Standard Growth Curve of Microorganisms (OCR A Level Biology)

• Bacterial colonies can grow rapidly when in culture with very large numbers of bacteria produced within hours
• Populations of microorganisms, such as bacteria, can be measured in three different ways:
  • Direct counting includes all cells (both living and dead) and involves taking samples to count these individual microorganisms
  • Viable counting involves culturing samples of microorganisms and counting the colonies that grow. This method only takes living cells from the sample into account
  • Turbidity is a measure of living and dead microorganisms in solution, taking an absorbance reading using a colorimeter

Turbidity

• Microorganisms, such as bacteria or yeast, can be grown in a broth culture
• Measuring the turbidity of this suspension can then be used as a way of estimating the number of cells (i.e. the population size) of the microorganisms in the broth culture
  • Turbidity is simply a measure of the cloudiness of a suspension (i.e. how much light can pass through it)

• As the microorganisms in the broth culture reproduce and their population grows, the suspension becomes progressively more turbid (cloudy)
• This changing turbidity can be monitored by measuring how much light can pass through the suspension at fixed time intervals after the initial inoculation of the nutrient broth with the microorganisms
  • A turbidity meter, a light sensor or a colorimeter (connected to a datalogger) can be used to take these measurements

• The results can then be used to plot a population growth curve to show how the population of microorganism grew over time

Standard population growth curves

• There are 4 phases in the population growth curve of a microorganism
  • Lag phase  - the population size increases slowly as the microorganism population adjusts to its new environment and gradually starts to reproduce
  • Log phase - with high availability of nutrients and plenty of space, the population moves into exponential growth (the population doubles with each division)
  • Stationary phase occurs when the population reaches its maximum as it is limited by resources e.g. nutrients, toxic substances. The number of microorganisms dying equals the number being reproduced by binary fission
  • Decline phase occurs due to lack of nutrients and death due to toxic substance build up. Death rate exceeds reproduction rate

There are 4 phases in the standard growth curve of a microorganism

Calculating population growth

• Bacteria divide using the process of binary fission where one cell will divide into two identical cells
• The process is as follows:

  1. The single, circular DNA molecule undergoes DNA replication
  2. Any plasmids present undergo DNA replication
  3. The parent cell divides into two cells, with the cytoplasm roughly halved between the two daughter cells
  4. 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 where a single cell divides into two identical daughter cells

• The following equation is used to calculate the rate of cell division by binary fission:

N = N₀ x 2ⁿ

• • N = the final number of bacteria
  • N₀ = the initial number of bacteria
  • n = the number of divisions

Stage 1: Work out how many divisions there will have been in 5 hours

5 hours = 300 minutes

There is one division every 25 minutes

300 ÷ 25 = 12 divisions in 5 hours

Stage 2: Apply the equation N = N₀ x 2ⁿ

N₀ = 1

n = 12

N = 1 x 2¹²

N = 4098 bacteria cells

Using logarithms in growth curves

• During the exponential growth phase, bacterial colonies can grow at rapid rates when in culture, with very large numbers of bacteria produced within hours
• Dealing with the experimental data relating to large numbers of bacteria can be difficult when using traditional linear scales
  • There is a wide range of very small and very large numbers
  • 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

Using logarithms to deal with orders of magnitude

• Logarithmic scales allow for a wide range of values to be displayed on a single graph
• For example, yeast cells were grown in culture over several hours. The number of cells increased very rapidly from the original number of cells present
• The results from the 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
  • 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

Image showing the number of yeast cells grown in culture over 10 hours, using a logarithmic scale