Bio Restriction Golden Gate Assembly

Version Compatibility

Reference examples tested with: BioPython 1.83+ (API verified on 1.86)

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show biopython then help(Bio.Restriction.BsaI.search) to confirm the search API

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Golden Gate / Type IIS Assembly

"Design (or check) my Golden Gate assembly" -> Make each part free of the assembly enzyme's internal sites, and give every junction a distinct, well-behaved fusion overhang, so one tube of enzyme plus ligase builds the construct directionally and scarlessly.

• Python: Bio.Restriction to find internal Type IIS sites and read the overhang a cut exposes; the overhang-set rules are sequence logic, not a database call.

The whole method rests on one property: a Type IIS enzyme cuts outside its recognition sequence, so the 4-nt overhang it leaves is set by the user's flanking DNA, and the recognition site is placed to be removed from the final product. Because the ligated junction no longer contains the site, the enzyme cannot re-cut it, so digestion and ligation run together in one pot. Two design obligations follow, and both are what this skill checks: (1) domestication -- no part may contain an internal copy of the assembly enzyme's site, or it will be fragmented during assembly; (2) a set of distinct, non-palindromic fusion overhangs -- one per junction -- so parts assemble in exactly one order.

Choosing The Assembly Enzyme

Hierarchical systems (MoClo, Golden Braid) alternate enzymes between levels so each assembly round removes the previous level's sites: assemble Level 0 -> 1 with one enzyme, 1 -> 2 with the other. Pick the level's enzyme first, then domesticate every part against it.

Method Context

Choose Golden Gate when assembling several parts repeatedly from a standardized library; classic digestion for a one-off two-piece clone with convenient sites; Gibson when parts cannot be domesticated or no site layout works.

Domesticate: Find Internal Sites

Goal: Confirm a part carries no internal copy of the assembly enzyme's site (on either strand), and locate any that must be removed.

Approach: enzyme.search(seq) finds Type IIS sites on both strands (the recognition sequence is asymmetric, so its reverse-complement is detected too). Any hit inside a part is a defect to silently mutate away.

from Bio import SeqIO
from Bio.Restriction import BsaI, BsmBI, BbsI, SapI

record = SeqIO.read('part.fasta', 'fasta')

for enzyme in (BsaI, BsmBI, BbsI, SapI):
    hits = enzyme.search(record.seq)            # both strands; recognition site is asymmetric
    status = 'clean' if not hits else f'{len(hits)} internal site(s) at {hits} -> domesticate'
    print(f'{enzyme} ({enzyme.site}): {status}')

Domesticate: Break A Site By A Silent Mutation

Goal: Remove an internal site from a coding part without changing the protein.

Approach: Anchor on the recognition sequence itself (on both strands), not the cut position -- a Type IIS enzyme cuts outside its site, so mutating the codon at the cut would not touch the site. Walk the codons overlapping each recognition-site occurrence, swap one for a synonymous codon that breaks the site, and assert the protein is unchanged. This needs the reading frame.

from Bio.Data import CodonTable
from Bio.Seq import Seq

def domesticate_cds(cds, enzyme, frame=0):
    '''Remove an enzyme's internal sites from a CDS by synonymous codon swaps (reading frame `frame`).'''
    table = CodonTable.unambiguous_dna_by_id[1]
    syn = {}
    for codon, aa in table.forward_table.items():
        syn.setdefault(aa, []).append(codon)
    s = list(str(cds).upper())
    end = frame + 3 * ((len(s) - frame) // 3)
    protein = str(Seq(''.join(s[frame:end])).translate())
    site = str(enzyme.site)
    motifs = (site, str(Seq(site).reverse_complement()))    # both strands; Type IIS sites are unambiguous
    for _ in range(len(s)):
        seqstr = ''.join(s)
        if not enzyme.search(Seq(seqstr)):
            break
        hit = max(seqstr.find(m) for m in motifs)           # a recognition-site start (either strand)
        for ci in range(((hit - frame) // 3) * 3 + frame, hit + len(site), 3):
            if ci < frame or ci + 3 > len(s):
                continue
            codon = ''.join(s[ci:ci + 3])
            alt = next((a for a in syn.get(table.forward_table.get(codon), ())
                        if a != codon and not enzyme.search(Seq(''.join(s[:ci] + list(a) + s[ci + 3:])))), None)
            if alt:
                s = s[:ci] + list(alt) + s[ci + 3:]
                break
    assert str(Seq(''.join(s[frame:end])).translate()) == protein   # protein unchanged
    return Seq(''.join(s))

# A site that overlaps only Met/Trp codons (no synonyms) is rare but cannot be silently broken;
# always confirm the result is clean: assert not enzyme.search(domesticate_cds(cds, enzyme))

Preview The Fusion Overhangs A Digest Exposes

Goal: Read the actual 4-nt overhang each Type IIS cut would leave, to confirm junctions match as designed.

Approach: Anchor on the literal forward recognition sequence so only forward-oriented sites are read (a reverse-oriented site cuts on the other side and would otherwise return a misleading overhang). The 5' overhang starts fst5 bases after the recognition-site start.

from Bio.Restriction import BsaI

def forward_overhangs(seq, enzyme=BsaI, width=4):
    '''4-nt overhangs at FORWARD-oriented Type IIS sites, anchored on the recognition sequence.'''
    s, site, out = str(seq).upper(), str(enzyme.site), []
    i = s.find(site)
    while i >= 0:
        cut = i + enzyme.fst5                  # top-strand cut offset from the site start
        out.append(s[cut:cut + width])
        i = s.find(site, i + 1)
    return out

# Reverse-oriented sites cut on the other side; for a full construct, design the overhangs
# explicitly (below) rather than inferring every one from sequence.

Validate A Fusion-Overhang Set

Goal: Check that the overhangs chosen for all junctions assemble uniquely and ligate efficiently.

Approach: Apply the design rules: every overhang distinct; none palindromic (self-ligates); no overhang equal to the reverse complement of another (cross-ligates); avoid all-identical bases. High-throughput ligation-fidelity data (Potapov 2018) underlies curated high-fidelity sets used for large assemblies.

from Bio.Seq import Seq

def validate_overhang_set(overhangs):
    issues = []
    if len(set(overhangs)) != len(overhangs):
        issues.append('duplicate overhangs (parts assemble ambiguously)')
    for o in overhangs:
        if o == str(Seq(o).reverse_complement()):
            issues.append(f'{o} is palindromic (self-ligates)')
        if len(set(o)) == 1:
            issues.append(f'{o} is a homopolymer (low ligation fidelity)')
    rc = {o: str(Seq(o).reverse_complement()) for o in overhangs}
    for a in overhangs:
        for b in overhangs:
            if a != b and rc[a] == b:
                issues.append(f'{a} is the reverse complement of {b} (cross-ligates)')
    return issues or ['overhang set OK']

print(validate_overhang_set(['AATG', 'GCTT', 'TACT', 'GGGG']))

Common Errors

Related Skills

• enzyme-selection - Choose a classic restriction enzyme when scarless assembly is not needed
• restriction-sites - Find any enzyme's sites in a part
• fragment-analysis - Predict fragments to verify an assembly digest
• genome-engineering/grna-design - Design constructs that this assembly will build
• sequence-manipulation/transcription-translation - Confirm domestication kept the reading frame

References

• Engler C, Kandzia R, Marillonnet S. A one pot, one step, precision cloning method with high throughput capability. PLoS One. 2008;3(11):e3647. doi:10.1371/journal.pone.0003647
• Engler C, Gruetzner R, Kandzia R, Marillonnet S. Golden gate shuffling: a one-pot DNA shuffling method based on type IIs restriction enzymes. PLoS One. 2009;4(5):e5553. doi:10.1371/journal.pone.0005553
• Weber E, Engler C, Gruetzner R, Werner S, Marillonnet S. A modular cloning system for standardized assembly of multigene constructs. PLoS One. 2011;6(2):e16765. doi:10.1371/journal.pone.0016765
• Potapov V, Ong JL, Kucera RB, et al. Comprehensive profiling of four base overhang ligation fidelity by T4 DNA ligase and application to DNA assembly. ACS Synth Biol. 2018;7(11):2665-2674. doi:10.1021/acssynbio.8b00333