Enrichment of a microbial community performing anaerobic oxidation of methane in a continuous high-pressure bioreactor

<p>Abstract</p> <p>Background</p> <p>Anaerobic oxidation of methane coupled to sulphate reduction (SR-AOM) prevents more than 90% of the oceanic methane emission to the atmosphere. In a previous study, we demonstrated that the high methane pressure (1, 4.5, and 8 MPa) stimulated <it>in vitro </it>SR-AOM activity. However, the information on the effect of high-pressure on the microbial community structure and architecture was still lacking.</p> <p>Results</p> <p>In this study we analysed the long-term enrichment (286 days) of this microbial community, which was mediating SR-AOM in a continuous high-pressure bioreactor. 99.7% of the total biovolume represented cells in the form of small aggregates (diameter less then 15 μm). An increase of the total biovolume was observed (2.5 times). After 286 days, the ANME-2 (anaerobic methanotrophic archaea subgroup 2) and SRB (sulphate reducing bacteria) increased with a factor 12.5 and 8.4, respectively.</p> <p>Conclusion</p> <p>This paper reports a net biomass growth of communities involved in SR-AOM, incubated at high-pressure.</p

Quantitative Proteomics of Chromochloris zofingiensis Reveals the Key Proteins Involved in Cell Growth and Bioactive Compound Biosynthesis

Glucose metabolism regulates cell growth and affects astaxanthin accumulation in the green algae Chromochloris zofingiensis. Hub gene functioning in this bioactive compound has been illustrated at the genome, transcriptome and metabolome level, but is rather limited from a proteome aspect. Microalgal cell produce an enhanced biomass (8-fold higher) but decreased lipid and astaxanthin content (~20% less) in the glucose condition compared to the control. Here, we investigate the proteomic response of C. zofingiensis grown with and without glucose using an LC-MS/MS-based Tandem Mass Tag (TMT) approach. The proteomic analysis demonstrated that glucose supplementation triggers the upregulation of 105 proteins and downregulation of 151 proteins. Thus, the carbon and energy flux might flow to cell growth, which increased the associated protein abundance, including DNA polymerase, translation initiation factor, 26S proteasome regulatory subunits, and the marker enzyme of the TCA cycle ribosomal protein. Moreover, the glucose supplement triggered the downregulation of proteins mainly involved in photosynthesis, chloroplasts, valine, leucine and isoleucine biosynthesis, 2-oxocarboxylic acid metabolism, and pantothenate and CoA biosynthesis pathways. This proteomic analysis is likely to provide new insights into algal growth and lipid or astaxanthin accumulation upon glucose supplementation, providing a foundation for further development of C. zofingiensis as oleaginous microalga for bioengineering applications

Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation

Social networks are considered to be heterogeneous graph neural networks (HGNNs) with deep learning technological advances. HGNNs, compared to homogeneous data, absorb various aspects of information about individuals in the training stage. That means more information has been covered in the learning result, especially sensitive information. However, the privacy-preserving methods on homogeneous graphs only preserve the same type of node attributes or relationships, which cannot effectively work on heterogeneous graphs due to the complexity. To address this issue, we propose a novel heterogeneous graph neural network privacy-preserving method based on a differential privacy mechanism named HeteDP, which provides a double guarantee on graph features and topology. In particular, we first define a new attack scheme to reveal privacy leakage in the heterogeneous graphs. Specifically, we design a two-stage pipeline framework, which includes the privacy-preserving feature encoder and the heterogeneous link reconstructor with gradients perturbation based on differential privacy to tolerate data diversity and against the attack. To better control the noise and promote model performance, we utilize a bi-level optimization pattern to allocate a suitable privacy budget for the above two modules. Our experiments on four public benchmarks show that the HeteDP method is equipped to resist heterogeneous graph privacy leakage with admirable model generalization

Understanding the action mechanisms of metformin in the gastrointestinal tract

Metformin is the initial medication recommended for the treatment of type 2 diabetes mellitus (T2DM). In addition to diabetes treatment, the function of metformin also can be anti-aging, antiviral, and anti-inflammatory. Nevertheless, further exploration is required to fully understand its mode of operation. Historically, the liver has been acknowledged as the main location where metformin reduces glucose levels, however, there is increasing evidence suggesting that the gastrointestinal tract also plays a significant role in its action. In the gastrointestinal tract, metformin effects glucose uptake and absorption, increases glucagon-like peptide-1 (GLP-1) secretion, alters the composition and structure of the gut microbiota, and modulates the immune response. However, the side effects of it cannot be ignored such as gastrointestinal distress in patients. This review outlines the impact of metformin on the digestive system and explores potential explanations for variations in metformin effectiveness and adverse effects like gastrointestinal discomfort

Assembly of Multi‐Spheroid Cellular Architectures by Programmable Droplet Merging

Artificial multicellular systems are gaining importance in the field of tissue engineering and regenerative medicine. Reconstruction of complex tissue architectures in vitro is nevertheless challenging, and methods permitting controllable and high‐throughput fabrication of complex multicellular architectures are needed. Here, a facile and high‐throughput method is developed based on a tunable droplet‐fusion technique, allowing programmed assembly of multiple cell spheroids into complex multicellular architectures. The droplet‐fusion technique allows for construction of various multicellular architectures (double‐spheroids, multi‐spheroids, hetero‐spheroids) in a miniaturized high‐density array format. As an example of application, the propagation of Wnt signaling is investigated within hetero‐spheroids formed from two fused Wnt‐releasing and Wnt‐reporter cell spheroids. The developed method provides an approach for miniaturized, high‐throughput construction of complex 3D multicellular architectures and can be applied for studying various biological processes including cell signaling, cancer invasion, embryogenesis, and neural development

N-Glycosylation of LRP6 by B3GnT2 Promotes Wnt/β-Catenin Signalling

Reception of Wnt signals by cells is predominantly mediated by Frizzled receptors in conjunction with a co-receptor, the latter being LRP6 or LRP5 for the Wnt/β-catenin signalling pathway. It is important that cells maintain precise control of receptor activation events in order to properly regulate Wnt/β-catenin signalling as aberrant signalling can result in disease in humans. Phosphorylation of the intracellular domain (ICD) of LRP6 is well known to regulate Wntβ-catenin signalling; however, less is known for regulatory post-translational modification events within the extracellular domain (ECD). Using a cell culture-based expression screen for functional regulators of LRP6, we identified a glycosyltransferase, B3GnT2-like, from a teleost fish (medaka) cDNA library, that modifies LRP6 and regulates Wnt/β-catenin signalling. We provide both gain-of-function and loss-of-function evidence that the single human homolog, B3GnT2, promotes extension of polylactosamine chains at multiple N-glycans on LRP6, thereby enhancing trafficking of LRP6 to the plasma membrane and promoting Wnt/β-catenin signalling. Our findings further highlight the importance of LRP6 as a regulatory hub in Wnt signalling and provide one of the few examples of how a specific glycosyltransferase appears to selectively target a signalling pathway component to alter cellular signalling events

Gestational weight gain and pregnancy outcomes in Chinese women with type 2 diabetes mellitus: evidence from a tertiary hospital in Beijing

ObjectiveTo examine the effects of gestational weight gain on pregnancy outcomes and determine the optimal range of weight gain during pregnancy for Chinese women with type 2 diabetes mellitus.MethodsThis retrospective cohort study included 691 Chinese women with type 2 diabetes mellitus from 2012 to 2020. The study utilized a statistical-based approach to determine the optimal range of gestational weight gain. Additionally, multivariate logistic regression analysis was conducted to assess the impact of gestational weight gain on pregnancy outcomes.Results(1) In the obese subgroup, gestational weight gain below the recommendations was associated with decreased risks of large for gestational age (adjusted odds ratio [aOR] 0.19; 95% confidence interval [CI] 0.06-0.60) and macrosomia (aOR 0.18; 95% CI 0.05-0.69). In the normal weight subgroup, gestational weight gain below the recommendations of the Institute of Medicine was associated with decreased risks of preeclampsia (aOR 0.18; 95% CI 0.04-0.82) and neonatal hypoglycemia (aOR 0.38; 95% CI 0.15-0.97). (2) In the normal weight subgroup, gestational weight gain above the recommendations of the Institute of Medicine was associated with an increased risk of large for gestational age (aOR 4.56; 95% CI 1.54-13.46). In the obese subgroup, gestational weight gain above the recommendations was associated with an increased risk of preeclampsia (aOR 2.74; 95% CI 1.02, 7.38). (3) The optimal ranges of gestational weight gain, based on our study, were 9-16 kg for underweight women, 9.5-14 kg for normal weight women, 6.5-12 kg for overweight women, and 3-10 kg for obese women. (4) Using the optimal range of gestational weight gain identified in our study seemed to provide better prediction of adverse pregnancy outcomes.ConclusionFor Chinese women with type 2 diabetes, inappropriate gestational weight gain is associated with adverse pregnancy outcomes, and the optimal range of gestational weight gain may differ from the Institute of Medicine recommendations