Multiplicity of Infection (MOI) Calculator
Multiplicity of Infection (MOI) is the average number of viral particles (or bacteria) delivered per target cell. It is one of the most fundamental design parameters in virology, gene delivery, and infection experiments.
Basic Dose Calculation
Required infectious units (IU) = MOI × cell count N
Required virus volume (mL) = required IU ÷ viral titer (IU/mL)
Worked example: 5×10⁵ cells, target MOI = 3, viral titer = 1×10⁸ TU/mL:
- Required IU = 3 × 500,000 = 1,500,000 TU
- Required volume = 1,500,000 ÷ 100,000,000 = 0.015 mL = 15 µL
Poisson Distribution and Infection Rate
When each viral particle infects cells independently at random, the number of particles received per cell follows a Poisson distribution with parameter λ = MOI:
Probability of no infection P(0) = e^(−MOI)
Probability of exactly one P(1) = MOI × e^(−MOI)
Probability of at least one P(≥1) = 1 − e^(−MOI)
Theoretical infection rates at common MOI values (verification: at MOI = 1, P(≥1) = 1 − e^(−1) ≈ 0.632, i.e. 63.2%):
| MOI | Infection rate P(≥1) | Single infection P(=1) |
|---|---|---|
| 0.1 | 9.5% | 9.1% |
| 0.3 | 25.9% | 22.2% |
| 1.0 | 63.2% | 36.8% |
| 3.0 | 95.0% | 14.9% |
| 5.0 | 99.3% | 3.4% |
| 10.0 | >99.9% | 0.05% |
Single-copy integration experiments (clonal analysis, insertion-site tracking) require MOI ≤ 0.3. The metric that actually matters is not the overall infection rate but the fraction of infected cells carrying exactly one viral copy, i.e. P(=1) ÷ P(≥1): at MOI 0.3 this is 85.7%; at MOI 1.0 it drops to 58.2%; at MOI 3.0 only 15.7% remain. This value is reported separately in the results.
Back-Calculating MOI from Measured Infection Rate
If the infection rate f has been measured by flow cytometry or fluorescence microscopy, the actual MOI can be back-calculated as:
Actual MOI = −ln(1 − f)
Verification: GFP-positive fraction f = 0.85, so actual MOI = −ln(1 − 0.85) = −ln(0.15) ≈ 1.90.
Note: when f ≥ 0.99, the slope of the ln function approaches infinity and back-calculated values become unreliable; experimentally it is not possible to reliably distinguish MOI 4.6 from MOI 10.
Applicable Range and Common Errors
1. Titer units must match the experimental system: lentivirus is typically expressed as TU/mL (transducing units), adenovirus as VP/mL or IFU/mL, phage as PFU/mL, and bacteria as CFU/mL. This tool does not distinguish between unit types; mixing them will produce incorrect results.
2. Titer is cell-line dependent: lentiviral TU/mL is usually determined on 293T cells; actual efficiency in other cell lines may differ several-fold, so the calculated value is only a starting point.
3. The Poisson model loses accuracy at very high MOI (> 50): at these levels cell-surface receptors approach saturation, actual infection rates fall below theoretical predictions, and the model no longer applies.
4. The infection volume should not be too large: it is generally recommended that the added virus volume does not exceed 10% of the total medium volume, to avoid a dilution effect that reduces transduction efficiency; if necessary, concentrate the viral supernatant by ultracentrifugation first.
FAQ
Why isn't 100% of cells infected at MOI = 1?
The randomness of the Poisson distribution means that even when one virus is assigned on average per cell, roughly 37% (= e^(−1) ≈ 0.368) of cells receive none, while about 18% are simultaneously hit by two or more particles.
What MOI should I use when generating a stable lentiviral cell line?
For single-copy integration (e.g. functional screening, insertion-site analysis), use MOI ≤ 0.3—at this level more than 90% of infected cells originate from a single integration event. If high transduction efficiency is the only goal, MOI 3–5 is usually sufficient, giving a theoretical infection rate of ~95–99%.
The calculated volume of undiluted stock is less than 1 µL—how do I handle that?
Dilute the stock 1:10 in medium, enter one-tenth of the original titer into the tool, and recalculate to obtain a workable volume (usually ≥ 5 µL). Perform the dilution on ice to avoid titer loss from repeated freeze-thaw cycles.
Can p24 ELISA results (ng/mL) be used directly as infectious units?
No. p24 reflects physical particle number, not functional infectious units (TU/mL). You need to perform a functional titration on the target cells—measuring fluorescent-protein-positive cells by flow cytometry or counting fluorescent foci—to obtain the IU/mL value this tool requires.
Can this formula be used for bacterial invasion assays (e.g. Salmonella, Listeria)?
The basic dose formula (CFU = MOI × N) applies fully. However, the Poisson infection-rate prediction (P(≥1) = 1 − e^(−MOI)) is designed for random viral infection; bacteria invade cells actively and do not strictly follow a Poisson process, so the infection-rate figures are for reference only.
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