High resolution AKT signaling in individual cells

Cells sense and respond to their environment by activating distinct intracellular signaling pathways, however an individual cell’s ability to faithfully transmit and discriminate environmental signals is thought to be limited. To assess the fidelity of signal transmission in the PI3K-AKT signaling pathway, we first developed an optimized genetically encoded sensor that had an increased dynamic range and reduced variation under basal conditions. We then used this reporter to track responses to varying doses of IGF-I in live cells and found that signaling responses from individual cells overlapped across a wide range of IGF-I doses, suggesting limited transmission accuracy. However, further analysis of individual cell traces revealed that responses were constant over time without stochastic fluctuations. We devised a new information theoretic approach to calculate the channel capacity using variance of the single cell time course data--rather than population-level variance as has been previously used—and predicted that cells were capable of discriminating multiple growth factor doses. We validated these predictions by tracking individual cell responses to multiple IGF-I doses and found that cells can accurately distinguish at least four different IGF-I concentrations, as demonstrated by their distinct responses. Furthermore, we found a similar discriminatory ability to pathway inhibition, as assessed by responses to the PI3K inhibitor alpelisib. Our studies indicate that cells can faithfully transmit an IGF-I input into a down-stream signaling response and that heterogeneous responses result from variation in the input-output relation across the population. These observations reveal the importance of viewing each cell as having its own communication channel and underscore the importance of understanding responses at the single cell level. in in , it differences in basal signaling , cell shape , , or phosphatase activity. Assessing each of these mechanisms independently is challenging, but our work suggests that it may be possible to tease apart these different mechanisms using a single-cell multi-treatment approach. studies indicate that signaling responses to molecules that activate or inhibit the IGF-I-AKT signaling pathway are not necessarily noisy. This is important as it rules out one mechanism for in that cells have large and variable signaling fluctuations that allow to overcome This conclusion also suggests a role for microenvironmental For may whereby dose fully inhibit these cells 19, . These experiments open the door to more in depth studies on how various pathway inhibitors alter signaling activity and how treatments regimens could be optimized for use in the clinic, particularly in the metastatic setting where cancer cells have to distinct tissue sites enriched with unique complements of signaling molecules.


Abstract
Cells sense and respond to their environment by activating distinct intracellular signaling pathways, however an individual cell's ability to faithfully transmit and discriminate environmental signals is thought to be limited. To assess the fidelity of signal transmission in the PI3K-AKT signaling pathway, we first developed an optimized genetically encoded sensor that had an increased dynamic range and reduced variation under basal conditions. We then used this reporter to track responses to varying doses of IGF-I in live cells and found that signaling responses from individual cells overlapped across a wide range of IGF-I doses, suggesting limited transmission accuracy. However, further analysis of individual cell traces revealed that responses were constant over time without stochastic fluctuations. We devised a new information theoretic approach to calculate the channel capacity using variance of the single cell time course data--rather than population-level variance as has been previously used-and predicted that cells were capable of discriminating multiple growth factor doses. We validated these predictions by tracking individual cell responses to multiple IGF-I doses and found that cells can accurately distinguish at least four different IGF-I concentrations, as demonstrated by their distinct responses. Furthermore, we found a similar discriminatory ability to pathway inhibition, as assessed by responses to the PI3K inhibitor alpelisib. Our studies indicate that cells can faithfully transmit an IGF-I input into a down-stream signaling response and that heterogeneous responses result from variation in the input-output relation across the population.
These observations reveal the importance of viewing each cell as having its own communication channel and underscore the importance of understanding responses at the single cell level.

Introduction
Cells sense and respond to their local environment by activating distinct intracellular signaling pathways. These pathways are composed of multi-step relays that use second messengers, protein translocations, and kinase/phosphatase cycles to encode, relay, and decode the extracellular signal into an intracellular response 1 . Given the multi-step nature of cell signaling in both space and time, much remains unknown about exactly how individual cells process extracellular signals into accurate intracellular responses [2][3][4][5] . Previous studies have observed that cell signaling is inherently noisy and that individual cells are limited in their detection of extracellular stimuli [2][3][4] , which suggests that ensemble averaging is required to decode extracellular signals into accurate signaling responses. However, these prior studies assessed signaling pathways with predominantly pulsatile--rather than sustained--responses, which hinders the ability to quantify and compare individual cell responses across time and may also obscure alternate explanations for heterogeneity.
The IGF-I -PI3K -AKT signaling pathway provides an excellent model to study cell signaling: it uses multiple modalities to encode, relay, and decode extracellular signals and also produces sustained responses. In brief, IGF-I binds to the receptor tyrosine kinase IGF1R to stimulate intracellular kinase activity 6 . This leads to recruitment of protein binding partners and translation of the protein signal into a lipid second messenger by PI3-Kinase and the subsequent phosphorylation and activation of AKT. The protein kinase AKT can then phosphorylate a range of proteins including the transcription factor FoxO1 [6][7][8][9] . Previously, we developed a fluorescent fusion protein using FoxO1, which can be used as a readout for IGF-I signaling activity 10 , and found that responses to IGF-I were sustained across time but heterogeneous across the population. We surmised that this heterogeneity could arise from various sources, including: noise in the signaling pathway, variability in the reporter and its quantification, non-specificity in the reporter, or cell-to-cell variation in the encoding of the signal.
Transitions from healthy to diseased states frequently involve changes to cell signaling, therefore a deep understanding of the fidelity of signaling in individual cells can provide insights into disease progression and treatment. For example, cancers arise from genetic alterations that drive activation of oncogenic pathways such as the PI3K-AKT pathway [11][12][13] . Moreover, cancers are frequently marked by substantial intratumoral heterogeneity 14 , indicating the need to quantify signaling at the single cell level. Several small molecule inhibitors have been developed to inhibit PI3K-AKT pathway activity and block cancer growth 15 . While promising, responses to these compounds are variable and resistance inevitably develops 16,17 . One possible explanation for incomplete therapeutic responses is variation in the signaling capability of individual cells [18][19][20] . Thus, a more complete understanding of responses to pathway-targeted activators and inhibitors at the single cell level will influence how clinical responses are interpreted and could inform mechanisms of drug resistance.
Here we report the development of an improved FoxO1 reporter to monitor AKT activity in individual cells and use it to assess growth factor signaling responses. In genetically transformed HeLa cells, we observed heterogeneous responses to IGF-I that were consistent with individual cells having different input-output relationships. To account for differences in the input-output relation across the population, we calculated the channel capacity-which provides an assessment of signaling fidelity-by measuring variance in individual cells over a time window when signaling responses had stabilized. This new approach nearly doubled the predicted number of IGF-I doses a cell could accurately discriminate. We then experimentally validated these predictions by treating cells with multiple IGF-I doses and showed that individual cells could accurately discriminate at least four IGF-I concentrations. Furthermore, we found that signaling fidelity extends to pathway inhibition such that the level of activation is largely correlated with the level of inhibition. We conclude that single cell responses to submaximal doses of IGF-I vary across a population because individual cells have different input-output relationships, and further that accounting for these differences reveals high signaling fidelity in individual cells.

Construction of a novel FoxO1 reporter with increased specificity
Signaling responses in the AKT, Erk, NF-kB, TRAIL and Ca 2+ pathways have been shown to be heterogeneous across the population [2][3][4][5]21 . This heterogeneity is frequently interpreted as arising from noise in signal transmission [2][3][4] . In previous work, we developed a live-cell reporter to study IGF-I responses at the single cell level: a fluorescently tagged FoxO1 protein 10 , which contains three canonical AKT phosphorylation sites that regulate protein localization to the nucleus or cytoplasm depending on their phosphorylation status 9,22 (Fig. 1A). We found that the relative fraction of the reporter in the nucleus was variable across a population of HeLa cells cultured in serum free conditions 21 and speculated that this variation resulted from phosphorylation on other non-AKT phosphorylation sites. In order to assess signaling noise in the IGF-PI3K-AKT pathway, we first sought to reduce basal variation in our readout for pathway activity.
To construct a new reporter with increased specificity, we started from the template of the previously developed reporter, termed Fox Tracer 1 (FT1) and made alanine substitutions to 10 serine and threonine sites previously identified as phosphorylation sites of other kinases [23][24][25][26][27] (Fig.   1A and Supplementary Fig. 1A, B). To reduce the protein size and eliminate other potential sources of non-specificity, we deleted a 234 amino acid segment from the C-terminus. Lastly, to increase the ease and efficiency of creating stable cell lines, we transferred the reporter from a lentiviral to a transposase-based genetic delivery system 28 (Sup. Fig. 1C).
The first construct tested, FT2-LAP, had a significantly reduced variance and increased nuclear localization compared to FT1 under serum free conditions, which suggested an increase in specificity from the alanine mutations. However, this came at the cost of a reduced export rate following IGF-I treatment, which limits the ability to rapidly assess responses. We next tested reporter variants containing a series of mutations near S326, which is located in an AKT phosphorylation domain thought to regulate the rate of FoxO1 nuclear export by creation of a negatively charged region when phosphorylated 26,29 (Fig. 1B). The single mutation of alanine 326 back to serine (FT2-LSP) increased the rate of nuclear export, but also added back a DYRK1/Erk phosphorylation site 26,29 (Fig. 1D, Sup. Fig. 1D). To eliminate this unwanted phosphorylation site, we mutated the peptide segment using the phosphomimetic amino acid aspartic acid. Furthermore, based on the concept that multiple negative charges better mimic the effect from phosphorylation 30, 31 , we tested four reporter variants that differed in the number of aspartic acid substitutions in this peptide segment. A comparison of these variants revealed that response rates increased with peptide charge, leading to a maximum rate of export for the FT2-DDD reporter (Fig. 1E, Movies 1-3).
As a control for the FT2-DDD reporter, we created a mutant with the three canonical AKT phosphorylation sites Thr24, Ser253 and Ser316 all mutated to alanine. As expected, this reporter (FT2-DDD 3A) does not translocate in response to IGF-I, which indicates that FT2-DDD responses to IGF-I were dependent on the canonical AKT phosphorylation sites (Fig. 1D). In summary, comparing the FT1 to the FT2-DDD reporter, we found that FT2-DDD is the optimal reporter for tracking the fidelity of IGF-I signaling responses based on its: increased specificity ( Fig. 1A, B), reduced population variance in both serum free conditions and following IGF-I treatment (Sup. Fig. 1E), and increased measurement range (Fig. 1F).

Responses to IGF-I stimulation are heterogeneous across the population
We next used the optimized FT2-DDD reporter to quantify responses of individual cells to IGF-I.
As expected, we found a progressive increase in the average population response with increasing IGF-I dose, which was quantified as a change in the relative nuclear intensity of the fluorescent reporter in individual HeLa cells ( Fig. 2A and B). Analysis of individual cells revealed heterogeneous responses to single doses of IGF-I and overlapping responses across multiple IGF-I doses, which has been interpreted as an inability of individual cells to discriminate different ligand doses 2 (Fig. 2C). Importantly, this heterogeneity was not due to differences in the relative expression of the reporter between cells, nor differences in the basal level of activation in individual cells (Sup. Fig. 2). Thus, despite reducing possible effects of nonspecificity in the readout for pathway activity, we find that responses to IGF-I remain heterogeneous across a population of individual cells.
Integration of multiple time points to quantify a cell's response has been shown to reduce the level of heterogeneity by reducing measurement noise 3 . To measure the effect of varying the number of measurements for each response, we compared dose-response relationships using either one image, which corresponds to the fluorescence at 90 min (Raw), two images, which allows cell responses at 90 min to be normalized based on their starting value (T0 normalized), or 15 images, which incorporates the signal change over a longer time window (Summed). We found that the EC 50 values remained similar between measures (Fig. 2D), which indicates that the quantification method does not distort the relationship between doses. Yet, a comparison of the cell responses to 0, 15, 25, and 125 pM showed that overlap between the populations was reduced--but not eliminated--as the measurement window increased (Fig. 2D). These observations indicate that single cell responses to IGF-I are heterogeneous, even with use of analytical approaches that reduce variance.

Responses of individual cells are stable across time
The Shannon-Hartley formula has been extensively used to quantify the signaling accuracy of biological systems [2][3][4] . A central assumption of the Shannon-Hartley channel capacity measurement, when applied to a population, is that the input-output relationship is identical for all cells in the population and observed variation is therefore attributed to noise in signal interpretation, transmission, and encoding. Based on this assumption, a noisy pathway would lead to varying responses in single cells over time (Fig. 3A, upper). Alternatively, there could be variation across the population in the input-output relationships of individual cells. In this case, we would expect to observe individual cells with minimal variation in signal transmission over time as well as heterogeneous responses across the population (Fig. 3A, lower). To separate these two scenarios, we quantified variation using the standard deviation of responses from each dose of IGF-I in the first 90-minute response window compared to the second 90-minute window when responses had reached a steady state (Fig. 3B). We found that the standard deviation during the first 90-minute response window increased as the dose of IGF-I increased  Based on this interpretation, we hypothesized that variance quantified from stabilized responses provides a more robust calculation of noise for channel capacity measurements. To test this, we quantified channel capacity in various ways. Channel capacity calculated from a single time point yielded 1 bit (Fig. 3D), which is similar to prior measures of other signaling pathways 2 .
This measure was increased to 1.2 bits when we computed channel capacity from the T0 normalized responses (Fig. 3D), and was further increased to 1.4 bits by using the summed responses drawn from 15 images. Finally, we quantified noise using the stable response window and found a channel capacity of 2.38 bits, which indicates that cells can discriminate at least 5 distinct IGF-I doses. While higher than previously reported, this is likely still an underestimate due to limitations in measuring individual cell responses. To test this idea, we treated cells with the nuclear export inhibitor Leptomycin B (LMB), which results in complete and All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/373993 doi: bioRxiv preprint sustained nuclear localization of the reporter. As a consequence, any variation in nuclear intensity after reaching steady state can be attributed to measurement noise rather than signaling noise. Comparison of how the signal varied across time for cells treated with LMB compared to cells treated with a submaximal dose of 17.5 pM IGF-I revealed nearly equivalent variances, which indicates that the true channel capacity may actually be much higher (Sup. Fig.   3B, C).

Individual cells can recapitulate population-derived dose response curves to reveal high signaling fidelity
To test the capacity of a single cell to discriminate different signal intensities, we treated cells showed measurable responses to even the lowest dose tested. Comparison of traces from cells centered at the 25 th and 75 th percentiles revealed similar responses within the groupings but distinct differences between the groupings (Fig. 5B). Likewise, the average dose response relationships from these cell subpopulations and a subpopulation of cells centered at the 50 th percentile revealed consistent responses within the groupings (Fig. 5C). Moreover, a cell's response to the first dose can be used to predict its response to the second dose (Sup. Fig. 4A).
Finally, we find that responses of multi-dose treated cells are significantly different from timeand dose-matched cells maintained in the same dose (Sup. Fig. 4B). These studies indicate that individual cells can discriminate a minimum of four distinct IGF-I concentrations, and the inputoutput relationship is consistent in individual cells but varies across the population. All rights reserved. No reuse allowed without permission.

Single cell responses to PI3Kα inhibition are influenced by IGF-I activation level
Our multi-dose single cell data indicate that cells can discriminate multiple concentrations of IGF-I, and that a continuum of responses exists across the population due to different inputoutput relations. This raised the question of whether responses to pathway inhibition similarly vary across a population of cells. To test this, we treated cells with 25 pM IGF-I, a submaximal dose that leads to a wide variation in single cell responses (see Fig. 2B), followed by dose escalation of the PI3Kα inhibitor alpelisib (0-500 nM). At the population level, we observed the expected dose-response relationship to alpelisib treatment (Fig. 6A). To understand single cell responses to alpelisib, we compared cells from the upper (blue traces) and lower (red traces) quantiles after treatment with 25 pM IGF-I. We found that these two populations remain separable after inhibitor treatment ( Fig. 6 B, Movie 6), and that responses to PI3Kα inhibition were correlated with the level of activation from IGF-I (Fig. 6C). Comparison of all drug doses revealed similar separations between quantiles, up to 500 nM alpelisib, the dose at which signaling from IGF-I is nearly completely blocked (Fig. 6D). Together, these observations indicate that a cell's response to inhibition is determined by its response to IGF-I, and as a consequence, responses to pathway inhibition are in line with a model in which there is variation in how cells encode a signaling input. All rights reserved. No reuse allowed without permission.

Discussion
Understanding how individual cells respond to diverse stimuli is a fundamental issue in cell biology [32][33][34] . To that end, we describe here the development of a FoxO1 reporter with a higher specificity for IGF-I signaling compared to our previous FoxO1 reporter 10 . With this improved reporter, we observed that individual cell responses to IGF-I still overlapped between doses, suggesting low signaling fidelity. Further analysis showed that this overlap was from differences in how cells encode the signal, rather than from noise in the signaling pathway. Multi-dose treatment protocols validated these findings and showed that cells could accurately discriminate at least four different IGF-I doses. These studies demonstrate that individual cells can accurately process extracellular growth factors into downstream signaling responses despite the observation that population responses overlap between doses.

Reporter optimization for live cell imaging studies
Genetically encoded fluorescent reporters provide a powerful tool for understanding and quantifying dynamic signaling responses 35 . Various types of signaling reporters have been developed, including FRET sensors 36,37 , synthetic translocation reporters 38 , and native proteins that translocate between the nucleus and cytoplasm (FoxO1 10, 39 , p53 40 , SMAD2 41 , NFkB 42 , Erk 43 ). Native proteins are advantageous in that they are biologically tuned to respond under physiological conditions and the function of critical protein regions are typically well-described.
Here we used knowledge of the FoxO1 sequence to optimize an existing FoxO1 reporter.
Specifically, we increased specificity by both targeting a large peptide region for deletion that is not involved in nuclear translocation and by mutating multiple phosphorylation sites that are not phosphorylated by AKT. Additionally, we optimized nuclear export through the modification of a short peptide sequence. These modifications would have been difficult to predict in the absence of previous studies. For example, nuclear export was improved by substitution of a phosphomimetic amino acid rather than an alanine at serine 326, and export was further aided by mutating the surrounding amino acids to better match the charge from phosphorylation 30,31 . All together these modifications significantly increased the specificity of the reporter for IGF-I signaling in HeLa cells, and allowed for increased accuracy in tracking individual cell responses.
Our approach to optimize the FoxO1 reporter, which considers the molecular structure and function of FoxO1, could be used to efficiently develop reporters of other signaling pathways.

Channel capacity quantification
Previous studies of the Erk, NFkB, and Ca 2+ signaling pathways have found channel capacities from 1-1.7 bits 2, 3, 5, 44 . Here, we assessed the channel capacity of the PI3K-AKT pathway using IGF-I. Importantly, this growth factor produces sustained Akt signaling responses 45 , making it All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.

Multi-treatment experiments reveal variation in single cell responses
The ability to quantify responses to multiple treatments in individual cells provides a powerful technique for understanding mechanisms of population variation 46,47 . This is in stark contrast to standard experiments in which single measures on individual cells are drawn from different populations, or the response to only a single stimulus is tracked across time. We used this multitreatment approach to achieve several means: first we used LMB normalization to quantify the measurement range of the reporter and to show that individual cell responses are not biased by the level of reporter expression, second we used multi-dose IGF-I treatments to validate that cells can accurately discriminate multiple doses of IGF-I and to identify variability in IGF-I encoding across the population, and third we used activation-inhibition experiments to determine that the level of signaling activity in an individual cell biases the extent of inhibition.
Without multiple measurements on the same cells, it would not be possible to identify these patterns nor accurately quantify potential sources of biological variation.

Cells exist in different states with different input-output relationships
Our data indicate that cells can accurately interpret multiple growth factor signals in their extracellular environment and that across the population there is variation in how cells encode this signal. As a consequence, it is not possible to accurately decode the input based on a single response. It is only through knowledge about how a cell responds to a second perturbation-either activation or inhibition-that the input signal could be decoded. This raises the question of what cellular parameter varies to create different input-output relationships All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/373993 doi: bioRxiv preprint across the population. It is reasonable to assume that variation in the input-output relationships between cells occurs because they differ in the content of the IGF-I receptor or another pathway component 48 , but it could also be from differences in basal signaling 49 , cell shape 50 , nuclear import/export machinery 38 , or phosphatase activity. Assessing each of these mechanisms independently is challenging, but our work suggests that it may be possible to tease apart these different mechanisms using a single-cell multi-treatment approach.
Our studies indicate that signaling responses to molecules that activate or inhibit the IGF-I-AKT signaling pathway are not necessarily noisy. This is important as it rules out one mechanism for drug resistance in cancer: that cells have large and variable signaling fluctuations that allow them to overcome inhibition. This conclusion also suggests a role for microenvironmental signals to modulate therapeutic response. For instance, subpopulations of cells may be subject to signals that lead to pathway activation, whereby a larger drug dose may be required to fully inhibit these cells 19,51 . These experiments open the door to more in depth studies on how various pathway inhibitors alter signaling activity and how treatments regimens could be optimized for use in the clinic, particularly in the metastatic setting where cancer cells have disseminated to distinct tissue sites enriched with unique complements of signaling molecules.

Summary
A significant question in cell biology is how much noise is present in a signaling pathway, and as a consequence how accurately a signal can be interpreted and processed. Along with the development of an improved reporter, we found that individual cells can faithfully interpret multiple IGF-I concentrations, although each cell encodes the signal differently. This conclusion has significant impacts on how we think about the regulation of biochemical pathways and cellcell heterogeneity.
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Cloning
The new FoxO1-Clover reporter was constructed from a modified pSBbi-RP plasmid 28   The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/373993 doi: bioRxiv preprint that migrated over the course of the experiment such that the T0 location no longer aligned with later time points were excluded from analysis. Additionally, cells that divided, died, were multinucleated, or overlapped with another cell were excluded from analysis.

Transfection and selection of stable cell lines
Three measures were used to quantify individual cell responses: the 'nuclear localization', the 'relative nuclear intensity', and the 'scaled relative nuclear intensity'. The 'nuclear localization' for each cell was calculated by normalizing fluorescence intensities to the nuclear fluorescence intensity 90 min after leptomycin (LMB) treatment. The 'relative nuclear intensity' for each cell was calculated by normalizing fluorescence intensities to the nuclear fluorescence intensity at T0 following 90 min in serum free media. The 'scaled relative nuclear intensity' was calculated by scaling each cell's response to the population average, where 0 pM was set to 0 and 125 pM IGF-I was set to 100.

Reporter Characterization
To characterize each HeLa reporter cell line, cells were serum starved for 90 minutes in Fluorobrite media (ThermoFisher) supplemented with 2 mM L-glutamine, 0.1% bovine serum albumin, penicillin and streptomycin. Cells were then treated with 250 pM R3-IGF-I for 90 minutes followed by the combined addition of the dual PI3K and mTOR inhibitor PI-103 (1 µM) and LMB (100 nM) for 90 minutes. From these experiments, we quantified: the average rate of reporter nuclear exclusion following IGF-I treatment, the average rate of nuclear localization following PI-103 and LMB, and the average measurement range, which was defined as the difference between the percent nuclear localization after serum starvation and the percent nuclear localization 90 min after IGF-I treatment. Export and import rates were calculated using the population average response and fit via non-linear regression (Graph Pad Prism 7). All cell lines were imaged using the same 75 millisecond imaging duration. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/373993 doi: bioRxiv preprint 0 min value. 'Summed responses' were calculating by summing the relative change of the T0 normalized data using 15 equally spaced images (every 6 min). Individual cell responses to multiple doses of IGF-I were sorted using the summed responses across the 300-minute experiment. Heat maps were created in R (https://www.R-project.org/) using the gplots heatmap package version 3.0.1.

Leptomycin B experiments
To quantify the relationship between reporter expression and sub-maximal IGF-I responses,

Quantification of channel capacity
Channel capacity was calculated using the Shannon-Hartley formula: CC = ½ log 2 (S 2 /N 2 ), where CC is the channel capacity in bits, S is the signal magnitude quantified by taking the variance of the average response across six relatively evenly spaced IGF-I doses representing the full dose range (0, 10, 15, 25, 40, 125 pM R3-IGF-I), and N is the noise magnitude quantified by taking the average variance within a dose and averaging across all doses 3 .

Data Availability
Source data are available from the corresponding author upon reasonable request.  The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/373993 doi: bioRxiv preprint   The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/373993 doi: bioRxiv preprint The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.  The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.

Channel Capacity (bits)
A All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/373993 doi: bioRxiv preprint The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.  All rights reserved. No reuse allowed without permission.