Improved biohydrogen production by co-fermentation of corn straw and excess sludge: Insights into biochemical process, microbial community and metabolic genes

The global climate change mainly caused by fossil fuels combustion promotes that zero-carbon hydrogen production through eco-friendly methods has attracted attention in recent years. This investigation explored the biohydrogen production by co-fermentation of corn straw (CS) and excess sludge (ES), as well as comprehensively analyzed the internal mechanism. The results showed that the optimal ratio of CS to ES was 9:1 (TS) with the biohydrogen yield of 101.8 mL/g VS, which was higher than that from the mono-fermentation of CS by 1.0-fold. The pattern of volatile fatty acids (VFAs) indicated that the acetate was the most preponderant by-product in all fermentation systems during the biohydrogen production process, and its yield was improved by adding appropriate dosage of ES. In addition, the content of soluble COD (SCOD) was reduced as increasing ES, while concentration of NH4+-N showed an opposite tendency. Microbial community analysis revealed that the microbial composition in different samples showed a significant divergence. Trichococcus was the most dominant bacterial genus in the optimal ratio of 9:1 (CS/ES) fermentation system and its abundance was as high as 41.8%. The functional genes prediction found that the dominant metabolic genes and hydrogen-producing related genes had not been significantly increased in co-fermentation system (CS/ES=9:1) compared to that in the mono-fermentation of CS, implying that enhancement of biohydrogen production by adding ES mainly relied on balancing nutrients and adjusting microbial community in this study. Further redundancy analysis (RDA) confirmed that biohydrogen yield was closely correlated with the enrichment of Trichococcus.

Impact of nanoplastics on the biodegradation, ecotoxicity, and key genes involved in imidacloprid metabolic pathways in papyrus (Cyperus papyrus L.)

Both nanoplastics (NPs) and imidacloprid (IMI) are widely distributed in the environment and have attracted significant attention due to their adverse effects on ecosystems. Constructed wetlands have the potential to remove IMI, but there is still limited understanding of how wetland plants interact with IMI, especially when influenced by different charged NPs. This study assessed their ecotoxicological effects, as well as the fate and transformation of IMI in papyrus (Cyperus papyrus L.) under the influence of different charged NPs and identified key driving genes in the plant. Results show that simultaneous exposure to positively charged PS-NH2 and IMI inhibited plant growth. The combined action of NPs and IMI intensified their toxicity, enhancing lipid peroxidation and altering antioxidant enzyme activities. The IMI removal efficiency, which was primarily driven by biodegradation, was 80.61%, 88.91%, and 74.71% in the IMI-alone, co-IMI/PS_COOH, and co-IMI/PS_NH2 systems, respectively. PS-NH2 restricted the roots-to-shoots translocation ability of IMI. PS-COOH enhanced IMI oxidation and nitro reduction, while PS-NH2 inhibited 2-OH-IMI dehydrogenation to IMI-olefin in papyrus. Transcriptomics and gene network analysis identified the genes encoding CYP450 enzymes, reductases, hydrolases, dehydrogenases, and peroxidases as those influencing IMI biodegradation. These enzymes play a crucial role in the hydroxylation, dehydrogenation, reduction, and oxidation processes during biodegradation of IMI in the presence of NPs. This study expands the understanding of the impact of differently charged NPs on the IMI remediation efficacy of papyrus, thus providing new insights into the phytoremediation of organic contaminants in constructed wetlands.

Metabolic causes of pediatric developmental & epileptic encephalopathies (DEE)- genetic variant analysis in a south Indian cohort

PURPOSE

Drug-resistant epilepsy is seen in patients with inborn errors of metabolism and metabolic dysfunction in neurons is crucial to brain disorders associated with psychomotor impairment. Diagnostic rates of metabolic causes of developmental and epileptic encephalopathy (DEE) using next generation sequencing have been rarely studied in literature.

METHODS

A prospective hospital study was carried out in 384 children with DEE, who underwent genetic testing. Metabolic disorders were evaluated with biochemical blood/urine assays and when required CSF estimations performed.

RESULTS

A total of 154 pathogenic/likely pathogenic variants in 384 children were identified. Out of 384 children, 89 were clinically suspected to have probable or possible metabolic disorders. Pathogenic/likely pathogenic variants in metabolic genes were identified in 39 out of 89 (43.8 %) and promising VUS in 28 (31.4 %). These included variants for progressive myoclonus epilepsies (21; 53.8 %), DEE with focal/multifocal seizures (8; 20.5 %), generalized epilepsy (5;12.8 %), early myoclonic encephalopathy (2; 5.1 %), LGS (1; 2.6 %) and West syndrome (2; 5.1 %).

CONCLUSION

Our cohort demonstrates for the first time from the Indian subcontinent that identification of metabolic variants can guide investigations and has therapeutic implications in patients with variable DEE phenotypes. A high utility is noted with regard to diagnosis and prognostication, given the low yield of available biochemical tests, indicating cost-effectiveness of this approach.

Identification and validation of an individualized metabolic prognostic signature for predicting the biochemical recurrence of prostate cancer based on the immune microenvironment

BACKGROUND

Prostate cancer (PCa) is the most prevalent genitourinary malignancy in men, with a significant proportion of patients developing biochemical recurrence (BCR) after treatment. The immune microenvironment and metabolic alterations have crucial implications for the tumorigenesis and progression of PCa. Therefore, identifying metabolic genes associated with the immune microenvironment holds promise for predicting BCR and improving PCa prognosis.

METHODS

In this study, ssGSEA and hierarchical clustering analysis were first conducted to evaluate and group PCa samples, followed by the use of the ESTIMATE and CIBERSORT algorithms to characterize the immunophenotypes and tumor microenvironment. The differential metabolic genes (MTGs) between groups were utilized to develop a prognostic-related signature. The predictive performance of the signature was assessed by principal component analysis (PCA), receiver operating characteristic (ROC) curve analysis, survival analysis, and the TIDE algorithm. A miRNA-MTGs regulatory network and predictive nomogram were constructed. Moreover, the expression of prognostic MTGs in PCa was detected by RT‒qPCR.

RESULTS

PCa samples from the TCGA cohort were separated into two groups: the immune-low group and immune-high group. Forty-eight differentially expressed MTGs between the groups were identified, including 37 up-regulated and 11 down-regulated MTGs. Subsequently, CEL, CYP3A4, and PDE6G were identified as the genes most strongly associated with the BCR of PCa patients and these genes were utilized to establish the MTGs-based prognostic signatures. PCA, ROC curves analysis, Kaplan-Meier survival analysis, and the nomogram all showed the good predictive ability of the signature regardless of clinical variables. Furthermore, the MTGs-based signature was indicated as a potential predictive biomarker for immunotherapy response. Nine miRNAs involved in the regulation of prognostic MTGs were determined. In addition to the CEL gene, the PDE6G and CYP3A4 genes were expressed at higher levels in PCa samples.

CONCLUSIONS

The MTGs-based signature represents a novel approach with promising potential for predicting BCR in PCa patients.

Identification of a robust scoring system based on metabolic genes followed by in-depth validation of ATP1A3 in glioma

AIMS

In the past few decades, the prognosis of glioma patients has not significantly improved. Therefore, to provide more precise medical services for glioma patients, it is urgent to identify more clinically meaningful subtypes, establish more robust clinical prediction models, and find more effective therapeutic targets.

MATERIALS AND METHODS

Four distinct metabolic-associated subtypes were identified by the NMF algorithm based on metabolic genes (MEGs). A robust scoring system was constructed based on the differentially expressed genes (DEGs) screened from the four metabolic-associated subtypes with the LASSO regression algorithm and multivariate Cox regression analysis. Further analysis of scoring systems was done by different R packages. In addition, the ATP1A3 gene was screened and bioinformatics analysis of it was conducted on several public websites. GSEA software was utilized to search hallmark signaling pathways closely related to ATP1A3. Cytological experiments were used to investigate the role of ATP1A3 in the malignant progression of glioblastoma (GBM) cells.

KEY FINDINGS

Four metabolic-associated subtypes with significantly different clinicopathological characteristics were identified, and a robust scoring system with outstanding clinical application value was established. In addition, a tumor suppressor gene ATP1A3 was found, which is expected to be a potential therapeutic target for glioma.

SIGNIFICANCE

This study is of great significance in the diagnosis, prognosis, and prediction of the response to immune checkpoint blockers (ICBs) for glioma patients. More importantly, this study found a potential therapeutic target for glioma.

Metabolic genes, a potential predictor of prognosis and immunogenicity of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Many ccRCCs are diagnosed at an advanced stage due to the lack of early symptoms, with a high mortality rate and a poor prognosis. The occurrence and development of ccRCC are closely related to metabolic disorders. This study aims to explore the relationship between metabolic genes and prognosis, immune microenvironment, and tumor development of ccRCC. Using data from TCGA, GEO, and ArrayExpress, we successfully established a risk model (riskScore) based on 4 metabolic genes (MGs) that can accurately predict the prognosis and immune microenvironment of ccRCCs. In addition, we determined the role of PAFAH2 in suppressing tumor cell proliferation and migration in ccRCC in vitro. Our research may shed new light on ccRCC patients' prognosis and treatment management.

Prognostic value of metabolic genes in lung adenocarcinoma via integrative analyses

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common malignant lung tumor. Metabolic pathway reprogramming is an important hallmark of physiologic changes in cancers. However, the mechanisms through which these metabolic genes and pathways function in LUAD as well as their prognostic values have not been fully established.

METHODS

Four publicly available datasets from GEO and TCGA were used to identify differentially expressed genes (DEGs) in LUAD, which were then subjected to GO and KEGG pathway enrichment analysis. Associations between metabolic gene expressions with overall survival, tumor stage, TP53 mutation status, and infiltrated immune cells were investigated. Protein-protein interactions were evaluated using GeneMANIA and Metascape.

RESULTS

By integrating four public datasets, 247 DEGs were identified in LUAD. These DEGs were significantly enriched in regulation of chromosome segregation, centromeric region, and histone kinase activity GO terms, as well as in cell cycle, p53 signaling pathway, metabolic pathways, and other KEGG pathways. Elevated expressions of ten metabolic genes in LUAD were significantly associated with poor survival outcomes. These metabolic genes were highly expressed in more advanced tumor stage and TP53 mutated patients. Moreover, expression levels were significantly correlated with tumor-infiltrating immune cells. PPI interaction analysis revealed that the top 20 genes interacting with each metabolic gene were significantly enriched in DNA replication, response to radiation, and central carbon metabolism in cancer.

CONCLUSION

This study elucidates on molecular changes in metabolic genes in LUAD, which may inform the development of genetically oriented diagnostic approaches and effective treatment options.

Phosphoserine phosphatase as a prognostic biomarker in patients with gastric cancer and its potential association with immune cells

Background

Because of dismal prognosis in gastric cancer, identifying relevant prognostic factors is necessary. Phosphoserine phosphatase (PSPH) exhibits different expression patterns in many cancers and has been reported to affect the prognosis of patients with cancer. In this study, we examined the prognostic role of metabolic gene PSPH in gastric cancer based on the TCGA dataset and our hospital–based cohort cases.

Methods

We collected and analysed RNA-seq data of Pan-cancer and gastric cancer in the TCGA dataset and PSPH expression data obtained from immunohistochemical analysis of 243 patients with gastric cancer from Sun Yat-sen University cancer center. Further, Kaplan–Meier survival analysis and Cox analysis were used to assess the effect of PSPH on prognosis. The ESTIMATE and Cibersort algorithms were used to elucidate the relationship between PSPH and the abundance of immune cells using the TCGA dataset.

Results

We observed that PSPH expression displayed considerably high in gastric cancer and it was significantly associated with inferior prognosis (P = 0.043). Surprisingly, there was a significant relationship between lower immune scores and high expression of PSPH (P < 0.05). Furthermore, patients with a low amount of immune cells exhibited poor prognosis (P = 0.046). The expression of PSPH significantly increased in activated memory CD4 T cells, resting NK cells and M0 macrophages (P = 0.037, < 0.001, and 0.005, respectively).

Conclusions

This study highlighted that PSPH influences the prognosis of patients with gastric cancer, and this is associated with the infiltration of tumour immune cells, indicating that PSPH may be a new immune-related target for treating gastric cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-021-02073-0.

Bioinformatics Analysis of the MicroRNA-Metabolic Gene Regulatory Network in Neuropathic Pain and Prediction of Corresponding Potential Therapeutics

Neuropathic pain (NP) involves metabolic processes that are regulated by metabolic genes and their non-coding regulator genes such as microRNAs (miRNAs). Here, we aimed at exploring the key miRNA signatures regulating metabolic genes involved in NP pathogenesis. We downloaded NP-related data from public databases and identified differentially expressed microRNAs (miRNAs) and mRNAs through differential gene expression analysis. The miRNA target prediction was performed, and integration with the differentially expressed metabolic genes (DEMGs) was used for constructing the miRNA-DEMG network. Subsequently, functional enrichment analysis and protein–protein interaction (PPI) analysis were performed to explore the role of DEMGs in the regulatory network. The drug prediction was performed based on the DEMGs in the miRNA-DEMG network. A total of 8251 differentially expressed mRNAs (4193 upregulated and 4058 downregulated), and 959 differentially expressed miRNAs (455 upregulated and 504 downregulated) were identified. Moreover, after target gene prediction, a miRNA-DEMG network composed of 22 miRNAs and 113 mRNAs was constructed. The network was constituted of 135 nodes and 236 edges. We found that DEMGs in the network were mainly enriched in metabolic pathways and metabolic processes. A total of 1200 drugs were predicted as potential therapeutics for NP based on the differentially expressed genes, while 170 drugs were predicted for the DEMGs in the miRNA-DEMG network. Conclusively, our study predicted drugs that may be effective against the metabolic changes induced by miRNA dysregulation in NP. This information will help further reveal the pathological mechanism of NP and provide more treatment options for NP patients.

Multiple metabolic pathways of enrofloxacin by Lolium perenne L.: Ecotoxicity, biodegradation, and key driven genes

Contamination of fluoroquinolones (FQs) are of emerging concerns because of their adverse effects on environment and humans. This study investigated the ecotoxicological effects, biodegradation, and multiple metabolic pathways of a frequently found FQ, enrofloxacin (ENR) by ryegrass (Lolium perenne L.). Key metabolic genes for driving the metabolism of ENR have been identified using transcriptome profiling of L. perenne and gene network analysis. Toxicity of ENR on ryegrass has been evaluated according to the morphological changes, lipid peroxidation content, and antioxidant enzymatic activities. Moreover, there was 94.33%, 71.58%, 57.22%, and 55.23% removal of 1, 10, 50 and 100 mg L^-1 ENR, respectively, which was mainly achieved by biodegradation according to the mass balance. A biodegradation pathway has been proposed by incorporating mass spectrums of extracted ENR intermediates with their formation dynamics. Analysis of differentially expressed genes (DEGs) and their network unraveled that the genes encoding monooxygenase, oxidative carboxylase, methyltransferase, lyase, hydroxylase, dehydrogenase, and peroxidase were the key functional genes. These enzymes can induce di/hydroxylation, decarboxylation, methylation, and bond and ring cleavage of ENR for its effective degradation. This study demonstrated that ryegrass can be used for efficient treatment of ENR polluted water and extended the understanding of the molecular mechanism of antibiotics' biodegradation in plants.

Selection and validation of differentially expressed metabolic and immune genes in weaned Ghurrah versus crossbred piglets

In the present investigation, differentially expressed genes (DEGs) were studied using RNA sequencing (RNA-seq) technique in porcine peripheral blood mononuclear cells (PBMC) of weaned Ghurrah and crossbred piglets at 3-month age. Transcriptomic analysis was done using three different packages, namely, EBSeq, DESeq2, and edgeR, to identify the DEGs between Ghurrah and crossbred piglets. Total 7717 DEGs were commonly identified by all three packages, out of which 4151 genes found to be up-regulated, and 3566 genes were down-regulated. Functional annotation of these DEGs indicated metabolism as the most commonly enriched category followed by the immune response. Genes related to metabolism and growth were up-regulated in crossbred piglets as compared with Ghurrah piglets, whereas immunity-related genes were up-regulated in Ghurrah piglets elucidating the disease resistance nature of this indigenous breed over crossbred counterparts. Further, eight DEGs, namely, LRP-1, ADCY4, ERRFI1, LDHD, ARG1, OASL, MGARP, and S100A8, were validated by qRT-PCR in a separate set of biological samples and found to be in concordance with RNA-seq results. Finding in the present study provides insight into genes and their molecular mechanisms governing difference in growth performance between Ghurrah and crossbred pigs.

Interaction effects of environmental response gene polymorphisms and benzene exposure on telomere length in shoe-making workers

Benzene is a globally occurring environmental and occupational pollutant that causes leukemia. To better understand telomere length (TL) as a function of benzene toxicity, we recruited 294 shoe-making workers and 102 controls from Wenzhou, China in 2011. Biomarkers of TL, cytokinesis-block micronucleus (MN) frequency, and white blood cells (WBC) were measured. In total, 18 polymorphic sites in environmental response genes, including metabolic and DNA repair genes, were analyzed. Results indicate that benzene exposure led to a longer TL at a threshold of 32 mg/m³-year of cumulative exposure dose (CED). Furthermore, the TL was longer in members of the damaged group, when evaluated for MN frequency (P < 0.001) and reduced WBC (P < 0.001), than in those of the normal group. Workers carrying genotype TT (β = 0.32, P = 0.042) in rs3212986 of ERCC1 and genotype TC (β = 0.24, P = 0.082) in rs1051740 of mEH exon3 were associated with a longer TL as compared to the wild-type group. TA (β = -0.53, P < 0.001) in rs6413432 of CYP2E1 was associated with a shorter TL. Benzene exposure interacted with the TA type in rs6413432 (β = 0.003, 95% CI: 0, 0.006, P = 0.042) and the CC type in rs1051740 (β = 0.007, 95% CI: 0.001, 0.013, P = 0.015) after adjusting for confounding factors. Our results indicate that benzene induces an increase in TL at a threshold of CED ≥32mg/m³-year. Rs1051740, rs3212986, and rs6413432 were found to be involved in benzene-induced telomere growth; in particular, rs1051740 and rs6413432 interacted with the benzene exposure, resulting in an extended TL.

Investigating the molecular basis of multiple insecticide resistance in a major malaria vector Anopheles funestus (sensu stricto) from Akaka-Remo, Ogun State, Nigeria

Background

Understanding the mechanisms used by Anopheles mosquitoes to survive insecticide exposure is key to manage existing insecticide resistance and develop more suitable insecticide-based malaria vector control interventions as well as other alternative integrated tools. To this regard, the molecular basis of permethrin, DDT and dieldrin resistance in Anopheles funestus (sensu stricto) at Akaka-Remo was investigated.

Methods

Bioassays were conducted on 3–5-day-old adult An. funestus (s.s.) mosquitoes for permethrin, DDT and dieldrin susceptibility test. The molecular mechanisms of mosquito resistance to these insecticides were investigated using microarray and reverse transcriptase PCR techniques. The voltage-gated sodium channel region of mosquitoes was also screened for the presence of knockdown resistance mutations (kdr west and east) by sequencing method.

Results

Anopheles funestus (s.s.) population was resistant to permethrin (mortality rate of 68%), DDT (mortality rate of 10%) and dieldrin (mortality rate of 8%) insecticides. Microarray and RT-PCR analyses revealed the overexpression of glutathione S-transferase genes, cytochrome P450s, esterase, trypsin and cuticle proteins in resistant mosquitoes compared to control. The GSTe2 was the most upregulated detoxification gene in permethrin-resistant (FC = 44.89), DDT-resistant (FC = 57.39) and dieldrin-resistant (FC = 41.10) mosquitoes compared to control population (FC = 22.34). The cytochrome P450 gene, CYP6P9b was also upregulated in both permethrin- and DDT-resistant mosquitoes. The digestive enzyme, trypsin (hydrolytic processes) and the cuticle proteins (inducing cuticle thickening leading to reduced insecticides penetration) also showed high involvement in insecticide resistance, through their overexpression in resistant mosquitoes compared to control. The kdr east and west were absent in all mosquitoes analysed, suggesting their non-involvement in the observed mosquito resistance.

Conclusions

The upregulation of metabolic genes, especially the GSTe2 and trypsin, as well as the cuticle proteins is driving insecticide resistance of An. funestus (s.s.) population. However, additional molecular analyses, including functional metabolic assays of these genes as well as screening for a possible higher cuticular hydrocarbon and lipid contents, and increased procuticle thickness in resistant mosquitoes are needed to further describe their distinct roles in mosquito resistance.

Dataset on the effect of Benzene exposure on genetic damage, hematotoxicity, telomere length and polymorphisms in metabolic and DNA repair genes

In this paper, we present an occupational dataset to evaluate benzene exposure on the effective biomarkers of genetic damage, indicated as cytokinesis-block micronucleus (MN) frequency, hematotoxicity, indicated as white blood cells (WBC) counts, and molecular marker of telomere length (TL). And we further to eliminate the mechanism of benzene induced damage. Then evaluate the effects of sites polymorphism in environmental response genes, including 18 sites in metabolic and DNA repair genes, and the interaction between gene polymorphism and benzene exposure. This dataset is supplementary to the submitted research by [1] focused on the biomarkers TL, and a detailed description of the subjects sampling, biomarkers detection, data analysis and discussion are discussed in detail.

Lack of hepcidin expression attenuates steatosis and causes fibrosis in the liver

AIM: To investigate the role of key iron-regulatory protein, hepcidin in non-alcoholic fatty liver disease (NAFLD).

METHODS: Hepcidin (Hamp1) knockout and floxed control mice were administered a high fat and high sucrose (HFS) or a regular control diet for 3 or 7 mo. Steatosis, triglycerides, fibrosis, protein and gene expression in mice livers were determined by histological and biochemical techniques, western blotting and real-time polymerase chain reaction.

RESULTS: Knockout mice exhibited hepatic iron accumulation. Despite similar weight gains, HFS feeding induced hepatomegaly in floxed, but not knockout, mice. The livers of floxed mice exhibited higher levels of steatosis, triglycerides and c-Jun N-terminal kinase (JNK) phosphorylation than knockout mice. In contrast, a significant increase in fibrosis was observed in knockout mice livers within 3 mo of HFS administration. The hepatic gene expression levels of sterol regulatory element-binding protein-1c and fat-specific protein-27, but not peroxisome proliferator-activated receptor-alpha or microsomal triglyceride transfer protein, were attenuated in HFS-fed knockout mice. Knockout mice fed with regular diet displayed increased carnitine palmitoyltransferase-1a and phosphoenolpyruvate carboxykinase-1 but decreased glucose-6-phosphatase expression in the liver. In summary, attenuated steatosis correlated with decreased expression of lipogenic and lipid storage genes, and JNK phosphorylation. Deletion of Hamp1 alleles per se modulated hepatic expression of beta-oxidation and gluconeogenic genes.

CONCLUSION: Lack of hepcidin expression inhibits hepatic lipid accumulation and induces early development of fibrosis following high fat intake. Hepcidin and iron may play a role in the regulation of metabolic pathways in the liver, which has implications for NAFLD pathogenesis.

Expression of calcification and metabolism-related genes in response to elevated pCO2 and temperature in the reef-building coral Acropora millepora

Declining health of scleractinian corals in response to deteriorating environmental conditions is widely acknowledged, however links between physiological and functional genomic responses of corals are less well understood. Here we explore growth and the expression of 20 target genes with putative roles in metabolism and calcification in the branching coral, Acropora millepora, in two separate experiments: 1) elevated pCO2 (464, 822, 1187 and 1638 μatm) and ambient temperature (27°C), and 2) elevated pCO2 (490 and 822 μatm) and temperature (28 and 31 °C). After 14 days of exposure to elevated pCO2 and ambient temperatures, no evidence of differential expression of either calcification or metabolism genes was detected between control and elevated pCO2 treatments. After 37 days of exposure to control and elevated pCO2, Ubiquinol-Cytochrome-C Reductase Subunit 2 gene (QCR2; a gene involved in complex III of the electron chain transport within the mitochondria and critical for generation of ATP) was significantly down-regulated in the elevated pCO2 treatment in both ambient and elevated temperature treatments. Overall, the general absence of a strong response to elevated pCO2 and temperature by the other 19 targeted calcification and metabolism genes suggests that corals may not be affected by these stressors on longer time scales (37 days). These results also highlight the potential for QCR2 to act as a biomarker of coral genomic responses to changing environments.

Maternal-fetal metabolic gene-gene interactions and risk of neural tube defects

Single-gene analyses indicate that maternal genes associated with metabolic conditions (e.g., obesity) may influence the risk of neural tube defects (NTDs). However, to our knowledge, there have been no assessments of maternal-fetal metabolic gene-gene interactions and NTDs. We investigated 23 single nucleotide polymorphisms among 7 maternal metabolic genes (ADRB3, ENPP1, FTO, LEP, PPARG, PPARGC1A, and TCF7L2) and 2 fetal metabolic genes (SLC2A2 and UCP2). Samples were obtained from 737 NTD case-parent triads included in the National Birth Defects Prevention Study for birth years 1999-2007. We used a 2-step approach to evaluate maternal-fetal gene-gene interactions. First, a case-only approach was applied to screen all potential maternal and fetal interactions (n = 76), as this design provides greater power in the assessment of gene-gene interactions compared to other approaches. Specifically, ordinal logistic regression was used to calculate the odds ratio (OR) and 95% confidence interval (CI) for each maternal-fetal gene-gene interaction, assuming a log-additive model of inheritance. Due to the number of comparisons, we calculated a corrected p-value (q-value) using the false discovery rate. Second, we confirmed all statistically significant interactions (q < 0.05) using a log-linear approach among case-parent triads. In step 1, there were 5 maternal-fetal gene-gene interactions with q < 0.05. The "top hit" was an interaction between maternal ENPP1 rs1044498 and fetal SLC2A2 rs6785233 (interaction OR = 3.65, 95% CI: 2.32-5.74, p = 2.09×10(-8), q=0.001), which was confirmed in step 2 (p = 0.00004). Our findings suggest that maternal metabolic genes associated with hyperglycemia and insulin resistance and fetal metabolic genes involved in glucose homeostasis may interact to increase the risk of NTDs.

Emerging roles of the ribonucleotide reductase M2 in colorectal cancer and ultraviolet-induced DNA damage repair

AIM

To investigate the roles of the ribonucleotide reductase M2 (RRM2) subunit in colorectal cancer (CRC) and ultraviolet (UV)-induced DNA damage repair.

METHODS

Immunohistochemical staining of tissue microarray was performed to detect the expression of RRM2. Seven CRC cell lines were cultured and three human colon cancer cell lines, i.e., HCT116, SW480 and SW620, were used. Reverse transcription polymerase chain reaction and Western blotting were performed to determine the mRNA and protein expression levels of RRM2, respectively. Cell proliferation assay, cell cycle analysis were performed. Cell apoptosis was evaluated by double staining with fluorescein isothiocyanate-conjugated Annexin V and propidium iodide (PI) using Annexin V/PI apoptosis kit. The motility and invasion of CRC cells were assessed by the Transwell chamber assay. Cells were irradiated with a 254 nm UV-C lamp to detect the UV sensitivity after RRM2 depletion.

RESULTS

Immunohistochemical staining revealed elevated RRM2 levels in CRC tissues. RRM2 overexpression was positively correlated with invasion depth (P < 0.05), poorly differentiated type (P = 0.0051), and tumor node metastasis stage (P = 0.0015). The expression of RRM2 in HCT116 cells was downregulated after transfection, and HCT116 cell proliferation was obviously suppressed compared to control groups (P < 0.05). In the invasion test, the number of cells that passed through the chambers in the RRM2-siRNA group was 81 ± 3, which was lower than that in the negative control (289 ± 7) and blank control groups (301 ± 7.2). These differences were statistically significant (P < 0.01). Our data suggest that RRM2 overexpression may be associated with CRC progression. RRM2 silencing by siRNA may inhibit the hyperplasia and invasiveness of CRC cells, suggesting that RRM2 may play an important role in the infiltration and metastasis of CRC, which is a potential therapeutic strategy in CRC. In addition, RRM2 depletion increased UV sensitivity.

CONCLUSION

These findings suggest that RRM2 may be a facilitating factor in colorectal tumorigenesis and UV-induced DNA damage repair.