Lentiviral Transduction Calculator

Calculate optimal MOI for lentiviral transduction and expected integration frequency.

% GFP+ cells at MOI tested (%)

MOI used for this measurement

MOI=virus particles per cell

Target % infected (for screen) (%)

Number of cells to infect (cells)

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Why MOI and Infection Rate Are Not the Same

Multiplicity of infection is the ratio of viral particles to cells, but infection is a random process. Particles distribute according to Poisson statistics, so at MOI 1 some cells receive none and others receive several.

% infected = (1 − e^−MOI) × 100 MOI = −ln(1 − fraction infected)

MOI	% infected	% of infected with >1 integration
0.1	9.5%	~5%
0.3	25.9%	~14%
1.0	63.2%	~42%
3.0	95.0%	~84%

Note that MOI 1 infects only 63%, not 100% — a frequent surprise. Reaching 95% requires MOI 3, and by then most infected cells carry multiple integrations.

Why Screens Use Low MOI

In a pooled CRISPR or shRNA screen, each cell must carry one perturbation so its phenotype can be attributed to that guide. A cell with two integrations has an uninterpretable phenotype and adds noise.

This is why screens target 20–30% infection despite wasting most cells. At MOI 0.3 roughly 14% of infected cells carry more than one integration — acceptable; at MOI 1 it would be 42%, which corrupts the data.

The trade-off is library representation. Fewer infected cells means fewer cells per guide, so the starting cell number must rise to maintain coverage — typically 500 to 1,000 cells per guide after selection.

Application	Target infection	Reason
Pooled screen	20–30%	Single integration per cell
Stable line	70–90%	Multiple copies acceptable, higher expression
Primary cells	As high as achievable	Often hard to transduce at all

Titre determines everything downstream and is functional rather than physical: transducing units per mL measured on the actual target cell type. The same viral prep gives very different titres on different cells, so a titre measured on HEK293T cannot be assumed for primary T cells.

Worked Examples

Example 1: CRISPR screen: target 30% infected, 1e7 cells

MOI=-ln(0.7)=0.357

Result: Single integration in most infected cells

Low MOI ensures 1 guide per cell

Example 2: Stable cell line: target 80% infection

MOI=-ln(0.2)=1.61

Result: High MOI → multiple integrations

Select clones to ensure single copy

Example 3: Why MOI 1 is not 100%

MOI = 1

Result: 63.2% infected

Poisson distribution: e⁻¹ = 0.368 of cells receive zero particles. Doubling MOI to 2 raises infection only to 86%.

Example 4: Screen coverage requirement

70,000 guide library at 500 cells per guide, 30% infection

Result: Need about 117 million cells at infection

35 million infected cells are required, which at 30% efficiency means starting with well over 100 million.

Common Mistakes

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Assuming MOI 1 infects all cells

Poisson statistics mean MOI 1 gives 63% infection. Reaching 95% requires MOI 3, at which point most infected cells carry multiple integrations.

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Using high MOI for pooled screens

Multiple integrations per cell make phenotypes uninterpretable. Screens target 20–30% infection to keep most infected cells at a single copy.

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Applying a titre measured on a different cell type

Transduction efficiency varies enormously between cell types. Functional titre must be determined on the actual target cells.

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Forgetting library coverage when lowering MOI

Fewer infected cells means fewer per guide. Starting cell numbers must increase to maintain 500–1,000 cells per guide after selection.

Frequently Asked Questions

Why low MOI for screens?

CRISPR/shRNA screens: each cell must have ONE perturbation. At MOI=0.3: 30% infected, >95% have single integration. Multiple sgRNAs per cell = cannot assign phenotype to one gene. Rule: MOI=0.3-0.5 for genome-scale screens.

Titer calculation?

Titer (TU/mL) = (% infected × cells / volume added) / MOI_used. Or: titer = (-ln(1-fraction_infected) × cells) / volume. Serial dilute and pick dilution giving 5-30% infection for accurate titer calculation.

Why doesn't MOI 1 infect every cell?

Because viral particles distribute randomly by Poisson statistics. At MOI 1, e⁻¹ or about 37% of cells receive no particle at all.

Why do pooled screens use low MOI?

So most infected cells carry a single integration. Multiple guides in one cell produce phenotypes that cannot be attributed to either.

How do I calculate the MOI for a target infection rate?

Take the negative natural log of the uninfected fraction. For 30% infection, MOI = −ln(0.70) = 0.357.

Why must titre be measured on the target cell type?

Transduction efficiency varies widely between cell types. A titre determined on HEK293T can overstate performance on primary cells by an order of magnitude.