Many coronaviruses are capable of interspecies transmission. Some of them have caused worldwide panic as emerging human pathogens in recent years, e.g., severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). In order to assess their threat to humans, we explored to infer the potential hosts of coronaviruses using a dual-model approach based on nineteen parameters computed from spike genes of coronaviruses. Both the support vector machine (SVM) model and the Mahalanobis distance (MD) discriminant model achieved high accuracies in leave-one-out cross-validation of training data consisting of 730 representative coronaviruses (99.86% and 98.08% respectively). Predictions on 47 additional coronaviruses precisely conformed to conclusions or speculations by other researchers. Our approach is implemented as a web server that can be accessed at http://bioinfo.ihb.ac.cn/seq2hosts.

Identification of gene expression changes that improve prediction of survival time across all glioma grades would be clinically useful. Four Affymetrix GeneChip datasets from the literature, containing data from 771 glioma samples representing all WHO grades and eight normal brain samples, were used in an ANOVA model to screen for transcript changes that correlated with grade. Observations were confirmed and extended using qPCR assays on RNA derived from 38 additional glioma samples and eight normal samples for which survival data were available. RNA levels of eight major mitotic spindle assembly checkpoint (SAC) genes (BUB1, BUB1B, BUB3, CENPE, MAD1L1, MAD2L1, CDC20, TTK) significantly correlated with glioma grade and six also significantly correlated with survival time. In particular, the level of BUB1B expression was highly correlated with survival time (p<0.0001), and significantly outperformed all other measured parameters, including two standards; WHO grade and MIB-1 (Ki-67) labeling index. Measurement of the expression levels of a small set of SAC genes may complement histological grade and other clinical parameters for predicting survival time.

Background: The contribution of a gene to the fitness of a bacterium can be assayed by whether and to what degree the bacterium tolerates transposon insertions in that gene. We use this fact to compare the fitness of syntenic homologous genes among related Salmonella strains and thereby reveal differences not apparent at the gene sequence level. Results: A transposon Tn5 derivative was used to construct mutants in Salmonella Typhimurium ATCC14028 (STM1) and Salmonella Typhi Ty2 (STY1), which were then grown in rich media. The locations of 234,152 and 53,556 integration sites, respectively, were mapped by sequencing. These data were compared to similar data available for a different Ty2 isolate (STY2) and essential genes identified in E. coli K-12 (ECO). Of 277 genes considered essential in ECO, all had syntenic homologs in STM1, STY1, and STY2, and all but nine genes were either devoid of transposon insertions or had very few. For three of these nine genes, part of the annotated gene lacked transposon integrations (yejM, ftsN and murB). At least one of the other six genes, trpS, had a potentially functionally redundant gene encoded elsewhere in Salmonella but not in ECO. An additional 165 genes were almost entirely devoid of transposon integrations in all three Salmonella strains examined, including many genes associated with protein and DNA synthesis. Four of these genes (STM14_1498, STM14_2872, STM14_3360, and STM14_5442) are not found in E. coli. Notable differences in the extent of gene selection were also observed among the three different Salmonella isolates. Mutations in hns, for example, were selected against in STM1 but not in the two STY strains, which have a defect in rpoS rendering hns nonessential. Conclusions: Comparisons among transposon integration profiles from different members of a species and among related species, all grown in similar conditions, identify differences in gene contributions to fitness among syntenic homologs. Further differences in fitness profiles among shared genes can be expected in other selective environments, with potential relevance for comparative systems biology.

Foodborne intestinal inflammation is a major health and welfare issue in aquaculture. To prevent enteritis, various additives have been incorporated into the fish diet. Considering anti-inflammatory immune regulation, an effective natural compound could potentially treat or prevent intestinal inflammation. Our previous study has revealed galantamine’s effect on soybean induced enteritis (SBMIE) and has highlighted the possible role of the cholinergic anti-inflammatory pathway in the fish gut. To further activate the intestinal cholinergic related anti-inflammatory function, α7nAchR signaling was considered. In this study, sinomenine, a typical agonist of α7nAChR in mammals, was tested to treat fish foodborne enteritis via its potential anti-inflammation effect using the zebrafish foodborne enteritis model. After sinomenine’s dietary inclusion, results suggested that there was an alleviation of intestinal inflammation at a pathological level. This outcome was demonstrated through the improved morphology of intestinal villi. At a molecular level, SN suppressed inflammatory cytokines’ expression (especially for tnf-α) and upregulated anti-inflammation-related functions (indicated by expression of il-10, il-22, and foxp3a). To systematically understand sinomenine’s intestinal effect on SBMIE, transcriptomic analysis was done on the SBMIE adult fish model. DEGs (sinomenine vs soybean meal groups) were enriched in GO terms related to the negative regulation of lymphocyte/leukocyte activation and alpha-beta T cell proliferation, as well as the regulation of lymphocyte migration. The KEGG pathways for glycolysis and insulin signaling indicated metabolic adjustments of α7nAchR mediated anti-inflammatory effect. To demonstrate the immune cells’ response, in the SBMIE larva model, inflammatory gatherings of neutrophils, macrophages, and lymphocytes caused by soybean meal could be relieved significantly with the inclusion of sinomenine. This was consistent within the sinomenine group as CD4⁺ or Foxp3⁺ lymphocytes were found with a higher proportion at the base of mucosal folds, which may suggest the Treg population. Echoing, the sinomenine group’s 16s sequencing result, there were fewer enteritis-related TM7, Sphingomonas and Shigella, but more Cetobacterium, which were related to glucose metabolism. Our findings indicate that sinomenine hydrochloride could be important in the prevention of fish foodborne enteritis at both immune and microbiota levels.

Aerobic photosynthetic organisms such as algae produce reactive oxygen species (ROS) as by-products of metabolism. ROS damage biomolecules such as proteins and lipids in cells, but also act as signaling molecules. The mechanisms that maintain the metabolic balance in aerobic photosynthetic organisms and how the cells specifically respond to different levels of ROS are unclear. Glutathione peroxidase (GPX) enzymes detoxify hydrogen peroxide or organic hydroperoxides, and thus are important components of the antioxidant system. In this study, we employed a Chlamydomonas reinhardtii glutathione peroxidase knockout (gpx5) mutant to identify the genetic response to singlet oxygen (¹O₂) generated by the photosensitizer rose bengal (RB). To this end, we compared the transcriptomes of the parental strain CC4348 and the gpx5 mutant sampled before, and 1 h after, the addition of RB. Functional annotation of differentially expressed genes showed that genes encoding proteins related to ROS detoxification, stress-response-related molecular chaperones, and ubiquitin–proteasome pathway genes were upregulated in CC4338. When GPX5 was mutated, higher oxidative stress specifically induced the TCA cycle and enhanced mitochondrial electron transport. Transcription of selenoproteins and flagellar-associated proteins was depressed in CC4348 and the gpx5 mutant. In addition, we found iron homeostasis played an important role in maintaining redox homeostasis, and we uncovered the relationship between ¹O₂ stress and iron assimilation, as well as selenoproteins. Based on the observed expression profiles in response to different levels of oxidative stress, we propose a model for dose-dependent responses to different ROS levels in Chlamydomonas.

High-throughput RNA sequencing unveiled the complexity of transcriptome and significantly increased the records of long noncoding RNAs (lncRNAs), which were reported to participate in a variety of biological processes. Identification of lncRNAs is a key step in lncRNA analysis, and a bunch of bioinformatics tools have been developed for this purpose in recent years. While these tools allow us to identify lncRNA more efficiently and accurately, they may produce inconsistent results, making selection a confusing issue. We compared the performance of 41 analysis models based on 14 software packages and different data sets, including high-quality data and low-quality data from 33 species. In addition, computational efficiency, robustness, and joint prediction of the models were explored. As a practical guidance, key points for lncRNA identification under different situations were summarized. In this investigation, no one of these models could be superior to others under all test conditions. The performance of a model relied to a great extent on the source of transcripts and the quality of assemblies. As general references, FEELnc_all_cl, CPC, and CPAT_mouse work well in most species while COME, CNCI, and lncScore are good choices for model organisms. Since these tools are sensitive to different factors such as the species involved and the quality of assembly, researchers must carefully select the appropriate tool based on the actual data. Alternatively, our test suggests that joint prediction could behave better than any single model if proper models were chosen. All scripts/data used in this research can be accessed at http://bioinfo.ihb.ac.cn/elit.