Changes in nitrogen metabolism of phosphorus-starved bloom-forming cyanobacterium Microcystis aeruginosa: Implications for nutrient management.

The surplus of nitrogen plays a key role in the maintenance of cyanobacterial bloom when phosphorus has already been limited. However, the interplay between high nitrogen and low phosphorus conditions is not fully understood. Nitrogen metabolism is critical for the metabolism of cyanobacteria. Transcriptomic analysis in the present study suggested that nitrogen metabolism and ribosome biogenesis were the two most significantly changed pathways in long-term phosphorus-starved bloom-forming cyanobacteria Microcystis aeruginosa FACHB-905. Notably, the primary glutamine synthetase/glutamate synthase cycle, crucial for nitrogen metabolism, was significantly downregulated. Concurrently, nitrogen uptake showed a marked decrease due to reduced expression of nitrogen source transporters. The content of intracellular nitrogen reservoir phycocyanin also showed a drastic decrease upon phosphorus starvation. Our study demonstrated that long-term phosphorus-starved cells also suffered from nitrogen deficiency because of the reduction in nitrogen assimilation, which might be limited by the reduced ribosome biogenesis and the shortage of adenosine triphosphate. External nitrogen supply will not change the transcriptions of nitrogen metabolism-related genes significantly like that under phosphorus-rich conditions, but still help to maintain the survival of phosphorus-starved cells. The study deepens our understanding about the survival strategies of Microcystis cells under phosphorus starvation and the mutual dependence between nitrogen and phosphorus, which would provide valuable information for nutrient management in the eutrophicated water body.

Integrated physiological and metabolomic analysis reveals new insights into toxicity pathways of paraquat to Microcystis aeruginosa.

Chemical pollutants, such as herbicides, released into the aquatic environment adversely affect the phytoplankton community structure. While majority of herbicides are specifically designed to target photosynthetic processes, they also can be toxic to phytoplankton; however, despite the photosynthetic toxicity, some herbicides can target multiple physiological processes. Therefore, a full picture of toxicity pathway of herbicide to phytoplankton is necessary. In the present study, the cyanobacterium Microcystis aeruginosa was exposed to two levels (17 µg L-1 (EC10) and 65 µg L-1 (EC50)) of paraquat for 72 h. The physiological and metabolic responses were analyzed to elucidate the toxicity pathway and establish the adverse outcome pathway of paraquat to M. aeruginosa. The results revealed that enhanced glycolysis (upregulation of pyruvic acid level) and tricarboxylic acid cycle (upregulation of the levels of malic acid, isocitric acid and citric acid) exposed to EC10 level of paraquat, which probably acted as a temporary strategy to maintain a healthy energy status in M. aeruginosa cells. Meanwhile, the expressions of glutathione and benzoic acid were enhanced to scavenge the excessive reactive oxygen species (ROS). Additionally, the accumulation of pigments (chlorophyll a and carotenoid) might play a supplementary role in the acclimation to EC10 level paraquat treatment. In cells exposed to paraquat by EC50 level, the levels of SOD, CAT, glutathione and benzoic acid increased significantly; however, the ROS exceeded the tolerance level of antioxidant system in M. aeruginosa. The adverse effects were revealed by inhibition of chlorophyll a fluorescence, the decreases in several carbohydrates (e.g., glucose 1-phosphate, fructose and galactose) and total protein content. Consequently, paraquat-induced oxidative stress caused the growth inhibition of M. aeruginosa. These findings provide new insights into the mode of action of paraquat in M. aeruginosa.

Texture Analysis of DCE-MRI Intratumoral Subregions to Identify Benign and Malignant Breast Tumors.

PURPOSE: To evaluate the potential of the texture features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) intratumoral subregions to distinguish benign from malignant breast tumors. MATERIALS AND METHODS: A total of 299 patients with pathologically verified breast tumors who underwent breast DCE-MRI examination were enrolled in this study, including 124 benign cases and 175 malignant cases. The whole tumor area was semi-automatically segmented on the basis of subtraction images of DCE-MRI in Matlab 2018b. According to the time to peak of the contrast agent, the whole tumor area was partitioned into three subregions: early, moderate, and late. A total of 467 texture features were extracted from the whole tumor area and the three subregions, respectively. Patients were divided into training (n = 209) and validation (n = 90) cohorts by different MRI scanners. The least absolute shrinkage and selection operator (LASSO) method was used to select the optimal feature subset in the training cohort. The Kolmogorov-Smirnov test was first performed on texture features selected by LASSO to test whether the samples followed a normal distribution. Two machine learning methods, decision tree (DT) and support vector machine (SVM), were used to establish classification models with a 10-fold cross-validation method. The performance of the classification models was evaluated with receiver operating characteristic (ROC) curves. RESULTS: In the training cohort, the areas under the ROC curve (AUCs) for the DT_Whole model and SVM_Whole model were 0.744 and 0.806, respectively. In contrast, the AUCs of the DT_Early model (P = 0.004), DT_Late model (P = 0.015), SVM_Early model (P = 0.002), and SVM_Late model (P = 0.002) were significantly higher: 0.863 (95% CI, 0.808-0.906), 0.860 (95% CI, 0.806-0.904), 0.934 (95% CI, 0.891-0.963), and 0.921 (95% CI, 0.876-0.954), respectively. The SVM_Early model and SVM_Late model achieved better performance than the DT_Early model and DT_Late model (P = 0.003, 0.034, 0.008, and 0.026, respectively). In the validation cohort, the AUCs for the DT_Whole model and SVM_Whole model were 0.670 and 0.708, respectively. In comparison, the AUCs of the DT_Early model (P = 0.006), DT_Late model (P = 0.043), SVM_Early model (P = 0.001), and SVM_Late model (P = 0.007) were significantly higher: 0.839 (95% CI, 0.747-0.908), 0.784 (95% CI, 0.601-0.798), 0.890 (95% CI, 0.806-0.946), and 0.865 (95% CI, 0.777-0.928), respectively. CONCLUSION: The texture features from intratumoral subregions of breast DCE-MRI showed potential in identifying benign and malignant breast tumors.

Long noncoding RNA lncRNA354 functions as a competing endogenous RNA of miR160b to regulate ARF genes in response to salt stress in upland cotton.

Long non-coding RNAs (lncRNAs) play important roles in response to biotic and abiotic stress through acting as competing endogenous RNAs (ceRNAs) to decoy mature miRNAs. However, whether this mechanism is involved in cotton salt stress response remains unknown. We report the characterization of an endogenous lncRNA, lncRNA354, whose expression was reduced in salt-treated cotton and was localized at the nucleus and cytoplasm. Using endogenous target mimic (eTM) analysis, we predicted that lncRNA354 had a potential binding site for miR160b. Transient expression in tobacco demonstrated that lncRNA354 was a miR160b eTM and attenuated miR160b suppression of its target genes, including auxin response factors (ARFs). Silencing or overexpressing lncRNA354 affected the expression of miR160b and target ARFs. Silencing lncRNA354 and targets GhARF17/18 resulted in taller cotton plants and enhanced the resistant to salt stress. Overexpression of lncRNA354 and targets GhARF17/18 in Arabidopsis led to dwarf plants, decreased root dry weight and reduced salt tolerance. Our results show that the lncRNA354-miR160b effect on GhARF17/18 expression may modulate auxin signalling and thus affect growth. These results also shed new light on a mechanism of lncRNA-associated responses to salt stress.

Texture Analysis Using Semiquantitative Kinetic Parameter Maps from DCE-MRI: Preoperative Prediction of HER2 Status in Breast Cancer.

OBJECTIVE: To evaluate whether texture features derived from semiquantitative kinetic parameter maps based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can determine human epidermal growth factor receptor 2 (HER2) status of patients with breast cancer. MATERIALS AND METHODS: This study included 102 patients with histologically confirmed breast cancer, all of whom underwent preoperative breast DCE-MRI and were enrolled retrospectively. This cohort included 48 HER2-positive cases and 54 HER2-negative cases. Seven semiquantitative kinetic parameter maps were calculated on the lesion area. A total of 55 texture features were extracted from each kinetic parameter map. Patients were randomly divided into training (n = 72) and test (n = 30) sets. The least absolute shrinkage and selection operator (LASSO) was used to select features in the training set, and then, multivariate logistic regression analysis was conducted to establish the prediction models. The classification performance was evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Among the seven prediction models, the model with features extracted from the early signal enhancement ratio (ESER) map yielded an area under the ROC curve (AUC) of 0.83 in the training set (sensitivity of 70.59%, specificity of 92.11%, and accuracy of 81.94%), and the highest AUC of 0.83 in the test set (sensitivity of 57.14%, specificity of 100.00%, and accuracy of 80.00%). The model with features extracted from the slope of signal intensity (SIslope) map yielded the highest AUC of 0.92 in the training set (sensitivity of 82.35%, specificity of 97.37%, and accuracy of 90.28%), and an AUC of 0.79 in the test set (sensitivity of 92.86%, specificity of 68.75%, and accuracy of 80.00%). CONCLUSIONS: Texture features derived from kinetic parameter maps, calculated based on breast DCE-MRI, have the potential to be used as imaging biomarkers to distinguish HER2-positive and HER2-negative breast cancer.

Intratumoral and Peritumoral Radiomics Based on Functional Parametric Maps from Breast DCE-MRI for Prediction of HER-2 and Ki-67 Status.

BACKGROUND: Radiomics has been applied to breast magnetic resonance imaging (MRI) for gene status prediction. However, the features of peritumoral regions were not thoroughly investigated. PURPOSE: To evaluate the use of intratumoral and peritumoral regions from functional parametric maps based on breast dynamic contrast-enhanced MRI (DCE-MRI) for prediction of HER-2 and Ki-67 status. STUDY TYPE: Retrospective. POPULATION: A total of 351 female patients (average age, 51 years) with pathologically confirmed breast cancer were assigned to the training (n = 243) and validation (n = 108) cohorts. FIELD STRENGTH/SEQUENCE: 3.0T, T1 gradient echo. ASSESSMENT: Radiomic features were extracted from intratumoral and peritumoral regions on six functional parametric maps calculated using time-intensity curves of DCE-MRI. The intraclass correlation coefficients (ICCs) were used to determine the reproducibility of feature extraction. Based on the intratumoral, peritumoral, and combined intra- and peritumoral regions, three radiomics signatures (RSs) were built using the least absolute shrinkage and selection operator (LASSO) logistic regression model, respectively. STATISTICAL TESTS: Wilcoxon rank-sum test, minimum redundancy maximum relevance, LASSO, receiver operating characteristic curve (ROC) analysis, and DeLong test. RESULTS: The intratumoral and peritumoral RSs for prediction of HER-2 and Ki-67 status achieved areas under the ROC (AUCs) of 0.683 (95% confidence interval [CI], 0.574-0.793) and 0.690 (95% CI, 0.577-0.804), and 0.714 (95% CI, 0.616-0.812) and 0.692 (95% CI, 0.590-0.794) in the validation cohort, respectively. The combined RSs yielded AUCs of 0.713 (95% CI, 0.604-0.823) and 0.749 (95% CI, 0.656-0.841), respectively. There were no significant differences in prediction performance among intratumoral, peritumoral, and combined RSs. Most (69.7%) of the features had good agreement (ICCs >0.8). DATA CONCLUSION: Radiomic features of intratumoral and peritumoral regions on functional parametric maps based on breast DCE-MRI had the potential to identify HER-2 and Ki-67 status. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2.

Effect of Iron Particles on the Coke Solution Loss Reaction.

The coke solution loss reaction was investigated by using a well-type Si-Mo rod electric furnace. The effects of the CO2 flow rate, reaction time, loading mode, and loading amount of iron particles on the coke solution loss reaction were investigated. By comparing the SEM and EDS before and after the reaction of loaded iron particle coke, the reasons for the influence of loading mode on the coke solution loss reaction were explored, and the mechanism behind it was further explored. The experimental results show that there is a positive proportional relationship between the CO2 flow rate and reaction time with coke solution loss reactivity. The adsorption and addition of iron oxide play an important role in promoting the coke solution loss reaction, but when the saturation point of iron oxide loading is exceeded (1%), the adsorption load of iron particles has little effect on the coke solution loss reaction. At the same reaction temperature, the carbon conversion of the adsorption method is 10% larger than that of the addition method. From the analysis of SEM, it can be seen that the mechanism of iron particles affecting the coke solution loss reaction is different under the two loading modes. In the addition method, some iron particles are wrapped in a coke pore wall matrix, so they cannot play a role. In the adsorption process, iron particles are uniformly distributed on the coke surface, which provide more effective catalytic active centers. In addition, when iron particles are loaded by the addition method, they participate in coke formation, which affects the coke structure and then affects the coke solution loss reaction. The iron particles in the adsorption method play a catalytic role in the coke solution loss reaction.

Application of Texture Analysis Based on Sagittal Fat-Suppression and Oblique Axial T2-Weighted Magnetic Resonance Imaging to Identify Lymph Node Invasion Status of Rectal Cancer.

Objective: To investigate the value of texture features derived from T2-weighted magnetic resonance imaging (T2WI) for predicting preoperative lymph node invasion (N stage) in rectal cancer. Materials and Methods: One hundred and eighty-two patients with histopathologically confirmed rectal cancer and preoperative magnetic resonance imaging were retrospectively analyzed, who were divided into high (N1-2) and low N stage (N0). Texture features were calculated from histogram, gray-level co-occurrence matrix, and gray-level run-length matrix from sagittal fat-suppression and oblique axial T2WI. Independent sample t-test or Mann-Whitney U-test were used for statistical analysis. Multivariate logistic regression analysis was conducted to build the predictive models. Predictive performance was evaluated by receiver operating characteristic (ROC) analysis. Results: Energy (ENE), entropy (ENT), information correlation (INC), long-run emphasis (LRE), and short-run low gray-level emphasis (SRLGLE) extracted from sagittal fat-suppression T2WI, and ENE, ENT, INC, low gray-level run emphasis (LGLRE), and SRLGLE from oblique axial T2WI were significantly different between stage N0 and stage N1-2 tumors. The multivariate analysis for features from sagittal fat-suppression T2WI showed that higher SRLGLE and lower ENE were independent predictors of lymph node invasion. The model reached an area under ROC curve (AUC) of 0.759. The analysis for features from oblique axial T2WI showed that higher INC and SRLGLE were independent predictors. The model achieved an AUC of 0.747. The analysis for all extracted features showed that lower ENE from sagittal fat-suppression T2WI and higher INC and SRLGLE from oblique axial T2WI were independent predictors. The model showed an AUC of 0.772. Conclusions: Texture features derived from T2WI could provide valuable information for identifying the status of lymph node invasion in rectal cancer.

Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps.

BACKGROUND: It is evident that an accurate evaluation of T and N stage rectal cancer is essential for treatment planning. It has not been extensively investigated whether texture features derived from diffusion-weighted imaging (DWI) images and apparent diffusion coefficient (ADC) maps are associated with the extent of local invasion (pathological stage T1-2 vs T3-4) and nodal involvement (pathological stage N0 vs N1-2) in rectal cancer. AIM: To predict different stages of rectal cancer using texture analysis based on DWI images and ADC maps. METHODS: One hundred and fifteen patients with pathologically proven rectal cancer, who underwent preoperative magnetic resonance imaging, including DWI, were enrolled, retrospectively. The ADC measurements (ADCmean, ADCmin, ADCmax) as well as texture features, including the gray level co-occurrence matrix parameters, the gray level run-length matrix parameters and wavelet parameters were calculated based on DWI (b = 0 and b = 1000) images and the ADC maps. Independent sample t-tests or Mann-Whitney U tests were used for statistical analysis. Multivariate logistic regression analysis was conducted to establish the models. The predictive performance was validated by receiver operating characteristic curve analysis. . RESULTS: Dissimilarity, sum average, information correlation and run-length nonuniformity from DWI b =0 images, gray level nonuniformity, run percentage and run-length nonuniformity from DWI b =1000 images, and dissimilarity and run percentage from ADC maps were found to be independent predictors of local invasion (stage T3-4). The area under the operating characteristic curve of the model reached 0.793 with a sensitivity of 78.57% and a specificity of 74.19%. Sum average, gray level nonuniformity and the horizontal components of symlet transform (SymletH) from DWI b =0 images, sum average, information correlation, long run low gray level emphasis and SymletH from DWI b =1000 images, and ADCmax, ADCmean and information correlation from ADC maps were identified as independent predictors of nodal involvement. The area under the operating characteristic curve of the model reached 0.802 with a sensitivity of 80.77% and a specificity of 68.25%. CONCLUSION: Texture features extracted from DWI images and ADC maps are useful clues for predicting pathological T and N stages in rectal cancer.

Preliminary study on discriminating HER2 2+ amplification status of breast cancers based on texture features semi-automatically derived from pre-, post-contrast, and subtraction images of DCE-MRI.

OBJECTIVE: To investigate whether texture features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with human epidermal growth factor receptor type 2 (HER2) 2+ status of breast cancer. MATERIALS AND METHODS: 92 MRI cases including 52 HER2 2+ positive and 40 negative patients confirmed by fluorescence in situ hybridization were retrospectively selected. The lesion area was semi-automatically delineated, and a total of 488 texture features were respectively extracted from precontrast, postcontrast, and subtraction images. The Student's t-test or Mann-Whitney U test was performed to identify statistically significant features between different HER2 2+ amplification groups. Least absolute shrinkage and selection operator (LASSO) was used to search for the optimal feature subsets. Three machine learning classifiers, logistic regression analysis (LRA), quadratic discriminant analysis (QDA), and support vector machine (SVM), were used with a leave-one-out cross validation method to establish the classification models of HER2 2+ status. Classification performance was evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Based on the texture analysis with SVM model, the areas under the ROC curve (AUCs) were 0.890 for subtraction images, 0.736 for postcontrast images, and 0.672 for precontrast images, respectively. For LRA model, the AUCs were 0.884, 0.733, and 0.623, respectively. For QDA model, the AUCs were 0.831, 0.726, and 0.568, respectively. LRA and the SVM model with subtraction images reached significantly better performance than the QDA model (P = 0.0227 and P = 0.0088, respectively). CONCLUSION: Texture features of breast cancer extracted from DCE-MRI are associated with HER2 2+ status. Additional studies are necessary to confirm the present preliminary findings.

Bioconcentration and depuration of cadmium in the selected tissues of rare minnow (Gobiocypris rarus) and the effect of dietary mulberry leaf supplementation on depuration.

A 56-day trial was conducted to elucidate the bioconcentration and depuration of Cd in the liver and muscle of rare minnow (Gobiocypris rarus) and determine the effect of dietary mulberry leaf supplementation on depuration. Juvenile rare minnow were exposed to environmentally relevant doses of Cd (1 and 10 µg/L) for 28 days of uptake and then allowed 28 days of depuration. The bioaccumulation factors of the treated rare minnow in the liver and muscle were calculated to be between 4.13-4.675 and 1.76-1.94, respectively. This results suggested that Cd had high potential for bioconcentration in rare minnow. To investigate the effect of dietary mulberry leaf supplementation on depuration, the remaining fish of each group were allowed to depurate with different ratios (0%, 10%, and 30% dry weight) of dietary mulberry leaf supplementation for an additional 28 days. Fish weights did not differ significantly (p >  0.05) between the control and mulberry leaf treated groups. Mulberry leaf powder did not significantly affect Cd depuration in the 10 µg/L group or in the muscle of the 1 µg/L group, but caused a significant decrease in Cd content in the liver of the 1 µg/L group (p <  0.05). This work was the first to model the bioconcentration of Cd in rare minnow and showed that mulberry leaf supplementation decreased Cd residues in the liver of the 1µg/L group. Such a finding may promote the development of new approaches to mitigate the potential hazards of heavy metals to human health.

A novel fed-batch strategy to boost cyst cells production based on the understanding of intracellular carbon and nitrogen metabolism in Haematococcus pluvialis.

Haematococcus pluvialis is a prominent feedstock of astaxanthin. The ratio of carbon to nitrogen (C/N) strongly influences the metabolic pathways of mixotrophic-grown microalgae, however, its role involved in astaxanthin biosynthesis is still not fully understood. In this study, integrative metabolic and physiologic profiles were analyzed in elucidating how C/N affected carbon and nitrogen assimilation and thereby exerted influence on astaxanthin biosynthesis. It was demonstrated that high C/N up-regulated the activities of acetate kinase by increase of 5.76 folds in early logarithmic phase, leading a significant increase of acetyl-CoA. The increased carbon skeletons were then funneled into astaxanthin biosynthesis. Additionally, high C/N increased the proportion of carotenoid-intermediates in cytoplasm from chloroplast. Finally, a fed-batch cultivation strategy based on C/N gradient was developed. Biomass attained 9.18 g L-1 in 100% type of immotile cyst cells, which presented astaxanthin productivity at 15.45 mg L-1 d-1 afterward, exhibiting a promising paradigm in commercial production.

The Potential Use of DCE-MRI Texture Analysis to Predict HER2 2+ Status.

Purpose: To evaluate the ability of texture analysis of breast dynamic contrast enhancement-magnetic resonance (DCE-MR) images in differentiating human epidermal growth factor receptor 2 (HER2) 2+ status of breast tumors. Methods: A total of 73 cases were retrospectively selected. HER2 2+ status was confirmed by fluorescence in situ hybridization. For each case, 279 textural features were derived. A student's t-test or Mann-Whitney U test was used to select features with statistically significant differences between HER2 2+ positive and negative groups. A principal component analysis was applied to eliminate feature correlation. Three machine learning classifiers, logistic regression (LR), quadratic discriminant analysis (QDA), and a support vector machine (SVM), were trained and tested using a leave-one-out cross-validation method. The area under a receiver operating characteristic curve (AUC) was measured to assess the classifier's performance. Results: The AUCs for the different classifiers were satisfactory, ranging from 0.808 to 0.865. The classification methods derived with LR and SVM demonstrated similarly high performances, and the accuracy levels were 81.06 and 81.18%, respectively. The AUC for the classifier derived with SVM was the highest (0.865), and a marked specificity (88.90%) was presented. For the classifier with LR, the AUC was 0.851, and the corresponding sensitivity (94.44%) was the highest. Conclusion: The texture analysis for breast DCE-MRI proposed in this study demonstrated potential utility in HER2 2+ status discrimination.

The Catalase Gene Family in Cotton: Genome-Wide Characterization and Bioinformatics Analysis.

Catalases (CATs), which were coded by the catalase gene family, were a type notably distinguished ROS-metabolizing proteins implicated to perform various physiological functions in plant growth, development and stress responses. However, no systematical study has been performed in cotton. In the present study, we identified 7 and 7 CAT genes in the genome of Gossypium hirsutum L. Additionally, G. barbadense L., respectively. The results of the phylogenetic and synteny analysis showed that the CAT genes were divided into two groups, and whole-genome duplication (WGD) or polyploidy events contributed to the expansion of the GossypiumCAT gene family. Expression patterns analysis showed that the CAT gene family possessed temporal and spatial specificity and was induced by the Verticillium dahliae infection. In addition, we predicted the putative molecular regulatory mechanisms of the CAT gene family. Based on the analysis and preliminary verification results, we hypothesized that the CAT gene family, which might be regulated by transcription factors (TFs), alternative splicing (AS) events and miRNAs at different levels, played roles in cotton development and stress tolerance through modulating the reactive oxygen species (ROS) metabolism. This is the first report on the genome-scale analysis of the cotton CAT gene family, and these data will help further study the roles of CAT genes during stress responses, leading to crop improvement.

Characterization of phosphorus forms in lake macrophytes and algae by solution (31)P nuclear magnetic resonance spectroscopy.

Debris from aquatic macrophytes and algae are important recycling sources of phosphorus (P), which can result in continuing blooms of algae by recycling bioavailable P in the eutrophic lakes. However, knowledge of forms of P in aquatic macrophytes and algae and their contribution to internal loads of P in lakes is limited. Without such knowledge, it is difficult to develop appropriate strategies to remediate and or restore aquatic ecosystems that have become eutrophic. Therefore, in this work, P was extracted from six types of aquatic macrophytes and algae collected from Tai Lake of China and characterized by use of solution (31)P-nuclear magnetic resonance (NMR) spectroscopy. When extracted by 0.5 M NaOH-25 mM EDTA, extraction recovery of total P(TP) and organic P(Po) exceeded 90 %. Concentrations of Po in algae and aquatic macrophytes were 5552 mg kg(-1) and 1005 mg kg(-1) and accounted for 56.0 and 47.2 % of TP, respectively. When Po, including condensed P, was characterized by solution (31)P-NMR Po in algae included orthophosphate monoesters (79.8 %), pyrophosphate (18.2 %), and orthophosphate diester (2.0 %), and Po in aquatic macrophytes included orthophosphate monoesters (90.3 %), pyrophosphate (4.2 %), and orthophosphate diester (5.5 %). Additionally, orthophosphate monoesters in algal debris mainly included ß-glycerophosphate (44.1 %), α-glycerophosphate (13.5 %), and glucose 6-phosphate (13.5 %). Orthophosphate monoesters in aquatic macrophytes mainly included ß-glycerophosphate (27.9 %), α-glycerophosphate (24.6 %), and adenosine 5' monophosphate (8.2 %). Results derived from this study will be useful in better understanding nutrient cycling, relevant eutrophication processes, and pollution control for freshwater lakes.

Ecological dynamics of toxic Microcystis spp. and microcystin-degrading bacteria in Dianchi Lake, China.

Toxic cyanobacterial blooms directly threaten both human safety and the ecosystem of surface waters. The widespread occurrence of these organisms, coupled with the tumor-promoting properties of the microcystin toxins that they produce, demands action to mitigate their potential impacts and, thus, a robust understanding of their ecological dynamics. In the present work, the abundance of toxic Microcystis spp. and microcystin (MC)-degrading bacteria in Dianchi Lake, located in Yunnan Province, China, was studied using quantitative PCR. Samples were taken at monthly intervals from June 2010 to December 2011 at three sampling stations within this freshwater lake. Results revealed that variation in the abundance of both total Microcystis spp. and toxic Microcystis spp. exhibited similar trends during the period of the algal bloom, including the reinvasion, pelagic growth, sedimentation, and overwintering periods, and that the proportion of toxic Microcystis was highest during the bloom and lowest in winter. Importantly, we observed that peaks in mlrA gene copy numbers of MC-degrading bacteria occurred in the months following observed peaks in MC concentrations. To understand this phenomenon, we added MCs to the MC-degrading bacteria (designated strains HW and SW in this study) and found that MCs significantly enhanced mlrA gene copy numbers over the number for the control by a factor of 5.2 for the microcystin-RR treatment and a factor of 3.7 for the microcystin-LR treatment. These results indicate that toxic Microcystis and MC-degrading bacteria exert both direct and indirect effects on each other and that MC-degrading bacteria also mediate a shift from toxic to nontoxic populations of Microcystis.

UVB radiation as a potential selective factor favoring microcystin producing bloom forming Cyanobacteria.

Due to the stratospheric ozone depletion, several organisms will become exposed to increased biologically active UVB (280-320 nm) radiation, not only at polar but also at temperate and tropical latitudes. Bloom forming cyanobacteria are exposed to UVB radiation on a mass scale, particularly during the surface bloom and scum formation that can persist for long periods of time. All buoyant species of cyanobacteria are at least periodically exposed to higher irradiation during their vertical migration to the surface that usually occurs several times a day. The aim of this study is to assess the influence on cyanobacteria of UVB radiation at realistic environmental intensities. The effects of two UVB intensities of 0.5 and 0.99 W/m(2) in up to 0.5 cm water depth were studied in vitro on Microcystis aeruginosa strains, two microcystin producing and one non-producing. After UVB exposure their ability to proliferate was estimated by cell counting, while cell fitness and integrity were evaluated using light microscopy, autofluorescence and immunofluorescence. Gene damage was assessed by TUNEL assay and SYBR Green staining of the nucleoide area. We conclude that UVB exposure causes damage to the genetic material, cytoskeletal elements, higher sedimentation rates and consequent cell death. In contrast to microcystin producers (PCC7806 and FACHB905), the microcystin non-producing strain PCC7005 is more susceptible to the deleterious effects of radiation, with weak recovery ability. The ecological relevance of the results is discussed using data from eleven years' continuous UVB radiation measurements within the area of Ljubljana city (Slovenia, Central Europe). Our results suggest that increased solar radiation in temperate latitudes can have its strongest effect during cyanobacterial bloom formation in spring and early summer. UVB radiation in this period may significantly influence strain composition of cyanobacterial blooms in favor of microcystin producers.

Responses and toxin bioaccumulation in duckweed (Lemna minor) under microcystin-LR, linear alkybenzene sulfonate and their joint stress.

Microcystin-LR (MCLR) and linear alkylbenzene sulfonate (LAS) are commonly found in eutrophic lakes due to toxic cyanobacterial blooms and exogenous organic compounds pollution. However, the ecotoxicological risk of their combination in the aquatic environment is unknown. This study investigated the effects of MCLR, LAS and their mixture on duckweed (Lemna minor) growth and physiological responses. MCLR accumulation in duckweed, with or without LAS, was also examined. Growth of duckweed and chlorophyll-a contents were significantly reduced after 8d exposure to high concentrations of MCLR (≥ 3 µg/ml), LAS (≥ 20 µg/ml) and their mixture (≥ 3+10 µg/ml). After 2d of exposure, superoxide dismutase activity and glutathione content in duckweed increased with increasing concentrations of MCLR, LAS and their mixture, with a significant difference observable after 8d of exposure. When MCLR and LAS concentrations were lower (≤ 0.1+1 µg/ml), the interaction of them is synergistic, but when the concentrations were higher, the synergy was weak. MC accumulation was much higher at 2d than at 8d when duckweed was exposed to lower concentrations of MCLR (≤ 3 µg/ml) or MCLR-LAS (≤ 3+10 µg/ml). Furthermore, LAS significantly enhanced the accumulation of MCLR in duckweed, even with LAS concentrations as low as 0.3 µg/ml (environmental concentration), indicating that greater negative ecological risks and higher MCLR phytoremediation potentials of duckweed might occur in MCLR-LAS-concomitant water.

Sulforaphane prevents microcystin-LR-induced oxidative damage and apoptosis in BALB/c mice.

Microcystins (MCs), the products of blooming algae Microcystis, are waterborne environmental toxins that have been implicated in the development of liver cancer, necrosis, and even fatal intrahepatic bleeding. Alternative protective approaches in addition to complete removal of MCs in drinking water are urgently needed. In our previous work, we found that sulforaphane (SFN) protects against microcystin-LR (MC-LR)-induced cytotoxicity by activating the NF-E2-related factor 2 (Nrf2)-mediated defensive response in human hepatoma (HepG2) and NIH 3T3 cells. The purpose of this study was to investigate and confirm efficacy the SFN-induced multi-mechanistic defense system against MC-induced hepatotoxicity in an animal model. We report that SFN protected against MC-LR-induced liver damage and animal death at a nontoxic and physiologically relevant dose in BALB/c mice. The protection by SFN included activities of anti-cytochrome P450 induction, anti-oxidation, anti-inflammation, and anti-apoptosis. Our results suggest that SFN may protect mice against MC-induced hepatotoxicity. This raises the possibility of a similar protective effect in human populations, particularly in developing countries where freshwaters are polluted by blooming algae.

Effects of microcystin-LR, linear alkylbenzene sulfonate and their mixture on lettuce (Lactuca sativa L.) seeds and seedlings.

Microcystin-LR (MCLR) and linear alkylbenzene sulfonate (LAS) are present widely in aquatic and terrestrial ecosystems, but their combined ecotoxicological risk is unknown. This study investigated the toxic effects of MCLR, LAS and their mixture on lettuce (Lactuca sativa L.) and evaluated MCLR accumulation level in lettuce with or without LAS. The changes in seed germination and shoot/root growth, responses of the antioxidative defense system, and the accumulation of MCLR in lettuce were tested to evaluate the single and combined toxic effect of MCLR and LAS in well-controlled conditions. The results showed that seedling growth (except for root elongation and leaf weight) was more sensitive to toxicant exposure than seed germination. For seedling leaves, lipid peroxidation was not observed when the antioxidative defense system (including superoxide dismutase, catalase and glutathione) was activated to relieve the adverse effects of oxidative stress via different pathways. Our results also confirmed that the interaction between MCLR and LAS was synergistic. Both toxicants in combination not only significantly inhibited seedling growth, but also increased the activities of superoxide dismutase and catalase, as well as the contents of glutathione. Furthermore, LAS dramatically enhanced the accumulation of MCLR in the plant, thus leading to a reduction in quality and yield and posing greater potential risk to humans via consumption of these edible plants.