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Background & Aims Alcohol-associated liver disease (ALD) is a significant cause of liver-related morbidity and mortality worldwide and with limited therapies. Soluble epoxide hydrolase (sEH; Ephx2) is a largely cytosolic enzyme that is highly expressed in the liver and is implicated in hepatic function, but its role in ALD is mostly unexplored. Methods To decipher the role of hepatic sEH in ALD, we generated mice with liver-specific sEH disruption (Alb-Cre; Ephx2fl/fl). Alb-Cre; Ephx2fl/fl and control (Ephx2fl/fl) mice were subjected to an ethanol challenge using the chronic plus binge model of ALD and hepatic injury, inflammation, and steatosis were evaluated under pair-fed and ethanol-fed states. In addition, we investigated the capacity of pharmacologic inhibition of sEH in the chronic plus binge mouse model. Results We observed an increase of hepatic sEH in mice upon ethanol consumption, suggesting that dysregulated hepatic sEH expression might be involved in ALD. Alb-Cre; Ephx2fl/fl mice presented efficient deletion of hepatic sEH with corresponding attenuation in sEH activity and alteration in the lipid epoxide/diol ratio. Consistently, hepatic sEH deficiency ameliorated ethanol-induced hepatic injury, inflammation, and steatosis. In addition, targeted metabolomics identified lipid mediators that were impacted significantly by hepatic sEH deficiency. Moreover, hepatic sEH deficiency was associated with a significant attenuation of ethanol-induced hepatic endoplasmic reticulum and oxidative stress. Notably, pharmacologic inhibition of sEH recapitulated the effects of hepatic sEH deficiency and abrogated injury, inflammation, and steatosis caused by ethanol feeding. Conclusions These findings elucidated a role for sEH in ALD and validated a pharmacologic inhibitor of this enzyme in a preclinical mouse model as a potential therapeutic approach., Graphical abstract

Background A distinct serum metabonomic pattern has been previously revealed to be associated with various forms of liver disease. Here, we aimed to apply mass spectrometry to obtain serum metabolomic profiles from individuals with cholangiocarcinoma and benign hepatobiliary diseases to gain an insight into pathogenesis and search for potential early-disease biomarkers. Methods Serum samples were profiled using a hydrophilic interaction liquid chromatography platform, coupled to a mass spectrometer. A total of 47 serum specimens from 8 cholangiocarcinoma cases, 20 healthy controls, 8 benign disease controls (bile duct strictures) and 11 patients with hepatocellular carcinoma (as malignant disease controls) were included. Data analysis was performed using univariate and multivariate statistics. Results The serum metabolome disparities between the metabolite profiles from healthy controls and patients with hepatobiliary disease were predominantly related to changes in lipid and lipid-derived compounds (phospholipids, bile acids and steroids) and amino acid metabolites (phenylalanine). A metabolic pattern indicative of inflammatory response due to cirrhosis and cholestasis was associated with the disease groups. The abundance of phospholipid metabolites was altered in individuals with liver disease, particularly cholangiocarcinoma, but no significant difference was seen between profiles from patients with benign biliary strictures and cholangiocarcinoma. Conclusion The serum metabolome in cholangiocarcinoma exhibited changes in metabolites related to inflammation, altered energy production and phospholipid metabolism. This study serves to highlight future avenues for biomarker research in large-scale studies.

Graphical abstract, Highlights • Size-based quantification of small heterogeneous proteins using electron microscopy. • Electron microscopy as an orthogonal tool for characterizing protein aggregates. • Quick assessment of small heterogeneous proteins via softEM, a GUI-based algorithm., Aggregation is a critical parameter for protein-based therapeutics, due to its impact on the immunogenicity of the product. The traditional approach towards characterization of such products is to use a collection of orthogonal tools. However, the fact that none of these tools is able to completely classify the distribution and physical characteristics of aggregates, implies that there exists a need for additional analytical methods. We report one such method for characterization of heterogeneous population of proteins using transmission electron microscopy. The method involves semi-automated, size-based clustering of different protein species from micrographs. This method can be utilized for quantitative characterization of heterogeneous populations of antibody/protein aggregates from TEM images of proteins, and may also be applicable towards other instances of protein aggregation.

Graphical abstract, Highlights • We proposed a doc2vec + RF classifier for predicting human-virus PPIs. • Doc2vec can effectively capture more context information from protein sequences. • The proposed method revealed better performance than several existing predictors., The identification of human-virus protein-protein interactions (PPIs) is an essential and challenging research topic, potentially providing a mechanistic understanding of viral infection. Given that the experimental determination of human-virus PPIs is time-consuming and labor-intensive, computational methods are playing an important role in providing testable hypotheses, complementing the determination of large-scale interactome between species. In this work, we applied an unsupervised sequence embedding technique (doc2vec) to represent protein sequences as rich feature vectors of low dimensionality. Training a Random Forest (RF) classifier through a training dataset that covers known PPIs between human and all viruses, we obtained excellent predictive accuracy outperforming various combinations of machine learning algorithms and commonly-used sequence encoding schemes. Rigorous comparison with three existing human-virus PPI prediction methods, our proposed computational framework further provided very competitive and promising performance, suggesting that the doc2vec encoding scheme effectively captures context information of protein sequences, pertaining to corresponding protein-protein interactions. Our approach is freely accessible through our web server as part of our host-pathogen PPI prediction platform (http://zzdlab.com/InterSPPI/). Taken together, we hope the current work not only contributes a useful predictor to accelerate the exploration of human-virus PPIs, but also provides some meaningful insights into human-virus relationships.

Highlights • A novel taxol-producing A. fumigatus strain explored from the Northern Himalayan region. • dbat and ITS genes were used as molecular markers for screening and identification. • Hyper-production (1.6 g/L) of taxol in S7 medium, highest from an endophytic fungus., Taxol® (generic name Paclitaxel) is a chemotherapeutic drug, effective against head, neck, breast, lung, bladder, ovary, and cervix cancers. Rising demands in chemotherapy and limited supply of natural taxol have ultimately increased the cost of the drug. Semi synthesis using taxol precursors is not able to meet the global supply and has intensified the need to find alternative ways of taxol production. In the present study, 34 different endophytes were isolated from Taxus sp. collected from Shimla, Himachal Pradesh (India). Primary screening of taxol-producing fungi was carried out based on the presence of dbat gene, essential for the taxol biosynthetic pathway. A fungal isolate TPF-06 was screened to be a taxol-producing strain based on the PCR amplification results. It was characterized and identified as Aspergillus fumigatus by 18S rRNA (Accession No. KU-837249). Multiple sequence alignment (MSA) of nuclear ribosomal internal transcribed spacer (ITS) region and phylogenetic analysis confirmed that strain belonged to A. fumigatus clade (Accession No. MF-374798) and is endophytic in nature. Presence of taxol was detected and quantified by High-Performance Liquid Chromatography (HPLC) and characterized by using Thin Layer Chromatography (TLC), Ultraviolet (UV) spectroscopy, Mass spectrometry (MS), Fourier-Transform Infrared Spectroscopy (FTIR) and Nuclear Magnetic Resonance (NMR) spectroscopy. Microbial fermentation in the S7 medium yielded 1.60 g/L of taxol, which to the best of our knowledge is the highest taxol production from an endophytic fungus. Findings of the present study suggest that the A. fumigatus is an excellent alternate source for taxol supply, and it may become a highly potent strain on a commercial scale. The involvement of dbat gene in A. fumigatus KU-837249 strain further suggested a way of increasing taxol yield in fungi by medium engineering and recombinant DNA technology in the future.

Mutations in the human SLC26A4/Pendrin polypeptide (hPDS) cause Pendred Syndrome /DFNB4, syndromic deafness with enlargement of the vestibular aqueduct and low-penetrance goiter. Here we present data on cloning, protein overexpression and purification, refolding, and biophysical characterization of the recombinant hPDS STAS domain lacking its intrinsic variable sequence (STAS-ΔIVS). We report a reproducible protein refolding protocol enabling milligram scale expression and purification of uniformly 15N- and 13C/15N-enriched hPDS STAS-ΔIVS domain suitable for structural characterization by solution NMR. Circular dichroism, one-dimensional 1H, two-dimensional 1H–15N HSQC, and 1H–13C HSQC NMR spectra confirmed the well-folded state of purified hPDS STAS-ΔIVS in solution. Heteronuclear NMR chemical shift perturbation of select STAS-ΔIVS residues by GDP was observed at fast-to-intermediate NMR time scales. Intrinsic tryptophan fluorescence quench experiments demonstrated GDP binding to hPDS STAS-ΔIVS with Kd of 178 μM. These results are useful for structure/function characterization of hPDS STAS, the cytoplasmic subdomain of the congenital deafness protein, pendrin, as well as for studies of other mammalian STAS domains., Highlights • Reproducible protein refolding protocol for human pendrin STAS domain. • Milligram scale purification of uniformly 15N- and 13C/15N-enriched protein. • Protein adopts folded conformation in solution. • Heteronuclear NMR and fluorescence demonstrate protein binding to GDP.

Genetic engineering is a powerful tool to steer bio-oil composition towards the production of speciality chemicals such as guaiacols, syringols, phenols, and vanillin through well-defined biomass feedstocks. Our previous work demonstrated the effects of lignin biosynthesis gene modification on the pyrolysis vapour compositions obtained from wood derived from greenhouse-grown poplars. In this study, field-grown poplars downregulated in the genes encoding CINNAMYL ALCOHOL DEHYDROGENASE (CAD), CAFFEIC ACID O-METHYLTRANSFERASE (COMT) and CAFFEOYL-CoA O-METHYLTRANSFERASE (CCoAOMT), and their corresponding wild type were pyrolysed in a Py-GC/MS. This work aims at capturing the effects of downregulation of the three enzymes on bio-oil composition using principal component analysis (PCA). 3,5-methoxytoluene, vanillin, coniferyl alcohol, 4-vinyl guaiacol, syringol, syringaldehyde, and guaiacol are the determining factors in the PCA analysis that are the substantially affected by COMT, CAD and CCoAOMT enzyme downregulation. COMT and CAD downregulated transgenic lines proved to be statistically different from the wild type because of a substantial difference in S and G lignin units. The sCAD line lead to a significant drop (nearly 51%) in S-lignin derived compounds, while CCoAOMT downregulation affected the least (7–11%). Further, removal of extractives via pretreatment enhanced the statistical differences among the CAD transgenic lines and its wild type. On the other hand, COMT downregulation caused 2-fold reduction in S-derived compounds compared to G-derived compounds. This study manifests the applicability of PCA analysis in tracking the biological changes in biomass (poplar in this case) and their effects on pyrolysis-oil compositions., Graphical Abstract Unlabelled Image