Enhanced Astaxanthin Production in Escherichia coli via Morphology and Oxidative Stress Engineering

Astaxanthin is a carotenoid of high commercial value because of its excellent antioxidative, anti-inflammatory, and anticancer properties. Here, we developed a novel strategy for improving the production of astaxanthin via morphology and oxidative stress engineering. First, we identified the morphology-/membrane- and oxidative stress-related genes, which should be knocked down, using the CRISPRi system. Deleting the morphology-/membrane-related genes (lpp and bamB) and the oxidative stress-related genes (uspE and yggE) generated longer and larger cells with higher reactive oxygen species (ROS) levels, thus enhancing the production of astaxanthin and decreasing cell growth. To not only improve cell growth but also obtain longer and larger cells with higher ROS levels, a complementary expression system using a temperature-sensitive plasmid was established. Complementarily expressing the morphology-/membrane-related genes (lpp and bamB) and the oxidative stress-related genes (uspE and yggE) further improved the production of astaxanthin to 11.92 mg/g dry cell weight in shake flask cultures

Quasi-invariance of scattering properties of multicellular cyanobacterial aggregates

The radiative/scattering properties of cyanobacterial aggregates are crucial for understanding microalgal cultivation. This study analyzed scattering matrix elements and cross-sections of cyanobacterial aggregates using the discrete dipole approximation (DDA) method. The stochastic random walk approach was adopted to generate a force-biased packing model for multicellular filamentous cyanobacterial aggregates. The effects of shape and size of multicellular cyanobacterial aggregates on their scattering properties were investigated by this work. The possibility of invariance in the scattering properties was explored for cyanobacterial aggregates. The invariance interpretation intuitively represented the radiative property characteristics of the aggregates. The presented results show that the ratios of the matrix elements of cyanobacterial aggregates are nearly shape, size, and wavelength invariant. The extinction and absorption cross-sections (EACSs) per unit volume were shape and approximate size invariance of cyanobacterial aggregates, respectively. The absorption cross-section of aggregates is not merely a volumetric phenomenon for aggregates that exceed a certain size. Furthermore, the absorption cross-sections per unit volume are independent of the volumetric distribution of the microalgae cells. The invariance interpretation presents crucial characteristics of the scattering properties of cyanobacterial aggregates. The existence of invariance greatly improves our understanding of the scattering properties of microalgal aggregates. The scattering properties of microalgal aggregates are the most critical aspects of light propagation in the design, optimization, and operation of photobioreactors

Additional file 1 of Adaptive laboratory evolution and shuffling of Escherichia coli to enhance its tolerance and production of astaxanthin

Additional file 1: Fig. S1. The colorimetry of culture media for high throughput screening. Fig. S2. Production of astaxanthin determined using OD515 by the evolved strains after ARTP mutation. Fig. S3. Production of astaxanthin determined using OD515 by the strains after error-prone whole-genome shuffling. Fig. S4. HPLC analysis of carotenoid products extracted from E. coli AST-4AS cultured in 2-L bioreactor. Fig. S5. Effect of CRISPR repressing of the mutated gene on the astaxanthin production. Table S1. Mutated genes identified in E. coli AST-4AS. Table S2. Primers used in this study

MOESM1 of Spontaneous C-cleavage of a truncated intein as fusion tag to produce tag-free VP1 inclusion body nanoparticle vaccine against CVB3-induced viral myocarditis by the oral route

Additional file 1. Supplementary material

Characterization of <i>LcGAPC</i> and its transcriptional response to salt and alkali stress in two ecotypes of <i>Leymus chinensis</i> (Trin.) Tzvelev

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a housekeeping protein which plays various roles in non-metabolic processes in addition to its role in glucose catabolism. There are several GAPDH isoforms in plant cells. In this study, we cloned the full-length cDNA encoding the isoform GAPC in two ecotypes of Leymus chinensis (Trin.) Tzvelev, gray–green type and yellow–green type. The LcGAPC sequence includes an open reading frame (ORF) of 1014 bp encoding 337 amino acids. The predicted molecular weight is 36.5 kDa, and the pI is 6.19. The mRNA expression of LcGAPC decreased at 24 h and then increased significantly after 7 d after 400 mmol/L NaCl stress. At 200 mmol/L mixed alkali stress (NaHCO3:Na2CO3=9:1), the LcGAPC expression level gradually increased as time increased in the two ecotypes of L. chinensis. The results suggested that LcGAPC is a stress-inducible gene that might play a role in the salt and alkali stress response. This study provided a basis to further study the mechanism of expression characteristics under salt and alkali stress conditions of L. chinensis.</p

Table5_Comprehensive analysis of m5C-Related lncRNAs in the prognosis and immune landscape of hepatocellular carcinoma.docx

5-Methyladenosine (m5C) is a type of epigenetic modification involved in the progression of various cancers. To investigate the role of m5C-related long non-coding RNAs (lncRNAs) in the prognosis and immune cell infiltration in hepatocellular carcinoma (HCC), we obtained patients’ clinical information and transcriptome data of HCC from the Cancer Genome Atlas (TCGA) database. We applied Pearson correlation analysis to construct an m5C-related lncRNA–messenger RNA (mRNA) co-expression network. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analysis were employed to establish an m5C-related lncRNA prognostic risk model. We then verified the model using Kaplan–Meier analysis, principal component analysis, as well as univariate and multivariate Cox analyses. The expression of m5C-related lncRNAs was validated in HCC tissues and different cell lines. Combining the risk score and clinicopathological features, a nomogram was established for predicting the overall survival (OS) of HCC patients. Furthermore, gene set enrichment analysis (GSEA) revealed that some tumor-associated pathways were significantly enriched in the high-risk group. Immune cell infiltration analysis demonstrated that the levels of Treg cells, neutrophils, and M2 macrophages were higher in the high-risk group. In addition, patients with high tumor mutation burden (TMB) had worse OS than those with low TMB. We also assessed the immune checkpoint level and chemotherapeutic agent sensibility. Then in vitro experiments were performed to examine the biological function of MKLN1-AS in HCC cells and found that knockdown of MKLN1-AS suppressed the proliferation, migration, and invasion. In conclusion, m5C-related lncRNAs played a critical role in predicting the prognosis of patients with HCC and may serve as new therapeutic targets for HCC patients.</p

Table6_Comprehensive analysis of m5C-Related lncRNAs in the prognosis and immune landscape of hepatocellular carcinoma.doc

5-Methyladenosine (m5C) is a type of epigenetic modification involved in the progression of various cancers. To investigate the role of m5C-related long non-coding RNAs (lncRNAs) in the prognosis and immune cell infiltration in hepatocellular carcinoma (HCC), we obtained patients’ clinical information and transcriptome data of HCC from the Cancer Genome Atlas (TCGA) database. We applied Pearson correlation analysis to construct an m5C-related lncRNA–messenger RNA (mRNA) co-expression network. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analysis were employed to establish an m5C-related lncRNA prognostic risk model. We then verified the model using Kaplan–Meier analysis, principal component analysis, as well as univariate and multivariate Cox analyses. The expression of m5C-related lncRNAs was validated in HCC tissues and different cell lines. Combining the risk score and clinicopathological features, a nomogram was established for predicting the overall survival (OS) of HCC patients. Furthermore, gene set enrichment analysis (GSEA) revealed that some tumor-associated pathways were significantly enriched in the high-risk group. Immune cell infiltration analysis demonstrated that the levels of Treg cells, neutrophils, and M2 macrophages were higher in the high-risk group. In addition, patients with high tumor mutation burden (TMB) had worse OS than those with low TMB. We also assessed the immune checkpoint level and chemotherapeutic agent sensibility. Then in vitro experiments were performed to examine the biological function of MKLN1-AS in HCC cells and found that knockdown of MKLN1-AS suppressed the proliferation, migration, and invasion. In conclusion, m5C-related lncRNAs played a critical role in predicting the prognosis of patients with HCC and may serve as new therapeutic targets for HCC patients.</p

Image2_Comprehensive analysis of m5C-Related lncRNAs in the prognosis and immune landscape of hepatocellular carcinoma.tif

5-Methyladenosine (m5C) is a type of epigenetic modification involved in the progression of various cancers. To investigate the role of m5C-related long non-coding RNAs (lncRNAs) in the prognosis and immune cell infiltration in hepatocellular carcinoma (HCC), we obtained patients’ clinical information and transcriptome data of HCC from the Cancer Genome Atlas (TCGA) database. We applied Pearson correlation analysis to construct an m5C-related lncRNA–messenger RNA (mRNA) co-expression network. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analysis were employed to establish an m5C-related lncRNA prognostic risk model. We then verified the model using Kaplan–Meier analysis, principal component analysis, as well as univariate and multivariate Cox analyses. The expression of m5C-related lncRNAs was validated in HCC tissues and different cell lines. Combining the risk score and clinicopathological features, a nomogram was established for predicting the overall survival (OS) of HCC patients. Furthermore, gene set enrichment analysis (GSEA) revealed that some tumor-associated pathways were significantly enriched in the high-risk group. Immune cell infiltration analysis demonstrated that the levels of Treg cells, neutrophils, and M2 macrophages were higher in the high-risk group. In addition, patients with high tumor mutation burden (TMB) had worse OS than those with low TMB. We also assessed the immune checkpoint level and chemotherapeutic agent sensibility. Then in vitro experiments were performed to examine the biological function of MKLN1-AS in HCC cells and found that knockdown of MKLN1-AS suppressed the proliferation, migration, and invasion. In conclusion, m5C-related lncRNAs played a critical role in predicting the prognosis of patients with HCC and may serve as new therapeutic targets for HCC patients.</p

Table7_Comprehensive analysis of m5C-Related lncRNAs in the prognosis and immune landscape of hepatocellular carcinoma.docx

5-Methyladenosine (m5C) is a type of epigenetic modification involved in the progression of various cancers. To investigate the role of m5C-related long non-coding RNAs (lncRNAs) in the prognosis and immune cell infiltration in hepatocellular carcinoma (HCC), we obtained patients’ clinical information and transcriptome data of HCC from the Cancer Genome Atlas (TCGA) database. We applied Pearson correlation analysis to construct an m5C-related lncRNA–messenger RNA (mRNA) co-expression network. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analysis were employed to establish an m5C-related lncRNA prognostic risk model. We then verified the model using Kaplan–Meier analysis, principal component analysis, as well as univariate and multivariate Cox analyses. The expression of m5C-related lncRNAs was validated in HCC tissues and different cell lines. Combining the risk score and clinicopathological features, a nomogram was established for predicting the overall survival (OS) of HCC patients. Furthermore, gene set enrichment analysis (GSEA) revealed that some tumor-associated pathways were significantly enriched in the high-risk group. Immune cell infiltration analysis demonstrated that the levels of Treg cells, neutrophils, and M2 macrophages were higher in the high-risk group. In addition, patients with high tumor mutation burden (TMB) had worse OS than those with low TMB. We also assessed the immune checkpoint level and chemotherapeutic agent sensibility. Then in vitro experiments were performed to examine the biological function of MKLN1-AS in HCC cells and found that knockdown of MKLN1-AS suppressed the proliferation, migration, and invasion. In conclusion, m5C-related lncRNAs played a critical role in predicting the prognosis of patients with HCC and may serve as new therapeutic targets for HCC patients.</p

Table2_Comprehensive analysis of m5C-Related lncRNAs in the prognosis and immune landscape of hepatocellular carcinoma.doc

5-Methyladenosine (m5C) is a type of epigenetic modification involved in the progression of various cancers. To investigate the role of m5C-related long non-coding RNAs (lncRNAs) in the prognosis and immune cell infiltration in hepatocellular carcinoma (HCC), we obtained patients’ clinical information and transcriptome data of HCC from the Cancer Genome Atlas (TCGA) database. We applied Pearson correlation analysis to construct an m5C-related lncRNA–messenger RNA (mRNA) co-expression network. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analysis were employed to establish an m5C-related lncRNA prognostic risk model. We then verified the model using Kaplan–Meier analysis, principal component analysis, as well as univariate and multivariate Cox analyses. The expression of m5C-related lncRNAs was validated in HCC tissues and different cell lines. Combining the risk score and clinicopathological features, a nomogram was established for predicting the overall survival (OS) of HCC patients. Furthermore, gene set enrichment analysis (GSEA) revealed that some tumor-associated pathways were significantly enriched in the high-risk group. Immune cell infiltration analysis demonstrated that the levels of Treg cells, neutrophils, and M2 macrophages were higher in the high-risk group. In addition, patients with high tumor mutation burden (TMB) had worse OS than those with low TMB. We also assessed the immune checkpoint level and chemotherapeutic agent sensibility. Then in vitro experiments were performed to examine the biological function of MKLN1-AS in HCC cells and found that knockdown of MKLN1-AS suppressed the proliferation, migration, and invasion. In conclusion, m5C-related lncRNAs played a critical role in predicting the prognosis of patients with HCC and may serve as new therapeutic targets for HCC patients.</p