A comparison of statistical approaches used for the optimization of soluble protein expression in Escherichia coli

During a discovery project of potential inhibitors for three proteins, TNF-α, RANKL and HO-1, implicated in the pathogenesis of rheumatoid arthritis, significant amounts of purified proteins were required. The application of statistically designed experiments for screening and optimization of induction conditions allows rapid identification of the important factors and interactions between them. We have previously used response surface methodology (RSM) for the optimization of soluble expression of TNF-α and RANKL. In this work, we initially applied RSM for the optimization of recombinant HO-1 and a 91% increase of protein production was achieved. Subsequently, we slightly modified a published incomplete factorial approach (called IF1) in order to evaluate the effect of three expression variables (bacterial strains, induction temperatures and culture media) on soluble expression levels of the three tested proteins. However, soluble expression yields of TNF-α and RANKL obtained by the IF1 method were significantly lower (<50%) than those obtained by RSM. We further modified the IF1 approach by replacing the culture media with induction times and the resulted method called IF-STT (Incomplete Factorial-Stain/Temperature/Time) was validated using the three proteins. Interestingly, soluble expression levels of the three proteins obtained by IF-STT were only 1.2-fold lower than those obtained by RSM. Although RSM is probably the best approach for optimization of biological processes, the IF-STT is faster, it examines the most important factors (bacterial strain, temperature and time) influencing protein soluble expression in a single experiment, and can be used in any recombinant protein expression project as a starting point. © 2015 Elsevier Inc. All rights reserved

Statistical approaches to maximize recombinant protein expression in Escherichia coli: A general review

The supply of many valuable proteins that have potential clinical or industrial use is often limited by their low natural availability. With the modern advances in genomics, proteomics and bioinformatics, the number of proteins being produced using recombinant techniques is exponentially increasing and seems to guarantee an unlimited supply of recombinant proteins. The demand of recombinant proteins has increased as more applications in several fields become a commercial reality. Escherichia coli (E. coli) is the most widely used expression system for the production of recombinant proteins for structural and functional studies. However, producing soluble proteins in E. coli is still a major bottleneck for structural biology projects. One of the most challenging steps in any structural biology project is predicting which protein or protein fragment will express solubly and purify for crystallographic studies. The production of soluble and active proteins is influenced by several factors including expression host, fusion tag, induction temperature and time. Statistical designed experiments are gaining success in the production of recombinant protein because they provide information on variable interactions that escape the "one-factor-at-a-time" method. Here, we review the most important factors affecting the production of recombinant proteins in a soluble form. Moreover, we provide information about how the statistical design experiments can increase protein yield and purity as well as find conditions for crystal growth. (C) 2013 Elsevier Inc. All rights reserved

Optimization of TNF-alpha, overexpression in Escherichia coli using response surface methodology: Purification of the protein and oligomerization studies

Tumor necrosis factor-alpha (TNF-alpha) is responsible for many autoimmune disorders including rheumatoid arthritis, psoriasis, Chron's disease, stroke, and atherosclerosis. Thus, inhibition of TNF-alpha is a major challenge in drug discovery. However, a sufficient amount of purified protein is needed for the in vitro screening of potential TNF-alpha inhibitors. In this work, induction conditions for the production of human TNF-alpha fusion protein in a soluble form by recombinant Escherichia coli BL21(DE3) pLysS were optimized using response surface methodology based on the central composite design. The induction conditions included cell density prior induction (OD600nm), post-induction temperature, IPTG concentration and post-induction time. Statistical analysis of the results revealed that all variables and their interactions had significant impact on production of soluble TNF-alpha. An 11% increase of TNF-alpha production was achieved after determination of the optimum induction conditions: OD600nm prior induction 0.55, a post induction temperature of 25 degrees C, an IPTG concentration of 1 mM and a post-induction time of 4 h. We have also studied TNF-alpha oligomerization, the major property of this protein, and a K-d value of 0.26 nM for protein dimerization was determined. The concentration of where protein trimerization occurred was also detected. However, we failed to determine a reliable Kd value for protein trimerization probably due to the complexibility of our model. (C) 2012 Elsevier Inc. All rights reserved

A statistical approach for optimization of RANKL overexpression in Escherichia coli: Purification and characterization of the protein

Receptor activator of nuclear factor-kappa B (RANK) and its cognate ligand (RANICL) is a member of the TNF superfamily of cytokines which is essential in osteobiology and its overexpression has been implicated in the pathogenesis of bone degenerative diseases such as osteoporosis. Therefore, RANKL is considered a major therapeutic target for the suppression of bone resorption in bone metabolic diseases such as rheumatoid arthritis and cancer metastasis. To evaluate the inhibitory effect of potential RANKL inhibitors a sufficient amount of protein is required. In this work RANKL was cloned for expression at high levels in Escherichia coli with the interaction of changing cultures conditions in order to produce the protein in a soluble form. In an initial step, the effect of expression host on soluble protein production was investigated and BL21(DE3) pLysS was the most efficient one found for the production of RANKL. Central composite design experiment in the following revealed that cell density before induction, IPTG concentration, post-induction temperature and time as well as their interactions had a significant influence on soluble RANKL production. An 80% increase of protein production was achieved after the determination of the optimum induction conditions: OD600nm before induction 0.55, an IPTG concentration of 0.3 mM, a post-induction temperature of 25 degrees C and a post-induction time of 6.5 h. Following RANKL purification the thermal stability of, the protein was studied. The interaction of RANKL with SPD304, a patented small-molecule inhibitor of TNF-alpha, was also studied in a fluorescence binding assay resulting in a K-d value of 14.1 +/- 0.5 mu M. (C) 2013 Published by Elsevier Inc

The effects of benzoic acid and essential oil compounds in combination with protease on the performance of chickens

Experiments were conducted to study the effect of benzoic acid and of essential oil blends in combination with protease on the growth performance of broiler chickens. In the first trial, the birds were divided into three dietary treatments. The control group was fed a basal diet, while the other two groups were given benzoic acid at 300 and 1000 mg . kg(-1), respectively. Growth performance was not affected by benzoic acid inclusion. The pH values of the caecal content decreased following benzoic acid supplementation, while no differences were noticed in the pH of the crop, gizzard, ileum and rectum contents. Following benzoic acid supplementation, lactic acid bacteria populations increased in the caecum, and coliform bacteria, decreased. In the second trial, the birds were divided into three dietary treatments. The controls were fed a basal diet, while the other two groups were given thymol and a mixture of essential oil compounds (30 mg . kg(-1)). The dietary inclusion of the mixture of essential oil compounds enhanced growth performance compared with the other groups (P < 0.05), increased lactic acid bacteria populations, and decreased the coliform bacteria population in the caecum. In the third trial, the control group was fed the basal diet, while the other group was given a diet with similar ingredients and containing more benzoic acid and a mixture of essential oils, protease, and less protein and amino acids. In vitro tests showed that addition of benzoic acid, the mixture of essential oils and protease reduced buffering capacity compared with control feed and simulation experiments revealed that the protease increased protein extraction, hydrolysis and digestion. The combination of benzoic acid, essential oils and protease effectively improved weight gain and the feed conversion ratio compared with the control, as well as villus height, lactic acid bacteria counts, and reduced coliform bacteria counts compared with the control group. Finally, it was demonstrated for the first time that the novel, acid-stable protease increases protein solubilization, hydrolysis and digestion in an in vitro simulation model

A bovine miRNA, bta-miR-154c, withstands in vitro human digestion but does not affect cell viability of colorectal human cell lines after transfection

Colorectal cancer (CRC) is the third most frequent human cancer with over 1.3 million new cases globally. CRC is a complex disease caused by interactions between genetic and environmental factors; in particular, high consumption of red meat, including beef, is considered a risk factor for CRC initiation and progression. Recent data demonstrate that exogenous microRNAs (miRNAs) entering the body via ingestion could pose an effect on the consumer. In this study, we focused on bovine miRNAs that do not share a seed sequence with humans and mice. We identified bta-miR-154c, a bovine miRNA found in edible parts of beef and predicted via cross-species bioinformatic analysis to affect cancer-related pathways in human cells. When bovine tissue was subjected to cooking and a simulation of human digestion, bta-miR-154c was still detected after all procedures, albeit at reduced concentrations. However, lipofection of bta-miR-154c in three different colorectal human cell lines did not affect their viability as evaluated at various time points and concentrations. These data indicate that bta-miR-154c (a) may affect cancer-related pathways in human cells, (b) can withstand digestion and be detected after all stages of an in vitro digestion protocol, but (c) it does not appear to alter epithelial cell viability after entering human enterocytes, even at supraphysiological amounts. Further experiments will elucidate whether bta-miR-154c exerts a different functional effect on the human gut epithelium, which may cause it to contribute to CRC progression through its consumption

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL)

We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure–based with ligand–based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases. © 2017 Melagraki et al

Current status and future prospects of small–molecule protein–protein interaction (PPI) inhibitors of tumor necrosis factor (TNF) and receptor activator of NF-κB ligand (RANKL)

The overexpression of Tumor Necrosis Factor (TNF) is directly related to the development of several autoimmune diseases, such as rheumatoid and psoriatic arthritis, inflammatory bowel disease, Crohn’s disease, refractory asthma, and multiple sclerosis. Receptor Activator of Nuclear Factor Kappa- B Ligand (RANKL) belongs to the TNF family and is the primary mediator of osteoclast-induced bone resorption through interaction with its receptor RANK. The function of RANKL is physiologically inhibited by the action of osteoprotegerin (OPG), which is a decoy receptor that binds to RANKL and prevents the process of osteoclastogenesis. Malfunction among RANK/RANKL/OPG can also result in bone loss diseases, including postmenopausal osteoporosis, rheumatoid arthritis, bone metastasis and multiple myeloma. To disrupt the unwanted functions of TNF and RANKL, current attempts focus on blocking TNF and RANKL binding to their receptors. In this review, we present the research efforts toward the development of low-molecular-weight pharmaceuticals that directly block the detrimental actions of TNF and RANKL. © 2018 Bentham Science Publishers

Discovery of Small-Molecule Inhibitors of Receptor Activator of Nuclear Factor-κB Ligand with a Superior Therapeutic Index

Receptor activator of nuclear factor-κB ligand (RANKL) constitutes the master mediator of osteoclastogenesis, while its pharmaceutical inhibition by a monoclonal antibody has been approved for the treatment of postmenopausal osteoporosis. To date, the pursuit of pharmacologically more favorable approaches using low-molecular-weight inhibitors has been hampered by low specificity and high toxicity issues. This study aimed to discover small-molecule inhibitors targeting RANKL trimer formation. Through a systematic screening of 39 analogues of SPD-304, a dual inhibitor of tumor necrosis factor (TNF) and RANKL trimerization, we identified four compounds (1b, 3b, 4a, and 4c) that selectively inhibited RANKL-induced osteoclastogenesis in a dose-dependent manner, without affecting TNF activity or osteoblast differentiation. Based on structure-activity observations extracted from the most potent and less toxic inhibitors of RANKL-induced osteoclastogenesis, we synthesized a focused set of compounds that revealed three potent inhibitors (19a, 19b, and 20a) with remarkably low cell-toxicity and improved therapeutic indexes as shown by the LC50 to IC50 ratio. These RANKL-selective inhibitors are an excellent starting point for the development of small-molecule therapeutics against osteolytic diseases.

Aqueous Solubility Enhancement for Bioassays of Insoluble Inhibitors and QSPR Analysis: A TNF-α Study

The aim of this study is to improve the aqueous solubility of a group of compounds without interfering with their bioassay as well as to create a relevant prediction model. A series of 55 potential small-molecule inhibitors of tumor necrosis factor–alpha (TNF-α; SPD304 and 54 analogues), many of which cannot be bioassayed because of their poor solubility, was used for this purpose. The solubility of many of the compounds was sufficiently improved to allow measurement of their respective dissociation constants (K d ). Parameters such as dissolution time, initial state of the solute (solid/liquid), co-solvent addition (DMSO and PEG3350), and sample filtration were evaluated. Except for filtration, the remaining parameters affected aqueous solubility, and a solubilization protocol was established according to these. The aqueous solubility of the 55 compounds in 5% DMSO was measured with this protocol, and a predictive quantitative structure property relationship model was developed and fully validated based on these data. This classification model separates the insoluble from the soluble compounds and predicts the solubility of potential small-molecule inhibitors of TNF-α in aqueous solution (containing 5% DMSO as co-solvent) with an accuracy of 81.2%. The domain of applicability of the model indicates the type of compounds for which estimation of aqueous solubility can be confidently predicted. © 2017, © 2017 Society for Laboratory Automation and Screening