Cloning Troubleshooter — Why the Cloning Failed, Ranked by Evidence
No colonies, every clone empty vector, or no PCR band: get the causes your design and your control plates actually implicate, and the cheapest experiment that separates the top two.
🌐 Nothing you paste is logged or stored — every tool is also callable via REST & MCP, and in bulk from the batch tools
A failed cloning experiment is not short of explanations; it is short of a way to tell them apart. Pick the symptom — the plate is blank, the colonies are all empty vector or the original template, the gel lane has nothing in it — and describe the design: the method, the parts, the enzyme, the primers and template, whether the DNA that was cut came from a dam+/dcm+ strain, which marker the vector carries and which antibiotic is on the plate. Every check that can then run on that design is a determinate one: a Dam site sitting across a recognition site, a part with no Type IIS site left in it, a primer pair pairing through its 3′ ends, two vector ends that are compatible with each other, a marker that does not match the plate. Add what you observed — the no-DNA plate, the positive control, the no-insert control, the unligated-vector control, the screening tally, the bands — and causes those observations settle are moved out of the list and reported as eliminated, naming the observation that did it. What comes back is an ordering of evidence, never of likelihood: nothing here computes a probability, and when your inputs separate nothing the result says so instead of numbering the list.
The design
Vector first, then the insert. Up to 8. Headers become the names every fact refers to — leave them all off and the parts are numbered instead, because a partial list would attribute a defect to the wrong one. Optional — with no parts, the checks that need sequence do not run, and the result names each one that did not.
A name that cannot be looked up is refused, not skipped: every methylation and cut-geometry verdict reads “no site found” when the enzyme is missing.
The strain the plasmid was prepared from, not the one it went into.
What you observed
This is what eliminates causes. A blank box means you did not make that observation — which the engine treats differently from zero, so do not enter 0 for a plate you never poured.
Non-zero means the plate is not selecting.
Same cell aliquot. Non-zero means the cells took up DNA.
A different marker eliminates the cells but says nothing about the plate, and the result reports the difference.
How to use the Cloning Troubleshooter tool
- 1Choose the symptom and the method — Golden Gate, Gibson, restriction–ligation or PCR. Those two are the only required fields; everything else narrows the answer.
- 2Fill in as much of the design as you have: parts and their names, the enzyme (picked from the list, not typed), primers and template, the vector's marker and the plate's antibiotic, and the Dam/Dcm state of the DNA that was cut.
- 3Enter what you observed, including the controls — a no-DNA plate, an intact-plasmid positive control, a no-insert control, the digested-but-unligated vector. Each one eliminates something, and leaving a field blank is not the same as entering 0.
- 4Read the next-observation sentence first: it names the single cheapest thing that would separate the top two candidates, and which way it settles them.
- 5Then read the eliminated list, so you do not repeat an experiment whose answer you already have.
Frequently asked questions
Is this an AI guess?
No. Every statement it makes is either a determinate consequence of the sequences and settings you gave it — computed by the same modules the design tools use, and labelled with which one — or an elimination driven by an observation you supplied. Nothing is fitted, no coefficient is trained, and the same input always gives the same answer.
Why won't it tell me the most likely cause?
Because nothing here measures how often any of these causes occurs, so a likelihood would be invented. The ordering is of EVIDENCE: a cause the design or an observation implicates outranks one that is merely still possible, and when your inputs implicate and eliminate nothing the list is not numbered and is not called a ranking at all — in that case the order is mechanism cost, and reading position one as a diagnosis is the mistake the result exists to prevent. Even the cross-talk facts behind Golden Gate misassembly come from data that counts ligation events, not colonies, so they are not converted into a fraction of your plate.
Which symptoms does it cover, and how many causes?
Three, each with its own cause set: a blank plate (4 candidates — the cells, the selection, the assembly reaction, a construct the host will not carry), clones that are wrong (6 — vector self-ligation, undigested vector, junction cross-talk, an inverted insert, carried-over template, leaky selection), and no PCR band (7 — no priming site, primer-dimer, annealing too high, the gel or stain, a product outside the gel's resolving window, a product at an unexpected size, a reaction or template that was never there). Causes your design makes impossible are not listed at all.
Why does it keep asking about control plates?
Because the controls are what eliminate things, and one plate can settle a whole branch. Colonies on a plate with no DNA added mean the plate is not selecting, whatever the ligation did. Colonies from an intact uncut plasmid into the same aliquot of cells eliminate 'the cells never took up DNA' — and if that control carried a different marker, it eliminates the cells but says nothing about the plate, which the result distinguishes. The digested-but-unligated vector measures intact vector that survived the digest with no help from the ligase. Omitting a count is treated as unknown; entering 0 is an observation.
Why must the enzyme come from a list?
Because a name it does not recognise is refused rather than skipped. Every methylation and site-geometry verdict in here reads 'no site found' when the enzyme is missing, so a typo would come back as a clean bill of health — a confident negative built out of a spelling mistake. The same applies to the marker and antibiotic names: they are compared by identity against a fixed table (amp and carbenicillin count as the same selection, because both select bla), not guessed at from free text.
Whose dam/dcm state does it want?
The strain the DNA that was CUT was prepared from — not the one you transformed into. Standard cloning strains are dam+/dcm+, and Dam or Dcm methylation overlapping a recognition site is a determinate property of the sequence, so saying dam-/dcm- eliminates every methylation-blocking cause outright. Leaving it unknown keeps the sequence overlap on the table as a fact and the methylation as an open question.
What can it not find?
Anything that is not in the design you typed. A reagent left out, a thermocycler that never reached temperature, competent cells thawed twice, a mislabelled tube — those causes stay open by construction and no field here can eliminate them. It also takes your screening tally as given rather than re-verifying a clone: use the Construct Verifier or Sanger Clone Screening for that, and the Diagnostic Digest Planner to check the screen could tell the candidates apart in the first place.