Did Maxwell Dream of Electrical Bacteria?
Round 1
Reviewer 1 Report
Quorum sensing is a collective behavior phenomenon of some bacteria, in which secreted autoinducer molecules (AIs) have concentration dependent effects on gene expression in nearby cells. This coordinated function of bacteria is biologically and medically relevant, for example in biofilm formation in the lung pathogen Pseudomonas aeruginosa. Here, Alfinito and colleagues present some simulation experiments in which quorum sensing phenomena are modeled as electrostatic interactions among cells. The buildup of charge in the nodes (cells) is the activity of the cell and as activity builds, so does AI production, inducing a "field -like" effect in the community. A very creative thought experiment. What follows are some minor suggestions to improve the text for publication.
Biggest concern: I don't understand what the charged particles analogy are in this simulation. Are they the cells (nodes)? or are they the AI molecules.
Why does a maximum value of Q cause death or biofilm formation? How was the parameter value 80 chosen?
Figure 4: Why is the colony formed circular? I would expect it to be square shaped, caused by edge effects of the 50x50 grid.
Figure 5: What is the difference between biofilm and colony?
P1 L34 Change "...cells are are the smallest living being..." to "...bacterial cells are the smallest living being..." or else change to "...with a size of about 1-10 µm..." in order to better describe eukaryotic cells here.
P1L43 "As a matter of fact, when bacteria come together..." This sentence needs multiple citations, or else should be deleted.
P2L53 Change "...present on different cells..." to "...present in different cells..."
Equation 2. For the Coulomb interaction, shouldn't the denominator be the square of the Distance between the nodes (cells)? If not, why not? This should be explained in text.
L175: What causes a node to die? This should be explained in a manner that is more consistent with biology--for example, using up of available nutrients? Is this stochastic in the model? In reality, this would not be stochastic, there would be an effect of location. For example, multiple nodes in an area depleted of nutrients might all die or become quiescent (e.g., biofilm formers).
Author Response
Referee 1
Quorum sensing is a collective behavior phenomenon of some bacteria, in which secreted autoinducer molecules (AIs) have concentration dependent effects on gene expression in nearby cells. This coordinated function of bacteria is biologically and medically relevant, for example in biofilm formation in the lung pathogen Pseudomonas aeruginosa. Here, Alfinito and colleagues present some simulation experiments in which quorum sensing phenomena are modeled as electrostatic interactions among cells. The buildup of charge in the nodes (cells) is the activity of the cell and as activity builds, so does AI production, inducing a "field -like" effect in the community. A very creative thought experiment. What follows are some minor suggestions to improve the text for publication.
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We thank the Referee for the positive comments and useful suggestions. In the following we answered all the questions/comments.
Q: Biggest concern: I don't understand what the charged particles analogy are in this simulation. Are they the cells (nodes)? or are they the AI molecules.
A: We thank the referee for highlighting this point, which we clarify as follows.
While bacteria are identified by means of the network nodes and are physical objects, AIs are associated with the interaction (mediators). Bacteria may gain charge (activity), i.e. improve the regulation of gene expression, and this happens when a sufficiently large number of contacts with other alive bacteria is reached (Eq.6). Higher charge means higher probability to reproduce. The role of AIs is in terms of interaction, i.e. in the putative electric field which establishes among the charges and transmits communication in between charges. To make this interaction “detectable” we associate to the network of bacteria a resistance network which evolves as in Eqs (4,5).
The revised version has been slightly modified as follows (lines 72-77):
In more details, the model describes the evolution of a bunch of initial seeds, i.e. bacteria, randomly distributed on the nodes of a regular graph and equipped with an initial kind of ‘internal energy’ [15], herein called activity. Activity reflects the level of gained genic regulation and plays the role of an electric charge, hence allowing each bacterium to electrically interact with other alive bacteria. The electrical interaction among active nodes (alive bacteria) mimics the exchange of auto-inducers.
A: Why does a maximum value of Q cause death or biofilm formation? How was the parameter value 80 chosen?
Q: We have postulated two different outcomes for the bacteria, not coexisting in the present formulation: death or evolution in a different form (biofilm). Let us remark that this is only a possible choice, for example, another kind of cell evolution could be into a “too active” form like a tumor cell and so on. The change is related to reaching the maximum value of Q that limits the power of the single cell. This implements a form of programmed death.
The chosen value (80) is not a critical choice, but just a computational compromise. A sentence has been added in the revised version to account for this point. Specifically, (lines 219-220):
- a quite large value of Qmax , in such a way to allow multiple replication events before the cell ending ;d
Q: Figure 4: Why is the colony formed circular? I would expect it to be square shaped, caused by edge effects of the 50x50 grid.
A: Edge effects deform the approximately circular growth only in the final stage of the evolution. This shows that the growth process is substantially local despite the non-local nature of the Coulomb-like interaction. This is because the spatial occupation is described in terms of a local migration mechanism, with interactions acting in the occupied bulk.
Q: Figure 5: What is the difference between biofilm and colony?
A: We thanks the Referee for noticing this typo in the figure caption. In the revised version the sentence has been rephrased as follows: Screenshots of the sample of bacteria at different evolution time from 1 to 200.
C: P1 L34 Change "...cells are the smallest living being..." to "...bacterial cells are the smallest living being..." or else change to "...with a size of about 1-10 µm..." in order to better describe eukaryotic cells here.
A: The revised version has been modified as suggested by the Referee.
C: P1L43 "As a matter of fact, when bacteria come together..." This sentence needs multiple citations, or else should be deleted.
A: We thanks the Referee for noticing this lack. In the revised version we added the reference : Jefferson, K. K. What drives bacteria to produce a biofilm?. FEMS microbiology letters, 2004, 236(2), 163-173, now ref 5.
C: P2L53 Change "...present on different cells..." to "...present in different cells..."
A: The revised version has been modified as suggested by the Referee
Q: Equation 2. For the Coulomb interaction, shouldn't the denominator be the square of the Distance between the nodes (cells)? If not, why not? This should be explained in text.
A: Eq.2 computes a quantity which is analogue to the electrostatic energy, hence, it involves the Coulomb potential that decreases as the inverse of the distance.
Q: L175: What causes a node to die? This should be explained in a manner that is more consistent with biology--for example, using up of available nutrients? Is this stochastic in the model? In reality, this would not be stochastic, there would be an effect of location. For example, multiple nodes in an area depleted of nutrients might all die or become quiescent (e.g., biofilm formers).
A: the Referee raises an important limitation of our model which we plan to improve in future work. In the present form, we only implemented the simplest form of programmed death, which occurs when the bacterial cell becomes too strong with respect the others in the colony. We have modified some sentences in the Conclusions, to better explain our point. Specifically at Lines 350-356:
The simple model presented here has many parameters which can be tuned to better account for more significant biological features and it has to be meant as a starting approach to explore their interrelated roles by some restricting choices pointing out the potentialities of the predictive power of the model. Other regions of this still uncharted parameter space may correspond to more complex bacteria features. Natural extensions are easily included with minor modifications, like different kinds of replications, the presence of multiple AIs or bacteria species, as well as of the role of environment (food, enemies and so on) and mutants
Reviewer 2 Report
In this paper, the authors propose a stochastic model for bacterial Quorum Sensing. The electrostatic-like interaction is given by a fictitious charge representing the bacteria activity. The stochastic algorithm is presented and simulations are provided in some relevant cases.
The paper is interesting, the results are appropriately discussed and the text is well written. In my opinion, the manuscript deserves publication. I point out the following minor remarks and typos.
1. At lines 219, the authors should highlight in this paragraph the discriminant conditions leading to the two different behaviors, even if they start from the same initial condition. Is it the value of sigma? What values were taken in both cases?
2. Line 31, quantum-mechanical.
3. Line 42, aggregate.
4. Line 49, extra full stop.
5. Line 62, extra parenthesis.
6. Line 74, connects.
7. Line 225, becomes.
8. Line 331, we have just begun.
9. Line 334, kinds.
Author Response
In this paper, the authors propose a stochastic model for bacterial Quorum Sensing. The electrostatic-like interaction is given by a fictitious charge representing the bacteria activity. The stochastic algorithm is presented and simulations are provided in some relevant cases.
The paper is interesting, the results are appropriately discussed and the text is well written. In my opinion, the manuscript deserves publication. I point out the following minor remarks and typos.
- At lines 219, the authors should highlight in this paragraph the discriminant conditions leading to the two different behaviors, even if they start from the same initial condition. Is it the value of sigma? What values were taken in both cases?
Q- We acknowledge the Reviewer for this observation and, accordingly, we have modified the paper by inserting the following sentence: “…formation; c. a quite large value of Qmax, in such a way to allow multiple replication events before the cell ending…”
- Line 31, quantum-mechanical.
Q: We have modified accordingly to the Reviewer’s suggestion
- Line 42, aggregate.
Q: We have corrected
- Line 49, extra full stop.
Q: We have corrected5. Line 62, extra parenthesis.
Q: We have modified corrected
- Line 74, connects.
Q: We have modified corrected
- Line 225, becomes.
Q: We have modified corrected
- Line 331, we have just begun.
Q: We have modified corrected
- Line 334, kinds.
Q: We have modified corrected
Reviewer 3 Report
The manuscript entitled, as “Did Maxwell dream of electrical bacteria?”, is an article describes a stochastic model that explains the bacterial Quorum Sensing (QS) mechanism. Authors have applied J.C. Maxwell mathematical equations to electrical signal associated with Quorum Sensing and analyzed in space and time. I think, this study highlighting how a simple electric interaction gives rise to a non-trivial complex dynamic in the biological mechanisms.
The manuscript was well written, and I was able to easily follow the content through the manuscript. Authors have nicely described the all-model parameters used in the DYING and STATIC simulation study in a table format so that readers from non-computational background can easily understand. Authors have investigated colony formation and biofilm formation in both in rectangular and square geometries. They found that QS signal is represented by the electrical current flowing in the network and this signal is a noisy low intensity signal when it is planktonic state and signal intensity grows sharply as colony formation occurs and provided useful information about the colony dynamics i.e., from colony formation to biofilm formation.
The manuscript looks great in current format I wouldn’t much see some improvement in the manuscript. I would recommend accepting the manuscript as such.
Author Response
We acknowledge you for the positive evaluation of our manuscript.
