Spatial Meta-transcriptomes of human and murine intestines

We developed an analysis pipeline that can extract microbial sequences from Spatial Transcriptomic data and assign taxonomic labels to them, generating a spatial microbial abundance matrix in addition to the default host expression one, enabling simultaneous analysis of host expression and microbial distribution. We applied it on both human and murine intestinal datasets and validated the spatial microbial abundance information with alternative assays. Finally, we present a few biological insights that can be gained from this novel data. In summary, this proof of concept work demonstrated the feasibility of Spatial Meta-transcriptomic analysis, and pave the way for future experimental optimization.

Adsorption Mechanism of High-Concentration of Ammonium onto Chinese Natural Zeolite by Experimental Optimization and Theoretical Computation

Background Natural zeolite, abundant hierarchically porous structure aluminosilicate mineral, have high affinity to ammonium in solution. A considerable amount of literature has been published on the removal of ammonium in waters by zeolite, but mainly focused on the low-content and even trace ammonium. Few literatures were reported about the natural zeolite as adsorbent to remove high-level of ammonium in coal chemical wastewater. Therefore, adsorption mechanism of high-concentration ammonium in aqueous solution using Chinese natural zeolite was disclosed by the strategy of experimental optimization combining with Molecular Dynamics simulation. ResultsThe natural zeolite presented unique adsorption performances for high- ammonium distinguish from that of low ammonium, which were characterized as exhibiting faster adsorption rate, greater loading capacity and apparent desorption. The hybrid physical-chemical adsorption as the mechanism was induced from the adsorption kinetics and isotherm study in 4000 mg-N/L solution. Besides to the electrostatic attraction between the framework and guest ammonium exchanged by metal cations in the zeolite framework, the existence of the chemical bonding and hydrogen bonding forces was supported experimentally from the ion exchange capacity (IEC) investigation by the great disequilibrium between the total exchanged metal cations and ammonium. Moreover, the above were confirmed theoretically by the calculated results in the perspective of bonding strength in MD simulation. Considering comprehensively, we concluded physisorption dominated the initial adsorption stage as multilayer adsorption and chemisorption governed the subsequent adsorption process as monolayer form. Besides, the putative explanation for the desorption-occurrence was given that most ammonium concentrated in the channel openings physically, and transferred into the bulk solution preferentially through the mesopores and macropores. Conclusions Overall, we have demonstrated that the Chinese natural zeolite had the potential to capture high-concentration ammonium in wastewater remediation effectively. Considering with several research thinking comprehensively, this investigation enriched the adsorption mechanism research, and provided a novel insight for designing a workable approach for rapidly alleviating subsequent water decontamination processes using low-cost abundant minerals.

High-throughput and high-sensitivity capillary electrophoresis–mass spectrometry method for sulfur-containing amino acids

Biological thiol amino acids have been suggested as biomarkers for pathological changes because they are reactive chemicals that participate in various physiological processes. In this study, multisegmented injection capillary electrophoresis–mass spectrometry with online sample preconcentration was used for analysis of thiol amino acids and intermediates of sulfur metabolism in human glioma cell line U-251 with high accuracy, throughput, and sensitivity. This was achieved using multiple, large-volume injections for online sample preconcentration. The 16 intermediates of sulfur metabolism had a good linear correlation coefficient range of 0.984–1 and the limit of detection range was 1.4–203.9 ng/mL. The recovery ranges of most amino acids were 88.1–114.5%, 89.0–104.3%, and 76.9–104.5% at 0.3, 0.75, and 1.5 μg/mL, respectively. The relative standard deviation ranges for the inter- and intra-day precision were 1.8–10.7% and 4.3–18.8%, respectively. Compared with the traditional injection method, the analytical time for compounds in sulfur metabolism was reduced to 4 min/sample, the method throughput was enhanced five times, and the sensitivity was increased 14.4–33.1 times. Customized injection sequences were applied in experimental optimization. The developed method simplified the experimental optimization to one injection and is suitable for the analysis of sulfur metabolites in biological samples and has high sensitivity, throughput, speed, and accuracy.