Malassezia restricta as an unexpected cause of infectious osteomyelitis diagnosed by metagenomic sequencing: a case report and literature review.

BACKGROUND: Malassezia restricta, a lipophilic and lipodependent yeast belonging to the basidiomycetes group, is an opportunistic fungal pathogen associated with various skin diseases, including seborrheic dermatitis and dandruff. Typically, Malassezia infection in neonates manifests as fungemia or hematogenous dissemination to the bone or lungs. However, vertebral osteomyelitis caused by these fungi is rarely reported owing to non-specific clinical presentations and laboratory/imaging findings. The Pathogen Metagenomics Sequencing (PMseq) technique enables direct high-throughput sequencing of infected specimens, facilitating the rapid and accurate detection of all microorganisms in clinical samples through comprehensive reports. CASE PRESENTATION: A 52-year-old male was admitted to our hospital on July 20, 2022 with a 3-month history of ambulatory difficulties and localized low back pain. Magnetic Resonance Imaging (MRI) examination of the spinal column revealed irregular bone destruction affecting the L2, L3, and L5 vertebral bodies. Additionally, low T1 and high T2 intensity lesions were observed at the intervertebral discs between L3 and L5. The presumptive diagnosis of tuberculous spondylitis was made based on the imaging findings, despite negative results in all mycobacterium tests. However, the patient exhibited no improvement after receiving regular anti-tuberculosis treatment for 3 months. Subsequent MRI revealed an expansive abnormal signal within the vertebral body, leading to progressive bone destruction. The absence of spinal tuberculosis or other infective microorganisms was confirmed through culture from blood and pathological tissue from the L4 vertebral body. Subsequently, PMseq was performed on the specimens, revealing M. restricta as the predominant pathogen with the highest relative abundance value. The pathological examination revealed the presence of fungal mycelium in the L4 vertebral body, with positive findings on periodic Schiff-methenamine and periodic acid-Schiff staining. The anti-tuberculosis treatment was discontinued, and an antifungal combination of fluconazole and voriconazole was administered. All symptoms were resolved after 7 consecutive months of treatment, and the patient was able to ambulate autonomously. Vertebral lesions were reduced on MRI during the 13-month follow-up. CONCLUSIONS: M. restricta is not a commonly recognized pathogen associated with infectious vertebral osteomyelitis. However, PMseq can aid in diagnosis, timely treatment, and decision making for some non-specific infectious diseases.

Response mechanism of a highly efficient partial nitritation-anammox (PN/A) process under antibiotic stress: Extracellular polymers, microbial community, and functional genes.

The Partial nitritation-Anammox (PN/A) process can be restricted when treating high ammonia nitrogen wastewater containing antibiotics. This study aims to explore the response mechanism of the PN/A process under antibiotic stress. Results showed the PN/A process achieved a nitrogen removal rate higher than 1.01 ± 0.03 kg N/m3/d under long-term sulfamethazine stress. The increase of extracellular polymers from 22.52 to 43.96 mg/g VSS was conducive to resisting antibiotic inhibitory. The increase of Denitratisoma and SM1A02 abundance as well as functional genes nirS and nirK indicated denitrifiers should play an important role in the stability of the PN/A system under sulfamethazine stress. In addition, antibiotic-resistant genes (ARGs) sul1 and intI1 significantly increased by 8.78 and 5.12 times of the initial values to maintain the resistance of PN/A process to sulfamethazine stress. This study uncovers the response mechanism of the PN/A process under antibiotic stress, offering a scientific basis and guidance for further application in the future.

Thiamethoxam adsorption by ZnCl2 modified cow manure biochar: Mechanism and quantitative prediction.

The overuse of thiamethoxam (THM) has threatened the survival of living organisms and it is necessary to find an environmentally friendly material to remove THM frequently detected in water. Biochar prepared from cow manure modified with ZnCl2 (Zn-CBC) was used to remove THM. Compared to the unmodified cow manure biochar (CBC), the removal ratio of THM by Zn-CBC was enhanced 35 times. In the mechanistic analysis, SEM and BET showed that Zn-CBC had a good pore structure and its specific surface area (166.502 m2 g-1) increased to 17 times that of CBC, indicating that Zn-CBC had good pore adsorption properties. The adsorption kinetic and isotherm implied that the main mechanism was chemisorption including π-π interaction and H-bonding. Furthermore, the stable graphitized structure of Zn-CBC allowed for efficient adsorption and reusability. In addition, this study constructed an intelligent prediction model using batch experiment data, and the high R2 (0.978) and low RMSE (0.057) implied that the model could accurately and quantitatively predict the adsorption efficiency. This paper provides a novel perspective to simultaneously remove the neonicotinoid insecticides and realize the resource utilization of cow manure.

Linking PAHs concentration, risk to PAHs source shift in soil and water in epikarst spring systems, Southwest China.

A systematic assessment of the variations in the ecological risk of PAHs and the key emission sources controlling the variations is of great importance to human health and aquatic organisms. PAH concentrations, composition, source, and ecological risk in soils and water in two different periods (2010-2011 and 2019) of three typical epikarst springs in Southwest China were investigated. Results showed that PAH concentrations in soil and water have an overall downward trend (a reduction of 57 % and 93 %, respectively) in the past 10 years, which is consistent with the downward trend in the relative contribution rate of raw coal production (a 66 % reduction). In terms of composition, the proportion of low-ring PAHs decreased, medium-ring and high-ring PAHs increased in the soil profile. The proportion of low-ring PAHs did not change obviously, the proportion of medium-ring PAHs increased, and the proportion of high-ring PAHs decreased in epikarst springs. The source of PAHs changed remarkably over time, the relative contribution of coal combustion to PAHs decreased from 38 % to 20 %, and the vehicle contribution of PAHs increased from 31 % to 44 % in soils. The relative contribution rate of unburned oil and coke oven and biomass combustion change is less. Furthermore, the ecological risk of PAHs in the soils was reduced from moderate risk 2 to moderate risk 1, the risk in epikarst spring was reduced from high risk to moderate risk 2 after 10 years. This study demonstrates that substituting petroleum and coal with green energies can reduce PAH concentrations and risk.

Ammonium sulfate supplementation enhances erythromycin biosynthesis by augmenting intracellular metabolism and precursor supply in Saccharopolyspora erythraea.

In this study, the cellular metabolic mechanisms regarding ammonium sulfate supplementation on erythromycin production were investigated by employing targeted metabolomics and metabolic flux analysis. The results suggested that the addition of ammonium sulfate stimulates erythromycin biosynthesis. Targeted metabolomics analysis uncovered that the addition of ammonium sulfate during the late stage of fermentation resulted in an augmented intracellular amino acid metabolism pool, guaranteeing an ample supply of precursors for organic acids and coenzyme A-related compounds. Therefore, adequate precursors facilitated cellular maintenance and erythromycin biosynthesis. Subsequently, an optimal supplementation rate of 0.02 g/L/h was determined. The results exhibited that erythromycin titer (1311.1 µg/mL) and specific production rate (0.008 mmol/gDCW/h) were 101.3% and 41.0% higher than those of the process without ammonium sulfate supplementation, respectively. Moreover, the erythromycin A component proportion increased from 83.2% to 99.5%. Metabolic flux analysis revealed increased metabolic fluxes with the supplementation of three ammonium sulfate rates.

Accurate multi-objective prediction of CO2 emission performance indexes and industrial structure optimization using multihead attention-based convolutional neural network.

The establishment of specific targets for the global carbon peaking and neutrality raises urgent requirements for prediction of CO2 emission performance indexes (CEPIs) and industrial structure optimization. However, accurate multi-objective prediction of CEPIs is still a knotty problem. In the present study, multihead attention-based convolutional neural network (MHA-CNN) model was proposed for accurate prediction of 4 CEPIs and further provided the rational suggestions for further industrial structure optimization. The proposed MHA-CNN model introduces deep learning mechanism with efficient resolution strategies for training model overfitting, feature extraction, and self-supervised learning to acquire the adaptability for CEPIs. Multihead attention (MHA) mechanism plays important roles in influence weight interpretation of variables to facilitate the prediction performance of CNN on CEPIs. The MHA-CNN model presented its overwhelmingly superior performance to CNN model and long short-term memory (LSTM) model, two frequently-used models, in multi-objective prediction of CEPIs using 8 influence variables, which highlighted advantages of MHA module in multi-dimensional feature extraction. Additionally, contributions of influence variables to CEPIs based on MHA analyses presented relatively high consistency with the geographical distribution analyses, indicating the excellent capacity of the MHA module in variable weights identification and contribution dissection. Based on the more accurate prediction results by MHA-CNN than those by CNN and LSTM model, the increase in the tertiary industry and the decreases in the first and secondary industries are conducive to improvement of total-factor carbon emission efficiency and further enhancement of effective energy utilization in regions with inefficient carbon emissions. This study provides insights towards the critical roles of the proposed MHA-CNN model in accurate multi-objective prediction of CEPIs and further industrial structure optimization for improvement of total-factor carbon emission efficiency.

Free nitrous acid prediction in ANAMMOX process using hybrid deep neural network model.

Free nitrous acid (FNA) is a critical metric for stabilization of ANAMMOX but can not be directly and immediately measured by sensors or chemical measurement method, which hinders the effective management and operation for ANAMMOX. This study focuses on FNA prediction using hybrid model based on temporal convolutional network (TCN) combined with attention mechanism (AM) optimized by multiobjective tree-structured parzen estimator (MOTPE), called MOTPE-TCNA. A case study in an ANAMMOX reactor is carried out. Results show that nitrogen removal rate (NRR) is highly correlated with FNA concentration, indicating that it can forecast the operational status by predicting FNA. Then, MOTPE successfully optimizes the hyperparameters of TCN, helping TCN achieve a high prediction accuracy, and AM furtherly improves model accuracy. MOTPE-TCNA obtains the highest prediction accuracy, whose R2 value gets 0.992, increasing 1.71-11.80% compared to other models. As a deep neural network model, MOTPE-TCNA has more advantages than traditional machine learning methods in FNA prediction, which is beneficial to maintain the stable operation and easy control for ANAMMOX process.

Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new water quality prediction CSWLSTM-GPR model, which fused the spatial feature of convolutional neural network (CNN), the temporal feature of sharing-weight long short-term memory (SWLSTM) and the probabilistic reliability of Gaussian process regression (GPR), was applied for monitoring papermaking wastewater treatment system with high-precision point prediction and interval prediction. Compared with SWLSTM-GPR and CLSTM-GPR, RMSE of CSWLSTM-GPR reduced by more than 48.9% on effluent chemical oxygen demand (CODeff), MAE reduced by more than 49.3%, R2 increased by more than 25.14%, R increased by more than 7.07%. And for the effluent suspended solids (SSeff), CSWLSTM-GPR had better predictive results than SWLSTM-GPR and CSWLSTM-GPR. Compared with SWLSTM-GPR, RMSE, MAE, R, R2 of CSWLSTM-GPR on effluent suspended solids (SSeff) were improved by 4.8%, 6.1%, 29.01% and 31.15%, respectively. Simulation results showed convincing comprehensive forecasting ability were obtained and the true values frequently stayed within the water quality range obtained by CSWLSTM-GPR model, which provided important insights for online monitoring, wastewater recycling and carbon neutrality of papermaking industry.

Engineering of succinyl-CoA metabolism in view of succinylation regulation to improve the erythromycin production.

As a novel protein post-translational modification (PTM), lysine succinylation is widely involved in metabolism regulation by altering the activity of catalytic enzymes. Inactivating succinyl-CoA synthetase in Saccharopolyspora erythraea HL3168 E3 was proved significantly inducing the global protein hypersuccinylation. To investigate the effects, succinylome of the mutant strain E3ΔsucC was identified by using a high-resolution mass spectrometry-based proteomics approach. PTMomics analyses suggested the important roles of succinylation on protein biosynthesis, carbon metabolism, and antibiotics biosynthesis in S. erythraea. Enzymatic experiments in vivo and in vitro were further conducted to determine the succinylation regulation in the TCA cycle. We found out that the activity of aconitase (SACE_3811) was significantly inhibited by succinylation in E3ΔsucC, which probably led to the extracellular accumulation of pyruvate and citrate during the fermentation. Enzyme structural analyses indicated that the succinylation of K278 and K373, conservative lysine residues locating around the protein binding pocket, possibly affects the activity of aconitase. To alleviate the metabolism changes caused by succinyl-CoA synthetase inactivation and protein hypersuccinylation, CRISPR interference (CRISPRi) was applied to mildly downregulate the transcription level of gene sucC in E3. The erythromycin titer of the CRISPRi mutant E3-sucC-sg1 was increased by 54.7% compared with E3, which was 1200.5 mg/L. Taken together, this work not only expands our knowledge of succinylation regulation in the TCA cycle, but also validates that CRISPRi is an efficient strategy on the metabolic engineering of S. erythraea. KEY POINTS: • We reported the first systematic profiling of the S. erythraea succinylome. • We found that the succinylation regulation on the activity of aconitase. • We enhanced the production of erythromycin by using CRISPRi to regulate the transcription of gene sucC.

Exploring the metabolic fate of propanol in industrial erythromycin-producing strain via 13C labeling experiments and enhancement of erythromycin production by rational metabolic engineering of Saccharopolyspora erythraea.

Propanol had been widely used as a precursor for erythromycin synthesis in industrial production. However, the knowledge on the exact metabolic fate of propanol was still unclear. In the present study, the metabolic fate of propanol in industrial erythromycin-producing strain Saccharopolyspora erythraea E3 was explored via 13C labeling experiments. An unexpected pathway in which propanol was channeled into tricarboxylic acid cycle was uncovered, resulting in uneconomic catabolism of propanol. By deleting the sucC gene, which encodes succinyl-CoA synthetase that catalyse a reaction in the unexpected propanol utilization pathway, a novel strain E3-ΔsucC was constructed. The strain E3-ΔsucC showed a significant enhancement in erythromycin production in the chemically defined medium compared to E3 (786.61 vs 392.94 mg/L). Isotopically nonstationary 13C metabolic flux analysis were employed to characterize the metabolic differences between Saccharopolyspora erythraea E3 and E3-ΔsucC. The results showed that compared with the starting strain E3, the fluxes of pentose phosphate pathway in E3-△sucC increased by almost 200%. The flux of the metabolic reaction catalyzed by succinyl-CoA synthetase in E3-ΔsucC was almost zero, while the glyoxylate bypass flux significantly increased. These new insights into the precursor utilization of antibiotic biosynthesis by rational metabolic engineering in Saccharopolyspora erythraea provided the new vision in increasing industrial production of secondary metabolites.

Photo-biodegradation of imidacloprid under blue light-emitting diodes with bacteria and co-metabolic regulation.

Imidacloprid (IMI) is existence in the soil environment with a half-life habitually more than hundred days. This study targets to determine, identify and characterize photo-biodegradation bacteria from neonicotinoids (NEOs) contaminated agricultural field soils. The sub-surface soil had a higher level contamination of NEOs, in specifically greater concentration of IMI (3445.2 ± 0.09 µg/g) and thiacloprid (4084.4 ± 0.09 µg/g) has been found. Three bacteria Ralstonia pickettii (PBMS-2), Bacillus cereus (PBMS-3) and Shinella zoogloeoides (PBMS-4) was identified from soil-free stable enrichment cultures. The biodegradability of IMI (50 mg L-1) by three bacteria under different colors of light-emitting diodes (LEDs) with a constant 12 V power supply was tested and found that the blue-LEDs had greatest efficiency in supporting biodegradation of IMI which is called photo-biodegradation. In specific, the rate of photo-biodegradation of IMI by Ralstonia pickettii (87%), Bacillus cereus (80%) and Shinella zoogloeoides (80%) was measured. Besides this study also tested the effect of aeration (rpm), pH, and temperature on photo-biodegradation of IMI. There were seven intermediate metabolites were measured as biodegradation products of IMI under photo-biodegradation conditions and they are; IMI-urea, IMI-desnitro, 6-chloronicotinic acid, 6-hydroxy nicotinic acid, IMI- aminoguanidine, IMI-nitrosoguanidine and 4,5-hydroxy IMI, these metabolites are may non-toxic to the environment.

Neighborhood component analysis for modeling papermaking wastewater treatment processes.

It is of great importance to obtain accurate effluent quality indices in time for pulping and papermaking wastewater treatment processes. However, considering the complex characteristics of industrial wastewater treatment systems, conventional modeling methods such as partial least squares (PLS) and artificial neural networks (ANN) cannot achieve satisfactory prediction accuracy. As a supervised metric learning method, neighborhood component analysis (NCA) is able to significantly improve the prediction performance by training an appropriate model in metric space using the distance between samples for papermaking wastewater treatment processes. The results on two data sets show that NCA has a higher prediction accuracy compared with PLS and ANN. Specifically, NCA has the highest determination coefficient (R2) and the lowest root mean square error in a benchmark simulation data set. On the other hand, the results on the data from an industrial wastewater process indicate that NCA has better modeling accuracy and its R2 increases by 32.80% and 29.08% compared with PLS and ANN, respectively. NCA provides a feasible way to realize online monitoring and automatic control in wastewater treatment processes.

Medroxyprogesterone acetate affects eye growth and the transcription of associated genes in zebrafish.

Medroxyprogesterone acetate (MPA) is a widely used synthetic progestin in contraception pills and hormone replacement therapy. However, its effects on eye growth and development and function were largely unknown. In this study, the transcription of genes in the Notch signaling pathway and the visual cycle network were evaluated after chronic MPA exposure at 4.32 (L), 42.0 (M), and 424 (H) ng L-1 for 120 days in zebrafish. Meanwhile, the histology of the eyes was also examined. Transcriptional results showed that MPA at all three concentrations significantly increased the transcription of notch1a, dll4, jag1a, ctbp1 and rbpjb (key genes in the Notch signaling pathway) in the eyes of females. The up-regulation of noth1a, ctbp1 and kat2b was also observed in the eyes of males exposed to MPA at 424 ng L-1. In the visual cycle pathway, MPA increased the transcription of opn1sw1, opn1sw2, arr3a and rpe65a in the eyes of females from the M and H treatments. Histopathological analysis showed that exposure to 42.0 ng L-1 of MPA increased the thicknesses of inner nuclear layer in females and outer segment in males. Moreover, exposure to 424 ng L-1 of MPA increased the lens diameter in females. These results indicated that chronic MPA exposure affected the transcription of genes in the Notch signaling and in the visual cycle pathways, resulting in overgrowth of the eyes and interference of the eye functions. This study suggests that MPA pose a risk to fitness and survival of zebrafish in areas where MPA contamination exists.

Discovery of nitropyridyl-based dichloropropene ethers as insecticides.

A series of nitropyridyl-based dichloropropene ethers were prepared and evaluated for their insecticidal activities against main lepidopteran pests such as M. separate, P. xylostella and P. litura. The compounds showed a broad-spectrum of remarkable insecticidal activities. Especially 4a (2,6-dichloro-4-(3,3-dichloroallyloxy)phenyl 3-[5-nitro-2-pyridyloxy]propyl ether) and 11a (2-(4-(3-(2,6-dichloro-4-((3,3-dichloroallyl)oxy)phenoxy)propoxy)phenoxy)-5-nitropyridine) displayed potent activities comparable to that of Pyridalyl, the only commercialized dichloropropene ether insecticide thus far. The structure-activity relationship was also discussed.

Dydrogesterone affects the transcription of genes in visual cycle and circadian rhythm network in the eye of zebrafish.

Dydrogesterone (DDG) is a synthetic progestin used in contraception and hormone replacement therapy. Our previous transcriptome data showed that the response to light stimulus, photoperiodism and rhythm related gene ontology (GO) terms were significantly enriched in the brain of zebrafish after chronic exposure to DDG. Here we investigated the effects of DDG on the eye of zebrafish. Zebrafish were exposed to DDG at three concentration levels (3.39, 33.1, and 329 ng L-1) for 120 days. Based on our previous transcriptome data, the transcription of genes involved in visual cycle and circadian rhythm network was examined by qPCR analysis. In the visual cycle network, exposure to all concentrations of DDG significantly decreased transcription of grk7a, aar3a and guca1d, while increased the transcription of opn1mw4 and opn1sw2 at the low concentration. Importantly, exposure to all concentrations of DDG down-regulated the transcription of rep65a that encodes a critical enzyme to catalyze the conversion from all-trans-retinal to 11-cis-retinal in the eye of male zebrafish. In the circadian rhythm network, DDG enhanced the transcription of clocka, arntl2 and nifil3-5 at all three concentrations, while it decreased the transcription of cry5, per1b, nr1d2b and si:ch211.132b12.7. In addition, DDG decreased the transcription of tefa in both males and females. Moreover, histological analysis showed the exposure to 329 ng L-1 of DDG decreased the thickness of retinal ganglion cell in the eye of male zebrafish. These results indicated that DDG exposure could affect the transcription of genes in visual cycle and circadian rhythm network in the eyes of zebrafish. This suggests that DDG has potential negative impact on the normal eye function.

Residue levels and spatial distribution of phthalate acid esters in water and sediment from urban lakes of Guangzhou, China.

The residue levels and composition profiles of phthalate acid esters (PAEs) in water and sediment samples were investigated in eight urban lakes of Guangzhou, China. A total of 23 water and 16 sediment samples were collected. Results showed that all target PAEs were detected with dimethyl phthalate and di(2-ethylhexyl) phthalate as the most abundant compounds. The total concentrations of PAEs from different urban lakes were in the range of 273-1173 ng/L for water and 16.5-242 ng/g for sediments, with the geometric mean of 515 ng/L and 75.0 ng/g, respectively. Zhongshan Park Lake and Liwan Lake were the most highly contaminated with PAEs in water and in sediment, respectively. The spatial distribution of PAEs exhibited that distribution coefficients of PAEs between sediment and water are consistent with hydrophilicity of PAEs, and pollution levels and characteristics of PAEs in different lakes had a close relationship with the geographical location of the lake, industrial and commercial types, population density, and the association between the lake and the Pearl River. According to Pearson correlation analysis, PAEs would be derived from similar or identical sources. Risk assessment suggested that the exposure of PAEs in Guangzhou has a moderate toxicity at the current level.

A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH4+-N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs.

Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13 C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13 C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger. Biotechnol. Bioeng. 2017;114: 685-695. © 2016 Wiley Periodicals, Inc.

Mixomics analysis of Bacillus subtilis: effect of oxygen availability on riboflavin production.

BACKGROUND: Riboflavin, an intermediate of primary metabolism, is one kind of important food additive with high economic value. The microbial cell factory Bacillus subtilis has already been proven to possess significant importance for the food industry and have become one of the most widely used riboflavin-producing strains. In the practical fermentation processes, a sharp decrease in riboflavin production is encountered along with a decrease in the dissolved oxygen (DO) tension. Influence of this oxygen availability on riboflavin biosynthesis through carbon central metabolic pathways in B. subtilis is unknown so far. Therefore the unveiled effective metabolic pathways were still an unaccomplished task till present research work. RESULTS: In this paper, the microscopic regulation mechanisms of B. subtilis grown under different dissolved oxygen tensions were studied by integrating 13C metabolic flux analysis, metabolomics and transcriptomics. It was revealed that the glucose metabolic flux through pentose phosphate (PP) pathway was lower as being confirmed by smaller pool sizes of metabolites in PP pathway and lower expression amount of ykgB at transcriptional level. The latter encodes 6-phosphogluconolactonase (6-PGL) under low DO tension. In response to low DO tension in broth, the glucose metabolic flux through Embden-Meyerhof-Parnas (EMP) pathway was higher and the gene, alsS, encoding for acetolactate synthase was significantly activated that may result due to lower ATP concentration and higher NADH/NAD+ ratio. Moreover, ResE, a membrane-anchored protein that is capable of oxygen regulated phosphorylase activity, and ResD, a regulatory protein that can be phosphorylated and dephosphorylated by ResE, were considered as DO tension sensor and transcriptional regulator respectively. CONCLUSIONS: This study shows that integration of transcriptomics, 13C metabolic flux analysis and metabolomics analysis provides a comprehensive understanding of biosynthesized riboflavin's regulatory mechanisms in B. subtilis grown under different dissolved oxygen tension conditions. The two-component system, ResD-ResE, was considered as the signal receiver of DO tension and gene regulator that led to differences between biomass and riboflavin production after triggering the shifts in gene expression, metabolic flux distributions and metabolite pool sizes.

Effect of E-waste Recycling on Urinary Metabolites of Organophosphate Flame Retardants and Plasticizers and Their Association with Oxidative Stress.

In this study, three chlorinated (Cl-mOPs) and five nonchlorinated (NCl-mOPs) organophosphate metabolites were determined in urine samples collected from participants living in an electronic waste (e-waste) dismantling area (n = 175) and two reference areas (rural, n = 29 and urban, n = 17) in southern China. Bis(2-chloroethyl) phosphate [BCEP, geometric mean (GM): 0.72 ng/mL] was the most abundant Cl-mOP, and diphenyl phosphate (DPHP, 0.55 ng/mL) was the most abundant NCl-mOP. The GM concentrations of mOPs in the e-waste dismantling sites were higher than those in the rural control site. These differences were significant for BCEP (p < 0.05) and DPHP (p < 0.01). Results suggested that e-waste dismantling activities contributed to human exposure to OPs. In the e-waste sites, the urinary concentrations of bis(2-chloro-isopropyl) phosphate (r = 0.484, p < 0.01), BCEP (r = 0.504, p < 0.01), dibutyl phosphate (r = 0.214, p < 0.05), and DPHP (r = 0.440, p < 0.01) were significantly increased as the concentration of 8-hydroxy-2'-deoxyguanosine (8-OHdG), a marker of DNA oxidative stress, increased. Our results also suggested that human exposure to OPs might be correlated with DNA oxidative stress for residents in e-waste dismantling areas. To our knowledge, this study is the first to report the urinary levels of mOPs in China and examine the association between OP exposure and 8-OHdG in humans.