Q.34 Structured William’s model
P. can describe the changes in intracellular components of the cell during growth
Q. can not describe the death phase of the cells
R. can describe the variation of size of cells in the different phases of growth
S. can not describe the lag period of growth
Which one of the following is CORRECT?
The Structured Williams model describes intracellular component changes and cell size variations during growth phases but cannot model cell death. Statement S is false as the model explicitly includes lag phase dynamics.
Option Analysis
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(A) P, Q and S only: Incorrect. The model shows lag phase where cells increase mass (S-component buildup) without division, directly contradicting S.
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(B) P, Q and R only: Correct. Williams model tracks P (synthetic ‘S’ vs structural ‘N’ compartments), R (largest cells during exponential phase), and lacks death phase modeling (Q true).
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(C) Q, R and S only: Incorrect. P is true; model fundamentally analyzes intracellular S/N ratios changing with growth rate.
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(D) P, R and S only: Incorrect. Model produces characteristic lag phase curves with initial mass increase, no division.
Structured Williams model revolutionizes bioprocess engineering by dividing cells into synthetic (S) and structural (N) compartments, explaining growth phase transitions critical for bioreactor design and microbial physiology studies.
Model Fundamentals
Cells contain S-portion (ribosomes, enzymes) fed by nutrients and N-portion (DNA, structural proteins) derived from S. Growth rate determines S/N ratio, producing phase-specific behaviors.
Growth Phase Predictions
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Lag phase: S-component accumulates, cells grow larger without division
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Exponential phase: Maximum S/N ratio, largest cells, rapid division
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Stationary phase: Balanced S/N, no net growth
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Death phase limitation: Model assumes constant nutrient, cannot describe viability loss
GATE Biotechnology Relevance
Tests understanding of structured vs unstructured models (Monod) for bioprocess optimization. Essential for predicting biomass quality, not just quantity, in fermentation processes.
