I want to do principal component analysis (factor analysis) on SPSS based on 22 variables. However, some of my variables are very skewed (skewness calculated from SPSS ranges from 2-80!!!). 

So here are my questions:

1. Should I keep the skewed variables like that or Could I transform the variables on principal component analysis? If yes, how would i interpret factor scores? 

2. What type of transformation should I do? log10 or ln?

3. Originally, my KMO (Kaiser-Meyer-Olsen) is 0.413. A lot of literature recommended the minimum of 0.5. Can I still do factor analysis or do I need to remove variables to raise my KMO to 0.5?