ABSTRACT
Microorganisms are closely associated with human diseases and health. Understanding the composition and function of microbial communities requires extensive research. Metaproteomics has recently become an important method for throughout and in-depth study of microorganisms. However, major challenges in terms of sample processing, mass spectrometric data acquisition, and data analysis limit the development of metaproteomics owing to the complexity and high heterogeneity of microbial community samples. In metaproteomic analysis, optimizing the preprocessing method for different types of samples and adopting different microbial isolation, enrichment, extraction, and lysis schemes are often necessary. Similar to those for single-species proteomics, the mass spectrometric data acquisition modes for metaproteomics include data-dependent acquisition (DDA) and data-independent acquisition (DIA). DIA can collect comprehensive peptide information from a sample and holds great potential for future development. However, data analysis for DIA is challenged by the complexity of metaproteome samples, which hinders the deeper coverage of metaproteomes. The most important step in data analysis is the construction of a protein sequence database. The size and completeness of the database strongly influence not only the number of identifications, but also analyses at the species and functional levels. The current gold standard for metaproteome database construction is the metagenomic sequencing-based protein sequence database. A public database-filtering method based on an iterative database search has been proven to have strong practical value. The peptide-centric DIA data analysis method is a mainstream data analysis strategy. The development of deep learning and artificial intelligence will greatly promote the accuracy, coverage, and speed of metaproteomic analysis. In terms of downstream bioinformatics analysis, a series of annotation tools that can perform species annotation at the protein, peptide, and gene levels has been developed in recent years to determine the composition of microbial communities. The functional analysis of microbial communities is a unique feature of metaproteomics compared with other omics approaches. Metaproteomics has become an important component of the multi-omics analysis of microbial communities, and has great development potential in terms of depth of coverage, sensitivity of detection, and completeness of data analysis.
Subject(s)
Proteomics , Databases, Protein , Mass Spectrometry/methods , Metagenomics/methods , Microbiota , Proteomics/methodsABSTRACT
The titanium-enriched slag was obtained via atmospheric hydrochloric acid leaching of mechanically activated vanadium titanomagnetite concentrates (VTMCs). Under the influence of mechanical activation, specific physicochemical changes were observed via X-ray diffractometry, scanning electron microscopy, and granulometric laser diffraction analysis. Experimental findings revealed that the mechanical activation of VTMCs resulted in a decrease in the median volume particle diameter (d50) and an increase in the specific surface area (SA) with an increased milling time. The results of the leaching experiment revealed that the mechanical activation treatment favors the extraction of iron (Fe) and titanium dioxide (TiO2) from the VTMCs. The Fe and TiO2 extractions from the mechanically activated sample after 10 h compared with the unactivated sample were increased by 12.82% and 4.73%, respectively. The presence of the ilmenite phase in the titanium-enriched slag was confirmed by X-ray diffractometry and EDS patterns, and the content of the TiO2 in the enriched slag can get as high as 43.75%.
ABSTRACT
Black TiO2 has attracted widespread attention due to its visible light absorption and wide range of applications. However, the currently reported preparation methods for black TiO2 are not suitable for large-scale production due to its being prepared under high vacuum and over a long time. We have successfully prepared black TiO2 under normal pressure and short time conditions. The as-prepared black titanium dioxide was characterized by XRD, XPS, TEM, UV-visible absorption spectrum and other characterization methods. The result shows that the as prepared black titanium dioxide had a disordered structure and oxygen vacancy defects on the surface, and exhibits excellent visible and near infrared absorption performance. The black TiO2 sample was prepared under 650 °C 60 min exhibits excellent visible light photocatalytic performance, and can degrade 56% MO after visible light irradiation for 120 min.
ABSTRACT
Our previous study demonstrates that hypoxia promotes human bone marrow-derived mesenchymal stem cell (hMSC) proliferation. The aim of the present study was to investigate the gene profile involved in this process by using cDNA microarray. Cultured hMSCs were treated with hypoxia (3% O(2)) for 4 h, 12 h, 24 h, 36 h, 48 h and 72 h, respectively. Then these cells were collected to prepare total RNA. Hypoxia-induced gene expression profile was examined and analyzed by GenePix Pro 4.0 software. Some of cDNA microarray results were confirmed by RT-PCR. Microarray analysis identified that 282 genes expressed differentially, of which most were involved in metabolism. The number of differentially expressed genes at different hypoxia time points was different, and most genes were regulated after 24-hour hypoxia. Among the 282 differentially expressed genes, 4 hypoxia-inducible factor 1 (HIF-1) targeted genes and 10 genes that changed at 3 continuous time points were found. The results obtained indicated that 4 HIF-1 targeted genes, i.e., transforming growth factor beta3 (TGFbeta3), phospho-glycerate kinase 1 (PGK1), insulin-like growth factor binding protein 3 (IGFBP3) and BCL2/adenovirus E1B 19 kDa interacting protein 3 (BNIP3), displayed up-regulated pattern at 36 h under hypoxia. BNIP3 displayed a dynamically up-regulated pattern at 12, 36 and 72 h under hypoxia. However, TGFbeta3 and PGK1 were down-regulated at 72 h. In addition, the gene expressions of adenylate kinase 3-like 1 (HAC), neurofilament light polypeptide 68 kDa (NEFL), N-myc downstream regultated gene 1 (NDRG1), discoidin domain receptor family member 1 (DDR1), tribbles homolog 3 (TRIB3), nucleoprotein (AHNAK) and eukaryotic elongation factor selenocyteine-tRNA-specific (EESTS) were up-regulated. Moreover, the gene expressions of EESTS, NEFL were up-regulated at 5 different time points under hypoxia. Furthermore, it was found that the gene expressions of histone cluster 1 (HIS1) and transferring receptor (TFRC) were down-regulated. These results suggest that the proliferation of hMSCs induced by hypoxia is a complex process in which a number of genes may be involved.