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This is the final report corresponding to the consultancy study performed by the research team of Prof. Francesc Gòdia at the Department of Chemical Engineering of UAB for the company Novo Nordisk Pharmatech A/S.
By: Francesc Gòdia Casablancas, Universitat Autònoma de Barcelona
Executive summary: This is the final report corresponding to the consultancy study performed by the research team of Prof. Francesc Gòdia at the Department of Chemical Engineering of UAB for the company Novo Nordisk Pharmatech A/S.
The main objective of the study was to investigate the effect of insulin as supplement to improve cell culture media for the growth of a CHO cell line. The approach of the study was similar to a previous work of UAB on the optimization of commercial serum free, chemically defined and animal derived component free media by supplementation with recombinant compounds, insulin among them, performed on HEK 293 cells. Nowadays, CHO are one of the most widely used platforms for the production of biopharmaceuticals. The cell line CHO-S was selected to perform the study.
The use of serum-free medium has grown significantly in industrial applications where the use of bovine serum represents a safety hazard as well as a source of unwanted contamination for the production of biopharmaceuticals. Serum-free medium is prepared without the use of animal serum, but may contain serum constituents or substitutes thereof. In this work, three commercial serum-free and chemically defined media were initially trade-off, and one of them (FreeStyleCHO) was selected to perform a further optimization based on testing the effect of eight non animal-derived compounds as supplements (r-insulin, r-transferrin, r-albumin, selenium, tocopherol acetate, synthetic cholesterol, tween 80 and fatty acids) in order to increase maximum cell density. Design of experiments methodologies was used to minimize the number of experiments, elucidate cross effects between compounds, as well as to evaluate the statistical significance of the obtained results. Plackett-Burman initial screening experiments indicated that only three of the supplements (r-insulin, r-transferrin and selenium) had positive effects on cell growth. The concentration of these components was further optimized by means of a Box-Behnken design. By using this strategy, a maximum cell density of 10 x 106 cells/mL was attained, a high cell concentration for batch culture operation, with FreeStyleCHO medium supplemented with selenium (1 µg/L), r-transferrin (20.2 mg/L) and r-insulin (26.1 mg/L).
Chinese hamster ovary (CHO) cell line is a widely extended platform to produce recombinant proteins based on mammalian cell culture. The first product receiving approval was human tissue plasminogen activator (Genentech, S. San Francisco, CA, USA) in 1986. More than 20 years after t-PA approval, CHO cells platform remain as the preferred mammalian cell line for the production of recombinant therapeutic proteins. CHO cells are capable of adapting and growing in suspension culture which is ideal for large scale culture in industry . This cell line poses less risk as few human viruses are able to propagate in them . Another important feature is that CHO cells can grow in serum-free and chemically defined media which ensures reproducibility between different batches and GMP compliance. It is also worth mentioning that CHO cells allow post translational modifications of recombinant proteins which are compatible and bioactive in humans due to the fact that glycosylation of glycoproteins produced by CHO cells are human-like . It is well known that CHO cells change their chromosome composition at random and frequently, more than the majority of mammalian cell lines do. This contributes to their easy adaptation to different culture conditions and the possibility to find high producers clones through screening. Currently, recombinant protein titter from CHO cell culture have reached the gram per litre range which is a 100-fold improvement since the 1980s typical yields . The significant improvement of titter can be attributed to progress in establishment of stable and high producing clones as well as optimization of culture process .
The culture media used for animal cell culture are very complex. Historically serum has been a crucial component of their composition, as a provider of complex biological molecules such as hormones, growth factors as well as numerous low molecular weight nutrients . The emergence of industrial scale mammalian cell culture for the production of protein pharmaceuticals presented a new challenge for cell culture medium design, where the question of quality control arose from the use of foetal bovine serum (FBS). The issues of reliability of supply, variability in performance and the risk for biological contaminants (mycoplasmas and viruses), created serious safety concerns in the regulatory agencies. In more recent years, the emergence of prion related diseases, specifically bovine spongiform encephalomyelitis, led to an increased demand for defined non-animal sourced medium components to replace both serum and medium supplements purified from animal sources such as insulin, transferrin and albumin . Insulin serves as a growth and maintenance factor and is considered to be important for serum-free cultures . Insulin stimulates uridine and glucose uptake and synthesis of RNA, proteins and lipids; it also increases fatty acid and glycogen synthesis . Transferrin is one of the most essential growth promoting supplements in serum-free medium, and its omission causes severe inhibition of cell growth . Transferrin is an iron binding glycoprotein that interacts with surface receptors. It is closely related to the transport of iron across the plasma membrane . Transferrin has additional in-vitro functions, e.g., chelation of deleterious trace materials that are unlikely replaced by other components. Selenium is a trace element essential for mammalian cell cultures ; its mechanism is poorly understood although there is evidence that selenium enhances growth rate in serum free-cultures . Lipids are required for proliferation, differentiation, and antibody secretion. They play a major role in the cell membrane which is composed of a phospholipid bilayer, and help in the transmission of nutrients into the cell and excretion of proteins out the cell . Albumin, most commonly known as human serum albumin (HSA), prevents toxic effects of free fatty acids on cells in culture, acts as a metal ion binding protein and it also has antioxidant effects .
Further, as the impact of medium components on cell growth or product synthesis is rather difficult to fully elucidate, statistical methods are adopted to develop a medium for cell culture that offers optimal viable cell density and product formation. Design of experiments (DoE) is a useful tool that enables to determine simultaneously the individual and interactive effects of many factors that could affect the response function. The traditional one-factor-at-a-time approach for optimization is time-consuming and incapable of reaching the true optimum because this approach assumes that the various growth parameters do not interact, which could induce to error when defining the optimum . In fact, the observed behavior of growth may result from the interactive influences of the various variables . To be effective, optimization requires statistical methods that take these interactions into account. When there are many variables to be analysed, an efficient way to screen for the important factors is the use of the Plackett-Burman design. The Plackett-Burman design is a two-level multifactorial design based on the rationale known as balanced incomplete blocks . The key to this technique is forming various combinations (which are called assemblies) of the components with varying amounts. With the help of this design, up to N-1 components can be studied in N experiments, where N must be a multiple of 4 . Plackett-Burman design is a statistical technique that is not useful to analyse interactions between supplements but doubling the number of experimental runs may allow to identify the most evident ones.
After finding the most relevant factors that influence cell growth, the next step is to optimize the concentrations of these components in the growth medium. Response surface methodology (RSM), a powerful experimental strategy for seeking the optimum conditions for a multivariable system, is the chosen technique for optimization . RSM comprises mathematical and statistical procedures that can be used to study relationships between one or more responses and a number of independent variables, and it also generates a mathematical model that describes the overall process . In this approach, a Box-Behnken design has been chosen as the RSM. This design is formed by combining 2k factorials with incomplete block designs. The resulting designs are usually very efficient since they require few number experiments .
In this consultancy study, a Plackett-Burman and Box-Behnken approach has been adopted to first screen and second determine the optimum levels of, r-insulin, r-transferrin, selenium, r-albumin, tocopherol acetate, tween 80, fatty acids and synthetic cholesterol in order to maximize maximum cell density of the cell line CHO-S. With this strategy, the purpose is to gain insight both into the single effects and also the interactions among these factors that significantly impact cell growth in order to select the most relevant ones and optimize their concentration.
3. Objectives, work plan and scheduling
The objective established for the study was the optimization of a commercial serum-free cell culture medium for CHO-S cells with various non-animal derived supplements in order to improve maximum cell density. To achieve this end, the work plan includes the following steps:
- Screening between three commercial media to select the best one for further optimization.
- Determination of the concentration range for each supplement based on toxicity assays including zinc.
- Screening of supplements by means of the Plackett-Burman design methodology in order to identify those with a positive effect on cell growth and discard those with negative or null effects.
- Optimization of the concentration of the supplements with positive effect on cell growth using the Box-Behnken design methodology.
- Validation of the optimal conditions previously determined.
The work plan was defined as represented in the scheme below:
The initial proposed schedule was:
This initial schedule had to be prolonged, mainly due to two delays faced with the supply of laboratory material, particularly culture media, and an episode where the research team was uncertain in respect a potential contamination of some of the preparations. The additional time necessary for the finalization of the study has not added additional costs to it. In total de effective time to perform the work has been 7 months (from December 2013 to July 2014).
4. Materials and methods
4.1 Cell line, media and culture conditions
The cell line used was a serum-free suspension-adapted CHO-S cell line (Invitrogen, Carlsbad, California, USA). Three commercial serum-free media formulations for CHO-S were tested for cell growth. These include ProCHO5 (Lonza Biologics, Basel, Switzerland), ActiCHO (GE Healthcare, Little Chalfont, Buckinghamshire, UK) and FreeStyleCHO (Invitrogen, Carlsbad, California, USA). All formulations were supplemented with GlutaMAXTM (8mM) (Invitrogen, Paisley, UK). Cell cultures were pre-adapted to each formulation prior to experimentation. Cells were routinely maintained in 125-mL disposable polycarbonate Erlenmeyer flasks (Corning, Steuben, NY, USA) in 20 mL of culture medium. Flasks were shaken at 130 rpm using orbital shaker (Stuart, Stone, UK) placed in an incubator maintained at 37°C in a humidified atmosphere of 5% CO2 in air. An YSI 2700 select glucose/lactate analyzer (YSI, Yellow Springs, OH, USA) was used to measure the concentrations of the major nutrients and by-products (glucose and lactic acid) in cell culture supernatants
4.2 Determination of cell concentration and viability, growth rate an duplication time
Cell count and viability were determined by Nucleocounter NC-3000 (Chemometec, Allerod, Denmark). The cell counter has been provided by FeF Chemicals as part of the study, and after its validation has been used routinely during all the study to count cell concentration and viability, with good performance. The maximum specific growth rate, µmax(h-1), was estimated from data corresponding to the exponential growth phase by using the following equation:
μ = ln(X_f⁄X_i ) / (t_f-t_i)(1)
where X is the viable cell concentration (cells · mL-1); t is the culture time (h); subscripts f and i indicate the final and initial points of the exponential growth phase respectively. Duplication time dt was calculated from the previous specific maximum growth rate μmax(h-1) determination:
dt = ln(2) / µ(2)
4.3 MTT assay and toxicity tests
The MTT assay is a colorimetric assay for assessing cell viability. NAD(P)H-dependent cellular oxidoreductase enzymes reflect the number of viable cells present. These enzymes are capable of reducing tetrazolium dye MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide to its insoluble form formazan, which has a purple colour.
The MTT assay was used to perform toxicity assays. 100 μL of CHO-S cells were cultured at 0.3 million/mL in 96-well plate together with 10 μL of different concentrations of the supplement from which its toxicity is to be studied. The plate was cultured under standard culture conditions. After 48 h, 20 μL of the MTT reagent were added to each well and then the 96-well plate was incubated during 1 h at 37°C temperature and at 130 rpm stirring. A calibration curve was performed just before the analysis. 100 μL of CHO-S cells were seeded at variable concentrations in different wells, from 0 cells/mL to 1-1.5·106 cells/mL. The calibration curve was performed in duplicate.
The absorbance was measured in the spectrophotometer at a wavelength of 490 nm. By means of the data obtained from the calibration curve, cell concentration values could be extrapolated from absorbance values, which showed the toxicity of the different analyzed supplements.
4.4 Medium optimization using design of experiments (DoE)
Non-animal derived medium components used for media supplementation (DoE variables) included 3 recombinant proteins: r-albumin, r-transferrin (Merck Millipore, Kankakee, Illinois, USA) and r-insulin (Novo Nordisk/FeF Chemicals, Denmark); sodium selenite (selenium), synthetic cholesterol, fatty acids, tocopherol acetate and tween 80 (Sigma, St. Louis, Missouri, USA). In order to determine the maximum reached cell density (DoE response function) under each experimental condition analyzed, CHO-S cells were seeded at a density of 0.3 x 106 cells/mL and their growth kinetics were followed during 10 days.
4.4.1 Plackett-Burman design
A 24-run Plackett-Burman design of Resolution III was used to identify supplements with a significant effect on CHO-S cell growth and screen out irrelevant variables . The eight selected variables were screened at two levels: a low level (no additive) coded as -1 and a high level coded as +1 as indicated in Table 5. High levels for each variable were defined based on pre-existing knowledge extracted from the literature . A 12-run Plackett-Burman would also be suitable for 8 components, but doubling the number of experiments allow to better infer evident interactions between the supplements since the obtained information is more statistically significant. The objective was not to ignore supplements that could have a negative effect on cell growth individually but altogether with another supplement could have a positive effect.
The effect of each experimental variable upon the measured response (cell density) was determined as the difference between the average responses at the high level (+1) and the average responses at the low level (-1), as shown in Eq. 3:
where Eij is the effect of the variable i on a response j, is the measured response j andn is the number of experimental runs. A positive value for Eij means that the variable iincreases response j if added at high level, and vice versa. Plackett-Burman experimental results were fitted to a first-order polynomial function as described in Eq. 4 by regression analysis:
where Y is the response (cell density in million cells/mL),ß0 is the model intercept and ßiis the linear coefficient for the independent variable Xi.
4.4.2 Box-Behnken design
In order to define the optimal concentration for each supplement selected in the previous step, a Box-Behnken design was used. The three significant variables selected from the previous study were screened at three levels: a low level coded as -1, a medium level coded as 0 and a high level coded as +1 as indicated in Table 7. Box-Behnken experimental results were fitted to a second-order polynomial equation described in Eq. 5 by non-linear regression analysis:
where Y is the response (cell density in million cells/mL), ßij is the offset term, ßi the linear coefficient, ßii the quadratic coefficient, ßij the interaction coefficient and Xi and Xjare the independent variables. This equation was used to predict the optimum values of the independent variables using the solver feature of Microsoft Excel 2007. Three-dimensional surface plots were generated to facilitate model interpretation.
4.4.3 Statistical analysis
Statistical analyses of the models were performed using R Software (R Development Core Team) and Sigma Plot 12.0 (Systat Software Inc.) . The quality of the fit of the model equation is expressed by the coefficient R2 obtained by regression analysis. Additionally, a lack of fit test was performed in order to compare the experimental error to the predicted error. The overall significance of the model was determined by analysis of variance (ANOVA) F-test, whereas the significance of each coefficient was determined by the corresponding t-test.
5.1 Cell growth in commercial media
Three serum-free commercially available formulations specific for CHO suspension growth were selected with the guide of the ”good cell culture” interactive online database . All formulations tested are also free of supplements of animal origin (ADCF) and chemically defined (CD) (Table 1). Chemically defined media refer to media that do not contain hydrolysates or compounds of unknown composition and therefore completely defined regarding their chemical composition.
However, the exact composition of these media is proprietary to the corresponding manufacturers, and it is not disclose for obvious commercial reasons. The results of the first experiments with CHO-S cells performed with the three commercial media in batch culture are shown in Fig. 1.
Table 1. CHO-S growth kinetics in the three commercially available serum-free media tested. Abbreviations: Max: maximum; t1/2: duplication time; ADCF: animal-derived component free; CD: chemically defined; ± number: standard deviation of the measured value.
After thawing, CHO-S cells were subcultured in FreeStyleCHO medium requiring little adaptation. Subsequently, cells were subcultured into ActiCHO and ProCHO5 media also requiring little adaptation. Cells maintained a high viability (>90%) and showed a doubling time of 19 to -35 h at the exponential phase (Table 1 and Fig. 1). The maximum cell density attained varied with the different media, being highest in ActiCHO medium (11.5 x 106 cells/mL) while ProCHO5 and FreeStyleCHO reached 3.6 x 106 and 5.2 x 106cells/mL, respectively. When cell viability started to decrease, the availability of glucose was not limiting in ProCHO5 medium (>1.5 g/L) while it was in ActiCHO and FreeStyleCHO media (Fig. 1B). Regarding lactate production, it did not exceed 2 g/L in any media tested, which is considered typically the toxic concentration.
Fig. 1. (A) Growth kinetics of CHO-S cells in batch culture in different culture media. Cells were seeded at 0.3 x 106 cells/mL in 125-mL flasks in their growing exponential phase. Cell density and viability of each culture were determined every 24h. (B) Lactic acid and glucose profiles in different culture media. Mean values ± standard deviation of triplicate experiments are represented.
5.2 Cell growth in MIX supplemented media
The three commercial media previously tested were supplemented with a mixture (MIX) of various components with their concentration optimized for HEK 293 cell line in a previous work . This mixture included r-insulin (19.8 mg/L), r-transferrin (1.6 mg/L), tocopherol acetate (0.9X) , tween 80 (0.9X), synthetic cholesterol (0.9X) and fatty acids (0.9X) . As the concentration of the different supplements was not optimized for CHO-S cell line, this experiment enabled to see whether the addition of these components to the media could improve maximum cell density. This experiment was performed in batch culture and the results are presented in Fig. 2:
Fig. 2. Growth kinetics of CHO-S cells in batch culture in different culture media with MIX supplementation. Cells were seeded at 0.3 x 106 cells/mL in 125-mL flasks in their growing exponential phase. Cell density and viability of each culture were determined every 24h. (B) Lactic acid and glucose profiles in different culture media. Mean values ± standard deviation of triplicate experiments are represented.
Cells maintained a high viability (>90%) and showed a doubling time of 17 to -29 h during the exponential phase (Table 2 and Fig. 2). The maximum cell density attained varied with the different formulations, being highest in ActiCHO medium (12.2 x 106cells/mL). Comparing this maximum cell density value to the value with the same medium without supplementation (Table 1), no relevant cell density improvement was achieved. Regarding ProCHO5 medium, a maximum cell density of 5.4 x 106 cells/mL was reached, 1.5-fold higher than the same media without supplementation (Table 1). With reference to FreeStyleCHO medium, a maximum cell density of 6.7 x 106 cells/mL was attained, 1.3-fold higher than the same media without supplementation (Table 1). As in the previous experiment, when cell viability started to decrease, the availability of glucose was not limiting in ProCHO5 medium (>1.5 g/L) while it was in ActiCHO and FreeStyleCHO media (Fig. 2B). Regarding lactate production, it did not exceed 2 g/L in any of the media tested.
Table 2. CHO-S growth kinetics in various commercially available serum-free media formulations with MIX supplementation. Abbreviations: Max: maximum; t1/2: duplication time; ADCF: animal-derived component free; CD: chemically defined; ± number: standard deviation of the measured value.
The selected medium for subsequent optimization was FreeStyleCHO because for ActiCHO medium, which showed the highest cell density, no relevant improvement in maximum cell density was attained due to the fact that this medium can be already considered as highly optimized. This is the reason why this medium is less suitable for mixture supplements optimization in order to maximize cell density, but it is considered as the highest cell density CHO-S cells can reach. ProCHO5 medium showed the highest fold change with regards to maximum cell density attained with (Table 2) and without mixture supplementation (Table 1), but as FreeStyleCHO medium reached a higher cell concentration, and for this reason it was the medium finally selected to perform the subsequent optimization study.
5.3 Toxicity assays for non-animal derived mixture supplements
Previous to the screening of supplements as defined for the Plackett-Burman design two levels for experimentation have to be defined (a low concentration and a high concentration). Toxicity tests for every compound were performed to determine which compounds have an effect on cell growth, and with this information the concentration ranges for all supplements could be defined. For this reason, nine toxicity experiments were performed. This corresponds to the eight compounds initially selected as supplements, as well as Zinc, since this was requested by FeF Chemicals.
All the toxicity assays performed are shown in Fig. 3 and the concentration ranges for each supplement tested are in Table 3. Fatty acids and tween 80 are the only supplements that show some cell growth inhibition in the concentration ranges tested for the toxicity assays.
Table 3. Concentration ranges of the different supplements tested in the toxicity assays.
Fig. 3. Toxicity assays curves for the different supplements
5.4 Screening of non-animal derived supplements using Plackett-Burman design
The potential beneficial effect of non-animal derived supplements on CHO-S cell growth using the selected FreeStyleCHO medium was further investigated using a Plackett-Burman design of experiments, as previously mentioned. As discussed, non-animal derived additives evaluated included three recombinant proteins (r-albumin, r-transferrin and r-insulin), selenium, synthetic cholesterol, fatty acids, tocopherol acetate and tween 80. All supplements were studied at two levels: a low level (no additive) coded as -1 and a high level coded as +1 (Table 4).
Table 4. Concentration of each supplement referring to coded values -1 and +1.
The experimental design matrix in coded values, response and statistical analysis are shown in Table 5.
Table 5. Matrix design, response and ANOVA analysis for Plackett-Burman design of the different supplements: selenium (X1), r-transferrin (X2), r-albumin (X3), r-insulin (X4), tocopherol acetate (X5), fatty acids (X6), tween 80 (X7) and synthetic cholesterol (X8). Responses ‘a’ and ‘b’ are maximum cell density values from duplicate experiments in millions of cells/mL. Abbreviations: Exp. no.: experiment number; r-: recombinant.
Estimation of the main effect for each variable according to Eq. (3) indicated that r-transferrin had the greatest positive effect on cell growth (Fig. 4):
Fig. 4. Effects of non-animal derived supplements on CHO-S cells growth in FreeStyleCHO medium according to Plackett-Burman DoE. Code levels refer to the presence (1) or absence (-1) of the supplement. The response variable is viable cell concentration (106 cells/mL).
Selenium, r-insulin and tween 80 also showed a positive effect on cell growth, whereas fatty acids and synthetic cholesterol had no effect and r-albumin and tocopherol acetate had a negative effect on cell growth. The ANOVA F test associated p-value for each regression coefficient can also be used as an indicator of the statistical significance of the factors. Variables with a p-value lower than 0.05 were accepted as significant factors affecting CHO-S cell growth. This only includes r-transferrin with p < 4.46 · 10-6. The effect of the other supplements was not statistically significant (p > 0.05). r-transferrin, selenium and r-insulin were selected for further optimization experiments due to their positive effect on cell growth. The experiment also served to identify that tween 80 interacted negatively with other supplements, and for this reason it was not selected for further medium optimization.
5.5 Optimization of the concentrations of non-animal derived supplements using Box-Behnken design
A three-factor, three-level Box-Behnken experimental design was used to further optimize the concentrations of r-transferrin, r-insulin and selenium in the culture medium. All variables were studied at three levels: a low level coded as -1, a medium level coded as 0 and a high level coded as +1 (Table 6).
Table 6. Concentrations of each supplement referring to coded values -1, 0 and +1.
Table 7 outlines the experimental design matrix coded in values, the response variable and the statistical analysis of the method. These data were fitted to the second-order polynomial model previously described in Eq. (4) by non-linear regression analysis. The obtained model equation is:
where Y is the maximum cell density (in million cells/mL), X1 is the coded value for r-insulin, X2 the coded value for r-transferrin and X3 the coded value for selenium.
Table 7. Matrix design, response and ANOVA analysis for Box-Behnken experimental design of the different supplements: selenium (X1), r-transferrin (X2), r-insulin (X3). Response is the maximum cell density value (runs 1-12) in millions of cells/mL. Run 13 was performed in triplicate because it was the center point. Abbreviations: Exp. no.: experiment number; r-: recombinant.
Regression analysis showed that the model was adequate with a coefficient R2 of 0.6953, therefore indicating that the model is consistent with 70% of the variability in the data. The correlation between the experimental and predicted responses is observed in Fig. 5. The lack of fit parameter is p = 0.7714, as it is not significant at 0.05 level, the prediction error is less than the experimental error and the model is consistent with the data. The statistical significance of the model was confirmed by ANOVA analysis. The Fisher’s F-test associated p-value of < 0.0001 indicated the model was significant. The second-order polynomial model was used to calculate optimal factor levels and construct response surface graphs. By solving the model equation, optimum concentrations of r-insulin, r-transferrin and selenium in FreeStyleCHO medium were calculated as 26.1 mg/L, 20.2 mg/L and 1 µg/L respectively. Under these conditions the predicted response was 9.4 x 106 cells/mL. Three-dimensional plots were constructed for visual observation of the trend of maximum responses and the interactive effects of the significant variables on the response (Fig. 5A-C).
Evaluation of the response over the experimental region indicates that the optimal concentrations of r-insulin, r-transferrin and selenium are toward the edge of the range concentrations tested.
Fig. 5. Medium optimization by design of experiments. (A-C) Response surface graphs based on Box-Behnken experimental results. These 3D graphs were constructed depicting two variables at a time while keeping the third one at its intermediate level. CHO-S maximum cell density as a function of the concentrations of (B) r-transferrin (mg/mL) vs. selenium (mg/mL), (C) r-insulin (mg/mL) vs. selenium (mg/mL) and (D) r-transferrin (mg/mL) vs. r-insulin (mg/mL). Cell density values presented are in millions of cells/mL.
5.6 Validation of the model
In order to validate the model, a verification experiment was carried out. Under the optimal culture medium conditions predicted by the model, a maximum cell density of 10 ± 0.3 x 106 cells/mL was reached (n = 2) (Fig. 6), close to the model prediction (9.4 x 106 cells/mL), confirming the model accuracy. The control experiment performed in parallel with non supplemented FreeStyleCHO medium allowed to achieve a final cell concentration of 8.32 ± 0.1 x 106 cells/mL.
Fig. 6. Model validation. CHO-S cell growth in FreeStyleCHO medium supplemented with the optimal levels of non-animal derived supplements were seeded at 0.4 x 106 cells/mL in 125 mL flasks. Cell density and viability were determined daily. Mean values ± standard deviation of duplicate experiments are represented.
An improved cell growth of CHO-S cells in FreeStyleCHO medium was achieved by adding three supplements at the following concentrations: selenium (1 µg/L), r-transferrin (20.2 mg/L) and r-insulin (26.1 mg/L). The optimization of FreeStyleCHO medium was successfully achieved by means of Design of Experiments methodology which led to a maximum cell density of 10 ± 0.3 x 106 cells/mL, that is near to that of one of the most optimized media for CHO cells in batch culture (ActiCHO), and represented an increase of 20.5 % in respect to a control culture run under the same conditions. Therefore, it has been proved that DoE techniques allow a fast identification of the most suitable supplements and their concentration for optimization of cell growth. In this direction, it is considered that DoE methodology is an interesting technique to be used with other cell lines for cell culture media optimization.
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8.1 Plackett-Burman experiments
Viable cell concentration (black line), viability (gray line) and the corresponding standard deviations from the Plackett-Burman experiments (n=2) are reported in each graphic.
8.2 Box-Behnken experiments
Viable cell concentration (black line) and viability (gray line) from the Box-Behnken experiments are reported in each graphic.
How does insulin work in mammalian cell culture? To understand its actions in mammalian cell bio-production it is important to know that the action of insulin in mammalian cell culture is primarily through the binding and activation of IGF-1R.
How does insulin work in mammalian cell culture? To understand its actions in mammalian cell bio-production it is important to know that the action of insulin in mammalian cell culture is primarily through the binding and activation of IGF-1R.
By Karina Kristensen, M.Sc. Cell Biology, FeF Chemicals A/S
Insulin is a 5,8kD protein hormone secreted in vivoby the b-cells of the pancreatic islets of
Langerhans (1). Insulin and the related insulin-like growth factors IGF-I and IGF-II act on cells through binding to specific receptors, the insulin receptor (IR) (1,2) and the type 1 IGF receptor (IGF-1R) (3,4), two highly homologous dimeric transmembrane glycoproteins that are part of the receptor tyrosine kinase (RTK) family. Insulin and IGF-I have high affinity (0,1-0.2 nM) for their cognate receptor but can bind at high concentration with a 100-500 lesser affinity to the noncognate receptor. Physiologically, the role of insulin is primarily metabolic while the IGFs are primarily growth factors, as evidenced by the phenotypes of mice where either receptor gene has been knocked out (5). The specificity is far from absolute, however (6,7), and in cells where the insulin receptor is absent, the IGF-IR can mediate metabolic effects (8), while in cells without IGF-I receptors, insulin can mediate mitogenic effects (9). Insulin through the IR also inhibits apoptosis induced by serum withdrawal in a variety of cell types (10-16). The signalling pathways of the IR and IGF-IR are largely shared (6-8). In cells with both IRs and IGF-IRs, hybrid receptors are present that behave essentially as IGF-IRs (8) In mammalian cell culture, recombinant insulin is added at approximately 100 times the physiological concentration. Insulin at this high concentration acts as a growth factor, with anti-apoptotic and mitogenic effects. These effects are not only through activation of the IR but also through activation of the IGF-1R. See Fig. 1a and b.
Figure 1a: Physiological function of insulin. Both IR and IGF-1R are expressed on the surface of a mammalian cell, but only the IR is activated by insulin at physiological concentration of insulin.
Structure of the receptor extracellular domain from ref. 19, PDB accession code 2DTG. Drawn using DSViewerPro.
Figure 1b: Function of insulin in mammalian cell culture. High concentrations of insulin trigger a mitogenic effect via the IGF-1R, and are resulting in a variety of effects via the native IR.
The insulin and IGF-1 molecules have a high degree of homology as well (1,2). In the folding of the molecule and in the surface areas involved in receptor binding the two molecules are highly alike.
Figure 2: Similar folding of insulin (A-chain -blue- 21 aa, B-chain-green- 30 aa) and IGF-1 (70 aa), C-domain in dark blue, D-domain in light blue. From reference 2, PDB accession codes 9INS and 1GZR. Drawn with DSViewerPro.
1. De Meyts P and Whittaker J. Structural biology of insulin and IGF-I receptors: implications for drug design. Nat Rev Drug Discov 1:769-783, 2002.
2. De Meyts P. My favourite molecule. Insulin and its receptor: structure, function and evolution. BioEssays 26:1351-1362, 2004.
3. Adams TE, Epa VC, Garrett TC and Ward CW. Structure and function of the type 1 insulin-like growth factor. Cell Mol Life Sci, 57:1050-1093, 2000.
4. De Meyts P, Wallach B, Christoffersen CT, Ursø B, Grønskov K, Latus LJ, Yakushiji F, Ilondo MM and Shymko RM. The insulin-like growth factor-I receptor. Structure, ligand binding mechanism and signal transduction. Horm Res 42:152-169, 1994.
5. Efstratiadis A. Genetics of mouse growth. Int J Dev Biol 42:955-976, 1998.
6. De Meyts P. Insulin and insulin-like growth factors: the paradox of signalling specificity.
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7. Kim JJ and Accili D. Signalling through IGF-I and insulin receptors: where is the specificity? Growth Horm and IGF Res 12:84-90, 2002.
8. Baudry A, Lamothe B, Bucchini D, Jami J, Montanas D, Pinset C and Joshi RL. IGF-1 receptor as an alternative receptor for metabolic signalling in insulin receptor-deficient muscle cells. FEBS Lett 488:174-178, 2001.
9. Lamothe B, Baudry A, Christoffersen CT, De Meyts P, Jami J, Bucchini D and Joshi RL.
Insulin receptor-deficient cells as a new tool for dissecting complex interplay in insulin and insulin-like growth factors. FEBS Lett 426: 381-385, 1998.
10. Diaz B, Pimentel B, De Pablo F and De La Rosa EJ. Apoptotic cell death of proliferating neuroepithelial cells in the embryonic retina is prevented by insulin. Eur J Neurosci 11:1124-1632, 1999.
11. Bertrand E, Atfi A, Cadoret A, L’Allemain G, Robin H, Lascols O, et al. A role for nuclear factor kappaB in the antiapoptotic function of insulin. J Biol Chem 273:2931-2938, 1998.
12. Rampalli AM and Zelenka PS. Insulin regulates expression of c-fos and c-jun and suppresses apoptosis of lens epithelial cells. Cell Growth and Differentiation 6:945-953, 1995.
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16. Iida KT, Suzuki H, Sone H, Shimano H, Toyoshima H, Yatoh S, Asano T, Okuda Y and Yamada N. Insulin inhibits apoptosis of macrophage cell line, THP-1 cells, via phosphatidylinositol-3-kinase-dependant pathway. Arterioscler Thromb Vasc Biol 22:380-386,2002.
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The ancestors of cell culture media were the balanced salt solutions (BSS) devised by early workers interested in studying isolated organs ex vivo.
The ancestors of cell culture media were the balanced salt solutions (BSS) devised by early workers interested in studying isolated organs ex vivo.
Such solutions provided irrigation and supply of water, bulk inorganic anions essential for normal cell metabolism, osmotic balance (isotonicity), a carbohydrate such as glucose as energy source, and a buffering system to maintain the medium within the physiological pH range (7.2 – 7.6) usually monitored by the addition of phenol red (1).
The first BSS was composed in 1885 by Sydney Ringer (1836-1910), a British clinician and pharmacologist from University College London who worked on the isolated frog heart (2).
By Pierre De Meyts, MD, PHD, F.A.C.E.
A version containing lactate is still used for intravenous perfusion. Ringer’s solution was modified by Maurice V. Tyrode (1878-1930), an American physiologist born in Besançon to study isolated kidneys. Another popular balanced salt solution was devised by John H. Hanks (1906-1990), an American microbiologist, in order to attempt to cultivate the leprosy bacillusin vitro (he never succeeded) (3). Renato Dulbecco, an Italian born (1914) American virologist (who won the Nobel Prize in Physiology and Medicine in 1975 with Howard Temin and David Baltimore for their discovery of reverse transcriptase), described the much used Phosphate Buffered Saline (PBS) (4).
However it became clear that in order to get cells to actually proliferate in vitro, additional nutrients had to be added to culture media.
The first successful attempt at tissue culture is attributed to Ross Harrison (1870-1959) at Johns Hopkins University, who explanted in 1907 tadpole tissues in clotted frog lymph as nutritional and growth support, using a hanging drop on a glass slide. He was successful in observing neurite expansions (5,6).
Building on Harrison’s success, the major early figure in tissue culture was Alexis Carrel (1873-1944), a French surgeon. He moved to the University of Chicago in 1903 and obtained the Nobel Prize in Physiology and Medicine in 1912 for inventing a method to suture blood vessels. In 1906 he moved to the Rockefeller Institute for Medical Reseach and started his work on tissue culture, in which he did pioneering work (124 articles, 7,8) and dominated the field, for better or for worse, until his death. He adopted Harrison’s hanging drop technique but replaced the frog lymph by a plasma clot and fed the explants serum, a salt solution and chick embryo extract, which he called “plasmatic medium”, which became a standard until the 1950’s. His most famous experiment was the maintenance for over 34 years of an embryonic chicken heart explant, finally discarded two years after Carrel’s death. This nurtured Carrel’s firm belief that primary cells in culture were immortal given the appropriate nutrition. Definitive evidence that this is wrong was provided by Leonard Hayflick (born 1928), an American gerontologist and professor of anatomy at UCSF, who demonstrated in 1965 that normal human diploid fibroblasts do not survive in vitro for more than approximately 50 divisions (“Hayflick’s limit”) (9). The survival of Carrel’s culture was likely due to the daily feeding of new embryonic cells from the embryonic extract.
The first continuous culture of a rodent cell line (L929) from a single cell was generated by Wilton R. Earle at the National Cancer Institute in 1943 (10). In 1951, George O. Gey (1899 -1970) at Johns Hopkins University developed the first continuous human cancer cell line from Henrietta Lacks’s cervical carcinoma, the celebrated HeLa cell line whose eagerness to grow has resulted in cross-contamination of many cell cultures…
In the early 50s, synthetic media were being developed. By then it had been determined that cell growth required a basal mix of salts, sugars, amino acids and vitamins, plus a supplement of poorly defined biological fluids or extracts such as plasma or serum from various sources (11) which provided a.o. what were later identified as growth factors (see section on insulin-like growth factors (IGFs)), hormones, albumin and transferrin.
Harry Eagle (1905-1992), an American pathologist (Johns Hopkins and NCI) was one of the first to define more precisely the nutritional needs of cells in culture, leading to the media still in use today, such as Eagle’s Minimal Essential Medium (MEM) (12) or its modification by Dulbecco (DMEM).
The earliest attempt to get rid of the variability introduced by the need for serum was the chemically defined, synthetic medium (F12) devised by Richard G. Ham at the University of Colorado in 1965 (13).
But the development of serum-free culture methods owes much to the pioneering work of Gordon H. Sato (born 1927), an American cell biologist at UCSD, with David Barnes at the University of Pittsburgh. They developed in the late seventies serum-free media for a variety of cell lines, and showed that the cell lines have different requirements for hormones, growth factors or other factors such as attachment factors (14). But they found out that there was a rather “universal” growth factor: insulin.
As stated by Barnes and Sato (14), “Although different cell lines have been found to respond to different hormones, and to varying degrees to these hormones,insulin thus far has been found to be stimulatory in serum-free medium for the growth of virtually every cell type examined. In many cases, the concentration of insulin required for good growth is much higher than can be considered physiologically relevant, suggesting that insulin may be mimicking the activity of a related peptide for such cells”.
We know today that indeed the bulk of the growth promoting effect of insulin in cell culture is likely through its low-affinity interaction for the insulin-like growth factor I receptor (IGF-IR) (see section on insulin-like growth factors). However, mammary tumour cell lines like the MCF-7 cell line appear to respond to low levels of insulin, suggesting that in those cells the growth-promoting effect is mediated by the insulin receptor (15, 16).
One advantage for using high concentrations of insulin rather than low concentrations of IGF-I is the lack of binding of insulin to IGF-binding proteins (IGFBPs), which are produced in variable amounts by different types of cells (see section on IGFs) and introduce a factor of variability by interfering with the actions of the IGFs (although there are engineered IGF-I variants with low affinity for the IGFBPs).
Another potential advantage is the conservation of signalling through the insulin receptor and therefore the maintenance of the anabolic effect of insulin, which would not be the case with low IGF-I concentrations. Anabolic metabolism appears to be important for optimal cell growth (17). This benefit may however be transient due to the likely downregulation of the insulin receptor by the high insulin concentrations (18).
For further reading, see ref. 19.
1. Sigma Life Sciences Cell Culture Manual 2011-2014, p.116.
2. Miller DJ. Sydney Ringer; physiological saline, calcium and the contraction of the heart. J Physiol555:585-587 (2004).
3. Hanks JH. Hanks’ balanced salt solution and pH control. Tissue Culture Association Manual,3,3 (1976).
4. Dulbecco R and Vogt M. Plaque formation and isolation of pure lines with polyomyelitis viruses. J Exp Med106:167-169 (1954).
5.Harrison R. Observation on the living developing nerve fiber. Anat Rec 1:116-128 (1907).
6.Harrison R. The outgrowth of the nerve fiber as a mode of protoplasmic movement. J Exp Zool9:787-846 (1910).
7. Carrel A. On the permanent life of tissues outside of the organism. J Exp Med15:516-528 (1912).
8. Carrel A andLindbergh CA, The culture of whole organs. Science 81:621-623 (1935).
9. Hayflick L. The limitedin vitrolifetime of human diploid cell strains. Exp Cell Res 37:614-636 (1965).
10. Earle WR, Schilling EL, Stark TH, Straus NP, Brown MF and Shelton E. Production of malignancyin vitro. IV. The mouse fibroblast cultures and changes seen in the living cells. J Nat Cancer Inst4:165-169 (1943).
11. Temin HM, Pierson RW and Dulak NC. The role of serum in the control of multiplication of avian and mammalian cells in culture. In: Growth, Nutrition and Metabolism of Cells in Culture, 1, G. Rothblat and V.J. Cristofalo, eds. (New York, Academic Press), pp.50-81 (1972).
12. Eagle H. Amino acid metabolism in mammalian cell cultures. Science130: 432-437 (1959).
13. Ham RG. Clonal growth of mammalian cells in a chemically defined, synthetic medium. Proc Natl Acad Sci USA 53:288-293 (1965).
14. Barnes D and Sato G. Serum-free culture: a unifying approach. Cell22:649-655 (1980).
15. Barnes D. and Sato G. Growth of a human mammary tumor cell line in a serum-free medium. Nature 281:388-389 (1979).
16. Allegra JC and Lippman ME. Growth of a human breast cancer cell line in a serum-free hormone-supplemented medium. Cancer Res. 38:3823-3829 (1978).
17. Locasale JW and Cantley LW. Metabolic flux and the regulation of mammalian cell growth. Cell Metabolism DOI 10.1016/j.cmet.2011.07.014
18. Gavin, JR III, Roth J, Neville DM jr, De Meyts P and Buell DN. Insulin-dependent regulation of insulin receptor concentrations: a direct demonstration in cell culture. Proc. Natl. Acad. Sci USA 71:84-88 (1974).88:
19. Langdon SP. Basic principles of cancer cell culture. In “Methods in Molecular Medicine”vol. 88: Cancer cell culture: Methods and protocols. Edited by SP Langdon, Humana Press,Totowa,NJ. pp 3-15.
As discussed in the section on history of cell culture, serum was used for several decades as a source of nutrients, hormones and growth factors, the nature of which was largely unknown.
As discussed in the section on history of cell culture, serum was used for several decades as a source of nutrients, hormones and growth factors, the nature of which was largely unknown. The first growth factor to be identified, nerve growth factor (NGF) was discovered in 1953 at Washington University in St Louis (1) by Rita Levi-Montalcini, an Italian-born physician (born in 1909 and now a still very active centenarian).
She purified it with the help of Stanley Cohen (born 1922) who went on to become professor of biochemistry at Vanderbilt University where he discovered in 1962 and extensively characterized epidermal growth factor (EGF) (2).
Levi-Montalcini and Cohen shared the 1986 Nobel Prize in Physiology and Medicine.
NGF was sequenced in 1971 (3) and EGF in 1972 (4).
The following discovery of the insulin-like growth factors I and II took nearly three decades of sometimes confusing research that stemmed from early studies of the mechanism of action of pituitary growth hormone on somatic growth.
In 1957, W.D. Salmon Jr and William H. Daughaday at Washington University in St Louis provided compelling evidence that the effects of growth hormone in stimulating the incorporation of radioactive sulfate into chondroitin sulfate in cartilagein vivoand in vitrowas not direct, but mediated by a factor circulating in serum that they named “sulfation factor” (5). In the early 70’s, many investigators started to search for the factor(s) mediating growth hormone effects that by consensus became known as “somatomedins” (6). Different groups used different target cell systems and different isolation and purification methods, resulting in a multiplicity of somatomedins of which the similarities and differences were unclear.
Somatomedin A was identified as a factor that promotes labelled sulfate uptake by chicken cartilage (7). Somatomedin B was identified as a factor that stimulates DNA synthesis in human glial cells (8,9). Future Nobel laureate Rosalyn Yalow developed in 1975 a radioimmunoassay for somatomedin B (10). Somatomedin C was a more basic peptide than somatomedin A or B and stimulated uptake of labelled sulfate into rat cartilage (11).
At about the same time, future Nobel laureate Howard Temin and coworkers isolated a new growth factor, which they named Multiplication Stimulation Activity (MSA), from serum-free medium that had been conditioned by a Buffalo rat liver cell line (BRL-3A) (12).
A different angle into the developing story came from the work of Rudolph E. Froesch and coworkers at the University of Zürich, who initially were studying, not as the groups above the mitogenic properties of serum components, but their metabolic properties. Before a radioimmunoassay for insulin had been developed in 1960 by Rosalyn Yalow and Solomon A. Berson, insulin in serum had been assayed inin vitrobioassays using e.g. rat diaphragm or rat fad pads, later collagenase- isolated rat or mouse adipocytes. When the radioimmunoassay became available, it became clear that the plasma immunoreactive insulin (IRI) represented less than 10% of the total insulin-like activity. Moreover, specific guinea-pig anti-insulin serum produced only a small suppression of the insulin-like effects of human serum. Therefore the large fraction of insulin-like material could not be identical to insulin, and was called “non suppressible insulin-like activity” (NSILA). The fraction of it that was soluble in acid-ethanol was called NSILA-S (13,14). It became clear that NSILA also had growth-promoting properties, in fact at much lower concentrations than the metabolic properties, and therefore was primarily a growth factor (14). NSILA cross-reacted in the radioreceptor assay for somatomedins A and C, and therefore it became clear that NSILA’s components were somatomedins (14). It took the Froesch group 20 years of a relentless effort led by René E. Humbel in the Institute of Biochemistry at the University of Zürich, starting with 11 kilos of an acetone powder from 6 tons of a Cohn fraction of human plasma (containing a and b globulin) obtained from Hoffmann-La Roche in Basel, to purify enough material (5 μmol) to sequence the two polypeptides that made up NSILA. It became evident that their sequence was closely related to insulin’s sequence and they were therefore called insulin-like growth factors I and II (15-17). Their characteristics will be described in more detail in the section on the insulin peptide family. 3D modelling by Tom L. Blundell (a former member of Dorothy Hodgkin’s team that solved the crystal structure of insulin in 1969) and Sri Bedarkar at Birkbeck College showed that the two IGFs likely had the same tertiary structure as insulin (18).
A few years later, the other groups also managed to sequence their favourite somatomedin. Somatomedin A (19) and C (20) turned out to be IGF-I. A rat basic somatomedin was also IGF-I (21). In contrast, the active component of MSA turned out to be IGF-II (22), which is not properly speaking a somatomedin since it is not growth hormone-dependent.
Somatomedin B was sequenced in 1978, the same year as the IGFs, and turned out to be completely unrelated to the above peptides, with characteristics that make it dubious that it is a somatomedin at all or even a growth factor. The sequence of somatomedin B showed it to be a novel 44 amino acid peptide with 8 cysteines, with protease-inhibiting activity (23), although still claimed to be growth hormone dependent. This peptide later turned out to be a N-terminal proteolytic fragment of vitronectin, now called somatomedin B domain (24), responsible for binding to the urokinase receptor and the plasminogen activator inhibitor-I. It is unclear how this relates to the initially reported growth promoting activities of somatomedin B. However, vitronectin has been shown to have synergistic effects with growth factor signalling (24), including IGF-I. Zee Upton at Queensland University in Australia has provided evidence for multimeric complexes between vitronectin, IGF-I and IGF binding proteins (25) with potential applications in wound healing.
In the 80’s, the cDNAs for the IGFs were cloned and sequenced as well (26-28). In the 90’s and early 2000’s, both NMR and crystal structures of the IGFs were solved (29-34), confirming the early predictions of structure similarity to insulin’s (18).
In the end, an apparent multiplicity of supposedly cell-type specific somatomedins turned out to be just the two but ubiquitous IGF-I and IGF-II. This helps explain why insulin, which at high concentrations binds to and stimulates the IGF-I receptor that binds IGF-I and II, is such a nearly universal growth factor in cell culture.
Further reading: for a contemporary update on the original “somatomedin hypothesis”, see ref. 35.
1. Levi-Montalcini R, Meyer H and Hamburger V.In vitroexperiments on the effects of mouse sarcomas 18 and 37 on the spinal and sympathetic ganglia of the chick embryo. Cancer Res 14:49-57 (1954).
2. Cohen S. Isolation of a mouse submaxillary gland protein accelerating incisor eruption and eyelid opening in the new-born animal. J Biol Chem 237:1555-1562 (1962).
3. Angeletti RH and Bradshaw RA. Nerve growth factor from mouse submaxillary gland: amino acid sequence. Proc Natl Acad Sci USA 68: 2417-2420 (1971).
4. Savage CR Jr, Inagami T and Cohen S. The primary structure of epidermal growth factor. J Biol Chem 247:7612-7621 (1972).
5. Salmon WD Jr and Daughaday WH. A hormonally controlled serum factor which stimulates sulfate incorporation by cartilagein vitro. J Lab Clin Med 49:825- 826 (1957).
6. Daughaday WH, Hall K, Raben MS, Salmon WD Jr, Van Den Brande JL, Van Wyk JJ. Somatomedin: proposed designation for sulphation factor. Nature 235:107 (1972).
7. Hall K. Human somatomedin: determination, occurrence, biological activity and purification. Acta Endocrinol Suppl 163:1-52 (1972).
8. Uthne K. Human somatomedins: purification and some studies on their biological actions. Acta Endocrinol 73 (Suppl. 175): 1-35 (1973).
9. Fryklund L, Uthne K and Sievertsson H. Isolation and characterization of polypeptides from human plasma enhancing the growth of human normal cells in culture. Biochem Biophys Res Commun 61: 957-962 (1974).
10. Yalow RS, Hall K and Luft R. Radioimmunoassay of somatomedin B. Application to clinical and physiologic studies. J Clin Invest 55:127-137 (1975).
11. Van Wyk JJ, Underwood LI, Hintz RL, Clemmons DR, Vorna SJ and Weaver RP. The somatomedins: a family of insulin-like hormones under growth hormone control. Recent Prog Horm Res 30:259-318 (1974).
12. Dulak N and Temin HM. Multiplication-stimulating activity for chicken embryo fibroblasts from rat liver cells conditioned medium: a family of small polypeptides. J Cell Physiol 81:153-160 (1974).
13. Jakob A, Hauri C and Froesch ER. Non-suppressible insulin-like activity. 3. Differentiation of two distinct molecules with nonsuppressible ILA. J Clin Invest 47:2768-2788 (1968).
14. Zapf J, Rinderknecht E, Humbel RE and Froesch ER. Nonsuppressible insulin-like activity (NSILA) from human serum: recent accomplishments and their physiologic implications. Metabolism 27:1803-1828 (1978).
15. Rinderknecht E and Humbel RE. The amino acid sequence of human insulin-like growth factor-I and its structural homology with proinsulin. J Biol Chem 253:2769-2776 (1978).
16. Hinderknecht E and Humbel RE. Primary structure of human insulin-like growth factor II. FEBS Lett 89:283-286 (1978).
17. Humbel RE. Insulin-like growth factors I and II.Eur J Biochem 190:445-462 (1990).
18. Blundell TL, Bedarkar S, Rinderknecht E and Humbel RE. Insulin-like growth factor: a model for tertiary structure accounting for immunoreactivity and receptor binding. Proc Natl Acad Sci USA75:180-184 (1978).
19. Engberg G, Carlquist M, Jörnvall H and Hall K. The characterization of somatomedin A, isolated by microcomputer-controlled chromatography, reveals an apparent identity to insulin-like growth factor-I. Eur J Biochem 143:117-124 (1984).
20. Klapper DG, Sroboda ME, VanWyk JJ. Sequence analysis of somatomedin C: confirmation of identity with insulin-like growth factor-I. Endocrinology 112:2215-2217 (1983).
21. Rubin JS, Mariz I, Daughaday WH and Bradshaw RA. Isolation and partial sequence analysis of rat basic somatomedin. Endocrinology 110: 734-740 (1982).
22. Marquardt H, Todaro GJ, Henderson LE and Orozlan S. Purification and primary structure of a polypeptide with multiplication-stimulating activity from rat liver cell cultures: homology with human insulin-like growth factor-II. J Biol Chem 256:6859-6865 (1981).
23. Fryklund L and Sievertsson H. Primary structure of somatomedin B, a growth-hormone dependent serum factor with protease inhibiting activity. FEBS Lett 87:55-60 (1978).
24. Schvartz I, Seger D and Shaltiel S. Vitronectin. Int J Biochem Cell Biol 31:539-544 (1999).
25. Kricker JA, Towne CL, Firth SM, Herington AC and Upton Z. Structural and functional evidence for the interaction of insulin-like growth factors (IGFs) and IGF binding proteins with vitronectin. Endocrinology 144:2807-2815 (2003).
26. Dull TJ, Gray A, Hayflick JS and Ullrich A. Insulin-like growth factor II: precursor gene organisation in relation to insulin gene family. Nature 310:777-781 (1984).
27. Stempien MM, Fong NM, Rall LB and Bell GI. Sequence of a placental cDNA encoding the mouse insulin-like growth factor II precursor. DNA5:357-361 (1986).
28. Murphy LJ, Bell GI, Duckworth ML and Friesen HG. Identification, characterization and regulation of a rat complementary deoxyribonucleic acid which encodes insulin-like growth factor-I. Endocrinology 121:684-691 (1987).
29. Cooke RM, Harvey TS and Campbell ID. Solution structure of human insulin-like growth factor 1: a nuclear resonance and restrained molecular dynamics study. Biochemistry 30:5484-5491 (1991).
30. Sato A, Nishimura S, Ohukuba T, Kyogoku Y, Koyama S, Kobayashi M, Ysuda T and Kobayashi Y. Three-dimensional structure of human insulin-like growth factor-I (IGF-I) determined by 1H NMR and distance geometry. Int J Pept Protein Res 41:433-440 (1993).
31. Torres AM, Forbes BG, Aplin SE, Wallace JC, Francis GL and Norton RS. Solution structure of human insulin-like growth factor II. Relationship to receptor and binding protein interactions. J Mol Biol 248:385-401.
32. Tersawa H, Kohda D, Hatanaka H, Nagata K, Higashihashi N, Fujiwara H, Sakano K and Inagaki F. Solution structure of human insulin-like growth factor II: recognition sites for receptors and binding proteins. EMBO J. 13:5590-5597 (1994).
33. Vajdos FF, Ultsch M, Schaffer ML, Deshayes KD, Liu J, Skelton J and De Vos AM. Crystal structure of human insulin-like growth factor -1: detergent binding inhibits binding protein interactions. Biochemistry 40: 11022-11029 (2001).
34. Zeslawski W, Beisel HG, Kamionka M, Kalus W, Engh RA, Huber R, lang K and Holak TA. The interaction of insulin-like growth factor with N-terminal domain of IGFBP-5. EMBO J20:3638-3644 (2001).
35. Brzozowski AM, Dodson EJ, Dodson GG, Murshudoo GN, Verma C, Turkenburg JP, Debree F and Dauter Z. Structural origins of the functional divergence of human insulin-like growth factor-I and insulin. Biochemistry 41:9389-9397 (2002).
36. LeRoith D, Bondy C, Yakar S, Liu JL and Butler A. The somatomedin hypothesis: 2001. Endocrine Rev. 22:53-74 (2001).
Insulin is only one member of a family of peptide hormones and growth factors that comprizes 10 members in humans: insulin, insulin-like growth factors I and II (IGF-I and II) and seven peptides related to relaxin.
Insulin is only one member of a family of peptide hormones and growth factors that comprizes 10 members in humans: insulin, insulin-like growth factors I and II (IGF-I and II) and seven peptides related to relaxin (Fig. 1).
They result from successive duplications of an ancestral gene that appeared early in animal evolution. Invertebrates also have many insulin-like peptides, e.g. 37 in the worm C. elegans and seven in the fruit fly Drosophila Melanogaster (1).
They play an important role in metabolism, growth, reproduction and longevity.
by Pierre De Meyts, MD, PHD, F.A.C.E.
Figure 1: Canonical structure of members of the insulin peptide family. A. Insulin in the T conformation (PDB file 9INS). B. Insulin in the R conformation (PDB file 1ZNJ). C. IGF-I (PDB file 1GZR). D. IGF-II (PDB file 1ZNJ). E. Relaxin (PDB file 6RLX). The A-chains or A-domain are shown in blue, the B-chain or B-domain are shown in light green, the C-domain is shown in dark blue, and the E-domain is shown in light blue. The disulphide bridges are shown in yellow.
A bit of history
Insulin was isolated and purified for the first time to a grade suitable for treating diabetic patients at the University of Toronto in 1921 (2, see ref. 3 for a detailed history), winning the Nobel Prize in 1923 to Frederick G. Banting (1891-1941) and John J.R. McLeod (1876-1935). Besides being a life-saving therapy for diabetic patients, insulin turned out to be a bonanza for scientists interested in the structure and chemistry of proteins and provided many technological milestones. Insulin was the first protein to be sequenced by Frederick Sanger (born 1918) in Cambridge (4), winning him his first Nobel Prize in Chemistry in 1958. It was the first protein to be made by total synthesis in the early 60’s independently by three groups: Panayotis Katsoyannis in New York (5), Helmut Zahn (1916-2004) in Aachen, Germany (6) and Yu Can Du and colleagues in Shanghai and Beijing (7). It was the first protein to be assayed by radioimmunoassay, developed by Rosalyn S. Yalow (1921-2011) and Solomon A. Berson (1918-1972) in New York. This achievement won the Nobel Prize in Physiology and Medicine to Yalow in 1977. Human insulin became the first protein made by recombinant DNA technology (see section on insulin bioengineering) to be produced commercially in 1982 (8).
Figure 2: Primary structure of human insulin. The A-chain is shown in light blue, the B-chain in light green.
The birth of the receptor concept dates back to the early work of John Newport Langley (1852-1925), a Cambridge physiologist, who postulated in 1905 that a "receptive substance" on the surface of skeletal muscle mediated the action of nicotine.
A bit of history The birth of the receptor concept dates back to the early work of John Newport Langley (1852-1925), a Cambridge physiologist, who postulated in 1905 that a “receptive substance” on the surface of skeletal muscle mediated the action of nicotine (1). At about the same time, Paul Ehrlich (1854-1915), a German immunologist who was the founding father of chemotherapy, came up with a “side chain theory” of cell receptors to explain the selectivity of immune reactions, winning him the Nobel Prize in Physiology or Medicine in 1908. His famous adage “Corpora non agunt nisi fixata” (“Substances do not act unless they are bound”) is an elegant and concise early statement of the receptor theory (2).
by Pierre De Meyts, MD, PHD, F.A.C.E.
The receptor concept was put on more solid ground with the seminal 1948 paper of Raymond P. Ahlquist (1914-1983), an American pharmacologist of Swedish descent at the Medical College of Georgia, who proposed that the excitatory and inhibitory effects of adrenotropic agents were mediated by two separate receptors which he termed a and b (3). The receptors would however remain hypothetical entities until the late 60’s, when direct methods to study their biochemistry were developed.
The concept that insulin exerts its effects by acting at the membrane of target cells was proposed over 60 years ago by Rachmiel Levine (1910-1991), considered by many as one of the founding fathers of modern diabetology, then working at Walter Reese Hospital in Chicago. He postulated that “insulin acts upon the cell membrane of certain tissues (skeletal muscle, etc.) in such a manner that the transfer of hexoses (and perhaps other substances) from the extracellular fluid into the cell is facilitated” (4). The direct demonstration of cell membrane receptors for polypeptide hormones took another twenty years. In 1969, two groups independently established methods for the radioiodination of peptide hormones with preserved bioactivity: Robert J. Lefkowitz, Jesse Roth and Ira Pastan at the National Institutes of Health in Bethesda (working on ACTH) (5) and Theodore L. Goodfriend´s group at the University of Wisconsin in Madison (working on angiotensin) (6). In 1970 and 1971, three groups independently published the first reports on 125I-insulin binding to liver plasma membranes: P.D.R. House and M.J. Weidemann in Canberra (7), Pierre Freychet, Jesse Roth and David M. Neville Jr at the NIH (8), and Pedro Cuatrecasas, Bernard Desbuquois and Folger Krug at Johns Hopkins University (9). Shortly afterwards in Denmark, Steen Gammeltoft and Jørgen Gliemann established independently radioligand binding assays for studying insulin receptors on isolated rat fat cells (10). Radioligand binding assays also established the existence of a separate receptor for somatomedins (IGFs) (11,12).
We will not give here a detailed account of the following four decades of productive research on the biochemistry of the insulin and IGF-I receptors, culminating in the cloning of the cDNAs of the two receptors in 1985 (13-15) as well as the elucidation of the crystal structure of their kinase domain (16) and that of the extracellular domain of the insulin receptor (17) and of the N-terminal domain of the IGF-I receptor (18) (see below). For further reading, see ref. 19.
Structure of the insulin and IGF-I receptors
The primary sequence of the insulin receptor was determined by cDNA cloning in 1985 simultaneously by two independent groups, that of Axel Ullrich at Genentech (13) and that of William J. Rutter at UCSF (14). Ullrich’s group solved the cDNA sequence of the IGF-I receptor the following year (15).
The gene for a mammalian related receptor (insulin receptor-related receptor or IRR) was identified in 1989 (20). No ligand for this receptor has been identified. The mouse IRR knockout has no phenotype, but the triple IR/IGF-IR/IRR knockout results in gonadal dysgenesis and male-to-female somatic sex reversal, providing the first glimpse of a function for this orphan receptor (21).
The insulin receptor, the IGF-I receptors and the IRR are members of the family of receptor tyrosine kinases (RTKs) (16). This family comprises in humans 59 members, grouped in 19 subfamilies depending on the architecture of the extracellular domains (Fig. 1).
Figure 1: The receptor tyrosine kinase family. The protein modules that comprise the extracellular domains are described on the right side. From ref. 27, adapted from ref. 16 with corrections and updates from multiple references and databases such as Pfam.
The 19 subfamilies shown are the following:
|1.ErbB (HER, EGF receptor), ErbB-2 (HER-2/Neu), ErbB-3 (HER-3), ErbB-4 (HER-4, Tyro-2)(ErbB-3 is a dead kinase)||11.Tie-1, Tek (Tie-2, angiopoietin receptor)|
|2.INSR, IGF-IR, IRRR||12.EphA1-8, B1-6|
|3.PDGFRa, PDGFRb, SCF1R (c-Kit), Flk-2||13.Ret (GDNF receptor)|
|4.VEGFR-1 (Flt-1), VEGFR-2 (Flk-1, KDR) VEGFR-3 (Flt-4)||14. Ryk|
|5. FGFR-1- 4||15. DDR-1, DDR-2|
|6.TRKA (NGF receptor), TRKB (BDNF receptor),TRKC (NT-3 receptor)||16. Ros|
|7. Ror1, Ror2||17. AATYK|
|8. MusK||18.ALK, LTK|
|9.Met (HGF/scatter factor receptor), Ron, Sea||19.PTK-7, KLG, CCK-4|
|10.AxI, Mer (Eyk), Nyk, Rse (Tyro-3)|
The RTKs shown in bold letters have been implicated in malignancies.
The extracellular domains use a variety of protein modules to compose specific binding sites for the specific ligands of a given family (Fig. 1 and table 1). The intracellular portion contains a tyrosine kinase domain that phosphorylates intracellular protein substrates on tyrosine side chains.
Most of the RTKs are made of single polypeptide chains that cross the cell membrane once, with the exception of the insulin/IGF-I/IRR subgroup that are made of covalent disulfide-bonded dimers made of two extracellular α-subunits and two transmembrane b-subunits (Fig. 2).
Figure 2: Insulin receptor modular structure. Left: schematic structure of the a2b2 insulin receptor dimer. The left half shows the exon-intron boundaries. The right half shows the boundaries of domains defined by secondary structure prediction (ref. 25). L1 and L2: large domains 1 and 2; CR: cysteine-rich domain; FnIII1-3: fibronectin type III domains 1-3; ID: insert domain; CT peptide: C-terminal domain (involved in binding site 1); TM: transmembrane domain; JM: juxtamembrane domain; TK: tyrosine kinase domain. Right: 3-D structure of the extracellular domains (PDB file 2DTG) and the tyrosine kinase domains (PDB file 1IR3) of the insulin receptor. One ab half of the extracellular domain is shown in green, the other one in blue. The RTK domains are shown in corresponding colors.
However, all RTKs are dimeric in the active state due to either ligand-induced dimerization or stabilization of preformed noncovalent dimers.
The insulin receptor has a modular structure encoded by a gene with 22 exons and 21 introns (Fig. 2). The short exon 11 is alternatively spliced, resulting in two isoforms (A and B) that differ slightly in affinity for insulin (22). The B isoform binds the IGFs with at least 100 times lower affinity than insulin, while the A isoform has significantly higher affinity than the B isoform for IGF-I and especially IGF-II (23). The IGF-I receptor binds IGF-II with a lower affinity than IGF-I and insulin with a 500-fold lower affinity.
The receptors are synthesized as single chain preproreceptors that are processed, glycosylated, folded and dimerized to yield the mature a2b2 receptor.
In cells expressing both insulin and IGF-I receptors, hybrid receptors are formed consisting of one half of each (24). Their physiological role is unknown but their binding properties resemble those of IGF-I receptors.
Comparative sequence analysis of the insulin/IGF-I receptors and the related EGF receptor had led Mona Bajaj in Tom Blundell’s group at Birkbeck College (25) to suggest that the N-terminal half of the a-subunits consists of two large homologous globular domains, L1 and L2, separated by a cysteine-rich region predicted to consist of a series of disulfide-linked modules (Fig. 2). These predictions were confirmed by the determination of the crystal structure of the insulin receptor extracellular domain and the N-terminal module of the IGF-I receptor (see below). The C-terminal portion of the extracellular part of the receptor was predicted to consist of three fibronectin type III (FnIII) domains (Fig. 2). The second FnIII domain contains a large insert domain of unknown structure containing the site of cleavage between a- and b-subunits. The intracellular portion of the b-subunit contains the kinase domain flanked by two regulatory regions, a juxtamembrane region involved in docking insulin receptor substrates (IRS) 1-4 and Shc as well as in receptor internalization, and a C-terminal tail.
The crystal structure of the unliganded insulin receptor ectodomain was solved in 2006 at 3.8 Å resolution by Colin Ward’s group at the CSIRO in Melbourne, Australia (17). The structure is depicted in Fig. 3.
Figure 3: 3-D structure of the insulin receptor extracellular domain. The X-ray structure of the insulin receptor extracellular domain is shown (PDB file 2DTG). One ab half of the extracellular domain is shown in green, the other one in blue.
The receptor ectodomain was crystallized in the absence of insulin, but as a complex with four Fabs from monoclonal antibodies 83-7 and 83-14, not shown in Fig. 3, and a fragment of an insulin mimetic peptide, invisible in the structure. Each monomer of the IR adopts a folded-over conformation, making an “inverted V” arrangement relative to the cell membrane; one leg made of the three FnIII domains stems from the membrane (the a-subunit C-terminal portion being superimposed linearly on top of the extracellular part of the b-subunit), while the other leg is formed by the L1-CR-L2 domains. The two monomers are disposed in an antiparallel symmetry consistent with the model proposed by Pierre De Meyts at Novo Nordisk A/S in 1994 (26). A critical element of the binding mechanism is unfortunately invisible due to a disordered structure, the insert domain (ID) in FnIII-2 that contains the a-b cleavage site, the CT domain that is part of binding site 1 (see section on how insulin binds to its receptor) and the triplet of a-b disulfide bonds Cys682, Cys 683 and Cys685.
A crystal structure of the L1-CR-L2 domain of the IGF-I receptor shows a very similar arrangement of this part to that of the insulin receptor (18).
The structures of the tyrosine kinase domain of the insulin and IGF-I receptors, both in the inactive and in the active states have been determined by Stevan Hubbard at New York University (Fig. 4) (for review see ref. 16).
Figure 4: Mechanism of insulin receptor tyrosine kinase (IRTK) activation. The X-ray structures of the inactive (left, PDB file 1IRK)) and activated (right, PDB file 1IR3) IRTK are shown. The activated structure on the right is bound to an ATP analogue, adenylyl imidodiphosphate (AMP-PNP) as well as a peptide substrate YMXM and magnesium. The figure illustrates the autoinhibition mechanism, whereby Tyr (Y) 1162 – one of the three tyrosines (Y1158, Y1162 and Y1163) that are autophosphorylated in the activation loop (in white) in response to insulin – is bound in the active site, hydrogen-bonded to a conserved Asp (D) 1132 residue in the catalytic loop (a). Y1162 in effect competes with protein substrates before autophosphorylation. In the activated state (b), the activation loop is tris-phosphorylated and moves out of the active site. Y1163 becomes hydrogen-bonded to a conserved R1155 residue in the beginning of the activation loop, which stabilizes the repositioned loop. From ref. 28, adapted from ref. 16.
They show the bilobed structure typical of protein kinases with the active site as a cleft in the middle, and shed light on the mechanism of kinase activation with an autoinhibitory loop being moved out of the active site when phosphorylated on three tyrosyle residues.
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The available crystal structure of the insulin receptor extracellular domain (1) and that of the L1-CR-L2 N-terminal domain of the IGF-I receptor (2) unfortunately do not contain the bound ligand.
The available crystal structure of the insulin receptor extracellular domain (1) and that of the L1-CR-L2 N-terminal domain of the IGF-I receptor (2) unfortunately do not contain the bound ligand.
However, a wealth of information on the mechanism of ligand binding to the insulin and IGF-I receptors has been gathered from a variety of biochemical approaches (for review see 3-6), including studies of the kinetics of radioligand binding (8), photoaffinity crosslinking of ligands to the receptors (9-12), and alanine (or other amino acids) scanning mutagenesis of both the ligands (4, 12-14) and receptors (15-18).
by Pierre De Meyts, MD, PHD, F.A.C.E.
From these studies plausible models have emerged (8, 19). The De Meyts 1994 bivalent crosslinking binding model (8, Fig. 1) was supported by the recent crystal structure of the insulin receptor (1) and by mathematical modelling (20,21), explaining the complex ligand binding kinetics of the insulin and IGF-I receptors which exhibit negative cooperativity, whereby the binding of a second ligand molecule weakens the binding of the first bound molecule by accelerating its dissociation from the receptor.
Figure 1: The insulin receptor symmetrical bivalent crosslinking model. Both a-subunits amino-terminal pairs of binding sites (1 and 2) are represented in asymmetrical anti-parallel arrangement. Insulin has two binding sites, 1 and 2, that each bind to one of the receptor binding sites 1 and 2. The first insulin molecule (shown as a green cone) binds with high affinity by crosslinking receptor sites 1 and 2. On partial dissociation of the first bound molecule, a second insulin molecule can crosslink the remaining sites 1 and 2, causing complete dissociation of the first bound insulin /accelerated dissociation, which is a hallmark of negative cooperativity). At high insulin concentrations, monovalent binding of two extra insulin molecules saturates the leftover sites 1 and 2 and stabilizes the binding of the pre-bound insulin in the first crosslink, explaining the bell-shaped curve for negative cooperativity. From ref. 3, see references 8 and 20 for more complete explanation.
According to the current model for insulin binding to its receptor, insulin has two binding surfaces (site 1 or “classical binding surface”) and site 2 (or “novel binding surface”) that bind each to two distinct sites (site 1 and site 2′, or site 1′ and site 2) on the two a-subunits of the insulin receptor (Fig. 2 and 3), and thereby crosslink the two receptor halves into a high affinity, slowly dissociating complex. The alternative crosslinking at sites 1 and 2′, and sites 1′ and 2, results in the observed negative cooperativity.
Figure 2: Insulin binding site 1 and 2. The two insulin sites that bind to the insulin receptor have been mapped by alanine scanning mutagenesis (refs. 12 and 4). Site 1 (also known as “classical binding surface”) is shown in light green and comprises residues Gly A1, Ile A2, Val A3, Gln A5, Tyr A19, Asn A21, Val B12, Tyr B16, Gly B23, Phe B24, Phe B25 and Tyr B26. It overlaps with the insulin surface involved in dimerization (see Fig. 5). Site 2 is shown in blue and comprises Ser A12, Leu A13, Glu A17, His B10, Glu B13 and Leu B17. It overlaps with the insulin surface involved in hexamerization (see Fig. 5). Backbone is shown in dark green. PDB file 9INS.
Figure 3: Insulin binding sites 1 and 2. See legend of Figure 2 for description.
Site 1 of insulin (Fig. 2) was already mapped in the 70’s by evaluation of conserved residues in various animal insulins (22,23) and confirmed more recently by alanine scanning mutagenesis (4, 12). It overlaps partially with the insulin surface involved in dimerization (see section on the insulin peptide family). See legend of Fig. 2 for specification of amino acids involved.
Site 2 of insulin (Fig. 2) was mapped more recently by alanine scanning mutagenesis (4). It overlaps partially with the insulin surface involved in hexamerization (see section on the insulin peptide family). See legend of Fig. 2 for specification of amino acids involved.
Thus, it is not surprising that a small globular protein like insulin uses partially the same domains for receptor binding and for self-aggregation.
IGF-I uses very similar surfaces as those on insulin for binding to the IGF-I receptor, as shown by site directed mutagenesis (for review see ref. 14) (see Fig. 4 and 5 for details).
Figure 4: IGF-I binding sites 1 and 2. The two IGF-I binding sites that bind to the IGF-I receptor have been partially mapped by various mutagenesis approaches (see ref. 14). Site 1 is shown in light green and comprises Ala 8, Phe 23, Tyr 24, Tyr 31, Val 44, Met 59, Tyr 60 and Ala 62. In addition, Arg 36 and Arg 37 which are missing from the crystal structure are depicted by two spheres. Site 2 comprises Glu 9, Asp 12, Phe 16, leu 54 and Glu 58. PDB file 1GZR.
Figure 5: IGF-I binding sites 1 and 2. See legend of Figure 4 for description.
In addition, the permanent C-peptide of IGF-I, absent on insulin, is involved in binding to the IGF-I receptor, binding to residues in the cysteine-rich region of the receptor (3,5). The low affinity of insulin for the IGF-I receptor is due to the lack of this C-peptide domain, while the low affinity of IGF-I for the insulin receptor is due to 4 substitutions in site 1 (24).
The ligand binding sites on the insulin receptor have been mapped by a combination of site-directed mutagenesis, construction of chimeric receptors with the IGF-I receptor, and alanine-scanning mutagenesis (for review see ref. 3 and other refs quoted above).
Site 1 of the insulin receptor is made of a combination of the central b-sheet of the L1 domain and the C-terminal peptide from the insert domain, binding in trans to complete the binding site (25, for review see ref. 6) (Fig. 6).
Figure 6: Insulin receptor with binding sites 1 and 2. The 3-D structure of the insulin receptor extracellular domain (PDB file 2DTG) is shown. One ab half is shown in light blue, the other one in green. Binding sites 1 and 2 have been mapped by alanine scanning (refs. 15, 19, 26). The insulin receptor backbone of one ab half is shown in light blue, the other in dark green. Sites 1 and 1′ are shown as CPK spheres in light green, sites 2 and 2´ in blue.
In site 1 of the IGF-IR, the homologous domain is extended to a part of the cysteine-rich domain that binds the C-domain of IGF-I (18).
Site 2 of the insulin receptor is less well defined but comprises the loops at the junction of FnIII-1 and-2 (for review see ref. 6) (Fig. 6).
The see-saw mechanism whereby insulin alternatively crosslinks sites 1 and 2′ and sites 1′ and 2 (“harmonic oscillator”) is shown in detail and explained in Fig. 6.
Figure 7: How insulin binds to its receptor. The domains of the insulin receptor that contain binding sites 1 (1′) and 2 (2′) have been “extracted” from the 3D structure. The backbones of the L1 domain of one ab half (top right) and of the FnIII-1 and N-terminal part of the FnIII-2 domains (bottom left) are shown in dark green. The backbone of the corresponding parts of the second ab half are shown in light blue. The binding sites 1 and 1´are shown as CPK spheres in light green, sites 2 and 2′ in blue. Site 1 is made of residues Asp 12, Arg 14, Asn 15, Gln 34, Leu 36, Leu 37, Phe 64, Leu 87, Phe 89, Asn 90, Tyr 91, Glu 97, Glu 120 and Lys 121. Site 2 is made of residues Lys 484, Leu 552, Asp 591, Ile 602, Lys 616, Asp 620 and Pro 621.
The backbone of insulin is shown in dark green, site 1 as CPK spheres in light green, site 2 in blue.
The Cys 524 disulphide bond that links the two receptor halves is shown in yellow. Lys 460 on each receptor half (which plays a role in negative cooperativity, see ref. 6) is shown as CPK spheres in dark blue.
See insulin move into its binding sites.
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The insulin receptor (IR) and the IGF-I receptor (IGF-IR) utilize common signalling pathways to mediate a broad spectrum of "metabolic" and "mitogenic" responses .
The insulin receptor (IR) and the IGF-I receptor (IGF-IR) utilize common signalling pathways to mediate a broad spectrum of “metabolic” and “mitogenic” responses (1 – 5).
This signalling network is also engaged by other receptor tyrosine kinases (RTKs) (6).
by Pierre De Meyts, MD, PHD, F.A.C.E.
That insulin and IGF-I receptors have distinct physiological functions is exemplified by the distinct phenotypes of IR versus IGF-IR knockout (KO) mice (7). IR KO mice are born with almost normal size but die within a few days from acute ketoacidosis, while IGF-IR KO mice are born small and die quickly from asphyxia due to underdevelopment of thoracic muscles. This downstream specificity is not inherent to the receptor structures since it has been shown that the IR and the IGF-IR can exert each other’s function in cases where the other receptor is absent. Thus, the IGF-IR can induce stimulation of glucose transport and glycogen synthesis, typical insulin metabolic effects, in fibroblasts from IR KO mice (8). Reciprocally, the IR stimulates thymidine incorporation and cell growth in a T-cell lymphoma line devoid of IGF-I receptors (9). There is therefore a paradox in having specific biological endpoints through ligand-specific receptors while the downstream signalling networks appear to be largely overlapping (1,10,11). There is currently no precise solution to this conundrum, except to state that the cellular context and the differential “combinatorial” use of the components of a common network, rather than intrinsic receptor activity, appear to be major determinants of biological “mitogenic” versus “metabolic” endpoints (1, 10, 11). A system biology approach to the modelling of complex signalling networks appears to be the way of the future in order to unravel this complexity.
A detailed description of the IR and IGF-IR signalling network is beyond the scope of this brief review, see refs. 1-5 for further reading.
Like other receptor tyrosine kinases, the IR and IGF-IR are activated upon ligand binding by transphosphorylation of specific tyrosyle residues in the inhibitory loop of the kinase domain (Fig. 1), making the loop move out of the active site (12).
Figure 1: Mechanism of insulin receptor tyrosine kinase (IRTK) activation. The X-ray structures of the inactive (left, PDB file 1IRK)) and activated (right, PDB file 1IR3) IRTK are shown. The activated structure on the right is bound to an ATP analogue, adenylyl imidodiphosphate (AMP-PNP) as well as a peptide substrate YMXM and magnesium. The figure illustrates the autoinhibition mechanism, whereby Tyr (Y) 1162 – one of the three tyrosines (Y1158, Y1162 and Y1163) that are autophosphorylated in the activation loop (in white) in response to insulin – is bound in the active site, hydrogen-bonded to a conserved Asp (D) 1132 residue in the catalytic loop (a). Y1162 in effect competes with protein substrates before autophosphorylation. In the activated state (b), the activation loop is tris-phosphorylated and moves out of the active site. Y1163 becomes hydrogen-bonded to a conserved R1155 residue in the beginning of the activation loop, which stabilizes the repositioned loop. From ref. 28, adapted from ref. 16.
Unlike other RTKs, the IR and IGF-IR intracellular domains do not engage directly SH2 domain-containing signalling elements of the downstream cascades, but bind through a phosphorylated tyrosyle in the juxtamembrane domain a variety of docking proteins that get phosphorylated at multiple SH2-domain binding sites (1-4). These docking proteins comprise among others IRS-1, -2 -3- and -4 (13), Shc (14), Gab1 and Cbl.
The two main canonical signalling pathways engaged by both IR and IGF-IR are the phosphoinositide 3-kinase pathway (PI3K)/Akt (15) and Ras/extracellular signal-regulated kinase (ERK or MAPK) (16) pathways (Fig. 2). The PI3K/Akt pathway appears to be involved in metabolic events such as GLUT4 translocation, but also in mitogenic events in cooperation with the ERK pathway.
Below animation shows the intracellular signalling pathways of insulin and IGF-I receptors.
The main signalling pathways activated by insulin and IGF-I (the MAP kinase or MEK cascade on the right, the PI 3-kinase on the left) are shown together with their main biological end-points.
IRS: Insulin receptor substrate.
SHC: Src homology 2-containing protein.
Grb2: Growth factor receptor-bound protein 2.
SOS: Son of Sevenless.
Ras: A small GTPase, named after Rat Sarcoma.
RAF: Not an abbreviation, a MAP kinase kinase kinase.
MEK: MAP kinase/ERK kinase, MAP kinase kinase.
ERK: Extracellular signal-regulated kinase.
P90 RSK: Ribosomal Protein S6 kinase.
PI3K: Phosphatidylinositol 3- kinase.
PIP2: Phosphatidylinositol 3,4 bisphosphate.
PIP3: Phosphatidylinositol 3,4,5 trisphosphate.
PDK: 3-phosphoinositide – dependent protein kinase.
Akt: Not an abbreviation. = Protein kinase B (PKB).
FOXO: Forkhead box O.
mTOR: Mammalian target of rapamycin.
GLUT4. Glucose transporter 4.
PTP1B: Protein tyrosine phosphatase 1B.
PTEN: Phosphatase and tensin homologue deleted on chromosome 10.
GSK3: Glycogen synthase kinase-3.
Other notable elements of the downstream signalling pathways are FoxO1 (a transcription factor downstream of Akt that is involved in cell cycle regulation, oxidative stress resistance, apoptosis and metabolism e.g. gluconeogenesis (17)) and mTOR (downstream of Akt) and p90RSK (downstream of ERK), that together regulate protein synthesis (3).
Negative regulation of IR and IGF-IR signalling occurs through phosphatases such as PTP1B, SOCS proteins, serine phosphorylation of IRS proteins and receptor downregulation/endocytosis, as well as negative regulation of PI3K by the phosphatase PTEN (3).
In summary, while physiologically insulin is more a metabolic hormone and IGFs are growth factors, both receptors are intrinsically capable of mitogenic and metabolic signalling, through largely overlapping signalling networks. The molecular basis of their signalling specificity is still poorly understood. However it is clear that at high concentrations insulin can perfectly substitute for IGF-I in cell culture through the IGF-IR, as well as mediating some mitogenic effects through its own receptor.
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An increase in the number of cells growing in cell culture is the result of two opposing effects: an increase in the number of cells that traverse the cell cycle and divide into two daughter cells (mitosis), or a decrease in the number of cells that die, principally through
An increase in the number of cells growing in cell culture is the result of two opposing effects: an increase in the number of cells that traverse the cell cycle and divide into two daughter cells (mitosis), or a decrease in the number of cells that die, principally through programmed cell death (apoptosis), or both.
by Pierre De Meyts, MD, PHD, F.A.C.E.
Insulin and IGF-I are both capable of facilitating cell progression through the cell cycle, and of inhibiting apoptotic mechanisms.
In this section we will review the mechanisms that control the cell cycle, while apoptosis will be discussed in another section.
Growing cells go through four successive phases (1,2) (Fig. 1):
– G1 (Gap1) where they get committed to grow and ribosomal biogenesis occurs,
– S, where they synthesize DNA and chromosomes replicate,
– G2 (Gap2) where they prepare to divide, and
– M (mitosis), where they divide.
Figure 1: The cell cycle and its regulation. The various phases of the cell cycle are shown below as well as the various activators and inhibitors. See text for explanation.
The phases before M are collectively known as “interphase”. Cells not actively dividing are in a resting or quiescent state called G0, from which they enter into G1 under appropriate growth stimuli. The transitions most tightly regulated by IGFs are G0/G1 and G1/S.
Much of what we know about the workings of the cell cycle is through the work of Sir Paul M. Nurse (born 1949) and Sir Timothy (“Tim”) Hunt (born 1943), two British yeast biologists, and Leland H. Hartwell (born 1939), am American biologist working with sea urchin eggs. They won the Nobel Prize in Physiology and Medicine in 2001.
They showed that cellular processes required for cells to successfully replicate and divide are driven by the sequential activation and inactivation of a family of cyclin dependent kinases (CDKs). These form bipartite complexes with different cyclins (1,2). Activation is driven predominately by the periodic expression of the cyclin subunit and requires activating phosphorylation of the kinase subunit. Inactivation is controlled by inhibitory phosphorylation of the kinase subunit, by ubiquitin-mediated degradation of the cyclin subunit and by interaction of the complex with small inhibitory proteins (1-3).
A detailed description of the complex regulation of the cell cycle is beyond the scope of this brief review. A clever minimization of this complex machinery has shown that basic control of the eukaryotic cell cycle is a CDK oscillator that acts as the primary organizer of the cell cycle, imposing timing and directionality to a system of two CDK activity thresholds that define independent cell cycle phases (4).
The cell cycle is also negatively regulated by several CDK inhibitors that are in fact tumor suppressors (5): retinoblastoma (Rb) protein, the INK4 family of proteins, p21cip1 and p27kip1(Fig. 1).
The way the IGF-I receptor signalling system is involved in the regulation of the cell cycle has been thoroughly reviewed by Dupont et al. (5). The PI3K/Akt pathway and the MAPK/ERK1/2 pathways are involved to variable degrees depending on the cell type (5).
Early work on chick embryo fibroblasts compared the effect of insulin with that of serum on confluent chick embryo fibroblasts (6). The authors found that the total cell population that is stimulated by insulin or serum to enter S and G2 is comparable initially (within 15 hours). However, serum-stimulated cells entered S later than insulin-stimulated cells, and had a shorter residence time in S and G2. They therefore divided earlier than insulin-stimulated cells. Insulin stimulated only part of the cell population to divide. These observations together with others suggested that insulin has a “permissive” role that is additive to other growth factors.
Further work from the lab of W. Jackson Pledger at University of North Carolina showed that human serum contains two sets of growth factors that function synergistically to promote cell growth through the G0-G1 traverse (7-9). “Competence factors” such as platelet-derived growth factor or fibroblast growth factor commit cells to enter the division cycle, and render them competent to respond to “progression factors” contained in platelet-poor plasma such as IGF-I (or its substitute insulin at high concentrations) or epidermal growth factor (EGF), up to a growth arrest point in mid Go/G1 termed the V point. In addition, IGF-I mediated the traverse from the V-point to the S-phase (9).
More recent work has worked some of the details of the components of the cell cycle affected by IGFs (for review see ref. 5). These include increase in D-type cyclins, hyperphosphorylation of Rb, release of the transcritption factor E2F, generation of cyclin E which then binds to CDK2 and leads to G1/S phase progression.
IGFs also regulate the CDK inhibitors (CDKIs). P27 transcription is downregulated through phosphorylation-dependent inhibition of FOXO-1 as well as post-transcriptionally (5).
In addition to its actions at the G1/S transition, IGF-I also affects the duration of G2 and the timely progression through G2/M phases, in synergy with estrogens (5).
More recently, a role for IGFs and insulin in regulating the cell cycle inhibitor cyclin G2 has been unravelled by the De Meyts group (10-12). Cyclin G2 is an unconventional cyclin highly expressed in postmitotic cells (13, 14). Unlike classical cyclins that promote cell cycle progression, cyclin G2 causes cell cycle arrest at the G1/S transition, not by associating with a CDK, but by associating with the phosphatase PP2A, thereby altering the activity of PP2A (15, Fig. 1). Cyclin G2 is markedly downregulated by insulin, insulin analogues and IGF-I in L6 myoblasts overexpressing the insulin receptor (10, 11), as well as in several other cell types (16). Overexpression of cyclin G2 inhibited cell proliferation induced by insulin, insulin analogues and IGF-I (11,12).
In summary, insulin-like growth factors (mimicked by high insulin in cell culture) play an important permissive role in the progression of cells through the cell cycle once the cells have been committed to grow by competence factors such as FGF. Such factors are probably provided by many cell lines in an autocrine fashion, explaining why insulin is capable of promoting the growth of so many cell lines without addition of other growth factors.
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11. Svendsen AM, Sajid W, Hald J, Rescan C, Horne MC and De Meyts P. Cell cycle regulation in the mitogenic effects of insulin, insulin analogues and insulin-like growth factor-I (IGF-I). Diabetes 59 suppl.1:A379-A380 (2010)
12. Svendsen AM. Molecular basis for the mitogenic effects of insulin and insulin analogues. PhD thesisUniversity of Copenhagen (2010)
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An increase in the number of cells growing in cell culture is the result of two opposing effects: an increase in the number of cells that traverse the cell cycle and divide into two daughter cells (mitosis), or a decrease in the number of cells that die according to differen
An increase in the number of cells growing in cell culture is the result of two opposing effects: an increase in the number of cells that traverse the cell cycle and divide into two daughter cells (mitosis), or a decrease in the number of cells that die according to different modalities, the most prominent one being apoptosis (1), or both.
by Pierre De Meyts, MD, PHD, F.A.C.E.
Insulin and IGF-I are both capable of facilitating cell progression through the cell cycle, and of inhibiting apoptotic mechanisms.
In this section we will review the mechanisms that control apoptosis, while regulation of the cell cycle is discussed in another section.
Although there were earlier descriptions of some of the cell morphological changes associated with programmed cell death, the term apoptosis was first used in the seminal paper published in the British Journal of Cancer in 1972 (2), by John Foxton Ross Kerr (born 1934), Professor of Pathology at the University of Queensland (Australia), Alastair A. Currie (1921-1994), Professor of Pathology at the University of Aberdeen (Scotland), where Kerr was on sabbatical, and his graduate student Andrew H. Wyllie (later Professor of Pathology at the University of Cambridge). In 2002, the Nobel Prize in Physiology and Medicine was given to Sydney Brenner (born 1927), a South African biologist at the Laboratory of Molecular Biology in Cambridge (UK), John E. Sulston (born 1942), a British biologist at University of Cambridge (UK), and to H. Robert Horwitz (born 1947), biologist at MIT in Boston (USA), for their work on the genetic regulation of organ development and programmed cell death in the worm Caenorhabditis Elegans.
This mechanism of controlled cell deletion is common to all multicellular organisms. Cells undergo marked morphological changes: blebbing, cell shrinkage, nuclear fragmentation, chromatin condensation and chromosomal DNA fragmentation. Cells eventually split into small closed entities (apoptotic bodies) that can be phagocytosed by other cells, preventing the release of toxic cellular substances that may cause necrosis. Apoptosis is triggered by a variety of environmental stimuli, both physiological and pathological including stress. The intracellular mechanisms involved in apoptosis are very complex (Fig. 1); while most proteins involved in the apoptotic network are known, much work remains to be done to unravel their interactions.
Figure 1: Mechanisms of apoptosis. Below you can see a schematic view of the three main apoptotic pathways: the intrinsic pathway, the extrinsic pathway and the granzyme pathway. See text for explanation. Adapted from ref. 2.
We will here only briefly summarize the salient features of the apoptotic process, see ref. 3 for more detailed review. Some cells apoptose through extrinsic pathways that involve death receptors such as Fas (fatty acid synthetase) or TNF (tumour necrosis factor) receptors; others have a default death pathway that must be blocked by a survival factor such as a hormone or a growth factor (3). Serum withdrawal is a classic way to initiate this pathway. In the end, apoptosis is an energy-dependent process that involves the activation of a group of cystine proteases called “caspases” and involves a complex cascade of events that link the initiating stimuli to the death of the cell (3). The two main regulatory mechanisms used by extracellular signals are either by targeting mitochondrial functionality (intrinsic pathway) or by directly transducing the signal via adaptor proteins to the apoptotic mechanisms (extrinsic pathway). There is an additional pathway mediating T-cell-induced cytotoxixity and perforin-granzyme (a serine protease) A or B-dependent killing of the cell (Fig. 1).
The mitochondrial pathway involves an increased mitochondrial permeability resulting in release in the cytosol of cytochrome c and SMACS (small mitochondria-derived activators of caspases) that bind to and desactivate IAPs (inhibitors of apoptosis proteins). IAPs repress the caspases. Mitochondrial permeability is regulated positively or negatively by 25 members of the Bcl-2 family of proteins (4), under the control of the tumor suppressor proteinp53.
Cytochrome c and ATP released from the mitochondrial intermembrane space form the apoptosome consisting of ATP, apoptosis protease-activating factor (APAF)-1, cytochrome c and caspase-9, which becomes activated by autoproteolytic cleavage and activates the execution caspase-3.-6 and -7, which leads to th collapse of cellular infrastructure (7).
The extrinsic pathway involves binding of trimeric ligands to their receptors which cluster (FasL to the FasR or TNFa to the TNR1). Binding of FasL to FasR recruits the adapter protein FADD (Fas-associated death domain), while binding of TNFa to the TNR1 recruits the adapter protein TRADD (TNF receptor-associated death domain). TRADD then recruits FADD and RIP (receptor-interacting protein). FADD forms a death-inducing signalling complex (DISC) with procaspase-8 resulting in its autocatalytic activation (3) and triggering of the “execution phase”.
The extrinsic, intrinsic and granzyme B pathways converge on the same terminal “execution” pathway, that is initiated by the cleavage of caspase-3 by caspases 8, 9 or 10. The granzyme A pathway activates a parallel, caspase-independent pathway via single stranded DNA damage (5).
There are many more players in the apoptosis cascades, see tables 1-4 in ref. 3.
IGF-I is a potent anti-apoptotic growth factor at low concentrations in multiple cell types (6,7). This anti-apoptotic effect involves both the PI-3K and MAPK/ERK1/2 pathways (Fig. 2) as shown by the use of specific inhibitors in serum-deprived PC12 cells (6), but other pathways also appear to be involved (for review, see ref. 7).
IGF-I anti-apoptotic signalling. Below you can see schematic views of the pathways whereby IGF-I inhibits apoptosis. See text and refs. 5 and 6 for explanation.
BAD: Bcl-2-associated death promoter.
CREB: cAMP response element-binding protein.
Bcl: B cell leukemia protein-
Mcl: Myeloid cell leukemia protein.
Many of the antiapoptotic actions of IGF-I appear to be through the regulation of mitochondrial membrane permeability via Bcl-2 proteins like Bad (7) via Akt. It also appears capable of inhibiting the extrinsic apoptotic pathway via regulation of death-inducing receptors (7). These properties may hold therapeutic potential for hypoxic/ischemic brain injury, amyotrophic lateral sclerosis, Huntington disease, Alzheimer disease and cancer (7).
Numerous papers indicate that insulin exerts also a potent anti-apoptotic role in a variety of cell types (8-17). The experimental conditions (e.g. using high concentrations of insulin and IGF-I, and no dose-response curve) do not always allow to conclude whether the insulin effect is through the insulin receptor or the IGF-I receptor. In a few carefully controlled studies using native cells or insulin receptor-transfected cells (e.g. 11,12,16), the authors established unequivocally that insulin at physiological concentrations has anti-apoptotic effects through the insulin receptor.
The PI3K pathway appears to play a prominent role in this effect.
In a recent intriguing paper (8), the group of C. Ronald Kahn at the Joslin Diabetes Center in Boston showed that brown adipocytes from mice with both the insulin receptor and IGF-I receptor knocked out were resistant to apoptosis induced by serum deprivation. Sensitivity to apoptosis was restored by knocking in either receptor, which was then prevented by the appropriate ligand. These data suggested that the unoccupied insulin and IGF-I receptors are proapoptotic (in a kinase independent fashion) while the ligand-occupied receptors are antiapoptotic.
Finally we should mention that autophagy or autophagocytosis (a process involving the lysosomal degradation of a cell’s own components), if dysregulated, can also lead to cell death (18). A recent study suggests that this process is also inhibited by IGF-I (19).
In summary, both IGF-I and insulin have antiapoptotic effects on multiple cell lines. Both the IGF-I and insulin receptors are capable of mediating this effect. Insulin at high concentrations in cell culture will thus protect cells against apoptosis through both the IGF-I receptor and the insulin receptor. Multiple signalling pathways are implicated but the PI3K pathway appears to play a prominent role.
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