Metformin, the most prescribed antidiabetic medicine, has shown other benefits such as anti-ageing and anticancer effects1–4. For clinical doses of metformin, AMP-activated protein kinase (AMPK) has a major role in its mechanism of action4,5; however, the direct molecular target of metformin remains unknown. Here we show that clinically relevant concentrations of metformin inhibit the lysosomal proton pump v-ATPase, which is a central node for AMPK activation following glucose starvation6. We synthesize a photoactive metformin probe and identify PEN2, a subunit of γ-secretase7, as a binding partner of metformin with a dissociation constant at micromolar levels. Metformin-bound PEN2 forms a complex with ATP6AP1, a subunit of the v-ATPase8, which leads to the inhibition of v-ATPase and the activation of AMPK without effects on cellular AMP levels. Knockout of PEN2 or re-introduction of a PEN2 mutant that does not bind ATP6AP1 blunts AMPK activation. In vivo, liver-specific knockout of Pen2 abolishes metformin-mediated reduction of hepatic fat content, whereas intestine-specific knockout of Pen2 impairs its glucose-lowering effects. Furthermore, knockdown of pen-2 in Caenorhabditis elegans abrogates metformin-induced extension of lifespan. Together, these findings reveal that metformin binds PEN2 and initiates a signalling route that intersects, through ATP6AP1, the lysosomal glucose-sensing pathway for AMPK activation. This ensures that metformin exerts its therapeutic benefits in patients without substantial adverse effects.

Hepatitis E virus (HEV), a non-enveloped, positive-stranded RNA virus, is transmitted in a faecal-oral manner, and causes acute liver diseases in humans. The HEV capsid is made up of capsomeres consisting of homodimers of a single structural capsid protein forming the virus shell. These dimers are believed to protrude from the viral surface and to interact with host cells to initiate infection. To date, no structural information is available for any of the HEV proteins. Here, we report for the first time the crystal structure of the HEV capsid protein domain E2s, a protruding domain, together with functional studies to illustrate that this domain forms a tight homodimer and that this dimerization is essential for HEV–host interactions. In addition, we also show that the neutralizing antibody recognition site of HEV is located on the E2s domain. Our study will aid in the development of vaccines and, subsequently, specific inhibitors for HEV.

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Hepatitis E virus (HEV) causes acute hepatitis in humans, predominantly by contamination of food and water, and is characterized by jaundice and flu-like aches and pains. To date, no vaccines are commercially available to prevent the disease caused by HEV. Previously, we showed that a monoclonal antibody, 8C11, specifically recognizes a neutralizing conformational epitope on HEV genotype I. The antibody 8C11 blocks the virus-like particle from binding to and penetrating the host cell. Here, we report the complex crystal structure of 8C11 Fab with HEV E2s(I) domain at 1.9 Å resolution. The 8C11 epitopes on E2s(I) were identified at Asp Mutations and cell-model assays identified Arg 512 as the most crucial residue for 8C11 interaction with and neutralization of HEV. Interestingly, 8C11 specifically neutralizes HEV genotype I, but not the other genotypes. Because HEV type I and IV are the most abundant genotypes, to understand this specificity further we determined the structure of E2s(IV) at 1.79 Å resolution and an E2s(IV) complex with 8C11 model was generated. The comparison between the 8C11 complexes with type I and IV revealed the key residues that distinguish these two genotypes. Of particular interest, the residue at amino acid position 497 at the 8C11 epitope region of E2s is distinct among these two genotypes. Swapping this residue from one genotype to another inversed the 8C11 reactivity, demonstrating the essential role played by amino acid 497 in the genotype recognition. These studies may lead to the development of antibody-based drugs for the specific treatment against HEV.

Methyltransferase-like 1 (METTL1) mediated 7-methylguanosine (m7G) is crucial for the regulation of chemoresistance in cancer treatment. However, the role of METTL1 in regulating chemoresistance of colon cancer (CC) cells to cisplatin is still unclear. This study established the cisplatin-resistant CC (CR-CC) cells and found that METTL1 was low-expressed in CR-CC cells compared to their paired cisplatin-sensitive CC (CS-CC) cells. Besides, overexpressed METTL1 enhanced the cytotoxic effects of cisplatin on CR-CC cells. In addition, miR-149-3p was the downstream target of METTL1, which could be positively regulated by METTL1. Further results validated that miR-149-3p was low-expressed in CR-CC cells comparing to the CS-CC cells. In addition, the promoting effects of overexpressed METTL1 on cisplatin induced CR-CC cell death were abrogated by synergistically knocking down miR-149-3p. Furthermore, S100A4/p53 axis was the downstream target of METTL1 and miR-149-3p, and either overexpressed METTL1 or miR-149-3p increased p53 protein levels in CR-CC cells, which were reversed by upregulating S100A4. Similarly, the promoting effects of overexpressed METTL1 on cisplatin-induced CR-CC cell death were abrogated by overexpressing S100A4. Taken together, overexpression of METTL1 sensitized CR-CC cells to cisplatin by modulating miR-149-3p/S100A4/p53 axis.

Colorectal cancer (CRC) remains an incurable disease. There are no effective noninvasive techniques that have achieved colorectal cancer (CRC) diagnosis, prognosis, survival and recurrence in clinic. To investigate colorectal cancer metabolism, we perform an electronic literature search, from 1998 to January 2016, for studies evaluating the metabolomic profile of patients with CRC regarding the diagnosis, recurrence, prognosis/survival, and systematically review the twenty-three literatures included. QUADOMICS tool was used to assess the quality of them. We highlighted the metabolism perturbations based on metabolites and pathway. Metabolites related to cellular respiration, carbohydrate, lipid, protein and nucleotide metabolism were significantly altered in CRC. Altered metabolites were also related to prognosis, survival and recurrence of CRC. This review could represent the most comprehensive information and summary about CRC metabolism to date. It certificates that metabolomics had great potential on both discovering clinical biomarkers and elucidating previously unknown mechanisms of CRC pathogenesis.

Background: To develop and validate a nomogram based on the conventional measurements and log of odds between the number of positive lymph node and the number of negative lymph node (LODDS) in predicting prognosis for cervical cancer patients after surgery.Methods: A total of 8202 cervical cancer patients with pathologically confirmed between 2004 and 2014 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All the patients were divided into training (n=3603) and validation (n=4599) cohorts based on consecutive age of diagnosis. Demographic and clinical pathological factors were evaluated the association with overall survival (OS). Parameters significantly correlating with OS were used to create a nomogram. An independent external validation cohort was subsequently used to assess the predictive performance of the model.Results: In the training set, age at diagnosis, race, marital status, tumor grade, FIGO stage, histology, size and LODDS were correlated significantly with outcome and used to develop a nomogram. The calibration curve for probability of survival showed excellent agreement between prediction by nomogram and actual observation in the training cohort, with a bootstrap-corrected concordance index of 0.749(95% CI, 0.731-0.767). Importantly, our nomogram performed favorably compared to the currently utilized FIGO model, with concordance indices of 0.786 (95% CI, 0.764 to 0.808) vs 0.685 (95%CI, 0.660 to 0.710) for OS in the validation cohort, respectively.Conclusions: By incorporating LODDS, our nomogram may be superior to the currently utilized FIGO staging system in predicting OS in cervical cancer patients after surgery.

Cervical cancer (CC) still remains a common and deadly malignancy among females in developing countries. More accurate and reliable diagnostic methods/biomarkers should be discovered. In this study, we performed a comprehensive analysis of metabolomics (285 samples) and transcriptomics (52 samples) on the potential diagnostic implication and metabolic characteristic description in cervical cancer. Sixty-two metabolites were different between CC and normal controls (NOR), in which 5 metabolites (bilirubin, LysoPC(17:0), n-oleoyl threonine, 12-hydroxydodecanoic acid and tetracosahexaenoic acid) were selected as candidate biomarkers for CC. The AUC value, sensitivity (SE), and specificity (SP) of these 5 biomarkers were 0.99, 0.98 and 0.99, respectively. We further analysed the genes in 7 significantly enriched pathways, of which 117 genes, that were expressed differentially, were mainly involved in catalytic activity. Finally, a fully connected network of metabolites and genes in these pathways was built, which can increase the credibility of our selected metabolites. In conclusion, our biomarkers from metabolomics could set a path for CC diagnosis and screening. Our results also showed that variables of both transcriptomics and metabolomics were associated with CC.