Search

Abstract Background Primary ovarian insufficiency (POI) is an early decline in ovarian function that leads to ovarian failure. Conventional treatments for POI are inadequate, and treatments based on mesenchymal stem cells (MSCs) have emerged as an option. However, the lack of consideration of the estrogen niche in ovarian tissue significantly reduces the therapeutic efficacy, with an unclear mechanism in the MSCs in POI treatment. Furthermore, the disruption of circadian rhythm associated with POI has not been previously addressed. Methods Conditioned medium (CM) and estradiol-conditioned medium (E2-CM) were generated from estrogen receptor positive MSCs (ER+pcMSCs). Chemotherapy-induced POI models were established using C57BL/6 mice (in vivo) and KGN cells (in vitro) treated with cyclophosphamide (CTX) or 4-hydroperoxycyclophosphamide (4-OOH-CP). Gene/protein expressions were detected using RT-qPCR, Western blotting, and immunohistochemistry assays. Locomotor activity was monitored for behavioral circadian rhythmicity. Cytokine arrays and miRNA analysis were conducted to analyze potential factors within CM/E2-CM. Results The secretome of ER+pcMSCs (CM and E2-CM) significantly reduced the CTX-induced defects in ovarian folliculogenesis and circadian rhythm. CM/E2-CM also reduced granulosa cell apoptosis and rescued angiogenesis in POI ovarian tissues. E2-CM had a more favorable effect than the CM. Notably, ER+pcMSC secretome restored CTX-induced circadian rhythm defects, including the gene expressions associated with the ovarian circadian clock (e.g., Rora, E4bp4, Rev-erbα, Per2 and Dbp) and locomotor activity. Additionally, the cytokine array analysis revealed a significant increase in cytokines and growth factors associated with immunomodulation and angiogenesis, including angiogenin. Neutralizing the angiogenin in CM/E2-CM significantly reduced its ability to promote HUVEC tube formation in vitro. Exosomal miRNA analysis revealed the miRNAs involved in targeting the genes associated with POI rescue (PTEN and PDCD4), apoptosis (caspase-3, BIM), estrogen synthesis (CYP19A1), ovarian clock regulation (E4BP4, REV-ERBα) and fibrosis (COL1A1). Conclusion This study is the first to demonstrate that, in considering the estrogen niche in ovarian tissue, an estrogen-priming ER+pcMSC secretome achieved ovarian regeneration and restored the circadian rhythm in a CTX-induced POI mouse model. The potential factors involved include angiogenin and exosomal miRNAs in the ER+pcMSC secretome. These findings offer insights into potential stem cell therapies for chemotherapy-induced POI and circadian rhythm disruption.

Abstract To reduce the use of antibiotics and chemicals in aquaculture, an edible herb, Bidens pilosa, has been selected as a multifunctional feed additive. Although there has been considerable research into the effects of B. pilosa on poultry, the wider effects of B. pilosa, particularly on the growth and gut microbiota of fish, remain largely unexplored. We aimed to investigate the interactive effects between the host on growth and the gut microbiota using transcriptomics and the gut microbiota in B. pilosa-fed tilapia. In this study, we added 0.5% and 1% B. pilosa to the diet and observed that the growth performance of tilapia significantly increased over 8 weeks of feeding. Comparative transcriptome analysis was performed on RNA sequence profiles obtained from liver and muscle tissues. Functional enrichment analysis revealed that B. pilosa regulates several pathways and genes involved in amino acid metabolism, lipid metabolism, carbohydrate metabolism, endocrine system, signal transduction, and metabolism of other amino acids. The expression of the selected growth-associated genes was validated by qRT–PCR. The qRT–PCR results indicated that B. pilosa may enhance growth performance by activating the expression of the liver igf1 and muscle igf1rb genes and inhibiting the expression of the muscle negative regulator mstnb. Both the enhancement of liver endocrine IGF1/IGF1Rb signaling and the suppression of muscle autocrine/paracrine MSTN signaling induced the expression of myogenic regulatory factors (MRFs), myod1, myog and mrf4 in muscle to promote muscle growth in tilapia. The predicted function of the gut microbiota showed several significantly different pathways that overlapped with the KEGG enrichment results of differentially expressed genes in the liver transcriptomes. This finding suggested that the gut microbiota may influence liver metabolism through the gut–liver axis in B. pilosa-fed tilapia. In conclusion, dietary B. pilosa can regulate endocrine IGF1 signaling and autocrine/paracrine MSTN signaling to activate the expression of MRFs to promote muscle growth and alter the composition of gut bacteria, which can then affect liver amino acid metabolism, carbohydrate metabolism, endocrine system, lipid metabolism, metabolism of other amino acids, and signal transduction in the host, ultimately enhancing growth performance. Our results suggest that B. pilosa has the potential to be a functional additive that can be used as an alternative to reduce antibiotic use as a growth promoter in aquaculture.

Abstract Background Owing to the heterogeneity of microbiota among individuals and populations, only Fusobacterium nucleatum and Bacteroides fragilis have been reported to be enriched in colorectal cancer (CRC) in multiple studies. Thus, the discovery of additional bacteria contributing to CRC development in various populations can be expected. We aimed to identify bacteria associated with the progression of colorectal adenoma to carcinoma and determine the contribution of these bacteria to malignant transformation in patients of Han Chinese origin. Methods Microbiota composition was determined through 16S rRNA V3–V4 amplicon sequencing of autologous adenocarcinomas, adenomatous polyps, and non-neoplastic colon tissue samples (referred to as “tri-part samples”) in patients with CRC. Enriched taxa in adenocarcinoma tissues were identified through pairwise comparison. The abundance of candidate bacteria was quantified through genomic quantitative polymerase chain reaction (qPCR) in tissue samples from 116 patients. Associations of candidate bacteria with clinicopathological features and genomic and genetic alterations were evaluated through odds ratio tests. Additionally, the effects of candidate bacteria on CRC cell proliferation, migration, and invasion were evaluated through the co-culture of CRC cells with bacterial cells or with conditioned media from bacteria. Results Prevotella intermedia was overrepresented in adenocarcinomas compared with paired adenomatous polyps. Furthermore, co-abundance of P. intermedia and F. nucleatum was observed in tumor tissues. More notably, the coexistence of these two bacteria in adenocarcinomas was associated with lymph node involvement and distant metastasis. These two bacteria also exerted additive effects on the enhancement of the migration and invasion abilities of CRC cells. Finally, conditioned media from P. intermedia promoted the migration and invasion of CRC cells. Conclusion This report is the first to demonstrate that P. intermedia is enriched in colorectal adenocarcinoma tissues and enhances the migration and invasion abilities of CRC cells. Moreover, P. intermedia and F. nucleatum exert additive effects on the malignant transformation of colorectal adenomas into carcinomas. These findings can be used to identify patients at a high risk of malignant transformation of colorectal adenomas or metastasis of CRC, and they can accordingly be provided optimal clinical management.

Glucocorticoid-induced osteoporosis (GIOP) is the most common form of secondary osteoporosis due to excessive or long-term glucocorticoid administration, disturbing the homeostasis between bone formation and bone resorption. The bone biology of zebrafish shares a high degree of similarities with mammals. In terms of molecular level, genes and signaling pathways related to skeletogenesis are also highly correlated between zebrafish and humans. Therefore, zebrafish have been utilized to develop multiple GIOP models. Taking advantage of the transparency of zebrafish larvae, their skeletal development and bone mineralization can be readily visualized through in vivo staining without invasive experimental handlings. Moreover, the feasibility of using scales or fin rays to study bone remodeling makes adult zebrafish an ideal model for GIOP research. Here, we reviewed current zebrafish models for GIOP research, focused on the tools and methods established for examining bone homeostasis. As an in vivo, convenient, and robust model, zebrafish have an advantage in performing high-throughput drug screening and could be used to investigate the action mechanisms of therapeutic drugs.

Studies have reported the effects of the gut microbiota on colorectal cancer (CRC) chemotherapy, but few studies have investigated the association between gut microbiota and targeted therapy. This study investigated the role of the gut microbiota in the treatment outcomes of patients with metastatic CRC (mCRC). We enrolled 110 patients with mCRC and treated them with standard cancer therapy. Stool samples were collected before administering a combination of chemotherapy and targeted therapy. Patients who had a progressive disease (PD) or partial response (PR) for at least 12 cycles of therapy were included in the study. We further divided these patients into anti-epidermal growth factor receptor (cetuximab) and anti-vascular endothelial growth factor (bevacizumab) subgroups. The gut microbiota of the PR group and bevacizumab-PR subgroup exhibited significantly higher α-diversity. The β-diversity of bacterial species significantly differed between the bevacizumab-PR and bevacizumab-PD groups (P = 0.029). Klebsiella quasipneumoniae exhibited the greatest fold change in abundance in the PD group than in the PR group. Lactobacillus and Bifidobacterium species exhibited higher abundance in the PD group. The abundance of Fusobacterium nucleatum was approximately 32 times higher in the PD group than in the PR group. A higher gut microbiota diversity was associated with more favorable treatment outcomes in the patients with mCRC. Bacterial species analysis of stool samples yielded heterogenous results. K. quasipneumoniae exhibited the greatest fold change in abundance among all bacterial species in the PD group. This result warrants further investigation especially in a Taiwanese population.

Summary: 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.

Depression is associated with gut dysbiosis that disrupts a gut-brain bidirectional axis. Gray matter volume changes in cortical and subcortical structures, including prefrontal regions and the hippocampus, have also been noted in depressive disorders. However, the link between gut microbiota and brain structures in depressed patients remains elusive. Neuropsychiatric measures, stool samples, and structural brain images were collected from 36 patients with late-life depression (LLD) and 17 healthy controls. 16S ribosomal RNA (rRNA) gene sequencing was used to profile stool microbial communities for quantitation of microbial composition, abundance, and diversity. T1-weighted brain images were assessed with voxel-based morphometry to detect alterations in gray matter volume between groups. Correlation analysis was performed to identify the possible association between depressive symptoms, brain structures and gut microbiota. We found a significant difference in the gut microbial composition between patients with late-life depression (LLD) and healthy controls. The genera Enterobacter and Burkholderia were positively correlated with depressive symptoms and negatively correlated with brain structural signatures in regions associated with memory, somatosensory integration, and emotional processing/cognition/regulation. Our study purports the microbiota-gut-brain axis as a potential mechanism mediating the symptomatology of LLD patients, which may facilitate the development of therapeutic strategies targeting gut microbes in the treatment of elderly depressed patients.

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.

Retrotransposons are known to be involved in aging. Here the authors show that the retrotransposon silencer Piwi contributes to germline stem cell loss during aging in Drosophila.

Abstract 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/.

Abstract Background Extraintestinal pathogenic E. coli (ExPEC) remains one of the most prevalent bacterial pathogens that cause extraintestinal infections, including neonatal meningitis, septicemia, and urinary tract (UT) infections (UTIs). Antibiotic therapy has been the conventional treatment for such infections, but its efficacy has decreased due to the emergence of antibiotic-resistant bacteria. Identification and characterization of bacterial factors that contribute to the severity of infection would facilitate the development of novel therapeutic strategies. The ExPEC periplasmic protease Prc contributes to the pathogen’s ability to evade complement-mediated killing in the serum. Here, we further investigated the role of the Prc protease in ExPEC-induced UTIs and the underlying mechanism. Methods The uropathogenic role of Prc was determined in a mouse model of UTIs. Using global quantitative proteomic analyses, we revealed that the expression of FliC and other outer membrane-associated proteins was altered by Prc deficiency. Comparative transcriptome analyses identified that Prc deficiency affected expression of the flagellar regulon and genes that are regulated by five extracytoplasmic signaling systems. Results A mutant ExPEC with a prc deletion was attenuated in bladder and kidney colonization. Global quantitative proteomic analyses of the prc mutant and wild-type ExPEC strains revealed significantly reduced flagellum expression in the absence of Prc, consequently impairing bacterial motility. The prc deletion triggered downregulation of the flhDC operon encoding the master transcriptional regulator of flagellum biogenesis. Overexpressing flhDC restored the prc mutant’s motility and ability to colonize the UT, suggesting that the impaired motility is responsible for attenuated UT colonization of the mutant. Further comparative transcriptome analyses revealed that Prc deficiency activated the σE and RcsCDB signaling pathways. These pathways were responsible for the diminished flhDC expression. Finally, the activation of the RcsCDB system was attributed to the intracellular accumulation of a known Prc substrate Spr in the prc mutant. Spr is a peptidoglycan hydrolase and its accumulation destabilizes the bacterial envelope. Conclusions We demonstrated for the first time that Prc is essential for full ExPEC virulence in UTIs. Our results collectively support the idea that Prc is essential for bacterial envelope integrity, thus explaining how Prc deficiency results in an attenuated ExPEC.

ABSTRACT Antimicrobial peptides (AMPs) are innate immune components that have recently stimulated considerable interest among drug developers due to their potential as antibiotic substitutes. AMPs are notable for their fundamental properties of microbial membrane structural interference and the biomedical applications of killing or suppressing microbes. New AMP candidates must be developed to oppose antibiotic resistance. However, the discovery of novel AMPs through wet-lab screening approaches is inefficient and expensive. The prediction model investigated in this study may help accelerate this process. We collected both the up-to-date AMP data set and unbiased negatives based on which the protein-encoding methods and deep learning model for AMPs were investigated. The external testing results indicated that our trained model achieved 90% precision, outperforming current methods. We implemented our model on a user-friendly web server, AI4AMP, to accurately predict the antimicrobial potential of a given protein sequence and perform proteome screening. IMPORTANCE Antimicrobial peptides (AMPs) are innate immune components that have aroused a great deal of interest among drug developers recently, as they may become a substitute for antibiotics. New candidates need to fight antibiotic resistance, while discovering novel AMPs through wet-lab screening approaches is inefficient and expensive. To accelerate the discovery of new AMPs, we both collected the up-to-date antimicrobial peptide data set and integrated the protein-encoding methods with a deep learning model. The trained model outperforms the current methods and is implemented into a user-friendly web server, AI4AMP, to accurately predict the antimicrobial properties of a given protein sequence and perform proteome screening. Author Video: An author video summary of this article is available.

Abstract 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.

Assay for transposase-accessible chromatin using sequencing data (ATAC-seq) is an efficient and precise method for revealing chromatin accessibility across the genome. Most of the current ATAC-seq tools follow chromatin immunoprecipitation sequencing (ChIP-seq) strategies that do not consider ATAC-seq-specific properties. To incorporate specific ATAC-seq quality control and the underlying biology of chromatin accessibility, we developed a bioinformatics software named ATACgraph for analyzing and visualizing ATAC-seq data. ATACgraph profiles accessible chromatin regions and provides ATAC-seq-specific information including definitions of nucleosome-free regions (NFRs) and nucleosome-occupied regions. ATACgraph also allows identification of differentially accessible regions between two ATAC-seq datasets. ATACgraph incorporates the docker image with the Galaxy platform to provide an intuitive user experience via the graphical interface. Without tedious installation processes on a local machine or cloud, users can analyze data through activated websites using pre-designed workflows or customized pipelines composed of ATACgraph modules. Overall, ATACgraph is an effective tool designed for ATAC-seq for biologists with minimal bioinformatics knowledge to analyze chromatin accessibility. ATACgraph can be run on any ATAC-seq data with no limit to specific genomes. As validation, we demonstrated ATACgraph on human genome to showcase its functions for ATAC-seq interpretation. This software is publicly accessible and can be downloaded at https://github.com/RitataLU/ATACgraph.

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.

The gut microbiota is reported to play an important role in carcinogenesis and the treatment of CRC. SW480 and SW620 colon cancer cells integrated with infrared fluorescent proteins were injected into the rectal submucosa of nude mice. In the subsequent 30 days, we observed tumor growth weekly using an in vivo imaging system. The bacterial solution was infused anally into the mice to perform bacterial transplant. Phosphate-buffered saline, Acinetobacter lwoffii, and Bifidobacterium longum solutions were infused individually. The 16S ribosomal DNA (rDNA) and polymerase chain reaction of murine feces were investigated to confirm the colonization of target bacteria. In the SW620 orthotopic xenograft rectal cancer model, 4 of 5 mice developed rectal cancer by 30 days after submucosal injection. In the SW480 orthotopic xenograft rectal cancer model, 2 of 6 mice developed rectal cancer by 30 days after submucosal injection. For the 16S rDNA analysis, the mice receiving the bacterial solution infusion demonstrated positive findings for A. lwoffii and B. longum. With the successful establishment of a mouse model of orthotopic rectal cancer and transplant of target bacteria, we can further explore the relationship between gut microbiota and CRC. The role of fecal microbiota transplant in the treatment and alleviation of adverse events of chemotherapy in CRC could be clarified in subsequent studies.

Abstract 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.

Spontaneous regression of an osteochondroma of the distal femur is unusual. This report highlights the spontaneous regression of a sessile osteochondroma of the distal femur in a 9-year-old boy which resolved over a 4-year period. The mechanism underlying regression of the tumor is discussed with a review of previous reports. Since this type of osteochondroma can spontaneously resolve, conservative treatment is always the first choice to avoid unnecessary surgery.

Taiwan tilapia is one of the primary species used in aquaculture practices in Taiwan. However, as a tropical fish, it is sensitive to cold temperatures that can lead to high mortality rates during winter months. Genetic and broodstock management strategies using marker-assisted selection and breeding are the best tools currently available to improve seed varieties for tilapia species. The purpose of this study was to develop molecular markers for cold stress-related genes using digital gene expression analysis of next-generation transcriptome sequencing in Taiwan tilapia (Oreochromis spp.). We constructed and sequenced cDNA libraries from the brain, gill, liver, and muscle tissues of cold-tolerance (CT) and cold-sensitivity (CS) strains. Approximately 35,214,833,100 nucleotides of raw sequencing reads were generated, and these were assembled into 128,147 unigenes possessing a total length of 185,382,926 bp and an average length of 1446 bp. A total of 25,844 unigenes were annotated using five protein databases and Venny analysis, and 38,377 simple sequence repeats (SSRs) and 65,527 single nucleotide polymorphisms (SNPs) were identified. Furthermore, from the 38-cold tolerance-related genes that were identified using differential gene expression analysis in the four tissues, 13 microsatellites and 37 single nucleotide polymorphism markers were identified. The results of the genotype analysis revealed that the selected markers could be used for population genetics. In addition to the diversity assessment, one of the SNP markers was determined to be significantly related to cold-tolerance traits and could be used as a molecular marker to assist in the selection and verification of cold-tolerant populations. The specific genetic markers explored in this study can be used for the identification of genetic polymorphisms and cold tolerance traits in Taiwan tilapia, and they can also be used to further explore the physiological and biochemical molecular regulation pathways of fish that are involved in their tolerance to environmental temperature stress.

Mammalian herbivores rely on microbial activities in an expanded gut chamber to convert plant biomass into absorbable nutrients. Distinct from ruminants, small herbivores typically have a simple stomach but an enlarged cecum to harbor symbiotic microbes; however, knowledge of this specialized gut structure and characteristics of its microbial contents is limited. Here, we used leaf-eating flying squirrels as a model to explore functional characteristics of the cecal microbiota adapted to a high-fiber, toxin-rich diet. Specifically, environmental conditions across gut regions were evaluated by measuring mass, pH, feed particle size, and metabolomes. Then, parallel metagenomes and metatranscriptomes were used to detect microbial functions corresponding to the cecal environment. Based on metabolomic profiles, >600 phytochemical compounds were detected, although many were present only in the foregut and probably degraded or transformed by gut microbes in the hindgut. Based on metagenomic (DNA) and metatranscriptomic (RNA) profiles, taxonomic compositions of the cecal microbiota were dominated by bacteria of the Firmicutes taxa; they contained major gene functions related to degradation and fermentation of leaf-derived compounds. Based on functional compositions, genes related to multidrug exporters were rich in microbial genomes, whereas genes involved in nutrient importers were rich in microbial transcriptomes. In addition, genes encoding chemotaxis-associated components and glycoside hydrolases specific for plant beta-glycosidic linkages were abundant in both DNA and RNA. This exploratory study provides findings which may help to form molecular-based hypotheses regarding functional contributions of symbiotic gut microbiota in small herbivores with folivorous dietary habits.

We coupled 16S rDNA PCR and DNA hybridization technology to construct a microarray for simultaneous detection and discrimination of eight fish pathogens (Aeromonas hydrophila, Edwardsiella tarda, Flavobacterium columnare, Lactococcus garvieae, Photobacterium damselae, Pseudomonas anguilliseptica, Streptococcus iniae and Vibrio anguillarum) commonly encountered in aquaculture. The array comprised short oligonucleotide probes (30 mer) complementary to the polymorphic regions of 16S rRNA genes for the target pathogens. Targets annealed to the microarray probes were reacted with streptavidin-conjugated alkaline phosphatase and nitro blue tetrazolium/5-bromo-4-chloro-3′-indolylphosphate, p-toluidine salt (NBT/BCIP), resulting in blue spots that are easily visualized by the naked eye. Testing was performed against a total of 168 bacterial strains, i.e., 26 representative collection strains, 81 isolates of target fish pathogens, and 61 ecologically or phylogenetically related strains. The results showed that each probe consistently identified its corresponding target strain with 100% specificity. The detection limit of the microarray was estimated to be in the range of 1 pg for genomic DNA and 103 CFU/mL for pure pathogen cultures. These high specificity and sensitivity results demonstrate the feasibility of using DNA microarrays in the diagnostic detection of fish pathogens.

Natural stocks of Japanese eel (Anguilla japonica) have decreased drastically because of overfishing, habitat destruction, and changes in the ocean environment over the past few decades. However, to date, artificial mass production of glass eels is far from reality because of the lack of appropriate feed for the eel larvae. In this study, wild glass eel, leptocephali, preleptocephali, and embryos were collected to conduct RNA-seq. Approximately 279 million reads were generated and assembled into 224,043 transcripts. The transcript levels of genes coding for digestive enzymes and nutrient transporters were investigated to estimate the capacities for nutrient digestion and absorption during early development. The results showed that the transcript levels of protein digestion enzymes were higher than those of carbohydrate and lipid digestion enzymes in the preleptocephali and leptocephali, and the transcript levels of amino acid transporters were also higher than those of glucose and fructose transporters and the cholesterol transporter. In addition, the transcript levels of glucose and fructose transporters were significantly raising in the leptocephali. Moreover, the transcript levels of protein, carbohydrate, and lipid digestion enzymes were balanced in the glass eel, but the transcript levels of amino acid transporters were higher than those of glucose and cholesterol transporters. These findings implied that preleptocephali and leptocephali prefer high-protein food, and the nutritional requirements of monosaccharides and lipids for the eel larvae vary with growth. An online database (http://molas.iis.sinica.edu.tw/jpeel/) that will provide the sequences and the annotated results of assembled transcripts was established for the eel research community.

ABSTRACT Pairing high-throughput sequencing technologies with high-throughput mutagenesis enables genome-wide investigations of pathogenic organisms. Knowledge of the specific functions of protein domains encoded by the genome of the hepatitis C virus (HCV), a major human pathogen that contributes to liver disease worldwide, remains limited to insight from small-scale studies. To enhance the capabilities of HCV researchers, we have obtained a high-resolution functional map of the entire viral genome by combining transposon-based insertional mutagenesis with next-generation sequencing. We generated a library of 8,398 mutagenized HCV clones, each containing one 15-nucleotide sequence inserted at a unique genomic position. We passaged this library in hepatic cells, recovered virus pools, and simultaneously assayed the abundance of mutant viruses in each pool by next-generation sequencing. To illustrate the validity of the functional profile, we compared the genetic footprints of viral proteins with previously solved protein structures. Moreover, we show the utility of these genetic footprints in the identification of candidate regions for epitope tag insertion. In a second application, we screened the genetic footprints for phenotypes that reflected defects in later steps of the viral life cycle. We confirmed that viruses with insertions in a region of the nonstructural protein NS4B had a defect in infectivity while maintaining genome replication. Overall, our genome-wide HCV mutant library and the genetic footprints obtained by high-resolution profiling represent valuable new resources for the research community that can direct the attention of investigators toward unidentified roles of individual protein domains. IMPORTANCE Our insertional mutagenesis library provides a resource that illustrates the effects of relatively small insertions on local protein structure and HCV viability. We have also generated complementary resources, including a website (http://hangfei.bol.ucla.edu) and a panel of epitope-tagged mutant viruses that should enhance the research capabilities of investigators studying HCV. Researchers can now detect epitope-tagged viral proteins by established antibodies, which will allow biochemical studies of HCV proteins for which antibodies are not readily available. Furthermore, researchers can now quickly look up genotype-phenotype relationships and base further mechanistic studies on the residue-by-residue information from the functional profile. More broadly, this approach offers a general strategy for the systematic functional characterization of viruses on the genome scale.

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients.

BackgroundExplosive growth of next-generation sequencing data has resulted in ultra-large-scale data sets and ensuing computational problems. Cloud computing provides an on-demand and scalable environment for large-scale data analysis. Using a MapReduce framework, data and workload can be distributed via a network to computers in the cloud to substantially reduce computational latency. Hadoop/MapReduce has been successfully adopted in bioinformatics for genome assembly, mapping reads to genomes, and finding single nucleotide polymorphisms. Major cloud providers offer Hadoop cloud services to their users. However, it remains technically challenging to deploy a Hadoop cloud for those who prefer to run MapReduce programs in a cluster without built-in Hadoop/MapReduce.ResultsWe present CloudDOE, a platform-independent software package implemented in Java. CloudDOE encapsulates technical details behind a user-friendly graphical interface, thus liberating scientists from having to perform complicated operational procedures. Users are guided through the user interface to deploy a Hadoop cloud within in-house computing environments and to run applications specifically targeted for bioinformatics, including CloudBurst, CloudBrush, and CloudRS. One may also use CloudDOE on top of a public cloud. CloudDOE consists of three wizards, i.e., Deploy, Operate, and Extend wizards. Deploy wizard is designed to aid the system administrator to deploy a Hadoop cloud. It installs Java runtime environment version 1.6 and Hadoop version 0.20.203, and initiates the service automatically. Operate wizard allows the user to run a MapReduce application on the dashboard list. To extend the dashboard list, the administrator may install a new MapReduce application using Extend wizard.ConclusionsCloudDOE is a user-friendly tool for deploying a Hadoop cloud. Its smart wizards substantially reduce the complexity and costs of deployment, execution, enhancement, and management. Interested users may collaborate to improve the source code of CloudDOE to further incorporate more MapReduce bioinformatics tools into CloudDOE and support next-generation big data open source tools, e.g., Hadoop BigTop and Spark.AvailabilityCloudDOE is distributed under Apache License 2.0 and is freely available at http://clouddoe.iis.sinica.edu.tw/.

BACKGROUND: Selecting an appropriate substitution model and deriving a tree topology for a given sequence set are essential in phylogenetic analysis. However, such time consuming, computationally intensive tasks rely on knowledge of substitution model theories and related expertise to run through all possible combinations of several separate programs. To ensure a thorough and efficient analysis and avert tedious manipulations of various programs, this work presents an intuitive framework, the phylogenetic reconstruction with automatic likelihood model selectors (PALM), with convincing, updated algorithms and a best-fit model selection mechanism for seamless phylogenetic analysis. METHODOLOGY: As an integrated framework of ClustalW, PhyML, MODELTEST, ProtTest, and several in-house programs, PALM evaluates the fitness of 56 substitution models for nucleotide sequences and 112 substitution models for protein sequences with scores in various criteria. The input for PALM can be either sequences in FASTA format or a sequence alignment file in PHYLIP format. To accelerate the computing of maximum likelihood and bootstrapping, this work integrates MPICH2/PhyML, PalmMonitor and Palm job controller across several machines with multiple processors and adopts the task parallelism approach. Moreover, an intuitive and interactive web component, PalmTree, is developed for displaying and operating the output tree with options of tree rooting, branches swapping, viewing the branch length values, and viewing bootstrapping score, as well as removing nodes to restart analysis iteratively. SIGNIFICANCE: The workflow of PALM is straightforward and coherent. Via a succinct, user-friendly interface, researchers unfamiliar with phylogenetic analysis can easily use this server to submit sequences, retrieve the output, and re-submit a job based on a previous result if some sequences are to be deleted or added for phylogenetic reconstruction. PALM results in an inference of phylogenetic relationship not only by vanquishing the computation difficulty of ML methods but also providing statistic methods for model selection and bootstrapping. The proposed approach can reduce calculation time, which is particularly relevant when querying a large data set. PALM can be accessed online at http://palm.iis.sinica.edu.tw.