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ABSTRACT Microalgae are a potential source of biodiesel owing to their simple structure and high biomass and lipid production rates. Here, we demonstrate that fatty acid (FA) contents can be altered in Chlorella sp. JB6 in the presence of sodium bicarbonate (NaHCO3). We cloned the key genes necessary for FA de novo synthesis conserved in JB6, including biotin carboxyl carrier protein (BCCP), β-carboxyltransferase (β-CT), malonyl CoA-ACP malonyl transferase (MCMT), 3-ketoacyl-ACP reductase (KAR), β-ketoacyl-[acyl carrier protein] synthase I (KASI), and KASII, and successfully transferred plasmids carrying these genes into JB6 cells. We found that overexpression of BCCP, MCMT, KASI, and KASII inhibited the growth of JB6 cells and decreased their resistance to NaHCO3. Notably, ectopic expression of these genes promoted very long-chain saturated FA (>20 C) accumulation. Taken together, we demonstrate that these genes are critical for JB6 growth and resistance to NaHCO3 and can be used for metabolic engineering. IMPORTANCE Fatty acid (FA) contents can be altered in Chlorella JB6 in the presence of sodium bicarbonate (NaHCO3). Overexpression of the FA de novo synthesis genes inhibited the growth of JB6 cells and decreased their resistance to NaHCO3, but these transgenic JB6 strains could grow in a medium containing as high as 300 mM NaHCO3. In JB6, ectopic expression of the FA de novo synthesis genes increased the synthesis of very long-chain saturated FA (> 20C).

Abstract Background Although gemcitabine has been considered as the first-line drug for advanced pancreatic cancer (PC), development of resistance to gemcitabine severely limits the effectiveness of this chemotherapy, and the underlying mechanism of gemcitabine resistance remains unclear. Various factors, such as ATP binding cassette (ABC) transporters, microRNAs and their downstream signaling pathways are included in chemoresistance to gemcitabine. This study investigated the potential mechanisms of microRNAs and ABC transporters related signaling pathways for PC resistance to gemcitabine both in vivo and in vitro. Methods Immunohistochemistry and Western blotting were applied to detect the expression of ABC transporters. Molecular docking analysis was performed to explore whether gemcitabine interacted with ABC transporters. Gain-of-function and loss-of-function analyses were performed to investigate the functions of hsa-miR-3178 in vitro and in vivo. Bioinformatics analysis, Western blotting and dual-luciferase reporter assay were used to confirm the downstream regulatory mechanisms of hsa-miR-3178. Results We found that P-gp, BCRP and MRP1 were highly expressed in gemcitabine-resistant PC tissues and cells. Molecular docking analysis revealed that gemcitabine can bind to the ABC transporters. Hsa-miR-3178 was upregulated in gemcitabine resistance PANC-1 cells as compared to its parental PANC-1 cells. Moreover, we found that hsa-miR-3178 promoted gemcitabine resistance in PC cells. These results were also verified by animal experiments. RhoB was down-regulated in gemcitabine-resistant PC cells and it was a downstream target of hsa-miR-3178. Kaplan–Meier survival curve showed that lower RhoB expression was significantly associated with poor overall survival in PC patients. Rescue assays demonstrated that RhoB could reverse hsa-miR-3178-mediated gemcitabine resistance. Interestingly, hsa-miR-3178 promoted gemcitabine resistance in PC by activating the PI3K/Akt pathway-mediated upregulation of ABC transporters. Conclusions Our results indicate that hsa-miR-3178 promotes gemcitabine resistance via RhoB/PI3K/Akt signaling pathway-mediated upregulation of ABC transporters. These findings suggest that hsa-miR-3178 could be a novel therapeutic target for overcoming gemcitabine resistance in PC.

BackgroundMany studies have reported that N6-methyladenosine (m6A) modification plays a critical role in the epigenetic regulation of organisms and especially in the pathogenesis of malignant diseases. However, m6A research has mainly focused on methyltransferase activity mediated by METTL3, and few studies have focused on METTL16. The aim of this study was to investigate the mechanism of METTL16, which mediates m6A modification, and its role in pancreatic adenocarcinoma (PDAC) cell proliferation.MethodsClinicopathologic and survival data were retrospectively collected from 175 PDAC patients from multiple clinical centers to detect the expression of METTL16. CCK-8, cell cycle, EdU and xenograft mouse model experiments were used to evaluate the proliferation effect of METTL16. Potential downstream pathways and mechanisms were explored via RNA sequencing, m6A sequencing, and bioinformatic analyses. Regulatory mechanisms were studied through methyltransferase inhibition, RIP, MeRIP‒qPCR assays.ResultsWe found that METTL16 expression was markedly downregulated in PDAC, and multivariate Cox regression analyses revealed that METTL16 was a protective factor for PDAC patients. We also demonstrated that METTL16 overexpression inhibited PDAC cell proliferation. Furthermore, we identified a METTL16-p21 signaling axis, with downregulation of METTL16 resulting in inhibition of CDKN1A (p21). Additionally, METTL16 silencing and overexpression experiments highlighted m6A modification alterations in PDAC.ConclusionsMETTL16 plays a tumor-suppressive role and suppresses PDAC cell proliferation through the p21 pathway by mediating m6A modification. METTL16 may be a novel marker of PDAC carcinogenesis and target for the treatment of PDAC.

This work addresses the multiscale optimization of the purification processes of antibody fragments. Chromatography decisions in the manufacturing processes are optimized, including the number of chromatography columns and their sizes, the number of cycles per batch, and the operational flow velocities. Data-driven models of chromatography throughput are developed considering loaded mass, flow velocity, and column bed height as the inputs, using manufacturing-scale simulated datasets based on microscale experimental data. The piecewise linear regression modeling method is adapted due to its simplicity and better prediction accuracy in comparison with other methods. Two alternative mixed-integer nonlinear programming (MINLP) models are proposed to minimize the total cost of goods per gram of the antibody purification process, incorporating the data-driven models. These MINLP models are then reformulated as mixed-integer linear programming (MILP) models using linearization techniques and multiparametric disaggregation. Two industrially relevant cases with different chromatography column size alternatives are investigated to demonstrate the applicability of the proposed models. Keywords: Antibody purification, Multiscale optimization, Antigen-binding fragment, Mixed-integer programming, Data-driven model, Piecewise linear regression

Transmembrane protease serine 4 (TMPRSS4) is upregulated in various kinds of human cancers, including pancreatic cancer. However, its biological function in pancreatic ductal adenocarcinoma (PDAC) remains unclear. In the current study, real-time qPCR, immunohistochemical staining, Western blotting, and database (Cancer Genome Atlas and Gene Expression) analysis revealed remarkable overexpression of TMPRSS4 in PDAC tissue as compared to non-tumor tissue. The TMPRSS4 overexpression was associated with poor prognosis of PDAC patients. Moreover, multivariate analysis revealed that TMPRSS4 serves as an independent risk factor in PDAC. We performed gain-and loss-of-function analysis and found that TMPRSS4 promotes cellular proliferation and inhibits apoptosis of PDAC cells both in vitro and in vivo. Furthermore, we showed that TMPRSS4 might promote cell proliferation and inhibit apoptosis through activating ERK1/2 signaling pathway in pancreatic cancer cells. These findings were validated by using ERK1/2 phosphorylation inhibitor SCH772984 both in vitro and in vivo. Taken together, this study suggests that TMPRSS4 is a proto-oncogene, which promotes initiation and progression of PDAC by controlling cell proliferation and apoptosis. Our findings indicate that TMPRSS4 could be a promising prognostic biomarker and a therapeutic target for the treatment of pancreatic cancer.

Background/Aims: Cancer stem cells (CSCs) are largely responsible for tumor relapse and metastatic behavior. Doublecortin-like kinase 1 (DCLK1) was recently reported to be a biomarker for gastrointestinal CSCs and involved in the epithelial-mesenchymal transition (EMT) and tumor progression. B cell-specific Moloney murine leukemia virus insertion site 1 (Bmi-1) is a crucial regulator of CSC self-renewal, malignant transformation and EMT, and a previous study from our group showed that Bmi-1 is upregulated in pancreatic cancer progression and participates in EMT. However, it remains unclear whether DCLK1 is involved in pancreatic cancer or whether DCLK1 is associated with the altered level of Bmi-1 expression. Methods: The correlation of DCLK1 expression and clinical features of pancreatic cancer was analyzed in 210 paraffin-embedded archived pancreatic cancer specimens by immunohistochemical analysis. The biological effects of DCLK1 siRNA on cells were investigated by examining cell proliferation using a cell counting kit and cell colony assays, cell migration by wound healing assay and cell invasion by Transwell invasion assay. We further investigated the effect of therapeutic siRNA targeting DCLK1 on pancreatic cancer cell growth in vivo. Moreover, the molecular mechanism by which DCLK1 upregulates Bmi-1 expression was explored using real-time PCR, western blotting and Co-immunoprecipitation assay. Results: DCLK1 is overexpressed in pancreatic cancer and is related to metastasis and prognosis. Knockdown of DCLK1 markedly suppressed cell growth in vitro and in vivo and also inhibited the migration and invasion of pancreatic cancer cells. Furthermore, we found that DCLK1 silencing could inhibit EMT in cancer cells via downregulation of Bmi-1 and the mesenchymal markers Snail and Vimentin and upregulation of the epithelial marker E-cadherin. Moreover, high DCLK1 expression in human pancreatic cancer samples was associated with a mesenchymal phenotype and increased cell proliferation. Further co-immunoprecipitation indicated that DCLK1 did not interact with Bmi-1 directly. Conclusion: Our data suggest that upregulation of DCLK1 may contribute to pancreatic cancer metastasis and poor prognosis by increasing Bmi-1 expression indirectly. The findings indicate that inhibiting DCLK1 expression might be a novel strategy for pancreatic cancer therapy.

The photophysical and photochemical properties of the novel hydrazine sensor TAPHP and the TAPDP generated by the cyclization reaction of TAPHP with hydrazine are investigated using the density functional theory and time-dependent density functional theory. The results show that both the excited-state intramolecular proton transfer and intramolecular charge transfer can occur for TAPHP and TAPDP. Analysis of bond parameters and infrared vibrational spectra indicate that hydrogen bonds are enhanced in the first excited state, which is beneficial to excited-state intramolecular proton transfer. The strength of hydrogen bonds is also visualized by using the independent gradient model and topological analysis. The core-valence bifurcation index and bond critical point parameters are further employed to measure hydrogen bonds. The reaction path of proton transfer is obtained through the potential energy curves. The excitation of TAPHP and TAPDP is attributed to the charge transfer excitation, which is determined by the characteristics of the hole-electron distribution. The reaction site and product configuration are verified by atomic charge and 1H-NMR spectra. The negative free energy difference indicates that the reaction between TAPHP and hydrazine can proceed spontaneously. In addition, the absorption and fluorescence spectra agree well with the experimental results, confirming that TAPHP is an excellent sensor of hydrazine.

Community structure detection has proven to be important in revealing the underlying properties of complex networks. The standard problem, where a partition of disjoint communities is sought, has been continually adapted to offer more realistic models of interactions in these systems. Here, a two-step procedure is outlined for exploring the concept of overlapping communities. First, a hard partition is detected by employing existing methodologies. We then propose a novel mixed integer non linear programming (MINLP) model, known as OverMod, which transforms disjoint communities to overlapping. The procedure is evaluated through its application to protein-protein interaction (PPI) networks of the rat, E. coli, yeast and human organisms. Connector nodes of hard partitions exhibit topological and functional properties indicative of their suitability as candidates for multiple module membership. OverMod identifies two types of connector nodes, inter and intra-connector, each with their own particular characteristics pertaining to their topological and functional role in the organisation of the network. Inter-connector proteins are shown to be highly conserved proteins participating in pathways that control essential cellular processes, such as proliferation, differentiation and apoptosis and their differences with intra-connectors is highlighted. Many of these proteins are shown to possess multiple roles of distinct nature through their participation in different network modules, setting them apart from proteins that are simply 'hubs', i.e. proteins with many interaction partners but with a more specific biochemical role.