Enhanced bacterial cellulose production in Gluconacetobacter xylinus by overexpression of two genes (bscC and bcsD) and a modified static culture.

Bacterial cellulose (BC), a nanostructured material, is renowned for its excellent properties. However, its production by bacteria is costly due to low medium utilization and conversion rates. To enhance the yield of BC, this study aimed to increase BC yield through genetic modification, specifically by overexpressing bcsC and bcsD in Gluconacetobacter xylinus, and by developing a modified culture method to reduce medium viscosity by adding water during fermentation. As a result, BC yields of 5.4, 6.2, and 6.8 g/L were achieved from strains overexpressing genes bcsC, bcsD, and bcsCD, significantly surpassing the yield of 2.2 g/L from wild-type (WT) strains. In the modified culture, the BC yields of all four strains increased by >1 g/L with the addition of 20 mL of water during fermentation. Upon comparing the properties of BC, minimal differences were observed between the WT and pbcsC strains, as well as between the static and modified cultures. In contrast, BC produced by strains overexpressing bcsD had a denser microstructural network and exhibited demonstrated higher tensile strength and elongation-to-break. Compared to WT, BC from bcsD overexpressed strains also displayed enhanced crystallinity, higher degree of polymerization and improved thermal stability.

Tuberculostearic acid incorporated predictive model contributes to the clinical diagnosis of tuberculous meningitis.

The conventional confirmation tests of tuberculous meningitis (TBM) are usually low in sensitivity, leading to high TBM mortality. Hence, sensitive methods for indicating the presence of bacilli are required. Tuberculostearic acid (TBSA), a constituent from Mycobacterium tuberculosis had been evaluated as a promising marker, but fails to demonstrate consistent results for definite TBM. This study retrospectively reviewed medical records of 113 TBM suspects, constructing a TBSA-combined scoring system based on multiple factors, which show sensitivity and specificity of 0.8148 and 0.8814, respectively, and the area under the receiver operating characteristic curve of 0.9010. Multivariate analyses revealed four co-predictive factors strongly associated with TBSA: extra-neural tuberculosis, basal meningeal enhancement, CSF glucose/Serum glucose <0.595, and coinfection in CNS (Total). The subsequent machine learning-based validation showed correspondent importance to factors in the TBSA model. This study demonstrates a simple scoring system to facilitate TBM prediction, yield reliable diagnoses and allow timely treatment initiation.

Multi-Omics Characterization of Tumor Microenvironment Heterogeneity and Immunotherapy Resistance Through Cell States-Based Subtyping in Bladder Cancer.

Due to the strong heterogeneity of bladder cancer (BC), there is often substantial variation in the prognosis and efficiency of immunotherapy among BC patients. For the precision treatment and assessment of prognosis, the subtyping of BC plays a critical role. Despite various subtyping methods proposed previously, most of them are based on a limited number of molecules, and none of them is developed on the basis of cell states. In this study, we construct a single-cell atlas by integrating single cell RNA-seq, RNA microarray, and bulk RNA-seq data to identify the absolute proportion of 22 different cell states in BC, including immune and nonimmune cell states derived from tumor tissues. To explore the heterogeneity of BC, BC was identified into four different subtypes in multiple cohorts using an improved consensus clustering algorithm based on cell states. Among the four subtypes, C1 had median prognosis and best overall response rate (ORR), which characterized an immunosuppressive tumor microenvironment. C2 was enriched in epithelial-mesenchymal transition/invasion, angiogenesis, immunosuppression, and immune exhaustion. Surely, C2 performed the worst in prognosis and ORR. C3 with worse ORR than C2 was enriched in angiogenesis and almost nonimmune exhaustion. Displaying an immune effective environment, C4 performed the best in prognosis and ORR. We found that patients with just an immunosuppressive environment are suitable for immunotherapy, but patients with an immunosuppressive environment accompanied by immune exhaustion or angiogenesis may resist immunotherapy. Furthermore, we conducted exploration into the heterogeneity of the transcriptome, mutational profiles, and somatic copy-number alterations in four subtypes, which could explain the significant differences related to cell states in prognosis and ORR. We also found that PD-1 in immune and tumor cells could both influence ORR in BC. The level of TGFß in a cell state can be opposite to the overall level in the tissues, and the level in a specific cell state could predict ORR more accurately. Thus, our work furthers the understanding of heterogeneity and immunotherapy resistance in BC, which is expected to assist clinical practice and serve as a supplement to the current subtyping method from a novel perspective of cell states.

Efficient Biofilm-Based Fermentation Strategies for L-Threonine Production by Escherichia coli.

Biofilms provide cells favorable growth conditions, which have been exploited in industrial biotechnological processes. However, industrial application of the biofilm has not yet been reported in Escherichia coli, one of the most important platform strains, though the biofilm has been extensively studied for pathogenic reasons. Here, we engineered E. coli by overexpressing the fimH gene, which successfully enhanced its biofilm formation under industrial aerobic cultivation conditions. Subsequently, a biofilm-based immobilized fermentation strategy was developed. L-threonine production was increased from 10.5 to 14.1 g/L during batch fermentations and further to 17.5 g/L during continuous (repeated-batch) fermentations with enhanced productivities. Molecular basis for the enhanced biofilm formation and L-threonine biosynthesis was also studied by transcriptome analysis. This study goes beyond the conventional research focusing on pathogenic aspects of E. coli biofilm and represents a successful application case of engineered E. coli biofilm to industrial processes.

Nitric oxide increases biofilm formation in Saccharomyces cerevisiae by activating the transcriptional factor Mac1p and thereby regulating the transmembrane protein Ctr1.

BACKGROUND: Biofilms with immobilized cells encased in extracellular polymeric substance are beneficial for industrial fermentation. Their formation is regulated by various factors, including nitric oxide (NO), which is recognized as a quorum-sensing and signal molecule. The mechanisms by which NO regulates bacterial biofilms have been studied extensively and deeply, but were rarely studied in fungi. In this study, we observed the effects of low concentrations of NO on biofilm formation in Saccharomyces cerevisiae. Transcriptional and proteomic analyses were applied to study the mechanism of this regulation. RESULTS: Adding low concentrations of NO donors (SNP and NOC-18) enhanced biofilm formation of S. cerevisiae in immobilized carriers and plastics. Transcriptional and proteomic analyses revealed that expression levels of genes regulated by the transcription factor Mac1p was upregulated in biofilm cells under NO treatment. MAC1 promoted yeast biofilm formation which was independent of flocculation gene FLO11. Increased copper and iron contents, both of which were controlled by Mac1p in the NO-treated and MAC1-overexpressing cells, were not responsible for the increased biofilm formation. CTR1, one out of six genes regulated by MAC1, plays an important role in biofilm formation. Moreover, MAC1 and CTR1 contributed to the cells' resistance to ethanol by enhanced biofilm formation. CONCLUSIONS: These findings suggest that a mechanism for NO-mediated biofilm formation, which involves the regulation of CTR1 expression levels by activating its transcription factor Mac1p, leads to enhanced biofilm formation. The role of CTR1 protein in yeast biofilm formation may be due to the hydrophobic residues in its N-terminal extracellular domain, and further research is needed. This work offers a possible explanation for yeast biofilm formation regulated by NO and provides approaches controlling biofilm formation in industrial immobilized fermentation by manipulating expression of genes involved in biofilm formation.

FLO Genes Family and Transcription Factor MIG1 Regulate Saccharomyces cerevisiae Biofilm Formation During Immobilized Fermentation.

Saccharomyces cerevisiae immobilization is commonly used for efficient ethanol fuel production in industry due to the relatively higher ethanol stress resistance of S. cerevisiae in biofilms relative to planktonic cells. The mechanisms of biofilm formation and stress resistance, however, remain ambiguous. By analyzing biofilm and planktonic cell transcriptomes, this study observed that MIG1 (encoding a transcription factor) expression in cells increases during the biofilm formation process. To identify the role of MIG1 in yeast biofilm formation and the ethanol resistance of these cells, MIG1 was deleted and complemented in S. cerevisiae 1308. Results showed the MIG1 deletion mutant strain demonstrated weaker biofilm formation ability both on fibers and plastic than the wild-type and these could be restored by expressing MIG1 in deletion mutant. To verify the ability of MIG1 to regulate the expression of FLO genes, which encode adhesions responsible for yeast biofilm formation, FLO gene transcription levels were measured via qRT-PCR. Relative to wild-type S. cerevisiae, the adhesion genes FLO1, 5, and 9 which also demonstrate increased expression in the transcriptome of yeast cells during biofilm formation, but not FLO11, were down-regulated in the MIG1 mutant strain. Additionally, the MIG1 mutant lost a majority of its flocculation ability, which depended on cell-cell adhesions and its slightly invasive growth ability, dependent on cell-substrate adhesion. Deleting FLO1, 5, and 9 decreased biofilm formation on plastics, suggesting these FLO genes contribute to the biofilm formation process alongside FLO11. Moreover, the ethanol tolerance of yeast decreased in the MIG1 deletion mutant as well as the FLO11 deletion mutant, resulting in reduced biofilm formation during fermentation. It remains possible that in the later period of fermentation, when ethanol has accumulated, an over-expression of the FLO1, 5, and 9 genes regulated by MIG1 would enhanced cell-cell adhesions and thus protect cells in the outer layer of biofilms from ethanol, a function primarily dependent on cell-cell adhesions. This work offers a possible explanation for how biofilm formation is regulated during the immobilized fermentation process, and can enhance environmental tolerance in industrial production.