HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts.

Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression.

Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier.

However the interplay of cell-to-cell spread and increased CD4+ T cell activation, that are likely to have profound influences on the progression of the disease have been hitherto little studied.

However, HIV-1 can also disseminate by direct transmission from one cell to another by a process of cell-to-cell spread.

Two pathways of cell-to-cell transmission have been reported.

The autocrine and para-crine uptake rates Iauto and Ipara depend on the level of cytokine receptor expression on the target cells (Fig 1E), and are practically independent of the cell-to-cell distance even at high cell density (Fig IF; the low cell-density scenario is independent of the cell-to-cell distance by construction).

Thus in a physiological setting, cytokine gradients between cells, and not bulk-phase concentrations, are crucial for cell-to-cell communication, emphasizing the need for spatially resolved data on cytokine

Having established that an effective paracrine IL-2 signal is possible in our model, and that it can be suppressed by Treg cells, we analyzed to which extent key parameters shape the spa-tio-temporal dynamics: IL-2 secretion rate, cell-to-cell distance, and fraction of IL-2 secreting cells.

Within the range from 2 to 20 um [12] , the cell-to-cell distance (measured between cell surfaces of neighbored cells) does not influence the amount of Th cells that become activated by the paracrine IL-2 stimulus (Fig 4E, right panel).

Thus, the exact cell-to-cell distance is unimportant in the physiological range.

Using experimentally established parameters for the T-cell cytokine IL-2, we find that cytokine signals emanating from producing cells are short-range (one to few cell-to-cell distances) because of uptake by target cells or competitors.

Thus we predict that gradients at the cellular length scale are a key property of cell-to-cell communication by cytokines.

Interestingly, a fourth system property one might expect to have a large influence on the dynamics of the system, the cell density or cell-to-cell distance, is unimportant for the results of our simulations (Fig 4E).

Cell-to-cell communication is a defining property of multicellular organisms.

To this end, we considered the two key spatial scales, the sub-um scale of the immunological synapse and the supra-um scale of cell-to-cell communication.

For example, the high aspect ratio of the immunological synapse evokes highly localized cytokine concentrations in the vicinity of cytokine secreting cells resembling secretion from a point source (see Fig 2B), and the high diffusion constant in relation to the receptor dynamics makes the system largely independent of the cell-to-cell distance (Fig 1E and IF).

By so doing, the approach may be useful in applications ranging from studying the implications of cell-to-cell variability to the prediction of intersubject differences in response to pharmacological treatment.

Despite such consistent changes, the parameterization also points to important cell-to-cell variability, in particular for the INa conductance, which is increased in three cells and decreased in one.

The differences in cell-to-cell variation in current densities have been linked to mRNA expression differences or post-translational modifications [38,39].

First, the models can obviously be used to study cell-to-cell variability [45].

In addition to improving model fidelity generally, because this approach can be used to generate a model from a single cardiac myo-cyte, it may be useful in applications ranging from studying the implications of cell-to-cell variability to the prediction of intersubject differences in response to pharmacological treatment.

Even in myocytes from the same region of the heart, there is considerable cell-to-cell variability in the action potential, presumably stemming from different levels of ion channel densities.

RNAi screens with single-cell readouts are becoming increasingly common, and they often reveal high cell-to-cell variation.

For the first time, image features are explicitly used on the single-cell level for NEM inference, acknowledging large cell-to-cell variation.

Such data sets are becoming more and more available, and they reveal that the high cell-to-cell variation has severe consequences when summarizing such heterogeneous observations.