Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. Colorectal adenomatous polyps are at high risk for the development of CRC. In this report, we described the metabolic changes in the sera from patients with colorectal polyps and CRC by using the NMR-based metabolomics. 110 serum samples were collected from patients and healthy controls, including 40 CRC patients, 32 colorectal polyp patients, and 38 healthy controls. The metabolic profiles and differential metabolites of sera were analyzed by multivariate statistical analysis (MSA), including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) methods. A total of 23 differential metabolites were identified from MSA. According to the pathway analysis and multivariate ROC curve-based exploratory analysis by using the relative concentrations of differential metabolites, we found abnormal metabolic pathways and potential biomarkers involved with the colorectal polyp and CRC. The results showed that the pyruvate metabolism and glycerolipid metabolism were activated in colorectal polyps. And the glycolysis and glycine, serine, and threonine metabolism were activated in CRC. The changed metabolism may promote cellular proliferation. In addition, we found that the rates of acetate/glycerol and lactate/citrate could be the potential biomarkers in colorectal polyp and CRC, respectively. The application of 1H-NMR metabolomics analysis in serum has interesting potential as a new detection and diagnostic tool for early diagnosis of CRC.

BackgroundAmbiguity in malignant transformation of glioma has made prognostic diagnosis very challenging. Tumor malignant transformation is closely correlated with specific alterations of the metabolic profile. Exploration of the underlying metabolic alterations in glioma cells of different malignant degree is therefore vital to develop metabolic biomarkers for prognosis monitoring.MethodsWe conducted 1H nuclear magnetic resonance (NMR)-based metabolic analysis on cell lines (CHG5, SHG44, U87, U118, U251) developed from gliomas of different malignant grades (WHO II and WHO IV). Several methods were applied to analyze the 1H-NMR spectral data of polar extracts of cell lines and to identify characteristic metabolites, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), fuzzy c-means clustering (FCM) analysis and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). The expression analyses of glial fibrillary acidic protein (GFAP) and matrix metal proteinases (MMP-9) were used to assess malignant behaviors of cell lines. GeneGo pathway analysis was used to associate characteristic metabolites with malignant behavior protein markers GFAP and MMP-9.ResultsStable and distinct metabolic profiles of the five cell lines were obtained. The metabolic profiles of the low malignancy grade group (CHG5, SHG44) were clearly distinguished from those of the high malignancy grade group (U87, U118, U251). Seventeen characteristic metabolites were identified that could distinguish the metabolic profiles of the two groups, nine of which were mapped to processes related to GFAP and MMP-9. Furthermore, the results from both quantitative comparison and metabolic correlation analysis indicated that the significantly altered metabolites were primarily involved in perturbation of metabolic pathways of tricarboxylic acid (TCA) cycle anaplerotic flux, amino acid metabolism, anti-oxidant mechanism and choline metabolism, which could be correlated with the changes in the glioma cells’ malignant behaviors.ConclusionsOur results reveal the metabolic heterogeneity of glioma cell lines with different degrees of malignancy. The obtained metabolic profiles and characteristic metabolites are closely associated with the malignant features of glioma cells, which may lay the basis for both determining the molecular mechanisms underlying glioma malignant transformation and exploiting non-invasive biomarkers for prognosis monitoring.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-4598-13-197) contains supplementary material, which is available to authorized users.

The cyclic nucleotide-gated channel (CNGC) family is involved in the uptake of various cations, such as Ca(2+), to regulate plant growth and respond to biotic and abiotic stresses. However, there is far less information about this family in woody plants such as pear. Here, we provided a genome-wide identification and analysis of the CNGC gene family in pear. Phylogenetic analysis showed that the 21 pear CNGC genes could be divided into five groups (I, II, III, IVA and IVB). The majority of gene duplications in pear appeared to have been caused by segmental duplication and occurred 32.94-39.14 million years ago. Evolutionary analysis showed that positive selection had driven the evolution of pear CNGCs. Motif analyses showed that Group I CNGCs generally contained 26 motifs, which was the greatest number of motifs in all CNGC groups. Among these, eight motifs were shared by each group, suggesting that these domains play a conservative role in CNGC activity. Tissue-specific expression analysis indicated that functional diversification of the duplicated CNGC genes was a major feature of long-term evolution. Our results also suggested that the P-S6 and PBC & hinge domains had co-evolved during the evolution. These results provide valuable information to increase our understanding of the function, evolution and expression analyses of the CNGC gene family in higher plants.

Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gastritis, GS; low-grade gastric dysplasia, LGD; high-grade gastric dysplasia, HGD; GC) and the normal control group (CON). The metabolic profiles of the five groups were clearly distinguished from each other. Furthermore, significant inter-metabolite correlations were extracted and used to reconstruct perturbed metabolic networks associated with the four pathological stages compared with the normal stage. Then, significantly altered metabolic pathways were identified by pathway analysis. Our results showed that oxidative stress-related metabolic pathways, choline phosphorylation and fatty acid degradation were continually disturbed during gastric carcinogenesis. Moreover, amino acid metabolism was perturbed dramatically in gastric dysplasia and GC. The GC stage showed more changed metabolite levels and more altered metabolic pathways. Two activated pathways (glycolysis; glycine, serine and threonine metabolism) substantially contributed to the metabolic alterations in GC. These results lay the basis for addressing the molecular mechanisms underlying gastric carcinogenesis and extend our understanding of GC progression.

Zeolite imidazolate framework-8 (ZIF-8) nanoparticles embedded in TiN/Ti/Si nanorod (NR) arrays without pyrolysis have shown increased energy storage capacity as anodes for lithium ion batteries (LIBs). A high capacity of 1650 μAh cm(-2) has been achieved in this ZIF-8 composited multilayered electrode, which is ∼100 times higher than the plain electrodes made of only silicon NR. According to the electrochemical impedance spectroscopy (EIS) and (1)H nuclear magnetic resonance (NMR) characterizations, the improved diffusion of lithium ions in ZIF-8 and boosted electron/Li(+) transfer by the ZIF-8/TiN/Ti multilayer coating are proposed to be responsible for the enhanced energy storage ability. The first-principles calculations further indicate the favorable accessibility of lithium with appropriate size to diffuse in the open pores of ZIF-8. This work broadens the application of ZIF-8 to silicon-based LIBs electrodes without the pyrolysis and provides design guidelines for other metal-organic frameworks/Si composite electrodes.