The Bacterial Growth Curve
- Bacteria divide using the process of binary fission during which one cell will divide into two identical cells
- The process is as follows
- The single, circular DNA molecule undergoes DNA replication
- Any plasmids present undergo DNA replication
- The parent cell divides into two cells, with the cytoplasm roughly halved between the two daughter cells
- The two daughter cells each contain a single copy of the circular DNA molecule and a variable number of plasmids
The process of binary fission produces two identical daughter cells
Bacterial growth curve
- The growth of a bacterial population follows a specific pattern over time; this is known as a growth curve
- There are 4 phases in the population growth curve of a microorganism population
- Lag phase
- The population size increases slowly as the microorganism population adjusts to its new environment and gradually starts to reproduce
- Exponential phase
- With high availability of nutrients and plenty of space, the population moves into exponential growth; this means that the population doubles with each division
- This phase is also known as the log phase
- Stationary phase
- The population reaches its maximum as it is limited by its environment, e.g. a lack of resources and toxic waste products.
- During this phase the number of microorganisms dying equals the number being produced by binary fission and the growth curve levels off
- Death phase
- Due to lack of nutrients and a build up of toxic waste build up, death rate exceeds rate of reproduction and the population starts to decline
- This phase is also known as the decline phase
- Lag phase
There are four phases in the standard growth curve of a microorganism
Using logarithms in growth curves
- During the exponential growth phase bacterial colonies can grow at rapid rates with very large numbers of bacteria produced within hours
- Dealing with experimental data relating to large numbers of bacteria can be difficult when using traditional linear scales
- There can be a wide range of numbers reaching from single figures into millions
- This makes it hard to work out a suitable scale for the axes of graphs
- Logarithmic scales can be very useful when investigating bacteria or other microorganisms
- The numbers in a logarithmic scale represents logarithms, or powers, of a base number
- If using a log10 scale, in which the base number is 10, the numbers on the y-axis represent a power of 10, e.g. 1=101 (10), 2=102 (100), 3=103 (1000) etc.
- Logarithmic scales allow for a wide range of values to be displayed on a single graph
- For example, if yeast cells were grown in culture over several hours the number of cells would increase very rapidly from the original number of cells present
- The results from such an experiment are shown in the graph below using a log scale
- The number of yeast cells present at each time interval was converted to a logarithm before being plotted on the graph
- This can be done using a log function on a calculator
- The log scale is easily identifiable as there are not equal intervals between the numbers on the y-axis
- The wide range of cell numbers fit easily onto the same scale
- The number of yeast cells present at each time interval was converted to a logarithm before being plotted on the graph
When a log10 scale is used, the scale increases by a factor of 10 each time; this allows large increases in numbers to be shown on a single graph
Examiner Tip
You won’t be expected to convert values into logarithms or create a log scale graph in the exam. Instead you might be asked to interpret results that use logarithmic scales or explain the benefit of using one! Remember that graphs with a logarithmic scale have uneven intervals between values on one or more axes.
Exponential growth rate constants
- To calculate the number of bacteria in a population the following formula can be used
- Where
- Nt = the number of organisms at time t
- N0 = the number of organisms at time 0
- k = the exponential growth rate constant
- t = the time for which the colony has been growing
- To use this equation the exponential growth rate constant k must be calculated
- This refers to the number of times the population doubles in a given time period
- The following formula can be used to calculate the exponential growth rate constant
Worked example
A bacterial colony started with 2 individuals and after 3 hours of growing there were 926 bacteria in the colony.
1. Calculate the exponential growth rate constant of this colony
2. Calculate the number of bacteria in the colony after 5 hours
Step 1: Calculate the exponential growth rate constant
Step 2: Calculate the number of bacteria after 5 hours