Lentinula edodes, one of the most popular, edible mushroom species with a high content of proteins and polysaccharides as well as unique aroma, is widely cultivated in many Asian countries, especially in China, Japan and Korea. As a white rot fungus with lignocellulose degradation ability, L. edodes has the potential for application in the utilization of agriculture straw resources. Here, we report its 41.8-Mb genome, encoding 14,889 predicted genes. Through a phylogenetic analysis with model species of fungi, the evolutionary divergence time of L. edodes and Gymnopus luxurians was estimated to be 39 MYA. The carbohydrate-active enzyme genes in L. edodes were compared with those of the other 25 fungal species, and 101 lignocellulolytic enzymes were identified in L. edodes, similar to other white rot fungi. Transcriptome analysis showed that the expression of genes encoding two cellulases and 16 transcription factor was up-regulated when mycelia were cultivated for 120 minutes in cellulose medium versus glucose medium. Our results will foster a better understanding of the molecular mechanism of lignocellulose degradation and provide the basis for partial replacement of wood sawdust with agricultural wastes in L. edodes cultivation.
Porcine epidemic diarrhea virus (PEDV), a member of the group of alphacoronaviruses, is the pathogen of a highly contagious gastrointestinal swine disease. The elucidation of the events associated with the intestinal epithelial response to PEDV infection has been limited by the absence of good in vitro porcine intestinal models that recapitulate the multicellular complexity of the gastrointestinal tract. Here, we generated swine enteroids from the intestinal crypt stem cells of the duodenum, jejunum, or ileum and found that the generated enteroids are able to satisfactorily recapitulate the complicated intestinal epithelium in vivo and are susceptible to infection by PEDV. PEDV infected multiple types of cells, including enterocytes, stem cells, and goblet cells, and exhibited segmental infection discrepancies compared with ileal enteroids and colonoids, and this finding was verified in vivo. Moreover, the clinical isolate PEDV-JMS propagated better in ileal enteroids than the cell-adapted isolate PEDV-CV777, and PEDV infection suppressed interferon (IFN) production early during the infection course. IFN lambda elicited a potent antiviral response and inhibited PEDV in enteroids more efficiently than IFN alpha (IFN-␣). Therefore, swine enteroids provide a novel in vitro model for exploring the pathogenesis of PEDV and for the in vitro study of the interplay between a host and a variety of swine enteric viruses. IMPORTANCE PEDV is a highly contagious enteric coronavirus that causes significant economic losses, and the lack of a good in vitro model system is a major roadblock to an in-depth understanding of PEDV pathogenesis. Here, we generated a porcine intestinal enteroid model for PEDV infection. Utilizing porcine intestinal enteroids, we demonstrated that PEDV infects multiple lineages of the intestinal epithelium and preferably infects ileal enteroids over colonoids and that enteroids prefer to respond to IFN lambda 1 over IFN-␣. These events recapitulate the events that occur in vivo. This study constitutes the first use of a primary intestinal enteroid model to investigate the susceptibility of porcine enteroids to PEDV and to determine the antiviral response following infection. Our study provides important insights into the events associated with PEDV infection of the porcine intestine and provides a valuable in vitro model for studying not only PEDV but also other swine enteric viruses.
We present a Prototheca wickerhamii wound infection case that failed treatment with ketoconazole but was cured with amphotericin-B plus tetracycline. The patient was immunocompetent but had had local steroid injections. We reviewed another 159 cases from the literature. Prototheca has infected many areas of the human body, but most often skin, olecranon bursa, or wounds. Prior treatment with steroids and immune deficiencies are contributing factors. Itraconazole and fluconazole are reasonable initial treatments for patients with mild infections. For serious infections, or for infections that have failed azole treatment, amphotericin-B is the treatment of choice.
BackgroundCurrently available microRNA (miRNA) target prediction algorithms require the presence of a conserved seed match to the 5' end of the miRNA and limit the target sites to the 3' untranslated regions of mRNAs. However, it has been noted that these requirements may be too stringent, leading to a substantial number of missing targets.ResultsWe have developed TargetS, a novel computational approach for predicting miRNA targets with the target sites located along entire gene sequences, which permits finding additional targets that are not located in the 3' un-translated regions. Our model is based on both canonical seed matching and non-canonical seed pairing, which discovers targets that allow one bit GU wobble. It does not rely on evolutionary conservation, so it allows the detection of species-specific miRNA-mRNA interactions and makes it suitable for analyzing un-conserved gene sequences. To test the performance of our approach, we have imported the widely used benchmark dataset revealing fold-changes in protein production corresponding to each of the five selected microRNAs. Compared to well-known miRNA target prediction tools, including TargetScanS, PicTar and MicroT_CDS, our method yields the highest sensitivity, while achieving a comparable level of accuracy. Human miRNA target predictions using our computational approach are available online at http://liubioinfolab.org/targetS/mirna.htmlConclusionsA simple but powerful computational miRNA target prediction method is developed that is solely based on canonical and non-canonical seed matches without requiring evolutionary conservation of the target sites. Our method also expands the target search space to different gene regions, rather than limiting to 3'UTR only. This improves the sensitivity of miRNA target identification, while achieving a comparable accuracy with existing methods.
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