Evaluation of graphical models for multi-group metabolomics data.

Gaussian graphical model is a strong tool for identifying interactions from metabolomics data based on conditional correlation. However, data may be collected from different stages or subgroups of subjects with heterogeneity or hierarchical structure. There are different integrating strategies of graphical models for multi-group data proposed by data scientists. It is challenging to select the methods for metabolism data analysis. This study aimed to evaluate the performance of several different integrating graphical models for multi-group data and provide support for the choice of strategy for similar characteristic data. We compared the performance of seven methods in estimating graph structures through simulation study. We also applied all the methods in breast cancer metabolomics data grouped by stages to illustrate the real data application. The method of Shaddox et al. achieved the highest average area under the receiver operating characteristic curve and area under the precision-recall curve across most scenarios, and it was the only approach with all indicators ranked at the top. Nevertheless, it also cost the most time in all settings. Stochastic search structure learning tends to result in estimates that focus on the precision of identified edges, while BEAM, hierarchical Bayesian approach and birth-death Markov chain Monte Carlo may identify more potential edges. In the real metabolomics data analysis from three stages of breast cancer patients, results were in line with that in simulation study.

The N6-Methyladenosine (m6A) Methylation Gene YTHDF1 Reveals a Potential Diagnostic Role for Gastric Cancer.

PURPOSE: Gastric cancer (GC) is aggressive cancer with a high mortality rate worldwide. N6-methyladenosine (m6A) RNA methylation is related to tumorigenesis, which is dynamically regulated by m6A modulators ("writer," "eraser," and "reader"). We conducted a comprehensive analysis of the m6A genes of GC patients in TCGA datasets to identify the potential diagnostic biomarkers. MATERIALS AND METHODS: We analyzed the expression profile of m6A genes in the TCGA cohort and constructed a diagnostic-m6A-score (DMS) by the LASSO-logistic model. In addition, by consensus cluster analysis, we identified two different subgroups of GC risk individuals by the expression profile of m6A modulators, revealing that YTHDF1's expression variation profile in GC diagnosis. We also performed RT-qPCR and WB verification in 17 pairs of GC specimens and paired adjacent non-tumor tissues and GC cell lines, and verified the expression trend of YTHDF1 in five GEO GC datasets. YTHDF1 expression and clinical features of GC patients were assessed by the UALCAN. RESULTS: The DMS with high specificity and sensitivity (AUC = 0.986) is proven to distinguish cancer from normal controls better. Moreover, we found that the expression profile variation of YTHDF1 was significantly associated with the high-risk subtype of GC patients. RT-qPCR and Western blot results are consistent with silicon analysis, revealing that YTHDF1's potential oncogene role in GC tumor. CONCLUSION: In conclusion, we developed the m6A gene-based diagnostic signature for GC and found that YTHDF1 was significantly correlated with the high-risk subtype of GC patients, suggesting that YTHDF1 might be a potential target in GC early diagnosis.

Dysregulated N6-methyladenosine methylation writer METTL3 contributes to the proliferation and migration of gastric cancer.

Accumulating evidence implies that N6-methyladenosine (m6A) methylation participated in the tumorigenesis of gastric cancer (GC). Here we synthetically analyzing the prognostic value and expression profile of seven m6A methylation-relevant genes through silico analysis of sequencing data downloaded from The Cancer Genome Atlas, Kaplan-Meier plotter, and Gene Expression Omnibus database. We explored the methyltransferase-like 3 (METTL3) expression in GC cell line and tumor tissues by reverse transcription quantitative polymerase chain reaction and western blot analysis. The m6A methylation status of total RNA was measured by m6A RNA methylation quantification kit. Small interfering RNA was used to establish METTL3 knockdown cell lines. We also measure the proliferation and migration capability GC cell. Furthermore, we detect the epithelial cell mesenchymal transition marker and m6A methylation level after METTL3 knock down. Our result revealed that METTL3 was significantly increased in GC tissues compared with control in big crowd data sets. Survival analysis showed that METTL3 serve as a poor prognostic factor for GC patients. The expression level of METTL3 gradually increased with the progress of tumor stage and grade. GFI1 is an important transcription factor associated with METTL3. We verified the up-trend of METTL3 in messenger RNA and protein expression and observed a significant increase in the m6A methylation status of total RNA in the GC cells and tissues. METTL3 knockdown inhibited total RNA m6A methylation level, as well as cell proliferation and migration capacity. Moreover, METTL3 knockdown decreased α-smooth muscle actin. Taken together, our finding revealed that m6A methylation writer METTL3 serve as an oncogene in tumorigenesis of GC.

Prognostic value of a two-microRNA signature for papillary thyroid cancer and a bioinformatic analysis of their possible functions.

BACKGROUND: Recent scientific evidence has suggested that microRNAs (miRNAs) play an important role in papillary thyroid cancer (PTC). In the current study, we aim to identify a miRNA-related signature as the sensitive and novel prognostic biomarkers. METHODS: We performed a comprehensive analysis of the data downloaded from the Cancer Genome Atlas (TCGA) database. The association between survival outcome and miRNA was assessed by the univariate and multivariate Cox proportional hazards model. The risk score model was built to evaluate the predicting value of miRNA signature. The potential biofunctions and transcription factors of target miRNAs were investigated through bioinformatic analysis. The result was verified by the quantitative real-time polymerase chain reaction (qRT-PCR) in 32 pairs of PTC and adjacent nontumor tissues. In addition, the results were verified by other cohorts from gene expression omnibus (GEO) as detected by microarrays. RESULTS: A total of 1030 miRNAs were identified from the TCGA database. Thirty-six key intersection miRNAs were obtained. The associations between clinical features and key miRNAs were evaluated. Eventually, a two-miRNA signature (hsa-miR-181a-2-3p and hsa-miR-138-1-3p) was identified. The power of the miRNA prognostic signature was effective. In total, we identified 202 genes that were associated with 2 miRNAs above, and the top 10 enriched transcript factors that highly related with the target miRNAs were explored. The qRT-PCR and GEO data validation were consistent with bioinformatics results. CONCLUSIONS: A tumor-specific miRNA signature was identified, and the joint prognostic power was evaluated, which may be potential biomarkers for prognosis of PTC. IMPACT: The two-miRNA signature could become the potential prognostic indicator of PTC in the future.

Comprehensive analysis of a novel lncRNA profile reveals potential prognostic biomarkers in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the main subtype of malignant kidney cancer. Long non­coding RNA (lncRNA) serves a key role in predicting survival in patients with cancer. The present study aimed to develop an lncRNA­related signature of prognostic values for patients with ccRCC. RNA sequencing data of 454 patients were analyzed from The Cancer Genome Atlas (TCGA). To identify the differentially expressed lncRNAs, the patients from four groups classified by tumor stages were compared. The association between survival outcome and lncRNA expression profile was assessed by the univariate and multivariate Cox proportional hazards model. Survival was analyzed using the log­rank test, and functions of target lncRNAs were investigated through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. Finally, 19 lncRNAs were identified as significantly associated with overall survival (OS) time. These lncRNAs were gathered as a signal prognostic signature, which may be a potential biomarker for the prognosis of ccRCC. The risk score was built to evaluate the predictive value of the lncRNA signature. There was a significant positive correlation between ccRCC patients with the low­risk score and OS time (P<0.001). Reverse transcription­quantitative polymerase chain reaction (RT­qPCR) was used to verify the result in 17 pairs of ccRCC and adjacent non­tumor tissues. Functional enrichment analysis revealed that these lncRNAs were associated with several molecular pathways of the tumor. The RT­qPCR validation was consistent with the TCGA bioinformatics results. In conclusion, a tumor­specific lncRNA signature of 19 lncRNAs was identified and the joint prognostic power was evaluated in the present study, and this signature was determined to be a potential biomarker for the prognosis of ccRCC.

Identification and functional characterization of long non-coding RNAs in human gastric cancer.

Abnormal regulation of long non-coding RNAs (lncRNAs) appears to be a primary feature of numerous types of human cancer. However, the association between the dysregulation of lncRNAs and functional alterations in gastric cancer (GC) remains unclear. In previous studies, we applied microarray and bioinformatics analyses to screen for key lncRNAs from the tumor tissues and matched adjacent non-tumor tissues of 10 patients with GC. There were seven key lncRNAs demonstrated to be significantly different between carcinoma tissues and adjacent non-tumor tissues. In the present study, the expression of these seven selected lncRNAs were validated in 82 patients with GC to further investigate the association between lncRNAs and GC clinical characterization. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) results demonstrated that RP5-919F19, MCPH1 antisense RNA 1 (CTD-2541M15) and urothelial carcinoma-associated 1 (UCA1) exhibited consistent upregulation in cancer compared with adjacent non-tumor tissues, whereas AP000459, LOC101928316, tumor suppressor candidate 8 (LINC01071) and maternally expressed 3 (MEG3) showed consistent downregulation. The results from the microarray and RT-qPCR experiments achieved 100% agreement. A correlation analysis indicated that RP5-919F19, LOC101928316 and MEG3 were significantly associated with tumor differentiation degree, RP5-919F19, UCA1 and MEG3 were significantly associated with lymph node metastasis, and RP5-919F19, CTD-2541M15 and UCA1 were significantly associated with tumor-node-metastasis stage (P<0.05). In addition, it was identified that the differential expression of LINC01071 and LOC101928316 significantly correlated with the age and gender of the GC patients, respectively (P<0.05). The results suggest that the lncRNAs RP5-919F19, LOC101928316, CTD-2541M15, UCA1 and MEG3 are closely associated with the invasion and metastasis of GC, which reveals these indicators as potential specificity biomarkers for the diagnosis, prognosis and classification of GC. Thus, these lncRNAs merit further study as novel candidate biomarkers for the clinical diagnosis of GC and as potential targets for therapy.

Integrated analysis of long non­coding RNA competing interactions revealed potential biomarkers in cervical cancer: Based on a public database.

Cervical cancer (CC) is a common gynecological malignancy in women worldwide. Using an RNA sequencing profile from The Cancer Genome Atlas (TCGA) and the CC patient information, the aim of the present study was to identify potential long non­coding RNA (lncRNA) biomarkers of CC using bioinformatics analysis and building a competing endogenous RNA (ceRNA) co­expression network. Results indicated several CC­specific lncRNAs, which were associated with CC clinical information and selected some of them for validation and evaluated their diagnostic values. Bioinformatics analysis identified 51 CC­specific lncRNAs (fold­change >2 and P<0.05), and 42 of these were included in ceRNA network consisting of lncRNA­miRNA­mRNA interactions. Further analyses revealed that differential expression levels of 19 lncRNAs were significantly associated with different clinical features (P<0.05). A total of 11 key lncRNAs in the ceRNA network for reverse transcription­quantitative polymerase chain reaction (RT­qPCR) analysis to detect their expression levels in 31 pairs of CC clinical samples. The results indicated that 7 lncRNAs were upregulated and 4 lncRNAs were downregulated in CC patients. The fold­changes between the RT­qPCR experiments and the TCGA bioinformatics analyses were the same. Furthermore, the area under the receiver operating characteristic (ROC) curve of four lncRNAs (EMX20S, MEG3, SYS1­DBNDD2 and MIR9­3HG) indicated that their combined use may have a significant diagnostic value in CC (P<0.05). To the best of our knowledge, the present study is the first to have identified CC­specific lncRNAs to construct a ceRNA network and has also provided new insights for further investigation of a lncRNA­associated ceRNA network in CC. In additon, the verification results suggested that the method of bioinformatics analysis and screening of lncRNAs was accurate and reliable. To conclude, the use of multiple lncRNAs may thus improve diagnostic efficacy in CC. In addition, these specific lncRNAs may serve as new candidate biomarkers for clinical diagnosis, classification and prognosis of CC.

miR-93-5p Transferred by Exosomes Promotes the Proliferation of Esophageal Cancer Cells via Intercellular Communication by Targeting PTEN.

OBJECTIVE: To investigate the relationship between plasma miR-93-5p and the risk of esophageal cancer, as well as the influence of miR-93-5p on the biological function of esophageal cancer cells, exerted through exosomes. METHODS: The expression of plasma miR-93-5p in esophageal cancer patients and healthy controls was analysed by real-time quantitative PCR. The influence of miR-93-5p on the risk and prognosis of esophageal carcinoma was analyzed by conditional logistic regression and survival analysis. The effect of miR-93-5p on the biological function of recipient cells was investigated by establishing an in vitro donor cell co-culture model. The target gene of miR-93-5p was validated by luciferase reporter assay and Western Blotting. RESULTS: Upregulation of plasma miR-93-5p expression significantly increases the risk of esophageal cancer and is associated with poor prognosis. miR-93-5p transferred by exosomes promotes the proliferation of recipient esophageal cancer cells and affects the expression of PTEN and its downstream proteins p21 and cyclin D1. CONCLUSION: Our study provides a reference for the identification of biomarkers for the diagnosis and prognosis of esophageal cancer.

Comprehensive analysis of a novel four-lncRNA signature as a prognostic biomarker for human gastric cancer.

Emerging evidence indicates that long non-coding RNAs (lncRNAs) play a crucial role in predicting survival for gastric cancer (GC) patients. This study aims to identify a lncRNA-related signature for evaluating the overall survival of 379 GC patients from The Cancer Genome Atlas (TCGA) database. The associations between survival outcome and the expression of lncRNAs were evaluated by the univariate and multivariate Cox proportional hazards regression analyses. Four lncRNAs (LINC01018, LOC553137, MIR4435-2HG, and TTTY14) were identified as significantly correlated with overall survival. These four lncRNAs were gathered as a single prognostic signature. There was a significant positive correlation between GC patients with low-risk scores and overall survival (P = 0.001). Further analysis suggested that the prognostic value of this four-lncRNA signature was independent in clinical features. Gene set enrichment analysis found that these four lncRNAs were correlated with several molecular pathways of the tumor. Our study indicates that this novel lncRNA expression signature may be a useful biomarker of the prognosis for GC patients, based on bioinformatics analysis.

Trends of long noncoding RNA research from 2007 to 2016: a bibliometric analysis.

PURPOSE: This study aims to analyze the scientific output of long noncoding RNA (lncRNA) research and construct a model to evaluate publications from the past decade qualitatively and quantitatively. METHODS: Publications from 2007 to 2016 were retrieved from the Web of Science Core Collection database. Microsoft Excel 2016 and CiteSpace IV software were used to analyze publication outputs, journals, countries, institutions, authors, citation counts, ESI top papers, H-index, and research frontiers. RESULTS: A total of 3,008 papers on lncRNA research were identified published by June 17, 2017. The journal, Oncotarget (IF2016, 5.168) ranked first in the number of publications. China had the largest number of publications (1,843), but the United States showed its dominant position in both citation frequency (45,120) and H-index (97). Zhang Y (72 publications) published the most papers, and Guttman M (1,556 citations) had the greatest co-citation counts. The keyword "database" ranked first in research frontiers. CONCLUSION: The annual number of publications rapidly increased in the past decade. China showed its significant progress in lncRNA research, but the United States was the actual leading country in this field. Many Chinese institutions engaged in lncRNA research but significant collaborations among them were not noted. Guttman M, Mercer TR, Rinn JL, and Gupta RA were identified as good candidates for research collaboration. "Database," "Xist RNA," and "Genome-wide association study" should be closely observed in this field.

Integrated analysis of competing endogenous RNA network revealing lncRNAs as potential prognostic biomarkers in human lung squamous cell carcinoma.

Accumulating evidence shows the important role of long non-coding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks for predicting survival in tumor patients. However, prognostic biomarkers for lung squamous cell carcinoma (LUSC) are still lacking. The objective of this study is to identify a lncRNA signature for evaluation of overall survival (OS) in 474 LUSC patients from The Cancer Genome Atlas (TCGA) database. A total of 474 RNA sequencing profiles in LUSC patients with clinical data were obtained, providing a large sample of RNA sequencing data, and 83 LUSC-specific lncRNAs, 26 miRNAs, and 85 mRNAs were identified to construct the ceRNA network (fold change>2, P<0.05). Among these above 83 LUSC-specific lncRNAs, 22 were assessed as closely related to OS in LUSC patients using a univariate Cox proportional regression model. Meanwhile, two (FMO6P and PRR26) of the above 22 OS-related lncRNAs were identified using a multivariate Cox regression model to construct a risk score as an independent indicator of the prognostic value of the lncRNA signature in LUSC patients. LUSC patients with low-risk scores were more positively correlated with OS (P<0.001). The present study provides a deeper understanding of the lncRNA-related ceRNA network in LUSC and suggests that the two-lncRNA signature could serve as an independent biomarker for prognosis of LUSC.

Comprehensive analysis of aberrantly expressed microRNA profiles reveals potential biomarkers of human lung adenocarcinoma progression.

Lung adenocarcinoma (LUAD) is a complex disease that poses challenges for diagnosis and treatment. The aim of the present study is to investigate LUAD-specific key microRNAs (miRNAs) from large-scale samples in The Cancer Genome Atlas (TCGA) database. We used an integrative computational method to identify LUAD-specific key miRNAs related to TNM stage and lymphatic metastasis from the TCGA database. Twenty-five LUAD-specific key miRNAs (fold change >2, p<0.05) from the TCGA database were investigated, and 15 were found to be aberrantly expressed with respect to clinical features. Three miRNAs were correlated with overall survival (log-rank p<0.05). Then, 5 miRNAs were randomly selected for verification of expression in 53 LUAD patient tissues using qRT-PCR. Diagnostic value of these above 5 miRNAs was determined by areas under receiver operating characteristic curves (ROC). Finally, the LUAD-related miRNA miR-30a-3p was selected for verification of biologic function in A549 cells. The results of tests for cell proliferation, apoptosis, and target genes suggested that miR-30a-3p decreases cell proliferation and promotes apoptosis through targeting AKT3. Therefore, miR-30a-3p may be a promising biomarker for the early screening of high-risk populations and early diagnosis of LUAD. Our studies provide insights into identifying novel potential biomarkers for diagnosis and prognosis of LUAD.

[Effects of pomegranate varieties on the development and fecundity of Assara inouei Yamanaka (Lepidoptera: Pyralidae)]. / 不同石榴品种对井上蛀果斑螟生长发育和繁殖的影响.

Assara inouei Yanmanaka is an important pest of pomegranate fruits in Yunnan Province. To examine the effects of different pomegranate varieties on the development and reproduction of A. inouei, the biological characteristics, such as the developmental duration, the survival rate and reproduction of this pest feeding on five pomegranate varieties including Tianlvzi, Houpitianshazi, Tianguangyan, Suanlvzi and Suanshazi were observed respectively, and the life table parameters were established under the laboratory conditions of (25±1) ℃, RH (70±10)% and a photoperiod of 15 L:9 D. The results showed that there were no significant differences in the egg stage, larval stage, pupal stage, the longevity of male adults, generation duration form egg to adult and egg hatch rate among the five varieties. There were significant differences in the pre-pupal stage, the longevity of female adults, larval survival, pupation, eclosion and total survival rates, the number of eggs laid per female as well as male and female pupal mass among the five varieties, and all of which except the larval survival were higher on Suanlvzi, followed by Houpitianshazi, but there was no significant difference between these two varieties. The results of life table showed the net reproduction rate, the intrinsic rate of increase and finite rate of increase of the Suanlvzi population were the highest. There were no significant differences in the mean generation time among the five varieties, but significant difference was observed in the population doubling time, which was the shortest on Suanlvzi population. The development and reproduction of A. inouei were better on the Suanlvzi and Houpitianshazi among the five varieties.

Integrated analysis of long non-coding RNA­associated ceRNA network reveals potential lncRNA biomarkers in human lung adenocarcinoma.

Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in tumor biology. However, the roles of cancer specific lncRNAs in lncRNA-related ceRNA network of lung adenocarcinoma (LUAD) are still unclear. In the present study, the 465 RNA sequencing profiles in LUAD patients were obtained from the cancer genome atlas (TCGA) database, which provides large sample RNA sequencing data free of charge, and 41 cancer specific lncRNAs, 25 miRNAs and 1053 mRNAs (fold change >2, p<0.05) were identified. Then, the lncRNA-miRNA-mRNA ceRNA network of LUAD was constructed with 29 key lncRNAs, 24 miRNAs and 72 mRNAs. Subsequently, we selected these 29 key lncRNAs to analyze their correlation with clinical features, and 21 of them were aberrantly expressed with tumor pathological stage, TNM staging system, lymph node metastasis and patient outcome assessment, respectively. Furthermore, there were 5 lncRNAs (BCRP3, LINC00472, CHIAP2, BMS1P20 and UNQ6494) positively correlated with overall survival (OS, log-rank p<0.05). Finally, 7 cancer specific lncRNAs were randomly selected to verify the expression in 53 newly diagnosed LUAD patients using qRT-PCR. The expression results between TCGA and qRT-PCR were 100% in agreement. The correlation between AFAP1-AS1 and LINC00472 and clinical features were also confirmed. Thus, our results showed the lncRNA expression profiles and we constructed an lncRNA-miRNA-mRNA ceRNA network in LUAD. The present study provides novel insight for better understanding of lncRNA-related ceRNA network in LUAD and facilitates the identification of potential biomarkers for diagnosis and prognosis.

Exosome-shuttling microRNA-21 promotes cell migration and invasion-targeting PDCD4 in esophageal cancer.

Recent evidence indicates that exosomes can mediate certain microRNAs (miRNAs) involved in a series of biological functions in tumor occurrence and development. Our previous studies showed that microRNA-21 (miR-21) was abundant in both esophageal cancer cells and their corresponding exosomes. The present study explored the function of exosome-shuttling miR-21 involved in esophageal cancer progression. We found that exosomes could be internalized from the extracellular space to the cytoplasm. The exosome-derived Cy3-labeled miR-21 mimics could be transported into recipient cells in a neutral sphingomyelinase 2 (nSMase2)-dependent manner. miR-21 overexpression from donor cells significantly promoted the migration and invasion of recipient cells by targeting programmed cell death 4 (PDCD4) and activating its downstream c-Jun N-terminal kinase (JNK) signaling pathway after co-cultivation. Our population plasma sample analysis indicated that miR-21 was upregulated significantly in plasma from esophageal cancer patients and showed a significant risk association for esophageal cancer. Our data demonstrated that a close correlation existed between exosome-shuttling miR-21 and esophageal cancer recurrence and distant metastasis. Thus, exosome-shuttling miR-21 may become a potential biomarker for prognosis among esophageal cancer patients.

Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer.

Abnormal expression of long non-coding RNAs (lncRNAs) have been shown to play an important role in tumor biology. The Cancer Genome Atlas (TCGA) platform is a large sample sequencing database of lncRNAs, and further analysis of the associations between these data and patients' clinical related information can provide new approaches to find the functions of lncRNA. In the present study, 361 RNA sequencing profiles of gastric cancer (GC) patients were selected from TCGA. Then, we constructed the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network of GC. There were 25 GC specific lncRNAs (fold change >2, p<0.05) identified, 19 of them were included in ceRNA network. Subsequently, we selected these 19 key lncRNAs and analyzed the correlations with clinical features and overall survival, 14 of them were discriminatively expressed with tumor size, tumor grade, TNM stage and lymphatic metastasis (p<0.05). In addition, eight lncRNAs (RPLP0P2, FOXD2-AS1, H19, TINCR, SLC26A4-AS1, SMIM10L2A, SMIM10L2B and SNORD116-4) were found to be significantly associated with overall survival (log-rank p<0.05). Finally, two key lncRNAs HOTAIR and UCA1 were selected for validation of their expression levels in 82 newly diagnosed GC patients by qRT-PCR. Results showed that the fold changes between TCGA and qRT-PCR were 100% in agreement. In addition, we also found that HOTAIR was significantly correlated with tumor size and lymphatic metastasis (p<0.05), and UCA1 was significantly correlated with tumor size, TNM stage and lymphatic metastasis (p<0.05). The clinical relevance of the two lncRNAs and the bioinformatics analysis results were almost the same. Overall, our study showed the GC specific lncRNAs expression patterns and a ceRNA network in GC. Clinical features related to GC specific lncRNAs also suggested these lncRNAs are worthwhile for further study as novel candidate biomarkers for the clinical diagnosis of GC and potential indicators for prognosis.

Differential immunosuppression by Campoletis chlorideae eggs and ichnovirus in larvae of Helicoverpa armigera and Spodoptera exigua.

The ichneumonid wasp, Campoletis chlorideae Uchida, successfully develops in the cotton bollworm Helicoverpa armigera (Hübner), but rarely survives in the beet armyworm Spodoptera exigua (Hübner) due to the encapsulation by host immunity. In this study, we investigated the role of C. chlorideae ichnovirus (CcIV) and eggs in the evasion of the host immune system. Washed eggs of different types, immature, mature, newly laid, or pretreated with protease K, were injected alone or with the calyx fluid containing CcIV into the larvae of H. armigera and S. exigua. In H. armigera, when injected with washed eggs alone, only 9.5% of the mature eggs were encapsulated at 24h post-injection. This is much lower than that of the immature eggs (100%), mature eggs pretreated with protease K (100%) and newly laid eggs (54.4%). No encapsulation was observed when the washed eggs were co-injected with calyx fluid at 24h post-injection. Conversely, the eggs in all treatments were encapsulated in S. exigua. Electron microscopic observations of parasitoid eggs showed structural differences between the surfaces of the mature and other kinds of eggs. The injected CcIV decreased the numbers of host hemocytes and suppressed the spreading ability of plasmatocytes and granulocytes in H. armigera, but had little effect on the hemocytes from S. exigua. In conclusion, the C. chlorideae egg provides a passive protection against encapsulation by itself, and CcIV supplies an active protection through disrupting host immune responses. These coordinated protections are host-specific, implying their role in host range determination.

Isolation and characterization of an algicidal bacterium indigenous to lake Taihu with a red pigment able to lyse microcystis aeruginosa.

OBJECTIVE: To isolate and characterize indigenous algicidal bacteria and their algae-lysing compounds active against Microcystis aeruginosa, strains TH1, TH2, and FACHB 905. METHODS: The bacteria were identified using the Biolog automated microbial identification system and 16S rDNA sequence analysis. The algae-lysing compounds were isolated and purified by silica gel column chromatography and reverse-phase high performance liquid chromatography. Their structures were confirmed by Nuclear Magnetic Resonance (NMR) and Fourier Transform Infrared (FT-IR) spectroscopy. Algae-lysing activity was observed using microscopy. RESULTS: The algae-lysing bacterium LTH-2 isolated from Lake Taihu was identified as Serratia marcescens. Strain LTH-2 secreted a red pigment identified as prodigiosin (C20H25N3O), which showed strong lytic activity with algal strains M. aeruginosa TH1, TH2, and FACHB 905 in a concentration-dependent manner. The 50% inhibitory concentration (IC50) of prodigiosin with the algal strains was 4.8 (± 0.4)× 10⁻² µg/mL, 8.9 (± 1.1)× 10⁻² µg/mL, and 1.7 (± 0.1)× 10⁻¹ µg/mL in 24 h, respectively. CONCLUSION: The bacterium LTH-2 and its pigment had strong Microcystis-lysing activity probably related to damage of cell membranes. The bacterium LTH-2 and its red pigment are potentially useful for regulating blooms of harmful M. aeruginosa.