Mutation Analysis¶

Mutations between sequences can be comprehensively analyzed.

In [1]:

import sys
from loguru import logger

from pyeed import Pyeed
from pyeed.analysis.mutation_detection import MutationDetection
from pyeed.analysis.standard_numbering import StandardNumberingTool

logger.remove()
level = logger.add(sys.stderr, level="WARNING")

import sys from loguru import logger from pyeed import Pyeed from pyeed.analysis.mutation_detection import MutationDetection from pyeed.analysis.standard_numbering import StandardNumberingTool logger.remove() level = logger.add(sys.stderr, level="WARNING")

• Pyeed: Main class for interacting with the PyEED database
• MutationDetection: Class for identifying differences between protein sequences
• StandardNumberingTool: Ensures consistent position numbering across different protein sequences

In [2]:

uri = "bolt://129.69.129.130:7687"
user = "neo4j"
password = "12345678"

eedb = Pyeed(uri, user=user, password=password)

eedb.db.wipe_database(date="2025-03-14")

uri = "bolt://129.69.129.130:7687" user = "neo4j" password = "12345678" eedb = Pyeed(uri, user=user, password=password) eedb.db.wipe_database(date="2025-03-14")

📡 Connected to database.
All data has been wiped from the database.

1. Establishes connection parameters to a local Neo4j database
2. Creates a PyEED instance with these credentials
3. Wipes existing database data (with date "2025-01-19")
4. Removes all database constraints for a fresh start

This ensures we're working with a clean database state.

Sequence Retrieval¶

In [3]:

ids = ["AAM15527.1", "AAF05614.1", "AFN21551.1", "CAA76794.1", "AGQ50511.1"]

eedb.fetch_from_primary_db(ids, db="ncbi_protein")
eedb.fetch_dna_entries_for_proteins()

ids = ["AAM15527.1", "AAF05614.1", "AFN21551.1", "CAA76794.1", "AGQ50511.1"] eedb.fetch_from_primary_db(ids, db="ncbi_protein") eedb.fetch_dna_entries_for_proteins()

1. Defines two protein sequence IDs to analyze
2. Fetches these sequences from NCBI's protein database
3. All sequences are beta-lactamase proteins
4. The sequences are automatically parsed and stored in the Neo4j database
5. Additional metadata like organism information and CDS (Coding Sequence) details are also stored

Apply Standard Numbering¶

In [4]:

sn_protein = StandardNumberingTool(name="test_standard_numbering_protein")


sn_protein.apply_standard_numbering(
    base_sequence_id="AAM15527.1", db=eedb.db, list_of_seq_ids=ids
)

sn_dna = StandardNumberingTool(name="test_standard_numbering_dna")

sn_dna.apply_standard_numbering(
    base_sequence_id="AF190695.1", db=eedb.db, node_type="DNA"
)

sn_protein = StandardNumberingTool(name="test_standard_numbering_protein") sn_protein.apply_standard_numbering( base_sequence_id="AAM15527.1", db=eedb.db, list_of_seq_ids=ids ) sn_dna = StandardNumberingTool(name="test_standard_numbering_dna") sn_dna.apply_standard_numbering( base_sequence_id="AF190695.1", db=eedb.db, node_type="DNA" )

1. Creates a new StandardNumberingTool instance named "test_standard_numbering"
2. Uses KJO56189.1 as the reference sequence for numbering
3. Performs multiple sequence alignment (MSA) using CLUSTAL
4. The alignment output shows:
   • Asterisks (*) indicate identical residues
   • Colons (:) indicate conserved substitutions
   • Periods (.) indicate semi-conserved substitutions
5. This step is crucial for ensuring mutations are correctly identified relative to consistent positions

Mutation Detection¶

In [5]:

md = MutationDetection()

seq1 = "AAM15527.1"
seq2 = "AAF05614.1"
name_of_standard_numbering_tool = "test_standard_numbering_protein"

mutations_protein = md.get_mutations_between_sequences(
    seq1, seq2, eedb.db, name_of_standard_numbering_tool
)

md = MutationDetection() seq1 = "AAM15527.1" seq2 = "AAF05614.1" name_of_standard_numbering_tool = "test_standard_numbering_protein" mutations_protein = md.get_mutations_between_sequences( seq1, seq2, eedb.db, name_of_standard_numbering_tool )

In [6]:

md = MutationDetection()

seq1 = "AF190695.1"
seq2 = "JX042489.1"
name_of_standard_numbering_tool = "test_standard_numbering_dna"

mutations_dna = md.get_mutations_between_sequences(
    seq1, seq2, eedb.db, name_of_standard_numbering_tool, node_type="DNA"
)

md = MutationDetection() seq1 = "AF190695.1" seq2 = "JX042489.1" name_of_standard_numbering_tool = "test_standard_numbering_dna" mutations_dna = md.get_mutations_between_sequences( seq1, seq2, eedb.db, name_of_standard_numbering_tool, node_type="DNA" )

1. Creates a MutationDetection instance
2. Compares the two sequences using the standard numbering scheme
3. Identifies all positions where amino acids differ
4. Automatically saves the mutations to the database
5. Returns a dictionary containing mutation information

Results¶

In [7]:

print(mutations_protein)

print(mutations_protein)

{'from_positions': [241, 272, 125], 'to_positions': [241, 272, 125], 'from_monomers': ['R', 'D', 'V'], 'to_monomers': ['S', 'N', 'I']}

Outputs a detailed mutation map showing:

• from_positions: [102, 162, 236] - Where mutations occur in the sequence
• to_positions: [102, 162, 236] - Corresponding positions in the second sequence
• from_monomers: ['E', 'S', 'G'] - Original amino acids
• to_monomers: ['K', 'R', 'S'] - Mutated amino acids

This means we found three mutations:

1. Position 102: Glutamic acid (E) → Lysine (K)
2. Position 162: Serine (S) → Arginine (R)
3. Position 236: Glycine (G) → Serine (S)

In [8]:

for i in range(len(mutations_dna['from_positions'])):
    print(f"Mutation on position {mutations_dna['from_positions'][i]} -> {mutations_dna['to_positions'][i]} with a nucleotide change of {mutations_dna['from_monomers'][i]} -> {mutations_dna['to_monomers'][i]}")

for i in range(len(mutations_dna['from_positions'])): print(f"Mutation on position {mutations_dna['from_positions'][i]} -> {mutations_dna['to_positions'][i]} with a nucleotide change of {mutations_dna['from_monomers'][i]} -> {mutations_dna['to_monomers'][i]}")

Mutation on position 682 -> 615 with a nucleotide change of T -> C
Mutation on position 407 -> 340 with a nucleotide change of C -> A
Mutation on position 92 -> 25 with a nucleotide change of C -> A
Mutation on position 162 -> 95 with a nucleotide change of G -> T
Mutation on position 929 -> 862 with a nucleotide change of A -> C
Mutation on position 346 -> 279 with a nucleotide change of A -> G
Mutation on position 87 -> 20 with a nucleotide change of C -> A
Mutation on position 88 -> 21 with a nucleotide change of T -> C
Mutation on position 130 -> 63 with a nucleotide change of C -> T
Mutation on position 175 -> 108 with a nucleotide change of G -> A
Mutation on position 131 -> 64 with a nucleotide change of T -> C
Mutation on position 132 -> 65 with a nucleotide change of A -> T
Mutation on position 914 -> 847 with a nucleotide change of G -> A
Mutation on position 604 -> 537 with a nucleotide change of T -> G
Mutation on position 925 -> 858 with a nucleotide change of G -> A
Mutation on position 226 -> 159 with a nucleotide change of T -> C

In [ ]: