Common peptides study of aminoacyl-tRNA synthetases

1. Common peptides study of aminoacyl-tRNA synthetases Assaf Gottlieb, Milana Frenkel-Morgenstern, Mark Safro, David Horn, Plos One, 2011 * Figure from Prous science

2. Aminoacyl-tRNA synthetases (aaRSs) Rosetta stone

3. aaRS classes • Divided into two classes (I & II), characterized by different structures and distinguishing motifs

4. Data • Method • Results

5. Data • 5,406 non-redundant aaRS protein sequences • ~500 species • 22 aaRSs • 20 standard • Pyrrolysine • O-phosphoseryl-tRNA synthetase (SepRS))

6. Data • Method • Results

7. Find patterns in strings of letters MEX-Motif Extraction algorithm Initially developed for learning text. given a sequence of letters a l i c e w a s b e g i n n i n g t o g e t v e r y t i r e d o f s i t t i n g b y h e r s i s t e r o n t h e b a n k a n d o f h a v i n g n o t h i n g t o d o o n c e o r t w i c e s h e h a d p e e p e d i n t o t h e b o o k h e r s i s t e r w a s r e a d i n g b u t i t h a d n o p i c t u r e s o r c o n v e r s a t i o n s i n i t a n d w h a t i s t h e u s e o f a b o o k t h o u g h t a l i c e w i t h o u t p i c t u r e s o r c o n v e r s a t i o n alicewas beginning toget verytiredof sitting by hersister onthebank and of having nothing todo onceortwice shehad peep ed intothe book hersister was reading butit hadno pictures or conversation s init and what is theuseof abook thoughtalice without pictures or conversation

8. (2,1) (2,2) j s e h d v a c g f u t b z q p o n r i k m l w x y (2,3) (2,4) begin end Creating the graph… • ∑ = {a-z} (1,1) • alice • was (1,6) (1,5) (1,2) (1,4) (1,3)

9. {1003;12} a {1003;11} b p c {1003;10} o {1003;13} {1003;4} d n {1003;5} structured graph m e {1003;3} {1003;14} {1003;6} {1003;9} l f {1003;7} k g {1002;2} {1002;1} {1003;8} h j i Creating the graph… - cont’d

10. MEX algorithm for proteins Finds deterministic motifs (peptides)

11. Method of Common Peptides (CPs) • Extract per-aaRS peptides to form 22 per-aaRS peptide lists • Merge the 22 lists • Search the merged list peptides on all aaRSs • CP-space: 5,406 sequences x 10,612 CPs.

12. Data • Method • Results

13. Inter-aaRSs similarity Class I Class II Heat map of Pearson cross-correlations of different aaRSs according to their shared CPs. * Self correlations were left out for cleaner view.

14. BLAST provides a complementary view -log (E-value)

15. aaRSs similarity-Eukaryotes

16. aaRSs similarity - Archaea

17. aaRSs similarity - Mitochondria

18. CPs & Mitochondrial aaRSs • Tested enrichment of mitochondrial CPs in kingdom-specific CPs. • 16 mitochondrial aaRSs enriched in Bacteria, 13 in α-proteobacteria • 4 aaRSs enriched in Eukaryotes, none in Archaea • Assessed which gene was retained for 5/8 aaRSs with single nuclear genes in higher eukaryotes.

19. Biotin-[acetyl-CoA carboxylase] synthetase (birA) and aaRSs • Structural similarity between birA and class II aaRSs was reported, but no sequence homology. • Extracted CPs from 1,630 birA sequences. • 28 CPs are common (p<2e-5)

20. birA and aaRSs, contd.

21. CPs as novel class signatures * Overlap a binding site ** less than four residues apart from a binding site Class I signatures Class II signatures

22. Functional role of CPs • 29/50 prevalent CPs overlap known catalytic and binding sites (p<e-5) • Additional 8 <4 residues from site (p<e-10) • Most hit amino acid esterification sites • Other hit tRNA or ions binding sites.

23. Summary • CP methodology identifies significant deterministic motifs. • These motifs characterize family and class specific sequences. • CPs can find subtle evolutionary traces • CPs overlap functional sites

24. Thank you