a) Viscoelastic properties and activity are measured within the cytoplasm of cells using a custom build optical tweezers setup. b) Sinusoidal forces (blue) at varying frequencies are applied to a probe particle while the particle displacement (red) in response to this force is monitored. c) Repeating this procedure at different frequencies allows to calculate viscoelastic material properties in terms of the complex shear modulus G∗(f) which consists of the storage modulus (blue) and a loss modulus (red). Both storage and loss modulus can collectively be fitted using a generalized fractional Kelvin-Voigt (fGKV) model(inset). d) This fGKV model consists of two power laws which in a simplified way can be pictured as a more solid-like material class resembling polymeric filaments and a more fluid-like material class (crowded molecules). e) Using an additional passive measurement, violation of the fluctuation-dissipation theorem can be directly visualized. (red area) f) The effective energy quantifies intracellular activity and can be fitted with a two parameter power law. g) Complex and frequency dependent intracellular active mechanical properties can be reduced to a fingerprint of just 6 parameters, which describe the intracellular mechanical state.

Wild type HeLa cells (WT) were treated with different cytoskeletal drugs to investigate their influence on the fingerprint parameters. a) Cytochalasin B (CytoB/CB) inhibits actin polymerization, Nocodazole (Nocoda/Noc) disturbs microtubule assembly and the combined treatment was used to disturb actin and microtubules simultaneously. b) The treatment with CB does not show a strong effect on the fingerprint parameters. c) Using Noc, intracellular activity in terms of E is strongly decreased while also the parameter B increases. d) The combined treatment shows a strong effect in decreasing intracellular activity E but also drastically softens the cytoplasm which is reflected in a decreased factor A. e,f,g) Change of fingerprint parameters in response to drug treatment. h,i,j) Effect of pharmacological treatment shown for the elastic modulus, loss modulus and effective energy

a) The mechanical fingerprint of 7 different cell types was determined by measuring their complex shear modulus and effective energy. b) Comparing HeLa cells to C2C12 muscle cells shows that muscle cells are overall stiffer (higher A). c) The comparison between HeLa cells and macrophages shows that macrophages of a higher intracellular activity (increased E) but are also more liquid-like and softer (increased α, β and decreased B) d-f). Using the fingerprint, active mechanical difference between cell types can be compared according to changes in the more solid-like material properties, more liquid-like material properties and the intracellular activity.

a) Number of significant different fingerprint parameter in pairwise cell type comparisons. b) Frequency of parameters showing the highest z-score. c) Distribution of z-score for all parameters for pairwise cell comparison. d) Correlation analysis between fingerprint parameters shows that not all parameters are varied independently. e) left: Explained variance ratio of the different principal components. Almost 80% of the variance is explained using the first two components. right: Relative contribution of the fingerprint parameter to the first two principal components. C1 mainly consists of α, β and B, C2 mainly consists of A, E, γ. f) Plotting all cell types according tothe first two principal components C1 and C2 shows that two parameters are already sufficient to distinguish between most cell types. g) Qualitative phase diagram of the active mechanical space. Activity, mainly captured by parameter E0, resistance, dominated by A and solid-liquid switching can be described as fluidity that is determined by principal component 1 (C1) are varied among different cell types. Using this three dimensional space allows to identify physical differences among different cell types which may be related to function.

Results of principal component analysis. Explained variance ratio quantifies how much information is captured by the corresponding component. The composition of each component is explained by its axis in parameter space. Here the values are shown until third decimal digit. Most information is explained by principal component 1 with an explained variance ration of 0.621. This component is mainly represented by fit parameter α, β and B in parameter space.

Parameter E: different cell types

Parameter γ: different cell types

Parameter A: different cell types

Parameter α: different cell types

Parameter B: different cell types

Parameter β: different cell types

Parameter E: different drugs

Parameter γ: different drugs

Parameter A: different drugs

Parameter α: different drugs

Parameter B: different drugs

Parameter β: different drugs

R2-values fGKV fit of complex shear moduli - bootstrapped data

R2-values power law fit of effective energy - bootstrapped data

R2-values fGKV fit of complex shear moduli

R2-values power law fit of effective energy

Schematic of bootstrapping significance test. a) Histogram for the estimates of two different parameters. b) Bootstrapping procedure was performed on both parameters to get an estimate for the distribution of the mean. c) Difference of both distribution is calculated. d) Depending on which percentile of the distribution is below 0, the significance score is determined

R2-Values for fitting the respective models to a) EEff, b) G′(f) and c) G′′(f)

R2-Values for fitting the respective models to the bootstrapped data of a) EEff, b) G′(f) and c) G′′(f)