The intratumor mycobiome promotes lung cancer progression via myeloid-derived suppressor cells.

Although polymorphic microbiomes have emerged as hallmarks of cancer, far less is known about the role of the intratumor mycobiome as living microorganisms in cancer progression. Here, using fungi-enriched DNA extraction and deep shotgun metagenomic sequencing, we have identified enriched tumor-resident Aspergillus sydowii in patients with lung adenocarcinoma (LUAD). By three different syngeneic lung cancer mice models, we find that A. sydowii promotes lung tumor progression via IL-1ß-mediated expansion and activation of MDSCs, resulting in suppressed activity of cytotoxic T lymphocyte cells and accumulation of PD-1+ CD8+ T cells. This is mediated by IL-1ß secretion via ß-glucan/Dectin-1/CARD9 pathway. Analysis of human samples confirms that enriched A. sydowii is associated with immunosuppression and poor patient outcome. Our findings suggest that intratumor mycobiome, albeit at low biomass, promotes lung cancer progression and could be targeted at the strain level to improve patients with LUAD outcome.

The hierarchical assembly of a multi-level DNA ring-based nanostructure in a precise order and its application for screening tumor cells.

DNA nanotechnology can be used to precisely construct nanostructures of different shapes, sizes and surface chemistry, which is appreciated in a variety of areas such as biomaterials, nanodevices, disease diagnosis, imaging, and drug delivery. Enzymatic degradation resistance and cell-targeting capability are indispensable for the applications of DNA nanostructures in biological and biomedical fields, and is challenging to rationally design the desirable nanoscale DNA materials suitable for the clinical translation by the existing assembly methodologies. Herein, we present a simple and efficient method for the hierarchical assembly of a three-level DNA ring-based nanostructure (DNA h-Nanoring) in a precise order, where DNA compositions at the primary level, the second level and the third level are a single DNA ring, two-ring-hybridized duplex and uniform complex macro-cycle, respectively. Most as-assembled DNA h-Nanorings exhibit the regular two-dimensional cycle-shaped structure characterized by atomic force microscopy (AFM). The Nanoring exhibits a significantly enhanced resistance to enzymatic attack, such that it can remain intact in 10% fetal bovine serum (FBS) for 24 h, and even stably exist in the presence of nuclease at a high concentration. More importantly, it is very easy to modify the DNA h-Nanoring with functional moieties (e.g., targeting ligand aptamer) because there are many single-stranded fragments available for further hybridization. By combining with receptor-targeted Sgc8, the nanoring can be used to accomplish the cell imaging and criminate target CEM cells from control cells, demonstrating a potential platform for in vivo tumor imaging and targeted chemotherapeutics delivery.

Snail1-dependent p53 repression regulates expansion and activity of tumour-initiating cells in breast cancer.

The zinc-finger transcription factor Snail1 is inappropriately expressed in breast cancer and associated with poor prognosis. While interrogating human databases, we uncovered marked decreases in relapse-free survival of breast cancer patients expressing high Snail1 levels in tandem with wild-type, but not mutant, p53. Using a Snail1 conditional knockout model of mouse breast cancer that maintains wild-type p53, we find that Snail1 plays an essential role in tumour progression by controlling the expansion and activity of tumour-initiating cells in preneoplastic glands and established tumours, whereas it is not required for normal mammary development. Growth and survival of preneoplastic as well as neoplastic mammary epithelial cells is dependent on the formation of a Snail1/HDAC1/p53 tri-molecular complex that deacetylates active p53, thereby promoting its proteasomal degradation. Our findings identify Snail1 as a molecular bypass that suppresses the anti-proliferative and pro-apoptotic effects exerted by wild-type p53 in breast cancer.

Responses of growth inhibition and antioxidant gene expression in earthworms (Eisenia fetida) exposed to tetrabromobisphenol A, hexabromocyclododecane and decabromodiphenyl ether.

Tetrabromobisphenol A (TBBPA), hexabromocyclododecane (HBCD) and decabromodiphenyl ether (BDE 209), suspected ubiquitous contaminants, account for the largest volume of brominated flame retardants (BFRs) since penta-BDE and octa-BDE have been phased out globally. In this paper, the growth inhibition and gene transcript levels of antioxidant enzymes (superoxide dismutase (SOD), catalase (CAT)) and the stress-response gene involved in the prevention of oxidative stress (Hsp70) of earthworms (Eisenia fetida) exposed to TBBPA, HBCD and BDE 209 were measured to identify the toxicity effects of selected BFRs on earthworms. The growth of earthworms treated by TBBPA at 200 and 400 mg/kg dw were inhibited at rate of 13.7% and 22.0% respectively, while there was no significant growth inhibition by HBCD and BDE 209. A significant (P<0.01) up-regulation of SOD expression level was observed in earthworms exposed to TBBPA at 50 mg/kg dw (1.77-fold) and to HBCD at 400 mg/kg dw (2.06-fold). The transcript level of Hsp70 gene was significantly up-regulated (P<0.01) when earthworms exposed to TBBPA at concentration of 50-200 mg/kg (2.16-2.19-fold) and HBCD at 400 mg/kg (2.61-fold). No significant variation of CAT gene expression in all the BFRs treatments was observed, neither does all the target gene expression level exposed to BDE 209. Assessed by growth inhibition and the changes at mRNA levels of encoding genes in earthworms, TBBPA showed the greatest toxicity, followed by HBCD and BDE 209, consistent with trends in molecular properties. The results help to understand the molecular mechanism of antioxidant defense.

Growth inhibition and altered gene transcript levels in earthworms (Eisenia fetida) exposed to 2,2',4,4'-tetrabromodiphenyl ether.

The toxic effects of the ubiquitous pollutant 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) on the earthworm Eisenia fetida were assessed by determining growth-inhibition and gene transcript levels of superoxide dismutase (SOD), catalase (CAT), glutathione transferase (GST), and transcriptional changes of the stress-response gene (heat-shock protein 70 [Hsp70]). Somatic growth and growth-inhibition rates in all BDE-47-treated groups were significantly different from those of the controls. The SOD gene transcripts were upregulated at all exposure doses and reached the maximum at the concentration of 400 mg/kg dry weight (dw) (3.84-fold, P < 0.01), which protected earthworms from oxidative stresses. However, downregulation of CAT and Hsp70 was present in all exposure doses and reached to the minimum at concentrations of 400 mg/kg dw (0.07-fold, P < 0.01 and 0.06-fold, P < 0.01, respectively). Upregulation of GST gene transcript level presented significant changes at concentrations of 10 (2.69-fold, P < 0.05) and 100 mg/kg dw (2.55-fold, P < 0.05). SOD maintained a dynamic balance to upregulate SOD expression to eliminate superoxide radicals in all dosage treatments, but downregulation of CAT decreased the ability to eliminate hydrogen peroxide. These changes could result in biochemical and physiological disturbances in earthworms.

Predicting protein structural class by incorporating patterns of over-represented k-mers into the general form of Chou's PseAAC.

Computational prediction of protein structural class based on sequence data remains a challenging problem in current protein science. In this paper, a new feature extraction approach based on relative polypeptide composition is introduced. This approach could take into account the background distribution of a given k-mer under a Markov model of order k-2, and avoid the curse of dimensionality with the increase of k by using a T-statistic feature selection strategy. The selected features are then fed to a support vector machine to perform the prediction. To verify the performance of our method, jackknife cross-validation tests are performed on four widely used benchmark datasets. Comparison of our results with existing methods shows that our method provides satisfactory performance for structural class prediction.

Prediction of protein subcellular multi-localization based on the general form of Chou's pseudo amino acid composition.

Many proteins bear multi-locational characteristics, and this phenomenon is closely related to biological function. However, most of the existing methods can only deal with single-location proteins. Therefore, an automatic and reliable ensemble classifier for protein subcellular multi-localization is needed. We propose a new ensemble classifier combining the KNN (K-nearest neighbour) and SVM (support vector machine) algorithms to predict the subcellular localization of eukaryotic, Gram-negative bacterial and viral proteins based on the general form of Chou's pseudo amino acid composition, i.e., GO (gene ontology) annotations, dipeptide composition and AmPseAAC (Amphiphilic pseudo amino acid composition). This ensemble classifier was developed by fusing many basic individual classifiers through a voting system. The overall prediction accuracies obtained by the KNN-SVM ensemble classifier are 95.22, 93.47 and 80.72% for the eukaryotic, Gram-negative bacterial and viral proteins, respectively. Our prediction accuracies are significantly higher than those by previous methods and reveal that our strategy better predicts subcellular locations of multi-location proteins.

Synthesis of alkyl and aryl C-pyranosides using organozinc reagents via a Ferrier-type rearrangement.

The reaction of 1,2-dihydropyranyl acetates with dimethylzinc, diethylzinc and diphenylzinc in the presence of CF3COOH gave the corresponding alky and aryl C-pyranosides via a Ferrier rearrangement in excellent yields. Use of the organozinc species, CF3CO2ZnPh, reacted with high stereoselectivity to give the phenyl C-glycosides. Arylzinc chlorides could also be successfully applied to this reaction in the presence of BF3.OEt2.