Optimizing recombinant antibody fragment production: A comparison of artificial intelligence and statistical modeling.

Maximizing the recombinant protein yield necessitates optimizing the production medium. This can be done using a variety of methods, including the conventional "one-factor-at-a-time" approach and more recent statistical and mathematical methods such as artificial neural network (ANN), genetic algorithm, etc. Every approach has advantages and disadvantages of its own, yet even when a technique has flaws, it is nevertheless used to get the best results. Here, one categorical variable and four numerical parameters, including post-induction time, inducer concentration, post-induction temperature, and pre-induction cell density, were optimized using the 232 experimental assays of the central composite design. The direct and indirect effects of factors on the yield of anti-epithelial cell adhesion molecule extracellular domain fragment antibody were examined using statistical methods. The analysis of variance results indicate that the response surface methodology (RSM) model is effective in predicting the amount of produced single-chain fragment variable (p-value = 0.0001 and R2 = 0.905). For ANN modeling, the evaluation using normalized root mean square error (NRMSE) and R2 values shows a good fit (R2 = 0.942) and accurate predictions (NRMSE = 0.145). The analysis of error parameters and R2 of a dataset, which contained 30 data points randomly selected from the complete dataset, showed that the ANN model had a higher R2 value (0.968) compared to the RSM model (0.932). Furthermore, the ANN model demonstrated stronger predictive ability with a lower NRMSE (0.048 vs. 0.064). Induction at the cell density of 0.7 and an isopropyl ß-D-1-thiogalactopyranoside concentration of 0.6 mM for 32 h at 30°C in BW25113 was the ideal culture condition leading to the protein yield of 259.51 mg/L. Under the optimum conditions, the output values predicted by the ANN model (259.83 mg/L) were more in line with the experimental data (259.51 mg/L) than the RSM (276.13 mg/L) expected value. This outcome demonstrated that the ANN model outperforms the RSM in terms of prediction accuracy.

Optimizing recombinant production of L-asparaginase 1 from Saccharomyces cerevisiae using response surface methodology.

L-asparaginase is an essential enzyme used in cancer treatment, but its production faces challenges like low yield, high cost, and immunogenicity. Recombinant production is a promising method to overcome these limitations. In this study, response surface methodology (RSM) was used to optimize the production of L-asparaginase 1 from Saccharomyces cerevisiae in Escherichia coli K-12 BW25113. The Box-Behnken design (BBD) was utilized for the RSM modeling, and a total of 29 experiments were conducted. These experiments aimed to examine the impact of different factors, including the concentration of isopropyl-b-LD-thiogalactopyranoside (IPTG), the cell density prior to induction, the duration of induction, and the temperature, on the expression level of L-asparaginase 1. The results revealed that while the post-induction temperature, cell density at induction time, and post-induction time all had a significant influence on the response, the post-induction time exhibited the greatest effect. The optimized conditions (induction at cell density 0.8 with 0.7 mM IPTG for 4 h at 30 °C) resulted in a significant amount of L-asparaginase with a titer of 93.52 µg/mL, which was consistent with the model-based prediction. The study concluded that RSM optimization effectively increased the production of L-asparaginase 1 in E. coli, which could have the potential for large-scale fermentation. Further research can explore using other host cells, optimizing the fermentation process, and examining the effect of other variables to increase production.

Novel Metal-Organic Framework Nanoparticle for Letrozole Delivery: A New Advancement in Breast Cancer Treatment.

Water-stable metal-organic frameworks based on UIO-66@NH2 were synthesized to transport Letrozole into breast cancer cells. The UIO-66@NH2 nanoparticles had a spherical shape and triangular base pyramid morphology, with a size range of 100-200 nm. Fourier transform infrared spectroscopy confirmed the efficient adsorption of Letrozole on UIO-66@NH2. The drug release profile showed a gradual, pH-dependent release of Letrozole from the nanoparticles, with a significant increase in acidic environments, indicating the adaptable release potential of UIO-66@NH2@Let in the breast cancer microenvironment. The size and entrapment efficiency were more stable at 4 °C than at 25 °C. To evaluate the cytotoxic effects of UIO-66@NH2@Let, MTT assay, gene expression analysis, flow cytometry, reactive oxygen species generation, migration assay, and DAPI staining were performed. Moreover, according to IC50 results, the incorporation of Letrozole into UIO-66@NH2 significantly improved its anticancer activity. The results also showed that the developed formulations induced apoptosis through both intrinsic and extrinsic pathways and inhibited cancer progression. The efficacy of the formulations in inducing apoptosis was validated by DAPI staining microscopy and flow cytometry analysis. Therefore, the Letrozole-loaded UIO-66@NH2 MOFs developed in this study can be considered as a unique and sophisticated anticancer delivery nanosystem with promising in vitro anticancer properties.

Evaluation of Antioxidant and Antibacterial Effects of Lyophilized Cell-Free Probiotic Supernatants of Three Lactobacillus spp. and Their Cytocompatibility Against Periodontal Ligament Stem Cells.

Background: Periodontitis is a chronic disease characterized by the inflammation of the periodontium and leads to progressive damage, such as gingival atrophy, alveolar bone loss, and tooth loss. Streptococcus mutans and Aggregatibacter actinomycetemcomitans are bacteria that support the occurrence of periodontitis via the ability to form biofilms or damage the alveolar bone and periodontal ligaments. On the other hand, periodontal ligament stem cells (PDLSCs) are cells with differentiation capability into osteoblasts or osteoblasts. Due to their role in periodontal homeostasis and regeneration, PDLSCs are considered to control periodontitis progression. However, probiotics are helpful microorganisms known to have antimicrobial and immune-regulating effects. Objectives: This study aimed to evaluate the antioxidant activity and antimicrobial effects of lyophilized cell-free supernatants (LCFSs) derived from three probiotic strains of Lactobacillus on S. mutans and A. actinomycetemcomitans. Moreover, the effect of these lyophilized supernatants was investigated on the viability and migration capability of PDLSCs. Methods: The antibacterial effects of LCFSs of three probiotic bacteria were investigated by determining the minimum inhibitory concentration and minimum bactericidal concentration. Then, the effect of LCFSs on the survival and migration of PDLSCs was investigated by the MTT method (at 24 and 72 hours) and scratch test (at 0, 24, and 48 hours), respectively. Finally, the antioxidant effect of LCFSs was assessed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay and ferric reducing/antioxidant power methods. Results: The antibacterial properties of different concentrations of acidic and neutral LCFSs derived from three studied probiotic bacteria on S. mutans and A. actinomycetemcomitans were observed within the range of 12.5 - 50% (v/v) (1/8 - 1/2 dilutions with culture medium). Although there were no significant toxic (~ 100% viability) and wound healing effects on PDLSCs when the cells were exposed to either acidic or neutral studied LCFSs in a concentration of 5% (v/v), they showed significant antioxidant activity (~ 90% DPPH inhibition and 0.5 mM Fe2+/L). Conclusions: The results revealed that 5% (v/v) 48-hour acidic and neutral supernatants of three studied probiotics might play a beneficial role in controlling periodontitis.

Genome-scale metabolic model-based engineering of Escherichia coli enhances recombinant single-chain antibody fragment production.

PURPOSE: Escherichia coli is an attractive and cost-effective cell factory for producing recombinant proteins such as single-chain variable fragments (scFvs). AntiEpEX-scFv is a small antibody fragment that has received considerable attention for its ability to target the epithelial cell adhesion molecule (EpCAM), a cancer-associated biomarker of solid tumors. Due to its metabolic burden, scFv recombinant expression causes a remarkable decrease in the maximum specific growth rate of the scFv-producing strain. In the present study, a genome-scale metabolic model (GEM)-guided engineering strategy is proposed to identify gene targets for improved antiEpEX-scFv production in E. coli. METHODS: In this study, a genome-scale metabolic model of E. coli (iJO1366) and a metabolic modeling tool (FVSEOF) were employed to find appropriate genes to be amplified in order to improve the strain for incresed production of antiEpEX-scFv. To validate the model predictions, one target gene was overexpressed in the parent strain Escherichia coli BW25113 (DE3). RESULTS: For improving scFv production, we applied the FVSEOF method to identify a number of potential genetic engineering targets. These targets were found to be localized in the glucose uptake system and pentose phosphate pathway. From the predicted targets, the glk gene encoding glucokinase was chosen to be overexpressed in the parent strain Escherichia coli BW25113 (DE3). By overexpressing glk, the growth capacity of the recombinant E. coli strain was recovered. Moreover, the engineered strain with glk overexpression successfully led to increased scFv production. CONCLUSION: The genome-scale metabolic modeling can be considered for the improvement of the production of other recombinant proteins.

Machine learning modeling for solubility prediction of recombinant antibody fragment in four different E. coli strains.

The solubility of proteins is usually a necessity for their functioning. Recently an emergence of machine learning approaches as trained alternatives to statistical models has been evidenced for empirical modeling and optimization. Here, soluble production of anti-EpCAM extracellular domain (EpEx) single chain variable fragment (scFv) antibody was modeled and optimized as a function of four literature based numerical factors (post-induction temperature, post-induction time, cell density of induction time, and inducer concentration) and one categorical variable using artificial neural network (ANN) and response surface methodology (RSM). Models were established by the CCD experimental data derived from 232 separate experiments. The concentration of soluble scFv reached 112.4 mg/L at the optimum condition and strain (induction at cell density 0.6 with 0.4 mM IPTG for 24 h at 23 °C in Origami). The predicted value obtained by ANN for the response (106.1 mg/L) was closer to the experimental result than that obtained by RSM (97.9 mg/L), which again confirmed a higher accuracy of ANN model. To the author's knowledge this is the first report on comparison of ANN and RSM in statistical optimization of fermentation conditions of E.coli for the soluble production of recombinant scFv.

Evaluation of Inflammasome Activation in Peripheral Blood Mononuclear Cells of Hemodialysis Treated Patients with Glomerulonephritis.

Recently, it has been found that abnormal activation of inflammasomes, the intracellular multiprotein complexes, plays an important role in the pathogenesis and the development of inflammatory diseases. To determine whether the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome is involved in chronic inflammatory condition reported in glomerulonephritic- hemodialysis (HD) patients, we investigated the mRNA levels of NLRP3, CASP-1, ASC, IL-1ß, IL-18, NLRC4, and P2X7 in human peripheral blood mononuclear cells (PBMCs) collected from 28 glomerulonephritic-HD patients. To confirm the mRNA quantification results, we investigated the IL-1ß content and Caspase 1 activity in serum and PBMC lysates, respectively. Compared with PBMCs derived from healthy subjects, genes encoding proinflammatory cytokines such as IL-1ß and IL-18 as well as NLRP3, ASC, CASP-1 were markedly overexpressed in those derived from patients. Moreover, there was no significant difference between the expression level of P2X 7 mRNA in PBMCs isolated from glomerulonephritis-HD patients and controls. The serum level of active IL1-ß and cell lysate CASP-1 activity were up-regulated in patients compared to controls. We also revealed that PBMCs isolated from glomerulonephritis-HD patients had elevated mRNA levels of NLRC4 compared to controls, suggesting the priming of NLRC4 inflammasome. These results revealed that the NLRP3-ASC-caspase-1 axis might have a role in increased inflammation severity reported in glomerulonephritic patients undergoing hemodialysis. These findings provide new insights into molecular mechanisms underlying chronic inflammation in HD- glomerulonephritic patients. Additionally, the NLRP3 inflammasome pathway can be attractive as a potential therapeutic target for complication avoidance in HD- glomerulonephritic patients.

Uncovering the stability status of the reputed reference genes in breast and hepatic cancer cell lines.

Accurate and reliable relative gene expression analysis via the Reverse Transcription-quantitative Real Time PCR (RT-qPCR) method strongly depends on employing several stable reference genes as normalizers. Utilization of the reference genes without analyzing their expression stability under each experimental condition causes RT-qPCR analysis error as well as false output. Similar to cancerous tissues, cancer cell lines also exhibit various gene expression profiles. It is crucial to recognize stable reference genes for well-known cancer cell lines to minimize RT-qPCR analysis error. In this study, we showed the expression level and investigated the expression stability of eight common reference genes that are ACTB, YWHAZ, HPRT1, RNA18S, TBP, GAPDH, UBC, and B2M, in two sets of cancerous cell lines. One set contains MCF7, SKBR3, and MDA-MB231 as breast cancer cell lines. Another set includes three hepatic cancer cell lines, including Huh7, HepG2, and PLC-PRF5. Three excel-based softwares comprising geNorm, BestKeeper, and NormFinder, and an online tool, namely RefFinder were used for stability analysis. Although all four algorithms did not show the same stability ranking of nominee genes, the overall results showed B2M and ACTB as the least stable reference genes for the studied breast cancer cell lines. While TBP had the lowest expression stability in the three hepatic cancer cell lines. Moreover, YWHAZ, UBC, and GAPDH showed the highest stability in breast cancer cell lines. Besides that, a panel of five nominees, including ACTB, HPRT1, UBC, YWHAZ, and B2M showed higher stability than others in hepatic cancer cell lines. We believe that our results would help researchers to find and to select the best combination of the reference genes for their own experiments involving the studied breast and hepatic cancer cell lines. To further analyze the reference genes stability for each experimental condition, we suggest researchers to consider the provided stability ranking emphasizing the unstable reference genes.

RSM-based Model to Predict Optimum Fermentation Conditions for Soluble Expression of the Antibody Fragment Derived from 4D5MOC-B Humanized Mab in SHuffle™ T7 E. coli.

Overexpression of the EpCAM in epithelial-derived neoplasms makes this receptor a promising target in antibody-based therapy. Due to the lack of N-glycosylation, Escherichia coli (E. coli) seems to be the most appropriate choice for the expression of antibody fragments. However, developing a robust and cost-effective process that produces consistent therapeutic proteins from inclusion bodies is a major challenge. Undoubtedly, it can be circumvented by the soluble expression of these proteins. Utilization of numerous genetically modified hosts and optimization of cultivation conditions are two effective approaches widely used to overcome the insolubility problem. Due to the cytoplasmic expression of DsbC and the ability to the correct formation of disulfide bonds, the Shuffle™ T7 strain can be a suitable host for the soluble production of recombinant proteins. Here, Box-Behnken design (BBD)- Response surface methodology (RSM) modeling was employed to develop optimized culture conditions for 4D5MOC-B scFv fragment production in SHuffle™ T7 strain while solubility and production level were considered as responses. Although both responses were significantly influenced by post-induction temperature, cell density at induction time, and IPTG concentration, the temperature had the largest effect. The maximum experimental soluble protein obtained by adding 1 mM of IPTG into the M9 medium when the cell density reached 0.7 at 23 ᵒC was 693.56 µg/mL which was in good correlation with the predicted value of 720.742 µg/mL. Predictable total expression value was also experimentally verified. This strategy can be scaled-up for the production of large amounts of scFvs from SHuffle™ T7 E. coli to facilitate their potential applications as therapeutic and diagnostic agents.

Statistical optimization of culture conditions for expression of recombinant humanized anti-EpCAM single-chain antibody using response surface methodology.

BACKGROUND AND PURPOSE: The epithelial cell adhesion molecule (EpCAM), is one of the first cancer- associated markers discovered. Its overexpression in cancer stem cells, epithelial tumors, and circulating tumor cells makes this molecule interesting for targeted cancer therapy. So, in recent years scFv fragments have been developed for EpCAM targeting. EXPERIMENTAL APPROACH: In this study, an scFv against EpCAM extracellular domain (EpEX) derived from 4D5MOC-B humanized mAb was expressed in Escherichia coli k12 strain, and in order to obtain the optimum culture conditions in chemically defined minimal medium, response surface methodology (RSM) was employed. According to the RSM-CCD method, a total of 30 experiments were designed to investigate the effects of various parameters including isopropyl-b-D-thiogalactopyranoside (IPTG) concentration, cell density before induction, post-induction time, and post-induction temperature on anti EpEX-scFv expression level. FINDINGS/RESULTS: At the optimum conditions (induction at cell density 0.8 with 0.8 mM IPTG for 24 h at 37 °C), the recombinant anti EpEX-scFv was produced at a titer of 197.33 µg/mL that was significantly consistent with the prediction of the model. CONCLUSION AND IMPLICATION: The optimized-culture conditions obtained here for efficient production of anti EpEX-scFv in shake flask cultivation on a chemically defined minimal medium could be applied to large- scale fermentation for the anti EpEX-scFv production.

RAB5A effect on metastasis of hepatocellular carcinoma cell line via altering the pro-invasive content of exosomes.

Tumor microenvironment exerts a critical role in cancer progression and metastasis. Exosomes, cell-cell communicators and major players of the tumor microenvironment are considered as a serious mediator of cancer metastasis. Here, we determined the effect of RAB5A gene on the hepatocellular carcinoma (HCC) cells particularly whether RAB5A could affect HCC metastasis via regulating the pro-invasive content of exosomes. In response to RAB5A knockdown, we analyzed the proliferation rate and migration capability of HCC cells. Then, we estimated changes in the total protein composition of exosomes via analyzing the expression of exosomal markers, CD63 and Alix. Thereafter, alterations of the pro-invasive content of exosomes were functionally evaluated using matrigel invasion assay. Our results revealed that knockdown of RAB5A could decrease HCC cell proliferation rate and migration capability significantly. Moreover, no significant changes in the expression of exosomal CD63 and Alix reflected that no differences might be occurred in protein composition of RAB5A knockdown cell-derived exosomes. Matrigel invasion assay functionally showed that exosomes-derived from RAB5A knockdown cells still had pro-invasive properties and their pro-invasive content was not affected in response to RAB5A knockdown. In conclusion, we believe that our results propose a new explanation about RAB5A and metastatic potentials of exosomes-derived from HCC cells.

Solubility assessment of single-chain antibody fragment against epithelial cell adhesion molecule extracellular domain in four Escherichia coli strains.

BACKGROUND: Overexpression of the EpCAM (epithelial cell adhesion molecule) in malignancies makes it an attractive target for passive immunotherapy in a wide range of carcinomas. In comparison with full-length antibodies, due to the small size, the scFvs (single-chain variable fragments) are more suitable for recombinant expression in E. coli (Escherichia coli). However, the proteins expressed in large amounts in E. coli tend to form inclusion bodies that need to be refolded which may result in poor recovery of bioactive proteins. Various engineered strains were shown to be able to alleviate the insolubility problem. Here, we studied the impact of four E. coli strains on the soluble level of anti-EpEX-scFv (anti-EpCAM extracellular domain-scFv) protein. RESULTS: Although results showed that the amount of soluble anti-EpEX-scFv obtained in BL21TM (DE3) (114.22 ± 3.47 mg/L) was significantly higher to those produced in the same condition in E. coli RosettaTM (DE3) (71.39 ± 0.31 mg/L), and OrigamiTM T7 (58.99 ± 0.44 mg/L) strains, it was not significantly different from that produced by E. coli SHuffleTM T7 (108.87 ± 2.71 mg/L). Furthermore, the highest volumetric productivity of protein reached 318.29 ± 26.38 mg/L in BL21TM (DE3). CONCLUSIONS: Although BL21TM (DE3) can be a suitable strain for high-level production of anti-EpEX-scFv protein, due to higher solubility yield (about 55%), E. coli SHuffleTM T7 seems to be better candidate for soluble production of scfv compared to BL21TM (DE3) (solubility yield of about 30%).

Validation of common reference genes stability in exosomal mRNA-isolated from liver and breast cancer cell lines.

Accurate relative gene expression analysis by reverse transcription-quantitative polymerase chain reaction relies on the usage of suitable reference genes for data normalization. The RNA content of small extracellular vesicles including exosomes is growingly considered as cancer biomarkers. So, reliable relative quantification of exosomal messenger RNA (mRNA) is essential for cancer diagnosis and prognosis applications. However, suitable reference genes for accurate normalization of a target gene in exosomes derived from cancer cells are not depicted yet. Here, we analyzed the expression and stability of eight well-known reference genes namely GAPDH, B2M, HPRT1, ACTB, YWHAZ, UBC, RNA18S, and TBP in exosomes-isolated from the liver (Huh7, HepG2, PLC/PRF/5) and breast (SK-BR-3) cancer cell lines using five different algorithms including geNorm, BestKeeper, Delta Ct, NormFinder, and RefFinder. Our results showed that ACTB, TBP, and HPRT1 were not expressed in exosomes-isolated from studied liver and breast cancer cell lines. The geNorm and BestKeeper algorithms indicated GAPDH and UBC as the most stable candidates. Moreover, Delta Ct and NormFinder algorithms showed YWHAZ as the most stable reference genes. Comprehensive ranking calculated by the RefFinder algorithm also pointed out GAPDH, YWHAZ, and UBC as the first three stable reference genes. Taken together, this study validated the common reference genes stability in exosomal mRNA derived from liver and breast cancer cell lines for the first time. We believe that this study would be the first step in finding more stable reference genes in exosomes that triggers more accurate detection of exosomal biomarkers.

Functional roles of exosomal miRNAs in multi-drug resistance in cancer chemotherapeutics.

Recent understanding of different molecular aspects of tumor initiation and progression has led to the discovery of a growing list of drugs. While these drugs have shown promising effects on tumor cells, their widespread usage has been hampered by the acquisition of drug resistance in a subpopulation of tumor cells. A differential pattern in the secretion of specialized vesicles named "exosomes" in drug-resistant cancer cells have recently received much attention. In addition, microRNAs (miRNAs) have been shown to be enriched in exosomes. Exosomal miRNAs (also known as exo-miRs) could be shuttled to recipient cells and play a role in the regulation of post-transcriptional gene expression, which may exert certain effects on cancer drug resistance. Here, we have reviewed the role of exo-miRs in chemotherapeutic resistance in different cancer types. Besides, studies which have focused on predictive role of circulating exo-miRs in cancer drug resistance are reviewed.

RAB5A is associated with genes involved in exosome secretion: Integration of bioinformatics analysis and experimental validation.

Exosomes, as cell-cell communicators with an endosomal origin, are involved in the progression of various diseases. RAB5A, a member of the small Rab GTPases family, which is well known as a key regulator of cellular endocytosis, is expected to be involved in exosome secretion. Here, we found the impact of RAB5A on exosome secretion from human hepatocellular carcinoma cell line using a rapid yet reliable bioinformatics approach followed by experimental analysis. Initially, RAB5A and exosome secretion-related genes were gathered from bioinformatics tools, namely, CTD, COREMINE, and GeneMANIA; and published papers. Protein-protein interaction (PPI) was then constructed by the Search Tool for Retrieval of Interacting Genes (STRING) database. Among them, several genes with different combined scores were validated by the real-time quantitative polymerase chain reaction (RT-qPCR) in stable RAB5A knockdown cells. Thereafter, to validate the bioinformatics results functionally, the impact of RAB5A knockdown on exosome secretion was evaluated. Bioinformatics analysis showed that RAB5A interacts with 37 genes involved in exosome secretion regulatory pathways. Validation by RT-qPCR confirmed the association of RAB5A with candidate interacted genes and interestingly showed that even medium to low combined scores of the STRING database could be experimentally valid. Moreover, the functional analysis demonstrated that the stable silencing of RAB5A could experimentally decrease exosome secretion. In conclusion, we suggest RAB5A as a regulator of exosome secretion based on our bioinformatics approach and experimental analysis. Also, we propose the usage of PPI-derived from the STRING database regardless of their combined scores in advanced bioinformatics analysis.

CRISPR-Cas9/CRISPRi tools for cell factory construction in E. coli.

The innovative CRISPR-Cas based genome editing technology provides some functionality and advantages such as the high efficiency and specificity as well as ease of handling. Both aspects of the CRISPR-Cas9 system including genetic engineering and gene regulation are advantageously applicable to the construction of microbial cell factories. As one of the most extensively used cell factories, E. coli has been engineered to produce various high value-added chemical compounds such as pharmaceuticals, biochemicals, and biofuels. Therefore, to improve the production of valuable metabolites, many investigations have been performed by focusing on CRISPR-Cas- based metabolic engineering of this host. In the current review, the biology underlying CRISPR-Cas9 system was briefly explained and then the applications of CRISPR-Cas9/CRISPRi tools were considered for cell factory construction in E. coli.

Challenges of in vitro genome editing with CRISPR/Cas9 and possible solutions: A review.

Microbial production of bio-based ingredients often requires metabolically engineered bacterial strains with the edited genome. Genome editing tools are also essential for gene identification and investigating genotype-phenotype connections. Currently, one of the most common tools of genome editing is based on a natural bacterial adaptive immune system known as CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas9 (CRISPR-associated protein 9) due to its simple, rapid, and efficient activities. Although successful in some in vitro systems, its application as an approach of metabolic engineering and genome editing is still not so extensive. Here, we discuss existing barriers and challenges of the CRISPR/Cas9 editing tool for in vitro systems. Firstly, we aim to briefly introduce the CRISPR/Cas9 method as an in vitro gene editing tool. Next, we discuss existing obstacles to CRISPR-based editing in bacterial and in vitro model systems and offer guidelines to help achieve editing in an expanded range of in vitro systems.

B1 protein: a novel cell penetrating protein for in vitro and in vivo delivery of HIV-1 multi-epitope DNA constructs.

OBJECTIVES: Enhancement of the potential ability of biomacromolecules to cross cell membranes is a critical step for development of effective therapeutic vaccine especially DNA vaccine against human immunodeficiency virus-1 (HIV-1) infection. The supercharged proteins were known as powerful weapons for delivery of different types of cargoes such as DNA and protein. Hence, we applied B1 protein with + 43 net charges obtained from a single frameshift in the gene encoding enhanced green fluorescent protein (eGFP) for delivery of two multi-epitope DNA constructs (nef-vpu-gp160-p24 and nef-vif-gp160-p24) in vitro and in vivo for the first time. For this purpose, B1 protein was generated in bacterial expression system under native conditions, and used to interact with both DNA constructs. RESULTS: Our data indicated that B1 protein (~ 27 kDa) was able to form a stable nanoparticle (~ 80-110 nm) with both DNA constructs at nitrogen: phosphate (N: P) ratio of 1:1. Moreover, the transfection efficiency of B1 protein for DNA delivery into HEK-293T cell line indicated that the cellular uptake of nef-vif-gp160-p24 DNA/ B1 and nef-vpu-gp160-p24 DNA/ B1 nanoparticles was about 32-35% with lower intensity as compared to TurboFect commercial reagent. On the other hand, immunization of BALB/c mice with different modalities demonstrated that B1 protein could enhance the levels of antibody, IFN-gamma and Granzyme B eliciting potent and strong Th1-directed cellular immunity. CONCLUSION: Generally, our findings showed the potency of B1 protein as a promising gene delivery system to improve an effective therapeutic vaccine against HIV-1 infection.

MicroRNA: Promising Roles in Cancer Therapy.

MicroRNAs (miRNA) are small non-coding RNAs that act as one of the main regulators of gene expression. They are involved in maintaining a proper balance of diverse processes, including differentiation, proliferation, and cell death in normal cells. Cancer biology can also be affected by these molecules by modulating the expression of oncogenes or tumor suppressor genes. Thus, miRNA based anticancer therapy is currently being developed either alone or in combination with chemotherapy agents used in cancer management, aiming at promoting tumor regression and increasing cure rate. Access to large quantities of RNA agents can facilitate RNA research and development. In addition to currently used in vitro methods, fermentation-based approaches have recently been developed, which can cost-effectively produce biological RNA agents with proper folding needed for the development of RNA-based therapeutics. Nevertheless, a major challenge in translating preclinical studies to clinical for miRNA-based cancer therapy is the efficient delivery of these agents to target cells. Targeting miRNAs/anti-miRNAs using antibodies and/or peptides can minimize cellular and systemic toxicity. Here, we provide a brief review of miRNA in the following aspects: biogenesis and mechanism of action of miRNAs, the role of miRNAs in cancer as tumor suppressors or oncogenes, the potential of using miRNAs as novel and promising therapeutics, miRNA-mediated chemo-sensitization, and currently utilized methods for the in vitro and in vivo production of RNA agents. Finally, an update on the viral and non-viral delivery systems is addressed.