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For the graph: a)Describe the graph: b) Describe the data: c) Interpret the data. Describe the statistics that are shown and what you can infer from them:

For the graph: a)Describe the graph: b) Describe the data: c) Interpret the data. Describe the statistics that are shown and what you can infer from them:

Human Anatomy & Physiology (11th Edition)
Human Anatomy & Physiology (11th Edition)
11th Edition
ISBN:9780134580999
Author:Elaine N. Marieb, Katja N. Hoehn
Publisher:Elaine N. Marieb, Katja N. Hoehn
Chapter1: The Human Body: An Orientation
Section: Chapter Questions
Problem 1RQ: The correct sequence of levels forming the structural hierarchy is A. (a) organ, organ system,...
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For the graph:

a)Describe the graph:

b) Describe the data:

c) Interpret the data. Describe the statistics that are shown and what you can infer from them:

 

## Figure 1 Analysis ### Overview Figure 1 presents data from an experiment involving various engineered strains of *E. coli* grown in bioreactors. The experiment measured two key parameters over a period of time: - **Graph A:** Levels of Taxadiene (a precursor for taxol) - **Graph B:** Cell growth (measured in OD600 nm) Each graph tracks three different strains: Strain 22, Strain 17, and Strain 26. --- ### Detailed Description #### Graph A: Taxadiene Production - **Axes:** The x-axis represents time (hours), while the y-axis displays the concentration of Taxadiene (mg/L). - **Data:** - Strain 22 shows a rapid increase in Taxadiene production, reaching its peak around 120 hours. - Strain 17 displays moderate growth with less pronounced Taxadiene production. - Strain 26 exhibits minimal Taxadiene production over time. #### Graph B: Cell Growth - **Axes:** The x-axis shows time (hours), and the y-axis indicates cell growth measured as optical density at 600 nm (OD600 nm). - **Data:** - Strain 22 demonstrates substantial cell growth, peaking at 120 hours. - Strain 17 shows moderate growth, following a similar trend to its Taxadiene production. - Strain 26 has the least growth, consistent with its low Taxadiene levels. --- ### Interpretation - **Significance:** The differences in Taxadiene production and cell growth between strains suggest varying abilities of the strains to synthesize Taxadiene. - **Statistical Analysis:** While no statistical analysis is provided, employing statistical tests such as ANOVA could determine the significance of differences observed in the data. - **Recommendations:** Including error bars and replicates would enhance data reliability and interpretation. The analysis highlights how genetic engineering can influence metabolic pathways in microorganisms, leading to potential applications in bioproduction industries.
Transcribed Image Text:## Figure 1 Analysis ### Overview Figure 1 presents data from an experiment involving various engineered strains of *E. coli* grown in bioreactors. The experiment measured two key parameters over a period of time: - **Graph A:** Levels of Taxadiene (a precursor for taxol) - **Graph B:** Cell growth (measured in OD600 nm) Each graph tracks three different strains: Strain 22, Strain 17, and Strain 26. --- ### Detailed Description #### Graph A: Taxadiene Production - **Axes:** The x-axis represents time (hours), while the y-axis displays the concentration of Taxadiene (mg/L). - **Data:** - Strain 22 shows a rapid increase in Taxadiene production, reaching its peak around 120 hours. - Strain 17 displays moderate growth with less pronounced Taxadiene production. - Strain 26 exhibits minimal Taxadiene production over time. #### Graph B: Cell Growth - **Axes:** The x-axis shows time (hours), and the y-axis indicates cell growth measured as optical density at 600 nm (OD600 nm). - **Data:** - Strain 22 demonstrates substantial cell growth, peaking at 120 hours. - Strain 17 shows moderate growth, following a similar trend to its Taxadiene production. - Strain 26 has the least growth, consistent with its low Taxadiene levels. --- ### Interpretation - **Significance:** The differences in Taxadiene production and cell growth between strains suggest varying abilities of the strains to synthesize Taxadiene. - **Statistical Analysis:** While no statistical analysis is provided, employing statistical tests such as ANOVA could determine the significance of differences observed in the data. - **Recommendations:** Including error bars and replicates would enhance data reliability and interpretation. The analysis highlights how genetic engineering can influence metabolic pathways in microorganisms, leading to potential applications in bioproduction industries.
**Figure 2.** New *E. coli* strains, strains 22, 12, and 37, were engineered to convert Taxadiene into a downstream precursor for Taxol. Strains were grown in a 1-L bioreactor for 24 hours then the concentration of the downstream product was measured. The data shows the mean measurements for 2 replicate bioreactors with the standard error. **1. For the graph:** a) **Describe the graph:** The graph is a bar chart that represents the conversion of taxadiene measured in mg/mL for three different *E. coli* strains: strain 17, strain 26, and strain 22. The y-axis indicates the conversion of taxadiene in mg/mL, ranging from 0 to 25 mg/mL. Each strain has a corresponding bar that shows the mean concentration of taxadiene converted, with error bars representing the standard error. b) **Describe the data:** - Strain 17 shows a conversion of approximately 10 mg/mL of taxadiene. - Strain 26 shows the highest conversion, approximately 22 mg/mL. - Strain 22 shows a conversion of approximately 8 mg/mL. c) **Interpret the data:** The data indicates that strain 26 is the most efficient in converting taxadiene into the downstream product, with the highest concentration of 22 mg/mL. Strain 22 is the least efficient, with a conversion rate of around 8 mg/mL. The standard error bars suggest variability in the measurements, but strain 26 consistently shows superior conversion performance compared to the other strains. This suggests that strain 26 may be the most promising candidate for large-scale production of the taxadiene-derived precursor for Taxol.
Transcribed Image Text:**Figure 2.** New *E. coli* strains, strains 22, 12, and 37, were engineered to convert Taxadiene into a downstream precursor for Taxol. Strains were grown in a 1-L bioreactor for 24 hours then the concentration of the downstream product was measured. The data shows the mean measurements for 2 replicate bioreactors with the standard error. **1. For the graph:** a) **Describe the graph:** The graph is a bar chart that represents the conversion of taxadiene measured in mg/mL for three different *E. coli* strains: strain 17, strain 26, and strain 22. The y-axis indicates the conversion of taxadiene in mg/mL, ranging from 0 to 25 mg/mL. Each strain has a corresponding bar that shows the mean concentration of taxadiene converted, with error bars representing the standard error. b) **Describe the data:** - Strain 17 shows a conversion of approximately 10 mg/mL of taxadiene. - Strain 26 shows the highest conversion, approximately 22 mg/mL. - Strain 22 shows a conversion of approximately 8 mg/mL. c) **Interpret the data:** The data indicates that strain 26 is the most efficient in converting taxadiene into the downstream product, with the highest concentration of 22 mg/mL. Strain 22 is the least efficient, with a conversion rate of around 8 mg/mL. The standard error bars suggest variability in the measurements, but strain 26 consistently shows superior conversion performance compared to the other strains. This suggests that strain 26 may be the most promising candidate for large-scale production of the taxadiene-derived precursor for Taxol.
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