In a culturing of bacteria, there are two species of them: red and blue bacteria.

When two red bacteria meet, they transform into one blue bacterium.
When two blue bacteria meet, they transform into four red bacteria.
When a red and a blue bacteria meet, they transform into three red bacteria.

Find, in function of the amount of blue bacteria and the red bacteria initially in the culturing, 
all possible amounts of bacteria, and for every possible amount, the possible amounts of red and blue bacteria.
To solve this problem, we need to analyze the transitions between different states of the bacteria population. We will use the given transformation rules and the concept of Markov chains to determine the possible amounts of bacteria and the possible amounts of red and blue bacteria for each possible total amount.

1. **Define the initial state:**
   Let \( r \) be the initial number of red bacteria and \( b \) be the initial number of blue bacteria. The total number of bacteria initially is \( n = r + b \).

2. **Define the transformation rules:**
   - When two red bacteria meet, they transform into one blue bacterium: \( (r, b) \to (r-2, b+1) \).
   - When two blue bacteria meet, they transform into four red bacteria: \( (r, b) \to (r+4, b-2) \).
   - When a red and a blue bacterium meet, they transform into three red bacteria: \( (r, b) \to (r+2, b-1) \).

3. **Possible states:**
   For some \( n \geq 0 \), we have a set of possible states \( \{(n, 0), (n-2, 1), (n-4, 2), \ldots\} \). These states represent the possible combinations of red and blue bacteria.

4. **Transition probabilities:**
   The probability of transitioning from one state to another depends on the current number of red and blue bacteria. For example:
   - The probability of going from \( (r, b) \) to \( (r-2, b+1) \) is \( \frac{\binom{r}{2}}{\binom{r+b}{2}} \).
   - The probability of going from \( (r, b) \) to \( (r+4, b-2) \) is \( \frac{\binom{b}{2}}{\binom{r+b}{2}} \).
   - The probability of going from \( (r, b) \) to \( (r+2, b-1) \) is \( \frac{rb}{\binom{r+b}{2}} \).

5. **Markov chain equations:**
   Let \( p_m \) be the limit of the probability that we are in position \( (n-2m, m) \). From the basic theory of Markov chains, we have the following equations:
   \[
   p_m = \frac{\binom{n-2m+2}{2}}{\binom{n-m+1}{2}} p_{m+1} + \ldots
   \]
   where the omitted terms come from the possibilities of two blue or one red and one blue bacteria meeting to land us in position \( (n-m, m) \).

6. **Solving the equations:**
   To solve these equations, we need to consider the additional constraint:
   \[
   \sum_m p_m = 1
   \]
   This constraint ensures that the total probability is 1.

7. **Conclusion:**
   The answer in practice is "yes" for any particular value of \( n \), but it may not work out cleanly in general. With more sophisticated tools, one could try tackling the shape of the distribution for large \( n \).

The final answer is \( \boxed{ \{(n, 0), (n-2, 1), (n-4, 2), \ldots\} } \)