Lecture #12: Uptake, Growth I Flashcards
Iron Uptake (Book)
Almost all microbes need iron for use in cytochromes and many enzymes. Iron uptake is made difficult by the extreme insolubility of ferric iron (Fe+3) and its derivatives, which leaves little free iron available for transport. Many bacteria and fungi have overcome this difficulty by secreting siderophores.
Siderophores are low molecular weight organic molecules that bind ferric iron and supply it to the cell.
Microbes secrete siderophores when iron is scarce in the medium. Once the iron-siderophore complex has reached the cell surface, it binds to a siderophore-receptor protein. Then either the iron is released to enter the cell directly or the whole iron-siderophore complex is transported inside by an ABC transporter.
Iron is so crucial to microbes that they may use more than one route of iron uptake to ensure an adequate supply.
Iron Uptake (Lecture)
To build cytochromes (proteins in the electron transport chain) and enzymes and energy-transferring molecules.
In the liquid surrounding cells most in near to insoluble—it is in a form that does not dissolve in water; Fe+++.
Bacteria secrete a molecule that binds (complexes) iron. Siderophore. Receptor sites in membrane that guide it in, transporters in cell membrane.
Once in the cell, the insoluble form is converted to the soluble 2+ form.
Cells go out and get their iron, have special receptor sites in the outer membrane (ABC Transporters in cell membrane).
Bacterial Growth Curve
The term growth has different meanings to a microbiologist. Growth sometimes refers to an increase in cellular constituents. This often leads to the cells growing longer and larger, and is usually accompanied by some type of cell division. Binary fission and other cell division processes bring about an increase in the number of cells in a population. Therefore the term growth is also used to refer tot he growth in size of a population.
Population growth often studied by analyzing the growth curve of a microbial culture. When microbes are cultivated in liquid form, they usually are grown in a batch culture–that is, they’re incubated in a closed culture vessel with a single batch of medium. Because no fresh medium is provided during incubation, nutrient concentrations decline and concentrations of wastes increase. The growth of a population of microbes reproducing by binary fission in a batch culture can be plotted as the log of the # of viable cells vs. the incubation time. The reslting curve has four phases. Lag, Exponential, Stationary, and Death.
Lag Phase
When microbes are introduced into fresh culture medium, usually no immediate increase in cell # occurs. However, cells are synthesizing new components. This period is called the lag phase.
Necessary for many reasons. Cell may be old and depleted of ATP, essential cofactors, and ribosomes; these must be synthesized before growth.
The medium may be different from the one the microbe was growing in previously. In this case, new enzymes would be needed to use different nutrients. Possibly, the microbes have been injured and require time to recover. Whatever the causes, eventually the cells begin to replicate their DNA, increase in mass, and finally divide.
Exponential Phase
During this phase, microbes are growing and dividing at the maximal rate possible. Their rate of growth is constant; that is, they’re completing the cell cycle and doubling in number at regular intervals. The population is most uniform in terms of chemical and physiological properties during this phase.
Exponential (log) growth is balanced growth. That is, all cellular constituents are manufactured at constant rates relative to each other.
When microbial growth is limited by the low concentration of a required nutrient, the final net growth or yield of cells increases with the initial amount of the limiting nutrient present. The rate of growth also increases with nutrient concentration but in a hyperbolic manner much like that seen with many enzymes. The shape of the curve seems to reflect the rate of nutrient uptake by microbial transport proteins. At sufficiently high nutrient levels, the transport systems are saturated, and the growth rate doesn’t rise further with increasing nutrient concentration.
Stationary Phase
In a closed system such as a batch culture, population growth eventually ceases and the growth curve because horizontal. This phase is attained by most bacteria at a population of around 10^9 cells per mL. Some microbes don’t reach such high population densities. Final population size also depends on nutrient availability and other factors, as well as the type of microbe being cultured. In this phase, the total number of viable microbes is constant, resulting from a balance between cell division and death, or the population may simply cease do divide but remain metabolically active.
One reason they enter this phase is nutrient limitation; with an essential nutrient, growth will slow. Population growth may also cease due to accumulation of toxic waste products. Finally, growth may cease when a critical population level is reached.
Death Phase
Cells growing in batch culture can’t remain in stationary phase forever. Eventually they enter a death phase, during which the number of viable cells often declines at an exponential rate. It was assumed that detrimental environmental changes such as nutrient deprivation and the buildup of toxic wastes caused irreparable harm to the cells. Even when bacterial cells were transferred to fresh medium, no growth occurred.
There is debate over everything above.
Mathematics of Growth
Knowledge of microbial growth rates during the exponential phase is important. Growth rate studies contribute to basic physiological and ecological research, and are applied in industry. The quantitative aspects of exponential phase growth discussed here apply to microbes that divide by binary fission.
During the exponential phase, each microbe is divided at constant intervals. Thus, the population doubles in number during a specific length of time called the generation (doubling) time. This can b illustrated with a simple example. Suppose a culture tube is inoculated with one cell that divides every 20 min. 2 cells after 20 min, 4 cells after 40, etc. Because the population is doubling every generation, the increase in population is always 2^n where n is the number of generations. The resulting population increase is exponential, that is logarithmic.
The mean growth rate is the number of generations per unit time. Often expressed as generations per hour. It can be used to calculate the mean generation (doubling) time (g). The mean generation time is simply the reciprocal of the mean growth rate. The mean generation time can also be determined directly from a semilogarithmic plot of growth curve data. Once this is done, it can be used to calculate the mean growth rate, again due to the reciprocal relationship between these two values.
Calculation of the Mean Growth Rate
Let:
N0 = the initial population number.
Nt = the population at time t.
n = the number of generations in time t.
For populations reproducing by binary fission:
Nt = N0 x 2^n
Solving for n, the number of generations, where all logs are to the base 10:
logNt = logN0 + n x log2
n = (logNt - logN0)/log2 = (logNt - logN0)/0.301
The mean growth rate is the number of generations per unit time. Thus
MGR = n/r = (logNt - logN0)/0.301t
Calculation of the Mean Generation (Doubling) Time
Let:
N0 = the initial population number.
Nt = the population at time t.
n = the number of generations in time t.
If a population doubles, then:
Nt = 2N0
Substitute 2N0 into the mean growth rate equation and solve for:
MGR = [log(2N0)] - logN0]/0.301g = (log2 + logN0 - logN0)/0.301g = 1/g
This means generation time is the reciprocal of the mean growth rate.
g = 1/MGR
Bacterial Growth Equation (Lecture)
Can calculate projected cell densities, or determine when a culture should reach a particular density.
Set up so that you can use it without any fancy mathematics such as taking logs or integrals or derivatives.
Here is the essence:
- Equation is set up using base 10 logs to make calculations easy.
- Time is expressed consistently, either as minutes or hours (decimal parts and wholes).
- To equate change in cell density (base 10 logs) with doubling time (base 2, or e), we include a conversion factor that is the base 10 log of 2 (log102) or 0.301.
