Growth Curve
Growth Curve - Related Videos
12:15
Growth Curves: Generating Growth Curves Using Colony Forming Units and Optical Density Measurements
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2023
Source: Andrew J. Van Alst1, Rhiannon M. LeVeque1, Natalia Martin1, and Victor J. DiRita1 1 Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, United States of America Growth curves provide valuable information on bacterial growth kinetics and cell physiology. They allow us to determine how bacteria respond in variable growth conditions as well as to define optimal growth parameters for a given bacterium. An archetypal growth curve progresses...
12:23
Bacterial Growth Curve Analysis and its Environmental Applications
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2023
Source: Laboratories of Dr. Ian Pepper and Dr. Charles Gerba - The University of Arizona Demonstrating Author: Luisa Ikner Bacteria are among the most abundant life forms on Earth. They are found in every ecosystem and are vital for everyday life. For example, bacteria affect what people eat, drink, and breathe, and there are actually more bacterial cells within a person’s body than mammalian cells. Because of the importance of bacteria, it is preferable to study particular species of bacteria...
01:28
Bacterial Growth Curve
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2025
The bacterial growth curve is a fundamental concept in microbiology that describes the dynamics of bacterial population growth in a closed system with controlled environmental conditions, such as temperature and nutrient availability. This curve is divided into four distinct phases: lag, log (exponential), stationary, and death phases, each reflecting a unique stage of bacterial adaptation and growth. During the lag phase, bacteria acclimate to their surroundings by synthesizing essential...
03:30
Assessing Rotavirus Growth Curve by Plaque Assay
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2026
Source: Kadoya, S., Sano, D. Assays for the Specific Growth Rate and Cell-binding Ability of Rotavirus. J. Vis. Exp. (2019).This video demonstrates the use of a plaque assay to assess the rotavirus growth curve. The method involves infecting host cells with diluted virus, overlaying with agarose to restrict spread, and staining to visualize plaques formed by viral replication. By counting plaque-forming units at defined time points, the resulting growth curve reveals the lag, exponential, and...
13:06
Solubilization and Bio-conjugation of Quantum Dots and Bacterial Toxicity Assays by Growth Curve and Plate Count
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Cited by 7 •
2012
Nanoparticles such as semiconductor quantum dots (QDs) can be used to create photoactivatable agents for anti-microbial or anti-cancer applications. This technique shows how to water-solubilize cadmium telluride (CdTe) QDs, conjugate them to an antibiotic, and perform a bacterial inhibition assay based upon growth curves and plate count.
FAQs
During the exponential phase, cells divide rapidly while resources remain sufficiently available, producing a consistent increase in population size over time. This regular pattern allows researchers to estimate growth rate and generation time more reliably than during the lag phase, when cells are adapting, or the stationary and death phases, when limitations and decline alter population behavior.
Generation time indicates how long a population takes to double, whereas growth rate describes how quickly population size increases over time. Researchers derive these measures from the changing population pattern, especially during active division. Comparing them across cultures helps reveal differences in organism performance, environmental response, or the effects of experimental conditions.
The transition occurs when conditions no longer support continued rapid division. Nutrient depletion, limited space, or the accumulation of waste can reduce the ability of cells to increase in number. Recognizing this shift is important because a stable population size does not necessarily indicate continued healthy growth; it may reflect environmental constraints balancing cell production.
Changes in the timing, slope, or extent of growth can indicate how an organism responds to its surroundings. A longer adaptation period may suggest difficulty adjusting, while altered exponential growth or reduced population yield can signal unfavorable conditions. Comparing curves from different environments therefore provides a quantitative way to evaluate biological performance.
Researchers monitor population size at successive time points, organize the measurements chronologically, and graph the resulting changes. They then identify periods of adaptation, active increase, stabilization, or decline and calculate growth-related measures when appropriate. Applying the same observation schedule and comparison criteria across samples helps distinguish biological differences from changes caused by experimental conditions.
A treated culture can be compared with an untreated culture by examining changes in growth pattern, population increase, stabilization, or decline. Reduced growth or an earlier decrease in population size may indicate that the treatment affects the biological system. This approach helps researchers assess treatment responses quantitatively rather than relying only on a single population measurement.