness of prototypes based on relatedness and on the genome regions of interest. Using phylogenetic methods, the most possible genotype is determined based on the closest neighbor among the selected references. To detect possible recombination events, EVIDENCE calculates the sequence distance and phylogenetic relationship among sequences of all sliding windows scanning over the whole genome. Detected recombination events are plotted in an interactive figure for viewing of fine details. In addition, all EV sequences available in GenBank were collected and revised using the latest classification and nomenclature of EV in EVIDENCE. These sequences are built into the database and are retrieved in an indexed catalog, or can be searched for by keywords or by sequence similarity. EVIDENCE is the first web-based tool containing pipelines for genotyping and recombination detection, with updated, built-in, and complete reference sequences to improve sensitivity and specificity. The use of EVIDENCE can accelerate genotype identification, aiding clinical diagnosis and enhancing our understanding of EV evolution.

The effect of red light and far-red light conditions on secondary metabolism in agarwood.

BACKGROUND: Agarwood, a heartwood derived from Aquilaria trees, is a valuable commodity that has seen prevalent use among many cultures. In particular, it is widely used in herbal medicine and many compounds in agarwood are known to exhibit medicinal properties. Although there exists much research into medicinal herbs and extraction of high value compounds, few have focused on increasing the quantity of target compounds through stimulation of its related pathways in this species. RESULTS: In this study, we observed that cucurbitacin yield can be increased through the use of different light conditions to stimulate related pathways and conducted three types of high-throughput sequencing experiments in order to study the effect of light conditions on secondary metabolism in agarwood. We constructed genome-wide profiles of RNA expression, small RNA, and DNA methylation under red light and far-red light conditions. With these profiles, we identified a set of small RNA which potentially regulates gene expression via the RNA-directed DNA methylation pathway. CONCLUSIONS: We demonstrate that light conditions can be used to stimulate pathways related to secondary metabolism, increasing the yield of cucurbitacins. The genome-wide expression and methylation profiles from our study provide insight into the effect of light on gene expression for secondary metabolism in agarwood and provide compelling new candidates towards the study of functional secondary metabolic components.

Compartment-specific transcriptomics in a reef-building coral exposed to elevated temperatures.

Although rising ocean temperatures threaten scleractinian corals and the reefs they construct, certain reef corals can acclimate to elevated temperatures to which they are rarely exposed in situ. Specimens of the model Indo-Pacific reef coral Pocillopora damicornis collected from upwelling reefs of Southern Taiwan were previously found to have survived a 36-week exposure to 30°C, a temperature they encounter infrequently and one that can elicit the breakdown of the coral-dinoflagellate (genus Symbiodinium) endosymbiosis in many corals of the Pacific Ocean. To gain insight into the subcellular pathways utilized by both the coral hosts and their mutualistic Symbiodinium populations to acclimate to this temperature, mRNAs from both control (27°C) and high (30°C)-temperature samples were sequenced on an Illumina platform and assembled into a 236 435-contig transcriptome. These P. damicornis specimens were found to be ~60% anthozoan and 40% microbe (Symbiodinium, other eukaryotic microbes, and bacteria), from an mRNA-perspective. Furthermore, a significantly higher proportion of genes from the Symbiodinium compartment were differentially expressed after two weeks of exposure. Specifically, at elevated temperatures, Symbiodinium populations residing within the coral gastrodermal tissues were more likely to up-regulate the expression of genes encoding proteins involved in metabolism than their coral hosts. Collectively, these transcriptome-scale data suggest that the two members of this endosymbiosis have distinct strategies for acclimating to elevated temperatures that are expected to characterize many of Earth's coral reefs in the coming decades.

Antibacterial effects on dry-fast and traditional water-based surgical scrubbing methods: a two-time points experimental study.

This study determined the in-use effects of dry-fast and traditional hand-washing surgical scrubs among operating room staff members. This is a static group comparison study with purposive sampling. A total of 156 staff members were recruited in an operating room in a medical center located in southern Taiwan. The participants were divided into traditional and dry-fast hand-washing groups. Microbial counts were measured right after the two groups finished surgical scrubbing and at the completion of surgery. The results showed that the use of dry-fast antisepsis has a better persistent effect (P = 0.001), more nurses chose dry-fast antisepsis than surgeons (P = 0.012), and the post-operation number of colonies for nurses was significantly higher than that for surgeons (P = 0.003). Operating room nurses are long-term and frequent users of antibacterial agents, and their requirement of skin protection is higher. The dry-fast technique has the advantage of being less irritating to the skin and less time consuming; therefore, brush-free and dry-fast antisepsis is recommended.

Decoding the genome of bloodsucking midge Forcipomyia taiwana (Diptera: Ceratopogonidae): Insights into odorant receptor expansion.

Biting midges, notably those within the Ceratopogonidae family, have long been recognized for their epidemiological significance, both as nuisances and vectors for disease transmission in vertebrates. Despite their impact, genomic insights into these insects, particularly beyond the Culicoides genus, remain limited. In this study, we assembled the Forcipomyia taiwana (Shiraki) genome, comprising 113 scaffolds covering 130.4 Mbps-with the longest scaffold reaching 7.6 Mbps and an N50 value of 2.6 Mbps-marking a pivotal advancement in understanding the genetic architecture of ceratopogonid biting midges. Phylogenomic analyses reveal a shared ancestry between F. taiwana and Culicoides sonorensis Wirth & Jones, dating back approximately 124 million years, and highlight a dynamic history of gene family expansions and contractions within the Ceratopogonidae family. Notably, a substantial expansion of the odorant receptor (OR) gene family was observed, which is crucial for the chemosensory capabilities that govern biting midges' interactions with their environment, including host seeking and oviposition behaviors. The distribution of OR genes across the F. taiwana genome displays notable clusters on scaffolds, indicating localized tandem gene duplication events. Additionally, several collinear regions were identified, hinting at segmental duplications, inversions, and translocations, contributing to the olfactory system's evolutionary complexity. Among the 156 ORs identified in F. taiwana, 134 are biting midge-specific ORs, distributed across three distinct clades, each exhibiting unique motif features that distinguish them from the others. Through weighted gene co-expression network analysis, we correlated distinct gene modules with sex and reproductive status, laying the groundwork for future investigations into the interplay between gene expression and adaptive behaviors in F. taiwana. In conclusion, our study not only highlights the unique olfactory repertoire of ceratopogonid biting midges but also sets the stage for future studies into the genetic underpinnings of their unique biological traits and ecological strategies.

Interplay of RsbM and RsbK controls the σ(B) activity of Bacillus cereus.

The alternative transcription factor σ(B) of Bacillus cereus controls the expression of a number of genes that respond to environmental stress. Four proteins encoded in the sigB gene cluster, including RsbV, RsbW, RsbY (RsbU) and RsbK, are known to be essential in the σ(B)-mediated stress response. In the context of stress, the hybrid sensor kinase RsbK is thought to phosphorylate the response regulator RsbY, a PP2C serine phosphatase, leading to the dephosphorylation of the phosphorylated RsbV. The unphosphorylated RsbV then sequesters the σ(B) antagonist, RsbW, ultimately liberating σ(B). The gene arrangement reveals an open reading frame, bc1007, flanked immediately downstream by rsbK within the sigB gene cluster. However, little is known about the function of bc1007. In this study, the deletion of bc1007 resulted in high constitutive σ(B) expression independent of environmental stimuli, indicating that bc1007 plays a role in σ(B) regulation. A bacterial two-hybrid analysis demonstrated that BC1007 interacts directly with RsbK, and autoradiographic studies revealed a specific C(14)-methyl transfer from the radiolabelled S-adenosylmethionine to RsbK when RsbK was incubated with purified BC1007. Our data suggest that BC1007 (RsbM) negatively regulates σ(B) activity by methylating RsbK. Additionally, mutagenic substitution was employed to modify 12 predicted methylation residues in RsbK. Certain RsbK mutants were able to rescue σ(B) activation in a rsbK-deleted bacterial strain, but RsbK(E439A) failed to activate σ(B), and RsbK(E446A) only moderately induced σ(B). These results suggest that Glu439 is the preferred methylation site and that Glu446 is potentially a minor methylation site. Gene arrays of the rsbK orthologues and the neighbouring rsbM orthologues are found in a wide range of bacteria. The regulation of sigma factors through metylation of RsbK-like sensor kinases appears to be widespread in the microbial world.

Elegancy: Digitizing the wisdom from laboratories to the cloud with free no-code platform.

One of the top priorities in any laboratory is archiving experimental data in the most secure, efficient, and errorless way. It is especially important to those in chemical and biological research, for it is more likely to damage experiment records. In addition, the transmission of experiment results from paper to electronic devices is time-consuming and redundant. Therefore, we introduce an open-source no-code electronic laboratory notebook, Elegancy, a cloud-based/standalone web service distributed as a Docker image. Elegancy fits all laboratories but is specially equipped with several features benefitting biochemical laboratories. It can be accessed via various web browsers, allowing researchers to upload photos or audio recordings directly from their mobile devices. Elegancy also contains a meeting arrangement module, audit/revision control, and laboratory supply management system. We believe Elegancy could help the scientific research community gather evidence, share information, reorganize knowledge, and digitize laboratory works with greater ease and security.

Peptide-Based Drug Predictions for Cancer Therapy Using Deep Learning.

Anticancer peptides (ACPs) are selective and toxic to cancer cells as new anticancer drugs. Identifying new ACPs is time-consuming and expensive to evaluate all candidates' anticancer abilities. To reduce the cost of ACP drug development, we collected the most updated ACP data to train a convolutional neural network (CNN) with a peptide sequence encoding method for initial in silico evaluation. Here we introduced PC6, a novel protein-encoding method, to convert a peptide sequence into a computational matrix, representing six physicochemical properties of each amino acid. By integrating data, encoding method, and deep learning model, we developed AI4ACP, a user-friendly web-based ACP distinguisher that can predict the anticancer property of query peptides and promote the discovery of peptides with anticancer activity. The experimental results demonstrate that AI4ACP in CNN, trained using the new ACP collection, outperforms the existing ACP predictors. The 5-fold cross-validation of AI4ACP with the new collection also showed that the model could perform at a stable level on high accuracy around 0.89 without overfitting. Using AI4ACP, users can easily accomplish an early-stage evaluation of unknown peptides and select potential candidates to test their anticancer activities quickly.

AI4AVP: an antiviral peptides predictor in deep learning approach with generative adversarial network data augmentation.

Motivation: Antiviral peptides (AVPs) from various sources suggest the possibility of developing peptide drugs for treating viral diseases. Because of the increasing number of identified AVPs and the advances in deep learning theory, it is reasonable to experiment with peptide drug design using in silico methods. Results: We collected the most up-to-date AVPs and used deep learning to construct a sequence-based binary classifier. A generative adversarial network was employed to augment the number of AVPs in the positive training dataset and enable our deep learning convolutional neural network (CNN) model to learn from the negative dataset. Our classifier outperformed other state-of-the-art classifiers when using the testing dataset. We have placed the trained classifiers on a user-friendly web server, AI4AVP, for the research community. Availability and implementation: AI4AVP is freely accessible at http://axp.iis.sinica.edu.tw/AI4AVP/; codes and datasets for the peptide GAN and the AVP predictor CNN are available at https://github.com/lsbnb/amp_gan and https://github.com/LinTzuTang/AI4AVP_predictor. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

A metagenomics study of hexabromocyclododecane degradation with a soil microbial community.

Hexabromocyclododecanes (HBCDs) are globally prevalent and persistent organic pollutants (POPs) listed by the Stockholm Convention in 2013. They have been detected in many environmental media from waterbodies to Plantae and even in the human body. Due to their highly bioaccumulative characterization, they pose an urgent public health issue. Here, we demonstrate that the indigenous microbial community in the agricultural soil in Taiwan could decompose HBCDs with no additional carbon source incentive. The degradation kinetics reached 0.173 day-1 after the first treatment and 0.104 day-1 after second exposure. With additional C-sources, the rate constants decreased to 0.054-0.097 day-1. The hydroxylic debromination metabolites and ring cleavage long-chain alkane metabolites were identified to support the potential metabolic pathways utilized by the soil microbial communities. The metagenome established by Nanopore sequencing showed significant compositional alteration in the soil microbial community after the HBCD treatment. After ranking, comparing relative abundances, and performing network analyses, several novel bacterial taxa were identified to contribute to HBCD biotransformation, including Herbaspirillum, Sphingomonas, Brevundimonas, Azospirillum, Caulobacter, and Microvirga, through halogenated / aromatic compound degradation, glutathione-S-transferase, and hydrolase activity. We present a compelling and applicable approach combining metagenomics research, degradation kinetics, and metabolomics strategies, which allowed us to decipher the natural attenuation and remediation mechanisms of HBCDs.

[Measures to reduce lighting-related energy use and costs at hospital nursing stations].

BACKGROUND: Hospitals have long been expected to deliver medical services in an environment that is comfortable and bright. This expectation keeps hospital energy demand stubbornly high and energy costs spiraling due to escalating utility fees. Hospitals must identify appropriate strategies to control electricity usage in order to control operating costs effectively. PURPOSE: This paper proposes several electricity saving measures that both support government policies aimed at reducing global warming and help reduce energy consumption at the authors' hospital. PROJECT: The authors held educational seminars, established a website teaching energy saving methods, maximized facility and equipment use effectiveness (e.g., adjusting lamp placements, power switch and computer saving modes), posted signs promoting electricity saving, and established a regularized energy saving review mechanism. RESULT: After implementation, average nursing staff energy saving knowledge had risen from 71.8% to 100% and total nursing station electricity costs fell from NT$16,456 to NT$10,208 per month, representing an effective monthly savings of 37.9% (NT$6,248). CONCLUSION: This project demonstrated the ability of a program designed to slightly modify nursing staff behavior to achieve effective and meaningful results in reducing overall electricity use.