Exclude a few columns from a grouped selection by `dplyr::contains` - regex

Question

Suppose a data frame with several groups of columns (linked by their names, here Bla and D):
df = data.frame(A=1, BlaTata=2, BlaTato=3, BlaTota=4, BlaToto=5,
C=6, D1=7, D2=8, D3=9, D4=10)
# A BlaTata BlaTato BlaTota BlaToto C D1 D2 D3 D4
# 1 2 3 4 5 6 7 8 9 10
How can I easily drop all columns containing Bla (i.e., select(-contains('Bla'))) except for a few of them that I would explicitely "protect" from the (de)selection procedure?
Supposing I want to "protect" BlaTato and BlaToto:
df %>% mutate(saveBlaToto=BlaToto, saveBlaTato=BlaTato) %>%
select(-starts_with('Bla')) %>%
mutate(BlaToto=saveBlaToto, BlaTato=saveBlaTato) %>%
select(-contains('save')) %>%
select(order(colnames(.)))
# A BlaTato BlaToto C D1 D2 D3 D4
# 1 3 5 6 7 8 9 10
There must be an easier and more elegant way ;-)
Supposing it is not handy to select by column index etc.
Something like select(-contains('Bla' but keep c('BlaTato','BlaToto'))) possibly for several columns to be preserved...
EDIT
This question is answered in Frank's "New Question" below.
The original question, simpler and answered in his "First Question", was "How to drop all columns containing B except from B2 in the following data frame":
df = data.frame(A=1, B1=2, B2=3, B3, B4=5, C=6, D1=7, D2=8, D3=9, D4=10)

Answer 1

First question. If you look at ?select, you'll see that you can enter a regular expression, like
# example
df = data.frame(A=1, B1=2, B2=3, B3=4, B4=5, C=6, D1=7, D2=8, D3=9, D4=10)
# goal: drop B, protect B2
df %>% select(-matches('^B[^2]$'))
A B2 C D1 D2 D3 D4
1 1 3 6 7 8 9 10
Reading the regex:
^ and $ indicate start and end of the string.
[^x] means any character except x.
New question. It looks like dplyr doesn't support Perl-style regexes yet, so...
# example
df = data.frame(A=1, BlaTata=2, BlaTato=3, BlaTota=4, BlaToto=5,
C=6, D1=7, D2=8, D3=9, D4=10)
# goal: drop Bla, protect BlaTato, BlaToto
df %>% select(-grep('^Bla(?!Tato|Toto)', names(.), perl=TRUE))
A BlaTato BlaToto C D1 D2 D3 D4
1 1 3 5 6 7 8 9 10
Reading the regex:
(?!xyz) means "don't be followed by xyz"
x|y means x or y
For more info on regular expressions and the base R functions for using them, read ?regex and ?grep. Really, though, you shouldn't name your columns like this. If you find yourself in a position where you need to parse column names, you probably made a mistake earlier on.