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The human microbiota-associated (HMA) mice model, especially the germ-free (GF)-humanized mice, has been widely used to probe the causal relationships between gut microbiota and human diseases such as type 1 diabetes (T1D). However, most studies have not clarified the extent to which the reconstruction of the human donor microbiota in recipient mice correlates with corresponding phenotypic reproducibility. In this study, we transplanted fecal microbiota from five patients with T1D and four healthy people into GF mice, and microbiota from each donor were transplanted into 10 mice. Mice with similar microbiota structure to the donor exhibited better phenotypic reproducibility. The characteristics of the microbial community assembly of donors also influenced the phenotypic reproducibility in mice, and individuals with a higher proportion of stochastic processes showed more severe disorders. Microbes enriched in patients with T1D had a stronger colonization potential in mice with impaired glucose metabolism, and microbiota functional features related to T1D were better reproduced in these mice. This indicates that assembly traits and colonization efficacy of microbiota influence phenotypic reproducibility in GF-humanized mice. Our findings provide important insights for using HMA mice models to explore links between gut microbiota and human diseases.

Dietary fibers are generally thought to benefit intestinal health. Their impacts on the composition and metabolic function of the gut microbiome, however, vary greatly across individuals. Previous research showed that each individual’s response to fibers depends on their baseline gut microbiome, but the ecology driving microbiota remodeling during fiber intake remained unclear. Here, we studied the long-term dynamics of the gut microbiome and short-chain fatty acids (SCFAs) in isogenic mice with distinct microbiota baselines fed with the fermentable fiber inulin and resistant starch compared to the non-fermentable fiber cellulose. We found that inulin produced a generally rapid response followed by gradual stabilization to new equilibria, and those dynamics were baseline-dependent. We parameterized an ecology model from the time-series data, which revealed a group of bacteria whose growth significantly increased in response to inulin and whose baseline abundance and interspecies competition explained the baseline dependence of microbiome density and community composition dynamics. Fecal levels of SCFAs, such as propionate, were associated with the abundance of inulin responders, yet inter-individual variation of gut microbiome impeded the prediction of SCFAs by machine learning models. We showed that our methods and major findings were generalizable to dietary resistant starch. Finally, we analyzed time-series data of synthetic and natural human gut microbiome in response to dietary fiber and validated the inferred interspecies interactions in vitro. This study emphasizes the importance of ecological modeling to understand microbiome responses to dietary changes and the need for personalized interventions.

Dietary fibers are generally thought to benefit intestinal health. Their impacts on the composition and metabolic function of the gut microbiome, however, vary greatly across individuals. Previous research showed that each individual’s response to fibers depends on their baseline gut microbiome, but the ecology driving microbiota remodeling during fiber intake remained unclear. Here, we studied the long-term dynamics of the gut microbiome and short-chain fatty acids (SCFAs) in isogenic mice with distinct microbiota baselines fed with the fermentable fiber inulin and resistant starch compared to the non-fermentable fiber cellulose. We found that inulin produced a generally rapid response followed by gradual stabilization to new equilibria, and those dynamics were baseline-dependent. We parameterized an ecology model from the time-series data, which revealed a group of bacteria whose growth significantly increased in response to inulin and whose baseline abundance and interspecies competition explained the baseline dependence of microbiome density and community composition dynamics. Fecal levels of SCFAs, such as propionate, were associated with the abundance of inulin responders, yet inter-individual variation of gut microbiome impeded the prediction of SCFAs by machine learning models. We showed that our methods and major findings were generalizable to dietary resistant starch. Finally, we analyzed time-series data of synthetic and natural human gut microbiome in response to dietary fiber and validated the inferred interspecies interactions in vitro. This study emphasizes the importance of ecological modeling to understand microbiome responses to dietary changes and the need for personalized interventions.

Background: Gut microbiota alters in patients with end-stage renal disease, which contributes to inflammation, atherosclerosis, and results in increased incidence of cardiovascular diseases. The present study investigated the potential clinical factors, which influence the gut microbial structure and function in patients undergoing peritoneal dialysis (PD).Methods: This is a cross-sectional study performed in 81 prevalent PD patients. Gut microbiota was assessed by high throughput sequencing of 16S ribosomal ribonucleic acid gene in fecal samples. Gas chromatography was conducted to measure stool short-chain fat acid (SCFA) concentrations. Demographic parameters and clinical characteristics, including dialysis regimen, residual renal function, nutrition, and inflammation, were retrieved and related to the properties of gut microbiota.Results: PD duration, peritoneal glucose exposure, and estimated glomerulus filtration rate (eGFR) were identified to be associated with microbial variations. Significant separation of microbial composition was shown between patients with short or long PD duration (p= 0.015) and marginal differences were found between patients grouped by different levels of peritoneal glucose exposure (p= 0.056) or residual renal function (p= 0.063). A couple of gut bacteria showed different abundance at amplicon sequencing variant level between these patient groups (p< 0.05). In addition, stool isobutyric and isovaleric acid concentrations were significantly reduced in patients with longer dialysis duration, higher peritoneal glucose exposure, or declined eGFR (p< 0.05).Conclusions: This pilot study demonstrated that long dialysis duration, high peritoneal glucose exposure, and loss of residual renal function were associated with gut microbiota alteration and reduced branched-chain SCFA production in PD patients.

Aim:To describe gut microbiome and functional genes of asthma. Patients & methods:Fecal microbiome in controls, asthma patients with and without inhaled corticosteroid (ICS) treatment was determined. Results:Patients with ICS had lower abundance of Alloprevotella, unclassified_f_Lachnospiraceaeand Lachnospiraceae_NC2004_group, higher abundance of Sutterellaand Sphingomonasthan patients without ICS. In all the asthma patients, there are microbial differences in aging distribution, different gender and different asthmatic phenotypes. Asthma patients without ICS treatment had more microbial genes related to geraniol degradation, ethylbenzene degradation and bladder cancer than controls; 15 pathways showed significant difference between asthma patients with and without ICS treatment. Conclusion:We found gut dysbiosis in asthma and different functional pathways associated with both asthma and ICS.

ABSTRACTAs a kind of renewable energy, wind energy is getting more and more attention with its advantage of rich, clean and environmentally sustainable. Stochastic volatility is the inherent property of wind energy and the essential factor hindering the development of wind power prediction research. In this paper, by considering the actual movement rule of wind energy described by Lorenz system, the Lorenz system and the wavelet decomposition were combined to improve the wind speed prediction models of BP, RBF, and Elman neural network for the first time, and a wind speed prediction model with the Lorenz system based on wavelet decomposition was established. The model has been compared with three traditional numerical prediction methods, proving that Lorenz disturbance model can get better prediction accuracy and can grasp the actual movement of wind more accurately. The research of this paper can make up for the neglect of the atmospheric system in the field of wind speed prediction, which is helpful to the large-scale development and utilization of wind energy resources.

Extranodal natural killer/T-cell lymphoma (ENKTCL), nasal type, is rare and aggressive and often involves the nose, nasopharynx, and upper aerodigestive tract. The non-nasal type can affect the skin, salivary glands, gut, testes, brain, salivary glands, and other sites. Primary ENKTCL of the lung is rare. Here, we report a 68-year-old non-smoking female who presented with fever, dry cough, and night sweats. The chest image showed lung consolidation in the right lower lung field. Pulmonary biopsy showed diffuse abnormal lymphocyte infiltrate in the necrotic exudate. Immunohistochemical data indicated that the tumour cells were positive for CD56, granzyme B, CD3, and TIA. Using in situ hybridization, Epstein–Barr virus-encoded ribonucleic acid (EBER) was detected. There was no evidence to indicate extrathoracic lymphoma involvement. Primary pulmonary ENKTCL was therefore diagnosed. The patient underwent chemotherapy using the P-GEMOX regimen (pegaspargase, gemcitabine, and oxaliplatin) and is still alive.

Triple-negative breast cancer (TNBC) is the most malignant breast cancer, with high rates of relapse and metastasis. Because of the nonspecific targeting of chemotherapy and insurmountable aggressiveness, TNBC therapy lacks an effective strategy. Exosomes have been reported as an efficient drug delivery system (DDS). CD82 is a tumor metastasis inhibitory molecule that is enriched in exosomes. Aptamer AS1411 specifically targets TNBC cells due to its high expression of nucleolin. We generated a “triple-punch” cell membrane-derived exosome-mimetic nanovesicle system that integrated with CD82 overexpression, AS1411 conjugation, and doxorubicin (DOX) delivery. CD82 enrichment effectively inhibits the migration of TNBC cells. AS1411 conjugation specifically targets TNBC cells. DOX loading effectively inhibits proliferation and induces apoptosis of TNBC cells. Our results demonstrate a system of exosome-mimetic nanovesicles with “triple-punch” that may facilitate TNBC therapeutics.

Wind power, as a new energy generation technology, has been applying widely and growing rapidly, which make it become the main force of renewable energy. However, wind speed sequence has its own character of the intermittent and uncertainty, which brings a great challenge to the safety and stability of the power grid, one of the valid ways solving the problem is improving the wind speed predicting accuracy. Therefore, given atmospheric disturbances, we firstly used empirical mode decomposition (EMD) to deal with the non-linear wind speed sequence, and combined with strong adaptive and self-learning ability of BP neural network, then, a wind speed prediction model, EMD-BP neural network based on Lorenz disturbance, was proposed. Finally, it was to made use of actual wind speed data to take a simulation experiment and explored the improvement effect of the preliminary forecasting sequence of wind speed influenced by Lorenz equation in the transient chaos and chaos. The results show that, the improved model weakened the random fluctuation of wind speed sequence, effectively corrected the wind speed sequences initial prediction values, and made a great improvement for the short-term wind speed prediction precision. This research work will help the power system dispatching department adjust the dispatching plan in time, formulate the wind farm control strategy reasonably, reduce the impact brought by wind power grid connection, increase the wind power penetration rate, and then promote the global energy power market innovation.

The dextran sulfate sodium (DSS)-induced colitis model is a widely applied mouse model, but controversial results have been obtained from experiments using the same mouse strain under the same conditions. Because the gut microbiota play an important role in DSS-induced colitis, it is essential to evaluate the influence of the initial gut microbiota in this model. Here, we identified significant variations in the initial gut microbiota of different batches of mice and found that the initial intestinal microbiota had a profound influence on DSS-induced colitis. We performed three independent trials using the same C57BL/6J mouse model with DSS treatment and used high-throughput 16S rRNA gene sequencing to analyze the gut microbiota. We found that the structure and composition of the gut microbiota in mice with severe colitis, as compared with mice with milder colon damage, had unique features, such as an increase in Akkermansiabacteria and a decrease in Barnesiellaspp. Moreover, these varied gut bacteria in the different trials also showed different responses to DSS treatment. Our work suggests that, in studies using mouse models, the gut microbiota must be considered when examining mechanisms of diseases, to ensure that comparable results are obtained.

Thanks to non-pollution and sustainability of wind energy, it has become the main source of power generation in the new era worldwide. However, the inherent random fluctuation and intermittency of wind power have negative effects on the safe and stable operation of power system and the quality of power. The key solving this problem is to improve the accuracy of wind speed prediction. In the paper, considering the forecasting accuracy is affected by many factors, we propose that, Principal Component Analysis (PCA) is combined with Independent Component Analysis (ICA) to process the sample, which can weaken the mutual interference between the various factors, extract accurately independent component reflected the characteristics of wind farm and achieve the purpose of improving the accuracy of wind speed prediction. At the same time, the adaptive and self-learning ability of neural network is more suitable for wind speed sequence prediction. The prediction results demonstrate that compared with the traditional neural network predicting model (RBF, BP, Elman), this model makes full use of the information provided by varieties of relevant factors, weakens the volatility of wind speed sequence and significantly enhances the short-term wind speed forecasting accuracy. The research work in the paper can help wind farm reasonably arrange the power dispatching plan, reduce the power operation cost and effectively boost the large-scale development and utilization of renewable energy.

The commensal microbiota regulates the self-renewal and differentiation of hematopoietic stem and progenitor cells (HSPCs) in bone marrow. Whether and how the microbiota influences HSPC development during embryogenesis is unclear. Using gnotobiotic zebrafish, we show that the microbiota is necessary for HSPC development and differentiation. Individual bacterial strains differentially affect HSPC formation, independent of their effects on myeloid cells. Early-life dysbiosis in chd8−/−zebrafish impairs HSPC development. Wild-type microbiota promote HSPC development by controlling basal inflammatory cytokine expression in kidney niche, and chd8−/−commensals elicit elevated inflammatory cytokines that reduce HSPCs and enhance myeloid differentiation. We identify an Aeromonas veroniistrain with immuno-modulatory activities that fails to induce HSPC development in wild-type fish but selectively inhibits kidney cytokine expression and rebalances HSPC development in chd8−/−zebrafish. Our studies highlight the important roles of a balanced microbiome during early HSPC development that ensure proper establishment of lineal precursor for adult hematopoietic system.

Resident gut microbes co-exist with transient bacteria to form the gut microbiota. Despite increasing evidence suggesting a role for transient microbes on gut microbiota function, the interplay between resident and transient members of this microbial community is poorly defined. We aimed to determine the extent to which a host’s autochthonous gut microbiota influences niche permissivity to transient bacteria using a fermented milk product (FMP) as a vehicle for five food-borne bacterial strains. Using conventional and gnotobiotic rats and gut microbiome analyses (16S rRNA genes pyrosequencing and reverse transcription qPCR), we demonstrated that the clearance kinetics of one FMP bacterium, Lactococcus lactisCNCM I-1631, were dependent on the structure of the resident gut microbiota. Susceptibility of the resident gut microbiota to modulation by FMP intervention correlated with increased persistence of L. lactis. We also observed gut microbiome configurations that were associated with altered stability upon exposure to transient bacteria. Our study supports the concept that allochthonous bacteria have transient and subject-specific effects on the gut microbiome that can be leveraged to re-engineer the gut microbiome and improve dysbiosis-related diseases.

Resident gut microbes co-exist with transient bacteria to form the gut microbiota. Despite increasing evidence suggesting a role for transient microbes on gut microbiota function, the interplay between resident and transient members of this microbial community is poorly defined. We aimed to determine the extent to which a host’s autochthonous gut microbiota influences niche permissivity to transient bacteria using a fermented milk product (FMP) as a vehicle for five food-borne bacterial strains. Using conventional and gnotobiotic rats and gut microbiome analyses (16S rRNA genes pyrosequencing and reverse transcription qPCR), we demonstrated that the clearance kinetics of one FMP bacterium, Lactococcus lactis CNCM I-1631, were dependent on the structure of the resident gut microbiota. Susceptibility of the resident gut microbiota to modulation by FMP intervention correlated with increased persistence of L. lactis. We also observed gut microbiome configurations that were associated with altered stability upon exposure to transient bacteria. Our study supports the concept that allochthonous bacteria have transient and subject-specific effects on the gut microbiome that can be leveraged to re-engineer the gut microbiome and improve dysbiosis-related diseases.

Summary.: Adenine phosphoribosyltransferase (APT) catalyzes the conversion of adenine and cytokinin bases to the corresponding nucleotides. An Arabidopsis thaliana mutant lacking the major APT isoform, APT1, is male sterile due to defects soon after meiosis. We have now used electron microscopy to define the effects of APT1 deficiency on pollen development to determine whether the changes might be attributed to adenine or cytokinin metabolism. Changes were observed in mutant anthers in both tapetal and pollen mother cells prior to meiosis with additional defects found at later stages, in both compartments. Principal changes include altered lipid accumulation in the tapetal cells, changes in pollen cell wall development, and a loss of synchrony in the development of the tapetum and microspores. Taken together our results suggest that APT1 deficiency causes a general metabolic decrease in energy metabolism, due to the lack of adenine recycling into adenylate nucleotides, which ultimately leads to pollen abortion. The early onset of meiosis in the mutant may be associated with altered cytokinin metabolism.

Malate, specifically labeled with carbon 13 on C3, was synthesized by chemical means and used to study malate metabolism by primary cultures of mouse cortical astrocytes. 3-13C-Malate in combination with glucose as well as 3-13C-malate alone were used as substrates; the effect of 3-nitropropionic acid, an inhibitor of succinate dehydrogenase and fumarase was also examined. The consumption of malate was only 0.26 μmol/mg of protein, approx. 25-fold lower than the consumption of glucose. Besides lactate, glutamine and fumarate were the two major metabolites released to the medium. Very low and similar levels of isotopic enrichment were detected on C2 and C3 of lactate; glutamine was labeled on C2 and C3 to a similar extent as well and labeling on C4 was only detected when glucose was not added. These labeling studies suggest that cytosolic malic enzyme is not active in primary astrocytes and support the occurrence of pyruvate recycling in astrocytes.

The ketogenic diet with extremely high fat and very low carbohydrate levels is very popular in society today. Although it has beneficial effects on epilepsy and neurodegenerative diseases, how ketogenic diets impact host glucose and lipid metabolism and gut microbiota still needs further investigation.

Anti-Aβ therapy has dominated clinical trials for the prevention and treatment of Alzheimer’s disease (AD). However, suppressing Aβ aggregation and disintegrating mature fibrils simultaneously remains a great challenge. In this work, we developed a new strategy using a charged tubular supramolecule (CTS) with pillar[5]arene as the backbone and modifying amino and carboxyl groups at the tubular terminals (noted as CTS-A, CTS-A/C, and CTS-C, respectively) to suppress Aβ fibrillation for the first time. According to the spectroscopic and microscopic characterizations, Aβ40fibrillation can be efficiently suppressed by CTS-A in a very low inhibitor:peptide (I:P) molar ratio (1:10). A greatly alleviated cytotoxic effect of Aβ peptides after the inhibition or disaggregation process is further disclosed. The well-organized supramolecular structure drives multivalent interaction and gains enhanced efficiency on amyloid fibrillar modulation. These results open a new path for the design of supramolecules in the application of AD treatment.

Improving the gut microbiota via calorie restriction is beneficial for human health. Our findings showed differential responses between calorie-restricted mice and ad libitum-fed mice. Compared with the ad libitum-fed mice, the calorie-restricted mice were less susceptible to cyclophosphamide side effects otherwise observed on the gut integrity and its microbiota. These results show the potential benefits of manipulating the gut microbiota with CR prior to cancer chemotherapy.

ABSTRACTAccumulating evidence implicates gut microbiota as promising targets for the treatment of type 2 diabetes mellitus (T2DM). With a randomized clinical trial, we tested the hypothesis that alteration of gut microbiota may be involved in the alleviation of T2DM with hyperlipidemia by metformin and a specifically designed herbal formula (AMC). Four hundred fifty patients with T2DM and hyperlipidemia were randomly assigned to either the metformin- or AMC-treated group. After 12 weeks of treatment, 100 patients were randomly selected from each group and assessed for clinical improvement. The effects of the two drugs on the intestinal microbiota were evaluated by analyzing the V3 and V4 regions of the 16S rRNA gene by Illumina sequencing and multivariate statistical methods. Both metformin and AMC significantly alleviated hyperglycemia and hyperlipidemia and shifted gut microbiota structure in diabetic patients. They significantly increased a coabundant group represented by Blautiaspp., which significantly correlated with the improvements in glucose and lipid homeostasis. However, AMC showed better efficacies in improving homeostasis model assessment of insulin resistance (HOMA-IR) and plasma triglyceride and also exerted a larger effect on gut microbiota. Furthermore, only AMC increased the coabundant group represented by Faecalibacteriumspp., which was previously reported to be associated with the alleviation of T2DM in a randomized clinical trial. Metformin and the Chinese herbal formula may ameliorate type 2 diabetes with hyperlipidemia via enriching beneficial bacteria, such as Blautiaand Faecalibacteriumspp.IMPORTANCEMetabolic diseases such as T2DM and obesity have become a worldwide public health threat. Accumulating evidence indicates that gut microbiota can causatively arouse metabolic diseases, and thus the gut microbiota serves as a promising target for disease control. In this study, we evaluated the role of gut microbiota during improvements in hyperglycemia and hyperlipidemia by two drugs: metformin and a specifically designed Chinese herbal formula (AMC) for diabetic patients with hyperlipidemia. Both drugs significantly ameliorated blood glucose and lipid levels and shifted the gut microbiota. Blautiaspp. were identified as being associated with improvements in glucose and lipid homeostasis for both drugs. AMC exerted larger effects on the gut microbiota together with better efficacies in improving HOMA-IR and plasma triglyceride levels, which were associated with the enrichment of Faecalibacteriumspp. In brief, these data suggest that gut microbiota might be involved in the alleviation of diabetes with hyperlipidemia by metformin and the AMC herbal formula.

ABSTRACTThe genomic basis of the response to dietary intervention of human gut beneficial bacteria remains elusive, which hinders precise manipulation of the microbiota for human health. After receiving a dietary intervention enriched with nondigestible carbohydrates for 105 days, a genetically obese child with Prader-Willi syndrome lost 18.4% of his body weight and showed significant improvement in his bioclinical parameters. We obtained five isolates (C1, C15, C55, C62, and C95) of one of the most abundantly promoted beneficial species, Bifidobacterium pseudocatenulatum, from a postintervention fecal sample. Intriguingly, these five B. pseudocatenulatumstrains showed differential responses during the dietary intervention. Two strains were largely unaffected, while the other three were promoted to different extents by the changes in dietary carbohydrate resources. The differential responses of these strains were consistent with their functional clustering based on the COGs (Clusters of Orthologous Groups), including those involved with the ABC-type sugar transport systems, suggesting that the strain-specific genomic variations may have contributed to the niche adaption. Particularly, B. pseudocatenulatumC15, which had the most diverse types and highest gene copy numbers of carbohydrate-active enzymes targeting plant polysaccharides, had the highest abundance after the dietary intervention. These studies show the importance of understanding genomic diversity of specific members of the gut microbiota if precise nutrition approaches are to be realized.IMPORTANCEThe manipulation of the gut microbiota via dietary approaches is a promising option for improving human health. Our findings showed differential responses of multiple B. pseudocatenulatumstrains isolated from the same habitat to the dietary intervention, as well as strain-specific correlations with bioclinical parameters of the host. The comparative genomics revealed a genome-level microdiversity of related functional genes, which may have contributed to these differences. These results highlight the necessity of understanding strain-level differences if precise manipulation of gut microbiota through dietary approaches is to be realized.